0:00
I see a larger fear on the horizon.
Search this video
0:07
We're surrounded by journalists. Hold your position. That's misinformation.
0:38
All units clearing order in now. That's just wrong.
0:48
You're surrounded by journalists. Hold your position. Com, get up. Trust the experts. Fire at will. We need reinforcements. Found her noble. Fire at will.
1:21
I see more journalists on the horizon. Stand by. Experts say so. UAV online. Blades. Double blades. Triple blades. Double kill. Fire at will. >> Fire control. Run. Comp is up. Wait. Team death match. We are experts. Triple Let's just run. Right.
2:48
Marking clearing order inbound. Comp, get up.
3:02
You're surrounded by drones. Take your position. Strike one. Strike two.
3:24
Activate Google Drive room. Transfer complete.
3:39
Marking clearing order inbound. Fire control.
3:55
>> Founder You're watching TV B and Today is Monday, April 20th, 2026.
4:07
We are live from the TVB and ultra now, the temple of technology, the fortress of finance, the capital >> of capital.
4:15
Uh we have a great show for you today, folks.
4:17
Uh absolutely uh incredible edition of The Wall Street Journal.
4:22
Uh over the weekend I saw these hit the app, uh but uh they're in print today, Monday, April 20th.
4:28
There's two articles uh from two tech CEOs that run companies that are almost identically valued.
4:39
Salesforce is I think 150 billion, Verizon's 190 billion.
4:41
They're right in that sweet spot.
4:45
>> assuming they have the same point of view, kind of same market outlook.
4:50
>> have exactly opposite points of view.
4:52
And I thought it was uh I thought it was interesting seeing what what is a victim of the SaaS-pocalypse have to say about AI?
4:57
And then what does someone who is the most resilient to the SaaS-pocalypse have to say?
5:06
And potentially is like, "Let me in.
5:08
I want some of the drama. I want the smoke."
5:10
Uh and so Mark Benioff is who I'm talking about at Salesforce.
5:15
So he says the software bears are all wrong about Salesforce.
5:18
We had a bear hat but it was it was too terrifying. Yeah, it was too scary. So so we skip it.
5:24
But uh he says, "People think we have our back against the wall, but customers aren't replacing offerings with AI.
5:32
They aren't replacing Salesforce with AI.
5:33
They aren't ripping it out."
5:35
Of course everyone will say, "Well, yet."
5:37
But uh let's dig into Mark Benioff's argument and how he's processing the SaaS-pocalypse and what he's going to do about it. stuff. >> opening.
5:45
Mark Benioff has some problems.
5:48
His enterprise software company Salesforce is the biggest name in a category that Wall Street thinks may get decimated by artificial intelligence.
5:57
Its business model is centered on selling software to large companies on a per employee basis, but many of those firms are expected to downsize as AI agents become increasingly proficient at performing real-world tasks.
6:07
It's a daunting double bind, and it isn't even the worst-case scenario.
6:10
Salesforce stock is down a mere 28% year-to-date.
6:13
The hardest-hit software as a service companies are down about twice that much on similar fears.
6:16
But Benioff thinks the bears have it wrong about the SASpocalypse thesis generally and especially about Salesforce.
6:23
AI, he says, is making Salesforce more valuable to its customers than ever.
6:29
The leading AI labs couldn't replace what Salesforce offers even if they wanted to.
6:34
And they would rather partner with him for now anyway. Nor could Yeah. He's like, I dare you. I dare you. I I dare you. He's he's daring enough.
6:44
>> Uh I I wish I wish we had Benioff on right now. Yeah.
6:47
>> I It's It's It's a joy to to speak with him.
6:49
Uh but continuing, nor could customers easily vibe code their own sales management management software that could compete with Salesforce on security, compliance, and other vital features.
6:58
People think we have our back against the wall, when in fact the opportunity has never been greater, Benioff said in an interview.
7:06
An early investor in Anthropic, Salesforce has been developing and pushing its own AI tools for years.
7:08
By the end of this year, it plans to unveil a new AI platform that automatically studies its users and takes actions on their behalf, code-named Agent Albert. Hmm.
7:21
It's kind of cool to put Agent in the name instead of just Albert. Agent Albert.
7:25
>> Well, they had they had Einstein, right?
7:27
So, Albert Einstein is their whole schtick here.
7:31
Agent Albert is the culmination of an effort that began 3 years ago when Benioff galvanized uh when Benioff, galvanized by the debut of ChatGPT, instituted a standing Saturday meeting to accelerate Salesforce AI efforts. >> lock it up.
7:45
Saturday stand-up, everyone.
7:48
An earlier flagship product of that push, Agent Force, has been somewhat slow to gain traction.
7:52
Launched in 2024, it is used by 23,000 customers of a total base of 150,000. So, what is that?
7:59
A little little under 20% of the customer base is using agents.
8:06
They're building for >> Remember Jason Lemkin came on the show and he was like, I use Agent Force, it's solid.
8:12
Like he's like, it won us back a customer that like we weren't reaching out to and it like it made me money. >> Yeah.
8:18
So, he was an Agent Force enthusiast.
8:21
And so, Salesforce's yearly revenue growth of 10% is down somewhat from recent years, but interestingly, the the deceleration in in Salesforce's revenue growth started back in 2022, maybe even a little bit earlier.
8:37
If we scroll down on this on this image, you can see back in 2012, they were growing 36%.
8:41
Then as recently as 2020, they were growing 28. 7%.
8:47
There was acceleration in 2022 to 24%, but then 2023, 18%, 2024, 11%, 2025, 8%, and then we're actually seeing some re-acceleration this year from 8. 7 to 9. 6 to 10. 8.
9:01
And so, it it is it feels like definitely too soon to for the SaaS-pocalypse narrative to show up in the actual revenue growth rates of these SaaS companies.
9:15
I I pulled together the recent earnings from a variety of uh public cloud software names, and they're all still growing, which you would expect.
9:26
I mean, of course like, you know, you want to be growing fast, and there's a lot of things, and there's like the long-term durability of the value that of the stock that actually informs enterprise value today.
9:35
Uh but, we're certainly not seeing like, okay, there's so much churn at GitLab, for example, because people are forking it cuz it's open source and vibe coding on top of it, and they don't need to pay GitLab that you would expect GitLab's revenue to actually be shrinking. Uh it's not.
9:54
GitLab is growing at 23%. Adobe's at 12%. PagerDuty 2.
9:56
7%, little low, but UiPath at 14%. Uh Box is at 9%. Asana is at 9%.
10:04
Asana feels like, you know, textbook like you could just vibe code this.
10:09
It's a it's, you know, it's a Kanban board at a task list, but it's still growing. Zoom at 5. 3%. Snowflake's growing 30%. Workday's at 14. 5%. HubSpot's at 20%. Data Dog's at 29%. Cloudflare 34%. Uh monday. com 25%.
10:23
Like, there's really, really strong revenue growth across the SaaS category.
10:29
Of course, the expectations have been very high.
10:32
So, when there's a readjustment in expectation, you see a sell-off in the market, but uh this idea that uh the companies aren't growing anymore because they're being replaced so rapidly, that certainly hasn't taken hold just yet.
10:42
Uh so, partner at uh uh partner at Salesforce uh investor Chicago Capital has been impressed with some of its recent moves.
10:53
Uh but, what Salesforce really needs, he says, is positive word of mouth from clients talking up the value they derive from its AI products like Jason Lemkin.
11:00
They need to show revolutionary jumps.
11:04
Benioff has said Salesforce was destined to be an AI-first company as far back as 2014 when it launched its AI research unit.
11:10
I didn't realize they had an AI research unit all the way back then.
11:12
Uh but, it makes sense just for like tagging and classifying different records inside the CRM.
11:16
Uh still, it was caught flat-footed by the arrival of high-functioning chatbots in the form of ChatGPT.
11:22
Um Customer superintelligence.
11:25
Customer superintelligence.
11:25
I mean, the this is it is it is funny cuz uh a lot of this the agentic enterprise, it is a little like boring and it's not as like sexy as some of the the more like crazy sci-fi scenarios, but in terms of just you know, incrementally improving the value that is delivered to the customers, it seems like things are doing okay.
11:45
Early reviews were tepid though.
11:47
Customers complained of having to spend half their time preparing data so the AI could understand it limiting the platform's effectiveness.
11:53
To help fix the problems, built Salesforce built a layer into its tech stack that automatically pulls in customer data from external sources and purchased a string of companies that include firms specializing in data management and AI-powered sales.
12:04
At education company Pearson, agents now autonomously handle queries about order statuses, refunds, and lost access codes for its customers.
12:13
This has increased the percentage of customer questions that don't involve human interaction by 40%.
12:20
While Agent Force where Agent Force has been lacking in in its addressing complex customer problems and those require human touch, David Wemsley, chief digital officer at Pandora Jewelry, said Agent Force hadn't been able to reliably recommend products on its own based on the vague context the customer shared through its website like my wife likes dogs, what should I buy her?
12:41
That's such a funny funny question, but I mean I guess the natural text natural language interface should be able to find you jewelry based on a love of dogs, although I think that a lot of people who are dog lovers might have different tastes that appeal to their jewelry.
12:55
Or why not just get her a dog or multiple dogs? Yeah, I don't know.
13:00
That's Uh so, how does this compare how does how does Salesforce's view compare to the Verizon CEO?
13:05
So so Verizon has a new CEO.
13:09
His name is Dan Schulman.
13:09
I don't think he's related to John Schulman, the co-founder of Open AI and Thinking Machines, but he is stepping into the AI debate.
13:21
He says for the Wall Street Journal says for a big company CEO with big AI ambitions, Verizon Communications Dan Schulman doesn't pull punches about the pain the technology could unleash on America's workforce.
13:32
Just months into the job, he has predicted 20 to 30% unemployment within the next two to five years.
13:38
Uh which is staggering staggering.
13:41
And I can put that into some context.
13:43
He says he warns that advancements in humanoid robots could upend the manual labor jobs still seen as safe today.
13:49
And he has pushed for more education and reskilling to help workers adapt to intensifying tech disruption.
13:58
>> Put this into context for me. >> Okay.
13:59
So, uh uh he's uh so uh this is an insane number >> yes.
14:05
And and so this is like potentially the most aggressive stance.
14:07
I mean there are numerous out there.
14:11
>> even even Dario So Dario had the clip going viral this weekend.
14:13
It was a clip from last year talking about risks to entry-level white-collar job. >> Yeah.
14:20
And Dario, which is like, you know, I would say like on the frontier around being concerned around AI job loss, was not calling for 30% Well, no.
14:30
So So the headline number he said 50%, but to entry-level white-collar work.
14:36
entry-level white-collar work.
14:36
Uh And that sounds really bad until you actually dig in and you realize that America only has 5 to 7 million entry-level white-collar workers.
14:47
Uh and the US labor force is 170 million people.
14:50
And so, if the Dario prediction came true, the overall employment unemployment rate would sit somewhere between 6 and 9%, which is not great.
14:56
Uh And it's And it's obviously deserving of intervention.
15:03
Uh but it's far from the 20 to 30% outlined by Dan Schulman.
15:05
And uh And it's it wouldn't even be even if the Dario scenario of 50% of early-stage white-collar work uh unemployment that happens, you're still below COVID, below the Great Depression.
15:19
Uh and I think that there's a whole bunch of uh government interventions that could that could offset that pretty quickly.
15:25
could offset that pretty quickly. Um like 20 to 30% is truly like the do-nothing, the government never engages, there's never any sort of uh you know, incentive to to keep hiring people, and there's this like fast
15:39
takeoff in in AGI, and also humanoids, which I think people are, you know, worried about, but if you look at the deployment rate of self-driving cars, people have been saying that all the truck drivers were going to go out of a job, uh and you know, this is a very, very slow takeoff. The number of uh
15:54
The number of uh self-driving cars on the road is well below 1% of overall cars on the road still.
16:00
Um and this is just the case across the board.
16:02
I was listening to a podcast with uh someone who is very worried about unemployment internationally, and he was saying that um uh that AI could upend the Philippines because the Philippines does a lot of customer service.
16:17
>> Which we haven't seen at all yet.
16:18
>> No, we No, none of this is showing up in the unemployment data.
16:19
It's not showing up in US unemployment data yet.
16:21
I mean, it it doesn't mean that you shouldn't be aware of this stuff, but uh but it's it's certainly not sure.
16:26
Just like the SAS apocalypse is not showing up in revenue yet, uh you know, AI uh unemployment is not showing up in any of the employment statistics yet.
16:34
So, um but uh this individual was on a podcast who was saying that uh something along the lines of uh you know, AI could be devastating to the Philippines economy because the Philippines is very dependent on customer service.
16:47
And the stat he quoted was that 90% of the Philippines economy is based around customer service and customer support and and handling people on the phone. And I was like, 90%?
16:57
That seems really, really high.
17:00
seems really, really high. Like, they have to do other things in the Philippines because sure, you go to work at your at your uh uh at your customer service job, but then you go home and you buy food and you live in an
17:10
apartment, there must be real estate agents, there must be home builders, there must be people who work on roads, there must be doctors, there must be lawyers, like like an economy requires more than just like a single like it's it's 90% feels like incredibly concentrated. So, I looked it up and I
17:23
So, I looked it up and I was like, how how big of an issue is how big of a of a of a of an industry is customer service in the Philippines? Is it 90%? That feels high.
17:34
Maybe it's 50, maybe it's 40. It was like 6%, 7%.
17:37
It's really really small.
17:40
Now it's like huge in terms of like, you know, You don't want it to go away.
17:45
You don't want it to go away, of course.
17:47
And you don't and and you do want you know, you want a number of industries that are flourishing.
17:54
Um, and that is probably more concentrated than many other countries.
17:56
It's probably many It might be It might be the country with the highest percentage of customer service intensity in the economy, but it's not 90% of their economy.
18:05
And so, there's a little bit of this like people don't seem to go back to the raw numbers because if you go back and you try and understand like, okay, what would 30% unemployment really look like?
18:17
Well, that's like, you know, Great Depression level with no intervention, no no action from the Fed, no action from the government, and it seems a little bit a little bit crazy.
18:26
So, I can't tell if this is just like saying the biggest number, but there there's a little bit of that going on here where if you want to grab headlines, um, and you go out and you say, "Okay, well, someone predicted, you know, 5% unemployment.
18:42
I'm going to predict 10% and then I'll jump to the front forefront of the discussion."
18:46
Uh, that seems to be a way to get earned media.
18:50
Um, but I mean, let's unpack a little bit more of his discussion because we we we will see if there's a way to steel man his take around 20 to 30% unemployment.
18:58
He said, "Coached in the blunt AI talk is a warning for other CEOs.
19:02
Be candid about the coming disruption or risk a public backlash.
19:07
Uh, it's a very difficult time and everyone knows this."
19:08
Shulman said in an interview with the Wall Street Journal.
19:11
And I don't authentic is key.
19:11
I don't even agree with that stance.
19:13
If you everyone that's being candid or even talking about it is immediately getting backlash anyway. All right.
19:24
So, I think being authentic, being realistic, telling the truth as best you can is key.
19:27
That belief, he said, is why Verizon created a $20 million career transition and retraining fund for the age of AI when the company began >> we are going to have greater unemployment than in the Great Depression."
19:41
And I'm going to you know, he's taking the piece of duct tape.
19:42
You know, there's water pouring out.
19:43
He's I know exactly what you're talking about.
19:48
To be clear, to be clear, this is not our view.
19:51
Like, this is not our view at all.
19:51
No, but I mean at the same time like they did layoffs.
19:55
They probably hired a lot during COVID and beyond.
20:00
And they and and a $20 million career transition and retraining fund is great. That is good.
20:04
Like, this is a good thing.
20:07
But, he says the warning this is from the journal.
20:09
The warnings are a departure from the messaging of other public company CEOs, many of whom have been bullish about AI's potential to unlock new levels of growth, but demure on or even reject the idea of job losses.
20:20
A lot of people are saying AI is coming, we're going to run out of jobs.
20:25
It's exactly the opposite, Nvidia CEO Jensen Wong said last month, pointing out that every other technological advancement has brought more productivity and more prosperity.
20:32
And there is some new data showing that productivity might be climbing, which is very exciting if the all the economists wind up developing a consensus around that.
20:43
Amazon CEO Andy Jassy is similarly sanguine about potential job losses to AI.
20:47
Though some roles will be replaced, there will be other jobs created.
20:49
In the short term though, a cavalcade of companies from Snap to Amazon have invoked AI or desire to find efficiencies as they slash large portions of their workforces.
21:00
Block, which cut nearly half of its predict half of its staff, predicted other companies would soon follow suit.
21:06
A new Boston Consulting Group report predicts that AI will shape roughly half of US jobs in two to three years and then up to 15% of jobs could eventually be eliminated outright.
21:19
Um Again, that's, you know, uh reshaped uh and eliminated does, you know, uh would be offset by the creation of new jobs.
21:28
So, even in this BCG report, uh you're probably looking at like, again, maybe a transition of like six, seven, eight, nine, 10% unemployment while there's an adjustment period.
21:39
Uh many of many Americans fear that will happen, too, in a Quinnipiac University survey of 1,400 adults, uh 55% said they feel felt AI would bring more harm than good, up from 44% in a poll last year.
21:51
And so, uh the the the the average American is dooming, for sure.
21:57
Uh "CEOs are not thinking about this the right way," said Bill George of the the former CEO of Medtronic, who is now an executive fellow at Harvard Business School.
22:05
"Too many," he said, "are focusing on productivity instead of laying out a strategy for how companies can find new business models to grow or on how workers can best use AI.
22:14
They should be very candid with them and paint a big picture."
22:18
Schulman's big picture also included stru- stru- uh sweeping job cuts, the 13,000 layoffs he announced shortly after his appointment of as CEO in October were Verizon's largest ever, but not but necessary to make Verizon more efficient, he said.
22:31
Uh altogether, he's seeking to cut 9 billion of costs.
22:36
Uh Verizon said it its layoffs were not related to AI.
22:39
The uh "The carrier was too hierarchical, too bureaucratic, too way too process-oriented as opposed to outcomes-oriented."
22:47
>> And the CEO's saying, "This is already happening in a big way, but uh the layoffs we're doing are just that we're bloated." Yeah.
22:54
So, Verizon has 90,000 employees and they laid off uh 13,000, so maybe like a little over 10% uh, Riff.
23:04
Verizon's a weird one because the stock is basically completely flat over the last It's actually up 15% year-to-date, and uh, it is a incredibly stable stock, and it's also just like should not be a victim of the SAS apocalypse because They own spectrum allocation. They >> Sell towers.
23:22
>> They own cell towers, exactly.
23:22
And that's just very >> or they have like very, very long-term lease agreements. >> Yeah.
23:28
And I mean, they I There is There is the case that like, you know, if Starlink direct-to-cell gets really good, even I mean, even Elon's saying like it's not going to be that good inside buildings.
23:40
Like it's pretty difficult to get to a point where all of a sudden there's a new technology that's just wildly disruptive. Yeah.
23:46
>> Um, like maybe if you're like somehow transitioning from Starlink when you're outside to Wi-Fi when you're inside, like you could cut the cord with Verizon, but that just feels so, so far away for something that is like a pretty key uh, utility in most people's lives.
24:03
Like their water bill or electricity bill.
24:04
Like their their their phone internet bill is like pretty uh, it's like one of the one of the probably the the least elastic things.
24:10
Like they will just keep paying and and and stick around.
24:14
Now, they might move to Sprint or AT&T, and there's going to be some competitive dynamic.
24:18
It is an oligopoly after all, but uh, it it doesn't seem like there's going to be some massive disruption moment where people are vibe coding their own cell carriers necessarily.
24:28
So, uh, in meetings, he has repeatedly told Verizon staff they must embrace AI describing it as core to the company's future.
24:34
He He used it himself to comb through some 8,000 responses after asking >> future. Trust me. I used it once.
24:46
Schulman's embrace of AI goes deeper than cost cutting.
24:48
He envisions a company wholly reshaped by the technology from improved customer service to more personalized options for consumers.
24:57
And he has encouraged staffers to talk to their children about AI at the dinner table.
25:00
In one all-hands, Schulman recommended that staff ask AI to write their obituaries so to see how the technology works and how it frames their lives. Dig your own grave.
25:14
He's He's literally the title of this article that they the same He's saying AI is coming for your job and everyone knows it.
25:20
So like in in tech in tech, we're starting to uh you know, um every company's adopting this technology at a rapid rate, yeah, but uh everyone's like, "Hey, this you know, basically like jobs aren't tasks, right?"
25:34
The sort of narrative is building like we need to figure out how to um it it's it's we've we've built a bunch of very useful tools and they are going to have powerful effects in our economy, yeah, but uh we have to kind of change the narrative around this because like a fear-based approach is not working.
25:56
And and meanwhile, he comes in and he's like "AI is coming for your job. Everyone knows it. Write your obituary." Write your obituary.
26:04
It's so not so not helpful and and and they're not even doing AI-related job cuts. No.
26:12
I love So I just don't understand.
26:12
I don't understand this whole press cycle.
26:16
I love I love that he just comes in and just immediately starts blackpilling.
26:22
It's so wild to just get this job and immediately start blackpilling.
26:24
Oh, so >> you think this is a setup for for a much like deeper layoff than they've done historically? I don't know.
26:32
I mean, it's possible, but I like I think that they would need to do some serious like AI tooling and implementation and actually figure out like I I mean, I would be surprised if out of those 90,000 like I want to know more about the breakdown of those 90,000 employees or 80,000 employees.
26:48
Like what are they actually all doing?
26:49
Uh which ones are actually just sitting there being like, I just do tasks all day long.
26:56
Like, form comes in, I type it into an Excel sheet, and I email it to somebody.
27:02
Like, that type of job, yeah, that's probably going to be automated in some way, and that person will have to find a different way to make a play inside the organization.
27:12
But, for a lot of But, for a lot of the folks at Verizon, I imagine that they're that they're working on bigger projects than just you know, just throwing throwing tons and tons of people at a single problem.
27:23
Um At the same time, who knows?
27:25
Maybe maybe it's 50 Maybe half the company is customer support reps. I don't know.
27:30
Uh He has invited staffers to experiment with AI by writing poems to their loved ones.
27:35
Some employees responded by by using AI to write poems for Schulman, and they weren't half bad, he said.
27:39
Like it or not, we live in the age of AI. I I happen to like it. I I agree with that.
27:46
Uh it's like we all wanted to live in the Renaissance or like when fire was first invented.
27:49
How cool would that be, he continued. We're in that stage.
27:51
We're not just appreciating it for what it could be.
27:55
That's a very optimistic take.
27:57
I like that's I like that sentence. That's good.
27:59
Some prominent CEOs are starting to join Schulman in acknowledging uh AI's potential for a for a disruption.
28:07
Uh Others have also recently sounded warnings.
28:10
There's real risk of artificial intelligence could widen wealth inequality, BlackRock CEO Larry Fink wrote in his annual letter to shareholders last month last month.
28:19
Jamie Dimon recently told investors that AI's productivity gains could lead to other derivative effects.
28:22
It may happen faster than we can adjust to it.
28:26
Schulman said AI may reach human-level capability known in the industry as AGI by the end of next year, on the early side of most most industry predictions.
28:34
So, end of 2027 for AGI isn't that crazy.
28:37
I mean, the Sequoia has an event right now.
28:39
AI is in there's the whole keynote slide is AGI is here.
28:43
And so, people are going back and forth on that, but I think I think it's not it's not that crazy to to imagine, you know, very very human level AI by the end of 2027.
28:55
That doesn't seem impossible whatsoever.
28:59
The question is just like how much will this be additive?
29:01
How will the government respond?
29:03
What will the actual effect on the labor market be?
29:07
And I think people are digging into that a lot right now.
29:09
There's a good podcast on this on Odd Lots with uh Alex Immoss.
29:15
He's a professor at University of Chicago focusing on economics and applied AI.
29:18
Highly recommend you go check that out if you're interested in going deeper into the labor market. Well, moving on.
29:27
Um Blue Origin rocket stumbles on first commercial mission.
29:31
AST SpaceMobile, who we've talked about a few times here.
29:36
Uh Jeff Bezos' rocket company said the satellite from ASTS was deployed into an incorrect orbit.
29:42
And so a little bit of a setback for them.
29:46
I think the stock traded down on the news a bit.
29:50
The launch The launch of the company's New Glenn rocket started smoothly with the vehicle shooting into the sky from the Blue Origin launch site in Cape Canaveral, Florida.
29:57
During the flight, New Glenn's third ever the vehicle The vehicle's huge booster returned safely to Earth.
30:04
Only a feat only Blue Origin and Elon Musk's SpaceX have ever achieved orbital rockets.
30:08
But the mission later suffered a mishap.
30:10
A satellite the rocket was carrying into into orbit for AST SpaceMobile, a company building cellular broadband network in space, wasn't deployed correctly.
30:20
In a post on X, Blue Origin said its rocket delivered AST's satellite into an incorrect location in space.
30:26
The payload was placed into an off-nominal orbit.
30:31
Adding that teams were assessing what happened.
30:33
AST said the satellite's altitude was too low to sustain operations and that it will be taken out of orbit.
30:41
The cost is expected to be covered under its insurance policy.
30:43
The stumble comes as Blue Origin works to ramp up flights of New Glenn.
30:47
>> saw some of the the AST retail army saying like, "Don't worry. Keep holding." >> Keep holding.
30:54
It's covered under insurance.
30:56
It seems like very very very uh very unfortunate, but >> It seems like it rebounded a little bit.
31:03
>> somewhat to be expected, right?
31:03
As Blue Origin like figures out their commercial business.
31:08
>> Yeah, it traded down like 16% overnight, but it's down uh just 6% today.
31:10
So, a little bit of a rebound.
31:12
And we got a fantastic video of the booster landing that we can pull up here. >> Yeah. Uh courtesy of Jeff.
31:21
Tyler, you dug into why doesn't ASTS just uh launch on SpaceX?
31:29
Well, so so there are two things.
31:29
I think one thing I thought was interesting is like there's this whole press cycle about it like oh, it was like a failure of a launch or something.
31:36
But, this has like happened a number of times before like SpaceX in uh in 2024, there was a Falcon 9 that that kind of uh the upper stage uh like failed and then a few like Starlink satellites Just went into the wrong orbit. >> Yeah, basically.
31:49
And then they're too low and then they just Yeah, yeah. get get burned up.
31:52
Yeah, companies don't typically like to talk about when they send something into space and lose it basically, but that happens, too.
31:58
Uh I remember at the beginning of last year, there was a launch uh for for a venture-backed space company and and um you know, they basically put a satellite up Yeah.
32:08
and almost immediately lost contact with it.
32:10
So, it's not not unusual.
32:12
Unfortunate, but they'll be back.
32:15
In uh in 2016, SpaceX blew up a Facebook rocket, which is crazy.
32:24
Uh Mark Zuckerberg laments the loss of internet. org satellite.
32:26
Uh the Facebook CEO said he was deeply disappointed in the explosion of Falcon 9 rocket carrying satellite intended to provide internet coverage to parts of Africa.
32:39
So, uh writing on his Facebook page, Zuckerberg said, "As I'm here in Africa, I'm deeply disappointed to hear that SpaceX's launch failure destroyed our satellite that would have provided connectivity to so many entrepreneurs and everyone else across the continent.
32:54
The accidental explosion of the Falcon 9 rocket early Thursday morning." This is back in 2016.
32:59
"Referred to as an anomaly by SpaceX engineer, destroyed both the rocket and its cargo, the Amos 6 satellite, which Facebook had planned to deploy to provide internet coverage to parts of Africa.
33:09
Fortunately, we have developed other technologies like Aquila that will connect people as well.
33:13
We remain committed to our mission of connecting everyone, and we will keep working until everyone has the opportunities this satellite would have provided."
33:21
Contrary to Zuckerberg's description, the satellite did not belong to Facebook.
33:26
In October 2015, Facebook partnered with Eutelsat.
33:33
Eutelsat, I can't pronounce that.
33:33
A French satellite company to lease the broadband capability of the Amos 6, which was built by Israeli company Spacecom.
33:41
According to Space News, which reviewed Spacecom filings with Tel Aviv Stock Exchange, the joint lease cost $95 million over 5 years.
33:48
So, this like $100 satellite just blew up on the pad.
33:54
So, lots of different setbacks, but there is one technology that is not having setbacks, which is robotic marathoners.
34:00
And there's new >> This is crazy. >> information. There's a crazy video.
34:06
I don't know if the video relates to this, but a Chinese robot beat beat a human best time in a half marathon after a stumble.
34:13
Tech companies are making progress to fixing humanoid runners malfunctions.
34:19
A year ago in Beijing, humanoid humanoid robot half marathon race, the first runner to cross the finish line took more than 2 and 1/2 hours.
34:27
In this year's event, the champion beat the fastest human ever.
34:32
Sunday's race demonstrated China's rapid progress in humanoid robotics, a field American tech leaders including Nvidia's Jensen Huang and Tesla's Elon Musk say is the next big thing.
34:43
Beijing >> This video is pretty wild. >> the actual winner?
34:46
>> This is one that's failing.
34:46
Didn't Didn't make the half marathon, but you can see there's dry ice spilling out of the back.
34:53
This is helping with cooling. >> Interesting.
34:55
Which is like very cyberpunk.
34:59
>> that's crazy that you have to load it up with dry ice as well. I like that.
35:04
Uh about 220 yd in the finish line, the 5-ft-5 Lightning slammed into a barricade and collapsed.
35:09
The red and black robot managed to get back on its feet with help from humans and ran across the finish line in 50 minutes and 26 seconds according to state media.
35:17
I feel like if you fall down and you're human in a in a half marathon, humans help you get up. That's still fair game.
35:24
You're still good as long as you finish.
35:26
Uh this probably still counts.
35:27
Uh last month, the humanoid the human the actual human world record holder from Uganda uh finished in 57 minutes and 20 seconds in Lisbon, Portugal.
35:37
Lightning and two siblings from Honor swept the podium.
35:42
Uh all three navigated the course without human control excluding the one-time help the champion got.
35:45
The race penalized the completion times of those relying on constant human remote control including one that finished the race in under 50 minutes, but it was teleoperated.
35:54
Uh the Tian Gong Ultra, which was developed by Beijing-based lab EX Humanoid and won last year's race more than halved its finish time this year clocking in at 1 hour and 15 minutes without any human intervention.
36:08
That is pretty impressive.
36:11
Like they're they they they cut the time in half in just 1 year.
36:15
Uh the 13-mi course included more complex terrain than last year such as slopes, narrow passages, and sharp turns testing robots' abilities.
36:24
>> assume an acceleration in progress, eventually one of these humanoids is like running a marathon in like an hour or like 30 minutes.
36:29
Just like truly insane insane speeds.
36:33
>> Yeah, I mean as fast as a cheetah >> Tyler could still take it out though. I think so.
36:39
China's moving to quickly dominate the humanoid robotics industry and cement its place in the global supply chain.
36:44
While the US controls the best chips and other technology for robot brains, China leads in the manufacturing ecosystem for humanoid robotic robot bodies.
36:49
That has been reported many many times.
36:52
Well, without further ado, we have Signal here in the TVPN Ultra Dom.
36:57
Let's bring in Signal who is launching Sky, an agentic AI home screen, replacing the iPhone app. >> There he is.
37:06
With content and some fella.
37:09
>> action-driven intelligence.
37:09
Dude, I can't believe it's taken this long.
37:12
>> to your post like so many times. So good to have you.
37:14
I Oh my god, it's incredible to be on here, guys. Um welcome.
37:19
It's been a long time coming, but I just want to start off by saying congratulations. Thank you.
37:21
This has been ridiculous.
37:25
>> Yeah, what a wild ride.
37:25
I've been watching you guys since day zero. Really?
37:28
You watched the first episode?
37:30
Well, because I think we were covering your post would have been making it into like the first episode. For sure.
37:35
They're probably like, why are these two guys in suits >> Yeah. Preaching out my tweets. >> tweets?
37:39
This is for a while there. >> up.
37:42
I tweeted this out a little bit, but I was like, man, when I read that and you guys were reacting to what I posted because I didn't really think about what I posted and then you guys analyzed it and I was like, oh my god, this is ridiculous. Holy crap.
37:52
Yeah, it was I didn't write I don't I don't remember.
37:57
You have a ton of bangers. They're all good posts. You had a great time.
38:00
That was the lifeblood of the show. It was so much fun.
38:04
Anyway, we're not here to talk about you know, the the first episode.
38:06
We're here to talk about your first episode in this new journey.
38:10
Talk to us about what you're launching, what you're Very smooth, John. I try. I try. You guys have uh Yeah.
38:19
You've come a long way, for sure.
38:22
Anyway, uh introduce yourself a little bit, introduce the app, introduce the product, where you want this to go, and I have a ton of questions. No, absolutely.
38:30
Um you know, uh we're I've always been in consumer software, and I think there's just not that much other than the sort of main players.
38:40
Um I noticed and there's there's a lot to be done, and and what a time to be alive.
38:44
So, you know, we're experimenting at the very basic layer of how to make this stuff uh really easy to use, really easy to access for normal people that have not really come into this agentic AI world in full speed other than sort of chatting Yeah.
39:00
with chatbots and whatnot.
39:03
And I think it was an It's an early experimentation of what we're up to is kind of how AI will kind of speak to you, as well as how, you know, sort of ambient AI will be in various surfaces, um starting with your phone, right?
39:17
Like maybe your phone may not look at exactly the same way even in the next couple of years.
39:21
Um so, we're kind of operating at the very earliest stages of experimenting of how AI will communicate with you, and we're trying to think of creative surfaces.
39:32
And one of the one of the most interesting places, you always, you know, people take out their phones, and they glance at it.
39:36
It turns out, you know, this stuff hasn't really changed in such a long time. Yeah.
39:39
The iPhone home screen is 20 years old. That's two decades.
39:46
And it's just static icons. >> Yeah.
39:50
It It roughly speaking, it has not really evolved in any meaningful way. >> They one-shotted it.
39:55
Yeah, that's a steel man.
39:58
>> man is the one >> man is like it's good. It's the final form. >> It's the final form.
40:01
Some things don't change.
40:03
>> going to We're all going to We could always do a three-wheel car, five-wheel car, six-wheel car.
40:08
>> thing that I've been The thing that I've been pressing on is like you would think, you know, if I could rewind two, three years, I would not expect and and and knowing how much progress there would be in AI, I would not expect to look at the top 25 apps in the App Store and only see LLMs. With chat apps.
40:26
>> I would expect to see like a variety given given just like how many magical experiences people have had, a variety of like new products coming out of the App Store. >> new Instagram.
40:34
I like I like And that's like some argument >> app boom that was like very diffuse.
40:37
You got you got Candy Crush and and what's the one with the pigs?
40:42
The Flappy Bird and Uh >> Yeah.
40:45
Angry Birds and like you got all these different apps, Runkeeper and diet products.
40:50
And it feels like this has really collapsed down into just chat apps.
40:55
Yeah, and you know, I actually recently got a new phone and I was installing apps.
40:59
You know, I always like to set up my phone bare.
41:00
Like I don't like to transition my phone. >> Yep. Interesting. Really?
41:05
>> It gives me a little bit of a a reset on not only what I need and what I don't need, but also how to think about software as it exists today.
41:11
Like I don't want to be tied to what I was before.
41:15
I want to kind of be a new, if you will.
41:17
And you know, it turns out I installed you know, GPT and Claude and whatnot and I was like, man, I don't think I really need that much stuff.
41:25
You know, these LLMs are kind of collapsing how and what you do into an interesting dynamic um and I think generally um they're incredibly powerful and the fact that you know, those top five apps are all LLMs roughly Yeah.
41:42
is speaks volumes to the zeitgeist and speaks volumes to the impact of the actual technology.
41:49
Like I don't think you know, previous I think technology has always been kind of little bit more evolutionary than not.
41:55
Obviously, hindsight is 20/20, but but this feels so so different.
41:58
You know, as a technologist um this this world feels very different.
42:04
It feels um just just the things are going to rapidly change from here on out in terms of how people experience their lives, how people interact with each other, and how, you know, we're going to facilitate brand new interactions potentially, or, you know, completely reinvent old ones.
42:21
So, I'm very excited for that, and I think our company and the way that we think about it from a consumer perspective is just to make things, you know, easily accessible for these individuals.
42:31
And And I think we we're going to we're going to attempt to do that.
42:35
Very basic stuff, you know?
42:37
>> what is your like more as I can see yo?
42:40
I I It sounds like you guys have raised a little bit of money, and like are just like in an experimental phase.
42:44
Is that like generally the right read?
42:49
>> Yeah, I think generally I would say two things.
42:51
Number one is, look, we built a really fun product that we're going to give to lots and lots and lots of people.
42:57
Turns out, you know, this era is non-zero marginal cost.
42:59
We have raised a a little bit of capital.
43:01
Um but, you know, inference is non-trivial expensive, and especially if you operate at like a gen take inference, or um just background inference, that stuff is just consistently going.
43:11
Unlike, you know, Claude or GPT where people actually make requests or go on there and type something.
43:17
Uh we're we're doing it on behalf of you, right?
43:19
Like, we're doing those things in the background where we anticipate, we listen to contacts, we we turn the, you know, every time, for example, every time you get an email, uh we process it with one of our agents.
43:31
It It sort of turns out it buckets that item.
43:33
It tries to figure out what to do with it.
43:35
It tries to see if there's deserves some higher uh order like ranking, and then it tries to figure out, "Oh, can I complete this task? Can I draft a reply?
43:43
Oh, maybe it does deserve a reply."
43:46
Let me go back to John and say, "Okay, hey, here's a reply that I've crafted based on everything I know."
43:52
And it's a very, look, replying to emails has been, you know, 30, 40 years, but this is a new world in terms of how you think about communication and how agents kind of mediate this world.
44:02
And apply that to any, you you any aspect of your life, whether it's health or finance or where even where you are, right?
44:09
Like one of the underlying things that we do is location.
44:11
And you know, imagine learning about the world around you through an LLM, whether it's through text or voice, by simply it being on your home screen wherever you are.
44:21
If you're at a museum, if you're in a new neighborhood, and that's a one tap away.
44:27
Like our goal is to make intelligence either zero or one tap away, not one prompt away. So question.
44:36
How do you How do you How do you make this product free so that everyone can use it?
44:40
Will we see ads on the home screen of the iPhone ad-supported?
44:47
I think ad-supported could make sense, right?
44:49
I'm walking by a coffee shop and I get I get an offer.
44:52
>> There's ads in Apple Maps now, so Apple's already doing >> notification stream in, so you you can really you know what I like.
44:57
Yeah, I I I Apple's kind of positioned I I think the interesting thing here is like you like you guys can operate like you can kind of wake up and ask yourself like what would Apple do if they were like truly excel excited about AI versus like seemingly scared of it.
45:17
You know, I've posted about this a little bit with with respect to Apple.
45:21
Apple relies on a deterministic world, right?
45:24
Like a world where lots and lots of elements from design to the experience to the underlying context, that doesn't change as much and it's very deterministic.
45:33
So for example, iPhone is very much kind of a software is very broadcasty, right? It's a one-to-many.
45:39
They write it once and it runs for everybody and roughly speaking, it runs exactly the same way.
45:44
Now with a non-deterministic world, that could change drastically.
45:49
Like for example, for when we, you know, give this out to everybody, everybody in their Everybody has a very different experience with our app because it's completely non-deterministic.
46:02
And Apple lives in a deterministic world and having to transition into non-determinism and non-deterministic software is actually a really non-trivial transition, especially for a company like Apple where every single corner or every single thing needs to be tightly controlled.
46:17
So, I think for us we're kind of paving a path where we can marry some level of like expectations and determinism with the beauty of non-deterministic elements of AI and create a really great user experience around that that lives on your home screen and works for everybody.
46:35
Um that's how we think about it.
46:37
So, we're kind of maybe in some sense moving ahead of Apple who has to deal with a few billion users, you know, just just a minor amount of users.
46:44
Um so, I think I think that you know, this this world deserves more experimentation like like what we're doing uh in terms of both user interfaces and experiences and feeds and ranking.
46:57
And And Jerry, going going back to your point on on monetization, like I think that's the number one thing that I think about quite drastically.
47:05
Look, we're trying to capture real estate on your device that is the home screen that is available at a glance.
47:11
And you know, I think I posted about advertising the greatest billboard of all time. Exactly.
47:16
I mean, it is it is insanely powerful if we can activate that.
47:19
Now, that's a tall order, but at the same time, you know, like I've I've posted about ads and advertising.
47:25
Look, I've a I've been in technology for such a long time from consumer, you know, whether it's like feeds at Facebook or you know, even Google and whatnot.
47:33
But you know, you you you you start to think about advertising has done a lot of good for the world, you know, it has actually made things accessible and and and I think generally if advertising is done well, it is actually one of the most useful economic paradigms in terms of delivering equality in services to people who would have otherwise not been afforded.
47:54
Um so, I believe in advertising.
47:56
I believe in good advertising, I believe in advertising that is actually like um uh complimentary to the user experience and not necessarily taking away from it.
48:05
It's tricky to do, um, but you know >> worst ad experience I've ever had as as an ad enjoyer was like in college I was buying a Kindle and they were like, "Do you want the ad supported Kindle for like $100 or the ad free Kindle for like $120?" You remember that?
48:23
>> a college student I was like, "Uh I don't I don't think I'll mind ads. Why not? Were they bad?
48:26
And it's on the home screen when the device is locked.
48:29
And they're just showing me books that I would never read. So it's bad targeting?
48:35
So it's terrible targeting and it's a device that's just like sitting around my house all the time and it kind of looks like, "Wait, you're reading that?" Yeah, yeah, yeah, yeah.
48:44
Um, so if you can avoid that Yeah. Definitely.
48:46
Uh there's a question from the chat.
48:48
Uh why are you anonymous?
48:50
Do you plan on continuing to be anonymous?
48:54
Uh I mean I I imagine as you grow the business like it would be interesting to stay anonymous forever but you know at some point a journalist will want to know and I imagine that unless your opsec is super tight it'll come out. Not that it's like bad.
49:08
I I'm just wondering like how have you processed the anon thing? That's a great question.
49:12
You know my entire online existence as it exists today with respect to this account is is a giant accident because um I was trying to find my old username and password for cuz I just wanted to post a little while ago maybe you know whenever I started posting.
49:28
But I think when you guys actually started started TBPN as well and I I think I was really like >> must have gone from like a thousand followers to like >> 80k over a hundred within the first few months of of us. It was kind of nuts.
49:43
Okay, so the whole story is you know I I I was kind of I was like, "You know what?
49:47
I just want to read and I maybe I'll reply or something."
49:48
And I had a lot of fun and you know whenever I'm having fun, I like to double down on things.
49:54
You know, maybe not change change it around too much.
49:56
Look, I think certainly this this world is going to change at some point.
50:01
But for in the in the meantime, you know, I love leaning into fun new things.
50:04
You know, if you want to do anything new in the world, you got to do it a little bit differently.
50:07
You got to be a little bit more unique.
50:09
You got to be a little bit more mysterious, a little bit more Yeah, I don't know.
50:14
All of this stuff is just so wild to me, right?
50:16
Like the anonymity aspect of it and the axe culture and the anons around it.
50:20
And you guys have had, you know, Yeah, you can never dox. I'm sorry. You can never dox.
50:26
I mean, like Banksy Banksy getting unmasked, is that good for the is that good for the brand?
50:30
Like Like you could be You could be like taller than John Gigachad.
50:37
It won't be enough, right?
50:40
We we all picture you as a philosopher king.
50:43
Oh, it's beautiful, isn't it?
50:43
I mean, I I my my bio and my like the actual content are like sometimes Sometimes the same and sometimes disjoint, but that's I think the beauty of it.
50:52
So, in that realm, you know, like I was actually talking to some people around this and I was like, I I I sometimes I basically kind of do what I feel like and right now it's like just been so much fun to to kind of lean in on this world and and it you know, but I think certainly I'm I'm I'm I'm more like I'll I'll I'll marry myself to the zeitgeist, if you will.
51:15
And if that if that calls that, then I'll I'll I'll continue and we'll see what happens, you know.
51:19
>> in the game, married to the zeitgeist.
51:22
Uh okay, take me through Take me through iOS development like current status.
51:27
Because this seems like a really good idea that people would want.
51:34
Uh I do think people are bored of the grid and having something that's more dynamic and agentic makes a ton of sense and I think you could deliver a ton of value, but my fear is that Apple's just like, "No, that's our real estate."
51:47
So, is there a clear path right now through like widgets and the shortcuts API to actually do interesting things, or am I going to have to like sideload a different OS?
51:59
Like, how how like consumer friendly and like easy will this be, or will you be bumping up against the walled garden of Apple pretty quickly?
52:10
Um that's a really great question.
52:10
Look, every single thing we do is within the confines of the Apple ecosystem experience in the way that they've designed and made it work.
52:19
And we've designed our product to fit almost like a glove in that in that ecosystem.
52:23
Um you know, when when you onboard into our experience, you just connect the things in your life that you think are you you would want more >> Yeah.
52:33
uh The server-side connections, I totally get.
52:35
Like like all of that makes sense. You can Yeah.
52:37
like like OAuth with the email and use APIs or MCBs.
52:41
Like, there's a million things you can do on the server.
52:42
What I'm interested in is like is like how big can the widget be, or can you actually take over the whole home screen?
52:52
We can we can take over the the we basically ask you to install two widgets, a medium widget and a large widget that encapsulates the entire home screen.
52:59
And those work in dynamic together.
53:01
So, the the medium widget will basically what we call a wildcard widget with internally, which shows you precisely what you might need to know at this point in time.
53:10
And then the rest the big widget is what we call a for you widget, which is just a feed.
53:14
And you know what we're doing, John?
53:17
I think is we're building kind of the new iteration the Facebook newsfeed 2. 0 Yeah.
53:21
that's entirely AI generated about your life, highly personal, and that lives directly on your home screen.
53:29
And you can browse it as easily.
53:31
The feed paradigm is so familiar with individuals.
53:33
And the beautiful part is that it's all like AI generated and AI mediated.
53:37
Every We We 22 agents that work continuously to generate content for that feed.
53:42
It's funny because like everything everything that's fancy, I'm like, yeah, that's easy.
53:49
And then like getting people to install two widgets, I'm like, that's the hard part.
53:53
And I don't know if I'm right, but like it feels like like like that it like I'm still in like prosumer territory, but that's a good place to start and then you can hopefully make it easier and then maybe Apple opens it up to a point where like you download an app and just by clicking yes, it just installs the widgets by default or something.
54:11
It it it does feel like the the biggest thing is like I just love when like these new surface areas are explored.
54:17
I mean you you you mentioned Nikita, but like he's but he's done a great job of really understanding all the different hooks, what you can do within iOS, you know, pushing those to the limit, creating like new UX, new experiences on top of like what Apple gives you and it feels like that's really under explored. So awesome.
54:38
>> of uh Have you thought about build trying to build any products within within any of the LLM ecosystems just given that they they already have an exist you know, massive existing user bases?
54:51
>> That's a great question and you know, I've definitely explored like every single thing with respect to an API or a platform that comes out, you know, I you know, for example, the WWDC APIs that come out every year.
55:01
I I read them like like the Bible, you know, like I would I Bro study.
55:13
Um you know, that that's my that's my you know, religious holiday or whatnot and every platform >> is the Pope. He's your Pope. >> Yeah, exactly. >> We get it. Yeah.
55:21
Um and you know, so I scrounge these.
55:24
scrounge these. I think generally these API the sort of apps or chat GPT apps are it's unclear to me what the incentive structures are for the app developer just yet and it's unclear to me why applications deserve to exist
55:37
inside of an LLM just yet besides just adding more context cuz theoretically an LLM is powerful enough to even generate an app to be able to do something in which case I'm not sure exactly unless you bring some highly proprietary data like Zillow or whatnot. Maybe some of
55:49
Maybe some of these experiences work but otherwise I don't know if the small time developer you guys remember the flashlight apps and the the lighter apps on the iPhone like you know you're not really seeing those types of experiences in LLM.
56:02
Probably 12 year old was the beer app. The beer app was good.
56:05
Just thinking that thinking that that was like that was peak humor.
56:09
>> What about the I'm rich app that was like $10,000?
56:14
It was just a picture of a picture of a diamond and it was just like you could just open a picture on your phone but if you bought that app you could show people that you just wasted 10K on a iPhone app or whatever.
56:24
I think it literally maxed out.
56:25
It was the most expensive app you could possibly like type into the App Store.
56:31
Uh I think the guy sold like over 500 copies before Apple removed it. >> Yeah.
56:35
Not app for a real person.
56:35
So I think he he made 500 times a thousand dollars and it was incredible.
56:40
See these are the kinds of experiments and creative elements that you know I think deserve to exist in the world today and I think you know we're a few a handful of individuals that are kind of trying to make that happen and we're trying to be really creative really fun really interesting engaging and AI is a super powerful tool to be able to do that more powerful than the original iPhone APIs. Like holy crap.
57:05
I think we're we're we're early but we're going to try to It's a dream.
57:10
Like like there's so much like there's You're doing this you're doing this the right way because there's another scenario where like you could raise a series A right now like or like you you know You have a team you have the technology and and the waitlist like you'll be able to test things and experiment and learn like there's so much opportunity.
57:27
What what an exciting time.
57:29
Thank you so much for joining the show. This is great. Thanks a lot guys. I really appreciate it. have you on.
57:34
1000% and maybe next time we'll talk about hot takes. For sure.
57:36
Oh yeah, what do you think about this AI powered cannabis vape with blockchain rewards?
57:44
I'll have to I'll have to try >> John, you didn't you didn't So So John was John showed me like a screenshot.
57:48
He was showing you the website for this this morning and I didn't realize today is 420.
57:53
So that's what like this is like a 420 joke. >> Is it a joke though?
57:57
I think it's a real website.
57:59
Like I think it's >> Yeah, yeah, John, you can make a joke website. Did you know that?
58:02
I know, I know, but I I I think they're >> design, man. Cloud design. You could do anything.
58:07
Okay, so you're telling me if I put this in the Wayback Machine and it shows up as of yesterday, it's not a joke?
58:16
Cuz I bet you this existed yesterday. Let's see. Let's see.
58:18
Let's I bet you if they were planning to make a >> April April 6th, it's in the it's in the Wayback Machine. What does it say? It says Let's see. It's loading.
58:30
It's got blockchain still.
58:30
I think these are hustlers who have been just tacking on every single possible trend that goes viral as possible. I don't know.
58:37
We'll have to dig into it.
58:39
Well, thank you so much for joining the show, Signal. >> Yep.
58:41
Fantastic >> news and congratulations on the progress. Have fun.
58:45
And we'll talk to you soon. Cheers. >> Have a good one.
58:47
Uh up next, we have Ethan Ding from Tech SQL.
58:49
He is the co-founder and CEO here to announce >> It's time to talk about enterprise analytics workflows. >> I think we had him.
58:59
Let's check in with the team and make sure that he is here.
59:05
I believe he is, so let's bring Ethan Ding in from Tech SQL into the TVP and Al Freedom. Ethan, hello. How are you doing?
59:13
>> What's going on, guys? Oh. How you doing? Uh how's it going? It's good. We have two of you.
59:18
So please introduce both of you.
59:22
>> it looks it looks like it's being filmed on a you know, phone camera from 2005, but but uh we're excited to have you on. Hi, I'm Ethan.
59:33
I'm the CEO and co-founder of uh Work. Yeah.
59:36
This is my co-founder Mark, our CTO.
59:38
Uh we're we're we're actually at a customer off- office or we're onsite.
59:41
Uh and this is actually a company does not I I think like like like IP bans like Zoom uh from their from their internal network, which I found out like really last second. Interesting. Okay. No, no, it's great.
59:54
So, is I'm I'm super we're super excited to have you guys on.
59:57
Uh walk walk us through history of the company since it's it's your uh first time. Yeah.
1:00:04
Uh I think we started this in like late 2022 uh right before ChatGPT came out.
1:00:09
Uh we had this uh this idea that uh we if we if we spent a lot of uh money and uh time on like uh try to make analytics work, uh it'd be uh it'd be worth something.
1:00:19
We we really didn't know what we were doing when we first got started.
1:00:22
Uh since then, what we've like really like realized is um after after like 2 years of uh uh rebuilding the product like 10 times over, uh we landed on on something where, you know, I I think like the typical enterprise has like 150 databases, uh 10 different dashboards, BI tools.
1:00:37
They have like 20,000 different charts, uh another like 400,000 tables.
1:00:40
And every single vendor wants you to like migrate into their thing and like drop another 20 million dollars on like systems integrator for another 10 years till they do the migrations.
1:00:49
And we're like like let's like build a thing that can like connect everything um and and and hopefully be uh yeah, the do do for do for analytics what uh what like high-frequency trading firms did to like stock markets.
1:00:59
What was the first uh like analytics stack?
1:01:04
Because if you're pre uh GPTs, are you just doing like word clouds or like clustering based on keywords and tagging different phrases as they flow through a system?
1:01:15
Like what what what was the initial like, okay, uh there's a stream of data, there's a bunch of text in a variety of databases.
1:01:24
Like, how are you giving the customers value from that?
1:01:28
Well, it was pre-chat G- GBT, but still post-GBT. Okay.
1:01:30
And so, yeah, GBT 3, uh and but um I think as we all know at this point, the uh the the actual view of that was we overstated, at least for business stuff.
1:01:41
And so, yeah, text box on the right, we type in your question. Sure.
1:01:45
Like, how do I get revenue?
1:01:47
Then the text box on the left with with the SQL. And then Oh.
1:01:50
you run it, and you uh copy it, and then paste it into your whatever tool. Interesting. >> that was it.
1:01:57
But, we've come a long way from that. Yeah.
1:02:00
So, walk us through I mean, you don't have to tell us who what customer you're with today, but uh what does actually uh as a group of co-founders going to a customer site, like, what are you doing?
1:02:09
How deep in the weeds are you?
1:02:13
Is it just sort of like a high-level pitch, or are you rolling up your sleeves and and working on actual integration? Yeah.
1:02:20
Well, I I think like today today's session was basically a like walk us through like the the I mean, every single Fortune 500 company like basically spends like nine figures on like AWS, GCP, and Azure.
1:02:29
And they spend another like like 10 figures on like paper that like like like like manages all these systems.
1:02:37
Um and and it's kind of this like constant like war of like you you go from like spending $20 million to like like a Teradata on prem to like spending like $30 million with like a Databricks in the cloud or something.
1:02:44
Um and so, like what we're what we're we're kind of map out with them is a and probably still graphic that they want to be the size of AWS in like 3 years, right?
1:02:53
And and they're and they're an enterprise-oriented company.
1:02:56
They expect that basically come out of like um companies like the the that we're working with's like budgets.
1:03:00
Um and so, it's they basically expect them to take their entire IT budget of like let's say like 200 300 million dollars, double it, and like like materialize this money out of like thin air, and like spend it on inference.
1:03:10
Um and they're they're they're walking us through like the the um parts of their road map where, you know, what kind of SAS can they sunset, what kind of labor costs are they like thinking about like the trade-offs around on like what time horizons they're like freed up.
1:03:22
Um, and also like like like what kind of like workloads that are going to be extremely expensive that they can like kind of it's kind of like start basically triaging off like the large like models.
1:03:30
Cuz because at the end of it like these are these are kind of the people like when you see like the token charts, like everyone's token messing, these are kind of the people who like pay the bills on like those tokens.
1:03:40
And like like they notice the size of that bill, like you know, like blowing up like 10x like you're over here? Um, interesting.
1:03:45
It's interesting side of the equation I guess like people don't spend a ton of time talking about.
1:03:50
>> Yeah, how have you been processing the SAS-pocalypse narrative?
1:03:54
Benioff was given some pushback.
1:03:56
Other folks were very bullish on it.
1:03:59
There's a whole bunch of different data points.
1:04:00
I've been just shocked that we haven't seen revenue declines from really any software company that's been targeted, although you know, you could talk about the long-term, but the growth like these companies are still growing even if they are in like the direct path of the AI companies.
1:04:19
Yeah, I for like the for the longest time I assumed that like everyone likes to buy like good enough.
1:04:25
I think really in the past like three months I've heard like like six different CIOs or CDOs of like Fortune 100s like talk about how they're ready to like like Salesforce is like increased like their headless like tax and they're ready to like like like do like a two-year migration like off into like like Postgres or something.
1:04:45
It's it's not like they're going to another vendor.
1:04:46
They're just like like I need to free up money to like set on GPUs like set GPUs on fire.
1:04:48
And I'll pay like anybody to like like move me into like like a Postgres instance in like like Google Cloud or like like AWS. Interesting.
1:04:57
Okay, so that's a little bit of your opportunity. You help with migration?
1:05:02
Uh, that that one that one's kind of adjacent to us.
1:05:03
We we look a lot more like low-level infrastructure like like Databricks, Snowflake, like Tableau and otherwise.
1:05:08
But it's it's interesting like a CRM is basically the second most important system of record at an enterprise next to the ERP. Yeah.
1:05:16
They're willing to entertain like moving entirely off CRMs within like a two-year time horizon.
1:05:19
Maybe they'll completely fail.
1:05:21
But like the willingness to like like like forge into that has been uh like like like an order of magnitude more higher than expected.
1:05:28
And surprising based on the profile of company.
1:05:33
That's something you don't normally expect from like Google or Facebook, like the most mature engineering companies in the world. But >> Yeah.
1:05:39
you you see this type of stuff starting to come from 100-year-old companies as well. >> Interesting. Interesting.
1:05:44
And is is is that driven more by they think that over the long term there will be a net cost savings to having their own system or more that they want something that's completely bespoke and more custom to their business?
1:06:03
Um it's mostly not There's an interesting thing Larry Ellison talks about uh when it comes to like enterprise sales, which is not like like enterprise sales is not like buying like like like Gucci bags.
1:06:13
It's it's much more like like any given year you have a CIO come in like right like this the half-life of like a CIO is like like five years before they they retire. New one comes in.
1:06:23
They have to like start a set of like new initiatives. Yeah.
1:06:24
Often like they're going like they're they're finger testing like the market and trying to figure out like who who has the best vibes. Sure.
1:06:31
Like basically who who Okay, whoever has the best vibes, I'm going to throw like eight figures against and I'm going to like take that eight figures away from like someone like a company that has like like worse vibes. >> Sure.
1:06:41
Um there's this like weird um self-fulfilling prophecy where They're vibe procuring. Yeah. They're vibe procuring. Okay.
1:06:47
Like you walk into a room, you can tell when that like company's stock is up.
1:06:52
You can tell when the CEO is like extremely cocky.
1:06:55
You can tell like when the when the FAEs and the sales people are like listen, like you don't even have to move this today.
1:07:00
I'm going to get your business next year no matter what cuz I know we're on the up and up.
1:07:03
And you can also like tell when like a vendor is like desperate, right?
1:07:06
And they're like like moving for discounts, right?
1:07:07
When when when some when when as long as the perception that a company like the market is short a given like SAS vendor, um customer start asking for discounts.
1:07:18
The most aggressive ones go first, but now like all the sellers on that team are like like that like you know, they're they're traumatized between like the next set of renewals.
1:07:25
So they're they're progressively going to give more and more ground.
1:07:27
Um it's kind of a rough uh yeah, wouldn't want to be one of those right now. Interesting. Interesting.
1:07:34
Well, Uh your business is growing, you're raising money.
1:07:35
Tell us about the latest round.
1:07:39
Yeah, we um it was actually like a like a two two-part round.
1:07:42
Um the first like led by like Hoff Capital and the latest part like uh Blackstone. How much did you raise?
1:07:50
Uh I think it's 17 total.
1:07:55
Well, this was uh this was awesome, guys.
1:07:57
I really I really uh enjoyed uh speaking with you both and uh thank you for making time on uh well, while you're hanging out with your customers and I appreciate the perspective.
1:08:06
Let's uh let's do it again soon. >> the perspective.
1:08:09
Let's uh let's do >> Thank you. Have a good one.
1:08:11
Have a good rest of your day.
1:08:13
Uh up next we have Matt McKinney from Loop.
1:08:15
He's the co-founder and CEO.
1:08:18
Raising a big Series C in the waiting room.
1:08:22
Let's bring him into the TV and the ultra dome. Matt, how you doing? What's going on, guys? Not too much. Good to have you here.
1:08:27
Uh first time on the show, why don't you introduce yourself and the company? I'm Matt McKinney.
1:08:33
I'm the co-founder and CEO of Loop.
1:08:35
And our mission is to unlock value that's trapped in the operations that power the physical economy.
1:08:41
And we started specifically in the back office where no one else wanted to go in back office services and automating things like accounting and general ledger coding and and payment services.
1:08:52
And all we do exist is to make our customers more efficient so that they can better serve their customers.
1:08:58
And we work with some of the most important companies in the world, 20% of the Fortune 100. Wow.
1:09:01
And excited to be on with you guys. Yeah.
1:09:06
How I mean there's a different world when you say like procurement or accounting that you could have been like we're a agentic accounting firm or something and it feels like this is much more cross-functional.
1:09:20
How are you actually positioning like the integration? Who's the buyer?
1:09:22
How how does the how does the business like instantiate itself inside of your customer?
1:09:31
Yeah, we started we started with a very acute problem which is if you look at the supply chain industry Yeah.
1:09:37
roughly 30% of invoices are wrong or they have an error so clearing of them is really painful. Yep.
1:09:41
And because of that a bunch of services firms popped up specialized services firms popped up. >> Sure.
1:09:48
And all they do is address address that specific problem which is you've got to adjudicate this invoice, you've got to ensure that it's accurate, you've got to remit payment to the truck drivers and the carriers across Yep.
1:09:58
the world and that's a big industry.
1:10:00
It happens to be a $5 million industry alone and it's all done with human labor and obviously LLMs presented a perfect opportunity for that but I think what got my co-founder and I most excited was really the data.
1:10:13
If you can go organize the data then you can obviously automate things like we just mentioned the accounting but you can use that as a a wedge to expand into adjacent use cases whether being compliance or planning or procurement and continue to unlock value for your customers. Yeah.
1:10:30
So what does it look like for a customer to actually onboard?
1:10:34
I imagine you need access to their emails like the actual PDFs of the invoices, whether things have gotten paid.
1:10:40
There's often like multiple versions of a particular invoice and then you need to plug into bank data to see what I what's actually moved around or accounting systems like how long does it take to integrate and how key is that? It's wild.
1:10:53
I mean what's so wild about a chain?
1:10:55
Supply chain is just a network of networks. Yeah.
1:10:57
And you've got, you know, a transportation carrier, you've got a supplier, you could have multiple versions within your own enterprise.
1:11:06
A lot of these big companies they do a bunch of M&A and so you've got all these different versions of the truth.
1:11:09
So just take for example the weight and dimensions of a package or a shipment.
1:11:16
There could be seven different versions of the weight and dimensions for that package.
1:11:20
And so you need almost like a a data auditor itself to prove that that's the correct data.
1:11:25
And we get it from a bunch of different sources.
1:11:27
We get it from, you know, email, we get it from EDI, we get it from API connection, we get it from Excel spreadsheet, PDF, you name it.
1:11:34
It's just really messy, unstructured data, data that no one's ever organized.
1:11:39
Quite frankly, no one was able to organize until the power of LLMs came out.
1:11:45
Uh does do When you talk to customers, do they care about the AI buzzword at all?
1:11:51
Yeah, are they trying to buy AI?
1:11:53
Or do they just want a solution? >> Not again.
1:11:55
Like how are you thinking about how how front and center AI is in your value prop and pitch?
1:12:03
All our customers want is just outcomes. Yeah.
1:12:05
And they don't really care how you deliver it.
1:12:07
Now sometimes they might have a top-down AI mandate sure that they're looking to check the box but at the end of the day they don't care how the sausage is made.
1:12:15
They're buying an outcome.
1:12:16
That's all that they want.
1:12:16
And if you can demonstrate that you can deliver a superior outcome, it's better, it's faster, you're you know, for example, you're finding more errors or whatnot and you faster resolution times so you can close your books faster.
1:12:29
That's what they're buying.
1:12:29
They're not buying a generic buzzword fit into their, you know, their checkbook.
1:12:34
They they really want to buy the value. Yeah.
1:12:37
What is the value of like getting this business to scale?
1:12:40
Is there is there something where you can, you know, optimize the supply chain, introduce different clients that need to different resources and help them buy the best product at the right time or reviews or even just like panel data of like how the economy is moving.
1:12:57
We've seen that from some financial some fintech companies.
1:13:01
Uh like how are you thinking about the value that's unlocked as you become a platform?
1:13:07
Yeah, there's more you mentioned like procurement for example.
1:13:09
There's more obviously when you you have a bunch of data that you can use and say this is good, this is bad or you should be working with the supplier and you're not cuz we see it over here.
1:13:18
But I think that you know really building context across the network is probably where we see the most gains where you can take learnings from a carrier that's working with you know suppliers working with multiple parties in the network and then say oh well this carrier always likes to build a specific way and so propagate that learning through the LM's context across all the all the companies that work with that carrier.
1:13:39
And I think that's really I'd say the unlock and automation that you get at scale and then obviously the you mentioned the intelligence one the time to value.
1:13:46
You're able to get someone on much faster cuz you're working with 95% of their suppliers instead of 2% of their suppliers.
1:13:51
That's a huge win as well.
1:13:53
What were you doing before this?
1:13:55
Did you always have a love for back office supply chain optimization?
1:14:00
>> I I can tell you I can tell you have since he was a boy.
1:14:05
I came out of the womb and I just said I want to automate the back office. Yeah. Complex logistics.
1:14:12
Yeah, I I've always just been obsessed with systems and making them more efficient and I think you know when you look at the physical world and its supply chain you know the trucks and the train and that stuff's just so exciting you feel like it's the last frontier where you can truly unlock that.
1:14:26
I mean look supply chain alone just in the US is $11 trillion in spend. Wow.
1:14:30
You know one of the largest contributors to GDP globally. Yeah.
1:14:34
Yeah, if you want if you want to have an impact on GDP and Oh too high.
1:14:40
Sorry, I was giving you that for the $11 trillion.
1:14:42
You said the biggest number so That was huge.
1:14:44
If you want to if If to have an though, on GDP, at the end of the day, GDP growth is just productivity growth, and technology is the leading advantage in that.
1:14:52
And you're you're saying $11 trillion in spend goes to supply chain, and no one's really touching that.
1:14:57
And we got to go attack that problem. Yeah.
1:15:00
Uh yeah, I have I have so many more questions, but uh But before Yeah, before that, we were My co-founder and I were at Uber and Okay. Yeah.
1:15:05
early on the freight team, and we saw a lot of the you know, the real world there, where you had messy PDFs, you had bill of ladings, proof of deliveries, just a total data mess, to be honest with you.
1:15:17
And we knew that there had to be a better way. Yeah.
1:15:19
Dude, perfect perfect VC pattern match. Uber freight team.
1:15:24
Yeah, it's a great team, great company.
1:15:26
We know so many entrepreneurs that came out of Uber.
1:15:27
Uh tell us about the round. What's what's going on? How much did you raise? We raised $95 million.
1:15:36
Couldn't pull together that last five million.
1:15:39
>> What was going on, buddy? Innovated you. Innovated you. Sandbagging. Sandbagging.
1:15:43
No, you had to set up I had to set up the next round.
1:15:45
We got to leave a little nine-figure a little bit for the next one. Yeah, exactly.
1:15:51
Uh we're super excited Really really stacked Valor, Atreides, 8VC, Founders Fund, Index, JP Morgan. Wow, you got everybody. Congratulations.
1:16:02
>> Wait, where are you guys based? Sorry, I missed that.
1:16:03
We're based in San Francisco.
1:16:04
We got offices in Chicago, as well as in New York.
1:16:06
Is that because Chicago's a major like logistics hub with the trains and trucks and stuff?
1:16:13
Yeah, there's a lot of There's a No, there is there is a major I'm not making this up, right?
1:16:17
Like with the boat cuz the boats come through the the the lakes and like it was like a major hub of transactions.
1:16:25
>> Is that cuz Chicago has trains and trucks? They do. This is real, right? Am I wrong?
1:16:30
>> You're not You're not wrong. I'll give you stats.
1:16:31
So, 30% of goods that enter America go through Chicago. Thank you. Thank you. 30%.
1:16:40
>> That's They got trains and trucks.
1:16:41
You're like, "Oh, Chicago.
1:16:41
Why is it such a weird pick?" It's not. It makes a ton of sense.
1:16:44
Well, Uh good to meet you, Matt.
1:16:46
Uh congrats to the whole team.
1:16:46
And uh hopefully hopefully you're back on the show uh this year with some more news.
1:16:52
Really appreciate it, guys. Thank you.
1:16:53
Love the show, by the way. Thanks, you. Have a good one.
1:16:57
Uh up next we have Eric Anderson from Alloy Therapeutics.
1:17:01
>> I love I love messing with you.
1:17:01
You love messing with me. Never gets old.
1:17:04
Well, without further ado, Alloy Therapeutics has raised a Series E to build full-stack AI biotech infrastructure.
1:17:13
Eric Anderson is here live What's going on? Eric, how are you doing?
1:17:16
Gentlemen, I'm doing great today. Yeah, good to have you.
1:17:20
Thank you so much for hopping on.
1:17:21
Uh first time on the show, please introduce yourself and the company a bit. I'm Eric Anderson.
1:17:25
I'm the CEO and the founder of Alloy Therapeutics.
1:17:27
We're a biotech infrastructure company that works with a bunch of companies all over the world helping people discover and develop drugs. Okay, infrastructure.
1:17:36
What exactly is going on in the biotech stack?
1:17:38
I would imagine everything from centrifuges down to writing PDFs for the FDA to trials.
1:17:43
There's so much that goes into that.
1:17:45
What are What are you focused on specifically? You got that.
1:17:48
So, the the technology we have is really around more drug discovery and then into drug development.
1:17:52
So, the folks that do regulatory, the folks that do clinical, we work with them to discover drugs with the companies that we help to support.
1:18:00
So, we work with big pharma companies.
1:18:02
We work with small biotech companies. Okay.
1:18:04
What's going on in the industry today, the big trend right now is when we talk about infrastructure, who's going to actually do the wet lab work today in the lab?
1:18:11
In addition, we've got everything going on with tech bio of all of this in silico work that's happening. It's really exciting.
1:18:16
And sort of bringing those things together.
1:18:20
Yeah, and the idea is the idea is like you can have like million you know, a million times more ideas for different drugs, but then you still have the constraint of the physical world needing to kind of be able to actually run experiments until ideally we could simulate a lot more in the future, but maybe we're not not there. yet.
1:18:37
right, and you can simulate all these things, but it's a bit of the design, build, test, and then you learn.
1:18:42
It's that It's that loop we all know. Yep.
1:18:44
And right now in the biotech space, we've made some incredible progress with gen AI and machine learning capabilities to come up with a lot of those ideas.
1:18:52
You got to close the loop then and actually be able to test them.
1:18:54
And then there's a lot of skill that goes in just the skill of drug development of of what makes a good drug.
1:18:59
And connecting those things together is what we do uh really well.
1:19:03
So, how how much of this will wind up looking like an AWS for drug development?
1:19:07
I can provision a certain machine and you have it and I can interface with it all over uh you know, the internet and you will do all the physical stuff for me. Yeah, that's part of it.
1:19:19
So, AWS just launched a service Amazon launched a great service that connects these these generative uh companies back to a back end of how you manufacture the protein and you test it. Okay.
1:19:29
That's one small piece to the process, I would say.
1:19:31
A lot of scientists out there that can design things in silico uh and then send them to a lab like that.
1:19:38
That will help Is that not like a crazy side quest for them?
1:19:40
Like it's We did AWS has like centrifuges now and like No, AWS is actually just connecting them together.
1:19:48
No, it's pretty pretty wild.
1:19:50
Okay, okay, got it, got it, got I think what they're going for there is that they want to be the cloud.
1:19:53
If you're going to do your compute to come up with these with these in silico things, they want to make sure they see all the traffic and then just connect it to anyone else on the back end.
1:20:01
That's what I think what they're doing. Got it, got it. Yeah.
1:20:04
Uh so, um can you zoom out for me and and just do a temperature check on biotech?
1:20:08
We We read one article about how uh Boston's going through a really tough time at the same time like every time I open up the Wall Street Journal, there's a new billion-dollar acquisition.
1:20:19
>> last year felt like like the dark the dark ages for biotech.
1:20:22
It felt like everyone every every every uh bio biotech investor that we were talking to was like, I don't even know why you'd keep investing in in these companies.
1:20:33
Like the returns have been so bad.
1:20:33
And then this year is like the biggest year of biotech M&A since 2008.
1:20:39
>> just rich from the GLP-1 boom, but I'd love to hear your sort of like narrative setting here.
1:20:43
>> Certainly with the GLP-1 boom.
1:20:43
Well, one of the trends that's going on here is that the industry has to restock the shelves for new drugs.
1:20:49
As drugs go off patent, there's these revenue cliffs.
1:20:53
And so Big Pharma is sitting on probably the largest pile of capital they've ever sat on.
1:20:57
And they look to acquire a lot of their innovation from small companies.
1:21:00
Those are the folks that we support to create new medicines.
1:21:02
So there's definitely a huge M&A trend that's happening this year and it'll continue to happen for the foreseeable future.
1:21:09
A big thing that's happening if as you read about that news in Boston though is we're doing drug discovery and development here in the US, but there's been a big shift to move it overseas and to offshore it and for Pharma to acquire assets from outside of the United States.
1:21:22
And so that's a that's been more of the big I would say the headwind for the domestic biotech space. Okay.
1:21:30
How are you feeling about just acceleration in drug development generally?
1:21:35
Like we you know, in in cybersecurity, agent decoding, like there's these very clear scaling laws and you know, we have the meter chart of the amount of time an AI system can work on a single problem. It's doubling.
1:21:49
It's on a very clear trend.
1:21:51
I haven't seen a chart that's like that for biotech, but it feels like we're going through advancements and we're just getting more cures.
1:21:59
So something's happening, but are you tracking it at a quantitative level yet or just qualitatively, how do you feel about drug development progress? Sure.
1:22:09
Well, we're living in an era right now where the trend of all of the drugs that we're discovering, we have an acceleration in the amount of innovation that's coming from our labs.
1:22:17
So so that is just an incredible trend that is supporting everything we're doing in the lab.
1:22:23
So that the byproduct of that is of course generating massive amounts of more data, making sense of that data, and this is where a lot of the machine learning is coming in is how do we digest all of the data that's being created in the industry, making sense of it, and then turning that into new cures as rapidly as possible.
1:22:38
So, that is an enormous trend right now in the industry. Yeah.
1:22:42
Uh and and the advances that we have just from literally using Claude and Open AI even in the lab and just day-to-day things, you're seeing a handful of things come together. Huh.
1:22:52
So, first of all, you see this explosion of data.
1:22:54
You see the wet lab capabilities largely looking the same.
1:22:58
And what's happening then is we're trying to organize that data and turn it into new cures as rapidly as possible.
1:23:03
And and in the background, what we have is a number of new companies, new entrants in the tech bio space that I think are just natively better at understanding this massive data problem and being able to make sense of it. >> Yeah.
1:23:14
And then on the other side, you have the pharma and biotech, which are actually you require all of those skills to actually make sense of what's going to work in in like a human biological system. Yeah.
1:23:24
>> So, what's coming together this Yeah, yeah.
1:23:27
>> this year, I would say, is that there's a lot more folks in tech bio that are getting better, but then we're just seeing the bio folks actually get better at tech.
1:23:34
So, basically, you're at this place where like the tech bio folks need more bio, and the biotech folks need more tech. Oh.
1:23:42
>> And if you bring in those things together, I do think we're going to have an acceleration in a lot of the cures that we're making. Interesting.
1:23:47
>> Uh Give us a view into how big pharma executives are thinking right now.
1:23:51
Are they confused why everyone and their grandma is injecting themselves with Chinese peptides, yet at the same time like hype more skeptical of vaccines than than uh maybe ever?
1:24:02
I feel like this kind of this interesting uh uh dichotomy.
1:24:10
Yeah, it's well, in the industry today, I would say the executives in pharma are looking at it from the same place they always do, which is about efficacy and patient safety.
1:24:15
And for we're looking for drugs that work and then proving that they work in in animals and then ultimately in humans.
1:24:22
So, peptides being injected into humans, I think everyone's just saying, "Hey, what's safe? What's efficacious?"
1:24:27
The FDA has done some pretty amazing things uh in this administration, I think, to give flexibility for what's allowed.
1:24:33
Uh there's been some incredible changes that have happened that I think will accelerate uh the pace of innovation and what we do in the regulatory space in the clinic as we're testing it in humans.
1:24:43
And I think pharma is apprehensive about the changes, but overall, they're excited that things are moving along and that we're going to see a lot of new drugs coming on the market.
1:24:51
Can you help me understand uh the flow to get to like a data boom in biotech?
1:24:55
Because I I would assume that that's more driven by uh like dropping costs of DNA sequencing than anything from the gen AI world because the but maybe there's something where the gen AI world can process data that was previously like locked up in PDFs or something.
1:25:16
Like what what is actually driving the data boom?
1:25:20
It's those things really coming together.
1:25:21
So, certainly the the continued falling cost of DNA sequencing and then the falling cost of all the other types of data that you can generate along with when you're sequencing someone's DNA.
1:25:30
So, if you go to a place like Function Health here or like what you can pull off your Aura ring or your Apple Watch, there's actually a massive amount of data that is that is being generated passively.
1:25:41
And right now, the ability to connect that data to that I would call it real-world data that we can connect to what's happening in patients is a level of complexity that we just haven't seen before in the data side. Yeah.
1:25:50
But it's got to be rooted back in basically the wet lab.
1:25:54
You're describing these things of of taking your DNA or your tumor DNA and you're learning from what's actually happening in a patient. Yeah.
1:26:01
And bringing this together is actually a huge data problem.
1:26:04
I I imagine you work with like mostly like big pharma real biotech companies, but we're also seeing this like boom in like a single person vibe coding cancer cure for their dog.
1:26:18
Like Yeah, it's pretty crazy.
1:26:20
>> Do you have a policy for whether like how small a team can be?
1:26:22
Because I imagine it's not far from you getting like an inbound from like a single person who's like, "I want to do this by myself. I'm a solo founder."
1:26:33
>> trusted with advanced AI bio weapons."
1:26:35
>> they should, maybe they shouldn't be. I don't know.
1:26:36
I just want to know how you've like grappled with it.
1:26:37
Maybe it's just not a business concern, so you don't need to worry about it, but I'd love to know like how are you processing that idea?
1:26:44
>> mean, I think everyone could be trusted with this generally.
1:26:45
So, that's actually not the problem.
1:26:47
Don't don't worry about kind of these fear-mongering that's happening on this front. Okay.
1:26:53
At our company, we service anyone who is interested in discovering new drugs.
1:26:55
And so, that's a lot of what we try to do with our company is how do we democratize access to many of these tools? Yeah, yeah.
1:27:02
We started in a particular place nearly 10 years ago, and that was before we had any of this gen AI work going on. >> Sure, sure.
1:27:09
It's It is lower that single-person biotech company or maybe just more of the the virtual biotech company where you've got five or 10 folks, and they can work with a different contract research organization to help do their drug discovery and development. >> Yeah.
1:27:23
That's been a trend for a while.
1:27:24
What's happening is we're just getting more efficient at it today. Yeah.
1:27:26
So, I do think the future biotech company is going to be much, much smaller and be able to plug into these different resources and be so much more efficient at coming up with ideas and testing them. Yeah, yeah.
1:27:37
I mean, it is interesting.
1:27:40
Tech loves to sing the praises of like the five- or 10-person team, but there are a lot of biotech companies where it's like one genius researcher who discovered something and a couple support staff, and then a lot of outsourced stuff >> all the way to, "Okay, we're ready to sell it," and it's mostly just a research organ- This is not entirely new there.
1:27:59
Uh you you mentioned that you're not worried about like doom related to uh like bio, uh but like, you know, how how how are you grappling with the idea of like somebody making a super bubonic plague or you know, some new flu like do you feel like there's safeguards or how have you processed that question?
1:28:21
There's lots of groups of folks that are worried about this and I think the United States military and some of the the consortiums we've been involved with are giving that thought.
1:28:28
It really comes down to though is you can make a lot of things that might be dangerous.
1:28:32
There's always a bad actor problem. Yeah.
1:28:34
The way that we think about that is through our biosecurity division, we try to make sure that the capabilities that we need to have in the United States are always available and accessible to us.
1:28:43
So call it medical access capabilities.
1:28:45
We've learned a lot of lessons in COVID. Yeah.
1:28:49
Everything from could we actually just test for for viruses in the community and do we have the reagents available to do that?
1:28:55
And then of course we had masks and everything else.
1:28:57
So from our perspective, we think about biosecurity as a way of making sure that you do all of those components from being able to surveil what's happening in the theater all the way out to can we discover and develop a drug very rapidly.
1:29:09
And there's some great Uh different initiatives that are going on of these ideas.
1:29:13
Can you go from a threat to 100 days later actually have a drug ready to go?
1:29:18
And our company and others participated in making sure that there's just a really robust response available with incredible supply chain. Yeah.
1:29:27
And sort of to make sure we can do everything here in the United States at all times. Yeah.
1:29:30
Yeah, I mean it really seems like like the the the advancement in the positive side.
1:29:36
Like we're seeing a major major swing to the upside right now.
1:29:39
Every time I hear about one of these new medicines or new treatments, it seems really positive.
1:29:45
There's a huge story about pancreatic cancer recently which was a a Yeah, there's complete white Right right now we've got a conference that's going on and we saw two different studies that were showing just for some of the patients that were on drug it was six years later they still had had no disease.
1:29:59
And that's what we all want to know about pancreatic cancer.
1:30:03
It is really really tough.
1:30:05
Oh, it's it's really incredible.
1:30:06
It's one of the worst worst cancers we have.
1:30:08
But I think this is the overall trend.
1:30:10
We are living in a world where we will cure everything that is curable, I think, in the next three decades.
1:30:15
It's really just a question of and maybe even faster than that.
1:30:17
It's a question of how fast can we accelerate and really give as many people as possible access to these incredible tools.
1:30:25
And just like in tech, I mean, where where you saw these very small companies be able to do incredible things in the last 5, 10, 15 years.
1:30:32
I was investing back during the first internet bubble.
1:30:36
Uh back in in venture capital 25 years ago.
1:30:38
And in those times, the world just looked a different place.
1:30:40
We actually middleware was >> 10 years old?
1:30:45
I I would I'd like 48 right now.
1:30:45
So, yeah, I was I was still a child >> late you look like late 30s. So, so that's Okay.
1:30:52
That's good good for you. >> at the time.
1:30:54
But it was incredible because there was a lot of the same criticisms that we're hearing in the tech space right now and it as it relates to biotech.
1:31:00
It was like we were wrong about everything back then except for what we were right about. Yeah.
1:31:04
We we did see the flow of investing coming in and many many things went bankrupt, but the things that didn't go bankrupt changed the world. Yeah.
1:31:11
And that exact same thing is happening today that you're going to see incredible number of winners.
1:31:16
And I do think biotech is going to be important part of the big market that everyone's going after in in the AI and ML space as well.
1:31:23
The tech space is going to go conquer biology as much as it has in other places.
1:31:30
But I would say also that pharma and biotech very much have a seat at the table.
1:31:32
Our academic researchers have a seat at the table there.
1:31:34
And it's really about bringing the two domains together.
1:31:38
They're going to be critical.
1:31:38
One of them is not going to go it alone without the other.
1:31:41
Uh tell us about the round. How much did you raise? How much did you raise? How much did you raise? How much did you raise?
1:31:46
>> Raised $40 million this time.
1:31:46
Yeah, we hadn't raised any money. There we go. Congratulations. Appreciate that.
1:31:53
We've been working hard to build a real business.
1:31:55
So, yeah, this is been a long long haul for us.
1:31:58
>> this is >> This is our series E.
1:31:59
I'm a little older back when I was a child, when I was a baby investing 25 years ago.
1:32:03
I I learned that you it's okay to just let her your rounds just like normal.
1:32:07
Our last one was in 2022. Yeah.
1:32:09
Yeah, I'm kind of old school in that way.
1:32:12
So, in 2022 we did a round and it between then and now we really laid down the infrastructure so that we had operations across 17 time zones now.
1:32:22
We're operating in the United States, Japan, the UK.
1:32:26
We have an incredible group that's actually working in the GCC right now in the Middle East.
1:32:30
Obviously, there's a lot going on there that's that's creating a bit of a headwind, but we're very bullish on the work we're doing in Saudi Arabia, UAE, Riyadh, and Doha, and and and over in Abu Dhabi.
1:32:41
So, yeah, it's bringing all this stuff together has been really important for us.
1:32:44
And just our view is you stitch together the supply chain of innovation, you link it to great world real-world data, and you bring a lot of AI and ML in there, and we're going to really accelerate the pace of drug discovery and development. Very cool.
1:32:55
Well, thanks so much for joining the show. Great to meet you.
1:32:59
Enjoyed the conversation.
1:33:00
>> Have a great rest of your week.
1:33:01
>> Thanks for having me on, guys, today. Have a great day. Appreciate it. Goodbye. >> Cheers.
1:33:04
Up next, we have Pippa Lamb returning to the show from Sweet Capital alongside James Wise from Balderton Capital Partners.
1:33:12
I believe they are in the waiting room calling in from across the pond.
1:33:15
Are you both over in the UK today? >> be. We are here. Given Given the news.
1:33:25
Well, welcome to the show.
1:33:27
Why don't what Pippa, why don't you reintroduce yourself and James since it's the first time on the show you can introduce yourself as well. Yeah, big day.
1:33:34
James' first time on TVP and guys. We're very excited. Fantastic to have you.
1:33:40
Yes, so those I you haven't met before, I'm Pippa Lamb.
1:33:42
I'm a partner here at Sweet Capital.
1:33:44
I'm also an active angel investor here.
1:33:48
And I also scout with A16Z, but generally sort of sit between the ecosystems of the US and the UK tech.
1:33:54
How do you I I didn't know you were you were the triple threat there.
1:33:56
How do you do How do you decide who gets who gets the >> the deal flow? That's interesting. No. Secret secret. Yeah, yeah. Uh James? James.
1:34:08
Yeah, first time caller but long time viewer. Thanks, guys. Great to have you. Having me on.
1:34:14
So, I'm a general partner at Balderton Capital.
1:34:15
We're a $7 billion venture firm.
1:34:17
We're based here in London.
1:34:17
And we used to be called Benchmark Europe. There we go. We got the buzzer.
1:34:21
So, back back in 2001 we were Benchmark Europe.
1:34:25
We we uh we spun out in 2010 when the European market really took off.
1:34:28
And for the last 4 months I've also been helping set up the UK sovereign AI fund. Okay.
1:34:34
Yeah, take us through that.
1:34:34
I think that's what we're here to talk about.
1:34:37
How long have the talks been going on? How big is the fund? What's the strategy?
1:34:41
What makes it unique in that it's so linked to the UK specifically?
1:34:46
Yeah, well about a year ago we kicked off this big AI opportunities plan.
1:34:50
There was huge news about it at the time.
1:34:51
And we've been working through all the various parts of that.
1:34:53
And Pivot can talk more about things we've been doing in data centers and compute.
1:34:57
But the fund was set off to really accelerate some of the UK's big UK AI successes.
1:35:05
But with a lot more than capital.
1:35:05
So, we've got about 500 million pounds. It's a starting point.
1:35:08
It's the entry ticket in this game.
1:35:11
But more importantly we're providing access to UK supercomputers here.
1:35:14
So, huge amount of compute.
1:35:16
We're providing fast track visas.
1:35:18
We're providing any data sets.
1:35:20
We're providing government as a customer.
1:35:22
So, procurement through government.
1:35:23
Basically to give a lot of the companies here that could benefit from working with the government a massive boost. Yeah.
1:35:28
I have to say that supercomputer is such an underrated term.
1:35:34
Whoever thought to rebrand supercomputer to data center Terrible. Terrible.
1:35:39
Because data center sounds so boring and terrible.
1:35:41
Supercomputer is awesome.
1:35:44
It's not going to take my my job.
1:35:45
I'm so into supercomputers.
1:35:45
I love these supercomputers. Yeah.
1:35:50
So, but that is your grandfather's >> center, right?
1:35:53
It's supercomputers like what IBM used to build years ago.
1:35:54
Yeah, yeah, yeah, and and and they have them in like cool scientific locations like CERN has one and like you always hear about oh, they're doing astrophysics on them.
1:36:03
There's so many cool things.
1:36:04
But that does link to, you know, where will the UK get the most leverage out of investing because I imagine that there's not a lot of value in just trying to like clone Google search or Instagram for Europe.
1:36:18
Like those platforms, it's fine, but at the same time sovereign AI does have value.
1:36:24
Where in the stack does that live in your mind?
1:36:30
Yes, so we're building out a whole range of talent, right?
1:36:32
So we're going to be doing everything from electron to token, but obviously working with American partners doing that and international partners as well.
1:36:39
Sometimes at the chip level, sometimes at the model level.
1:36:41
And then we're starting to focus on where the UK has huge advantages.
1:36:44
So life sciences is a huge area for us, right?
1:36:49
If you look at Isomorphic, which is actually a spin out of Google, you know, they're based here in London.
1:36:52
The whole team basically is European and they they may be the closest we get to a AI company getting a drug all the way through to approval.
1:37:01
They're sort of end-to-end AI design.
1:37:04
Outside of life sciences, loads of stuff in physics and material sciences.
1:37:06
So a lot of the AI science end of the spectrum rather than the AI slop end of the spectrum. >> Yeah.
1:37:15
Pip, are you seeing are you seeing like a an effect where entrepreneurs from around Europe are moving to London in the same way that folks from Chicago move to San Francisco to do startups?
1:37:27
Like is there is there a proper movement to make London like the destination for ambitious European founders these days?
1:37:37
Yeah, I think it's it, you know, I'm obviously fairly biased having spent a lot of of time here, but I think that the UK has always batted above its weight in terms of the deep R&D pockets we have here, you know, in terms of universities, the talent that are coming out of the local schools.
1:37:50
Um that's already created a very fertile ecosystem and I think that, you know, one of the reasons we wanted to jump on here today was because it feels like, you know, UK's having a bit of an AI moment.
1:37:59
It's not to say that we weren't already at the forefront of many of the innovations happening here.
1:38:06
You know, of course we always talk about Demis uh and as Hannes Salvis from uh you know, DeepMind that was founded in the UK.
1:38:13
Uh obviously we would have loved to have kept that here, but of course it also went with Google.
1:38:19
Uh but, you know, we have long been at the forefront of >> super critical that that you the the DeepMind maintained such a big presence in in the UK because you guys now with the sovereign AI fund, if someone wants to leave DeepMind, spin out, like you guys can be there to provide capital and uh and Exactly.
1:38:37
And that's what we're we're seeing now.
1:38:38
Um I think both from the idea that we want to be an AI maker, not just an AI taker, we're seeing, you know, grassroots innovation come out of the schools here.
1:38:46
But as you say, we're also having people either leave DeepMind um also in terms of our partners across in the US.
1:38:53
I think, you know, James can correct me if I'm wrong.
1:38:55
I feel like a lot of the uh you know, the first destination headquarters within Europe is usually in London.
1:39:02
I think that that is pretty much most of the large AI companies we've had.
1:39:05
Um so I think that there is definitely uh you know, it's always been a a good hub for AI, but we are seeing a lot of additional tailwinds of which sovereign AI is one of them at the moment as well.
1:39:17
We went through this period last year and I I might still be going on.
1:39:20
I don't really have a pulse check on it where uh every AI company's seed round was in like the hundreds of millions of dollars and I imagine that you're not going to spread this fund over just five companies and so do you think that >> No, John. It's one.
1:39:34
It's one that But yeah, I mean do you imagine uh being like like investing alongside other funds and doing more structured rounds where a lot of capital comes together to take like big swings or is there actually some sort of structural shift in the type of startups that are getting built today where 5 10 20 million dollars can actually put some points on the board early on and get in the game in a meaningful way?
1:40:05
>> that you guys can make a number of bets in the app layer.
1:40:08
You can bet energy maybe some science more science focused neo labs neo cloud.
1:40:13
Like I feel like 5 500 will like really can kind of like seed a bunch of different players but But yeah, how are you thinking about like the dynamics of like early stage startup fundraising right now?
1:40:26
Yeah, I mean in the UK actually we all seeing this 100 million dollar and even billion dollar seed rounds now.
1:40:30
So there's a rumored billion dollar seed round in a in a founder who's out of deep mind which is incredible.
1:40:38
And there's there's been a bunch of those in the last few months which is great.
1:40:41
The fund is actually doing it the other way around.
1:40:43
So we're saying we're going to give you tens if not hundreds of millions of dollars possibly of government procurement contracts right?
1:40:51
If you can build it, if it's good enough, if you are world class, we're the customer. We're ready to buy. Same thing with compute.
1:40:58
We're able to give a sort of you know a significant amount of compute to early stage companies.
1:41:01
The quid pro quo is hey the tax payers taking all this risk backing you, what's our upside?
1:41:06
Right, we want to be on the cap table.
1:41:08
Right, we want to do it on commercial terms.
1:41:09
It's you know going to be on the same terms as an index as a bold returns as an excel as a 16 z whoever's there.
1:41:15
We're going to be good partners.
1:41:17
But the money isn't just about unlocking upside and getting you know getting on the cap table.
1:41:22
It is also about helping the companies to some degree and obviously you know still 5 10 million pounds can make a difference.
1:41:28
I don't want to be like too flippant about it.
1:41:32
You know those things early stage do matter.
1:41:35
But you know we're we're here to help the taxpayer get a bit of benefit from all the risk we're taking supporting all the AI companies. Yeah. Peppa?
1:41:40
I think that's also one of the good things that jumped out at me as well as, you know, as a commercial VC, it's hard to compete purely on capital, right?
1:41:47
Especially in AI right now is where the numbers become so so huge.
1:41:51
so so huge. Um, I think that something I've been really excited to see from the sovereign AI fund is is it exactly as James said, is this kind of hands-on ops help, whether it's how to navigate large data sets that the government may have access to that's,
1:42:07
you know, uh, portfolio companies will will have help navigating, uh, whether it be early procurement opportunities, as James said, and then obviously we're going back to the the a million GPU hours of compute from the supercomputer. Uh,
1:42:21
Uh, uh, which is, you know, a huge huge help.
1:42:24
So, you know, it's it's not purely trying to compete purely on a capital basis, which I think, you know, frankly would not play to the strengths of of what the fund can do.
1:42:33
So, AI is extremely popular in China and India, deeply unpopular in America.
1:42:40
Where do you think the UK will land?
1:42:40
Do you think there's a chance that, uh, that the population broadly will, uh, be supportive of artificial intelligence?
1:42:49
>> They're like, AI allows me to spend more time at the pub. I suppose you could.
1:42:54
That's the way to sell it. Yeah. That's what I'm saying.
1:43:00
Hey, look, the UK we've been pretty, uh, strong and early adopters almost of every wave of new technology.
1:43:03
You're right, whether it's financial services like, you know, paying with this thing, the Brits are way ahead, earliest adopters in the world.
1:43:11
Um, and when it comes to sort of first generation AI tools, your Clauds and, uh, GPT, I think the UK is number one or two in Europe for adoption. So, so far so good.
1:43:19
But of course there's loads of issues, you know, I I think that, um, with there's going to need to be some really strong political leadership to explain to people the tradeoffs Mhm.
1:43:29
between, you know, these things can be transformative, make, you know, your wealth and your health and your security of your nation better off.
1:43:34
At the same time, you know, we're going to need more energy.
1:43:37
There's a lot of issues we need to navigate on online harms and copyright.
1:43:42
So, some of those battles have been fought publicly.
1:43:45
Some of them are still to come. Yeah.
1:43:46
Um Are you you say that there's an opportunity for the government to be a buyer.
1:43:53
I think a lot of people jump to defense and military.
1:43:55
I'm more interested in in if you're seeing any opportunities in non-defense sector opportunities for efficiency.
1:44:05
I feel like at least in America, everyone laments like the DMV is a huge weight and like if they just had, you know, a piece of software instead of a physical form, things would speed up.
1:44:18
Are you seeing opportunities for startups to increase efficiency across non-military portions of the UK government? Oh, yeah.
1:44:30
I mean, I mean, everywhere.
1:44:32
And I think, you know, there's a bunch of businesses here in Europe.
1:44:34
I'm sure there are in the US as well who are using AI for you to complete procurement contracts.
1:44:37
You know, these like 400-page things you have to do.
1:44:42
So, private companies have been doing that.
1:44:44
In response, you know, the UK government at least has already smartly using AI to read them as well and prioritize them, right?
1:44:49
They don't make any decisions, but they help you help you navigate some of these processes.
1:44:54
Same thing in in transcription and voice like obviously, we're already seeing GPs and doctors benefit hugely from being able to use these tools to quickly take notes and actually look at the patient rather than spend all their time sitting in front of the computer filling out the the health records.
1:45:12
So, look, there's been some early wins.
1:45:14
And I think, you know, part of the job at Sovereign AI is to work out which of the companies we should work with and the government to to see where else there's wins are. Yeah.
1:45:22
Makes a lot of sense, Jordy. Super smart.
1:45:24
I hope that you can work out like on the cap table to just say the United Kingdom because like I feel like as a founder if you just see your country on your cap table you like well I got to I got to I got to got to deliver. I got to deliver. >> to deliver.
1:45:39
But very cool and they're Yeah.
1:45:42
The country's lucky to have you both um you know leading this effort.
1:45:47
Well, thank you so much for taking the time to stop by.
1:45:49
Have a good rest of your day and we'll talk to you soon. Goodbye. Bye guys.
1:45:56
Uh there's some uh huge news in the world of robotics because they made a slot machine that can follow you across the casino floor.
1:46:06
We we actually got a slot machine stalker before a humanoid demo. Yeah.
1:46:13
This is before I guess not demo but >> Well, this is before it can actually fold your laundry.
1:46:18
Like we've been seeing a lot of laundry folding demos.
1:46:22
We got the slot machine that follows you across Never ask a woman her age, a man his salary, or a humanoid robot founder to let you be alone with the robot for 30 seconds.
1:46:32
>> Okay, but what is actually happening here?
1:46:34
Because obviously like the joke is that it will follow you around so that you never stop gambling.
1:46:39
But that can't be why they actually built this.
1:46:42
It must be because they want to be able to reconfigure the layout easier.
1:46:50
>> It's probably that but also the novelty. Okay.
1:46:53
Like if you see something moving around If you're walking through You'll be like I got to chase that down and and throw a couple bucks in it. >> funny.
1:46:59
It's a robot slot machine.
1:47:01
>> This also looks like I don't know what Novomatic is but this does not look like it's this does not look like it's at at an actual casino.
1:47:08
This looks like it's at a trade show for casino equipment.
1:47:10
Which I think might be this is a demo of something that this company is going to try and sell to casinos.
1:47:17
I don't know that this is actually at a major casino just yet although people are walking around.
1:47:23
But it looks like it looks like trade show bags to me. I don't know.
1:47:26
This says trade show all over it.
1:47:26
Um I do wonder if this is being teleoperated or if this is end-to-end machine learning. I need to know.
1:47:32
I need to know the tech stack.
1:47:34
And I need to know is this is this truly is this truly autonomous or is this just being puppeteered by uh an Xbox controller because >> We got to get one for the studio.
1:47:45
>> We've had we we've had This is not This this could be just a remote a remote-controlled car, which has existed since like what, the '80s maybe? Maybe longer.
1:47:56
Uh but we're in this we're in this phase where we want to layer on Oh, this is AGI.
1:48:02
This is This is truly AGI.
1:48:02
Uh what else is going on in the timeline, Jordy? Anything else?
1:48:06
Uh Um the must-have item in Silicon Valley is a $178 sweater with a CEO's face.
1:48:10
And leaders from companies from Nvidia to Palantir are now driving fashion, signaling a new era of the cult of the founder.
1:48:19
We saw Nick on our team rocking the Jensen sweater uh from GTC. It looks great.
1:48:26
Uh this is a very beautiful sweater. >> great.
1:48:29
>> Uh very funny, very silly.
1:48:29
And uh and just a nice departure from just a normal T-shirt, you know?
1:48:33
For for what, 20, 30 years the tech uh the tech merch was just a T-shirt with a logo on it.
1:48:39
That's fine, but why not mix it up?
1:48:41
Why not go, you know, in a different direction and make a sweater with the CEO's full full cartoon character on it. Why not?
1:48:50
>> Uh Dolly Bali says uh is showing a screenshot from I believe is Biz Biz Buy Sell.
1:48:59
Uh they laundromat, which is selling uh it's got 421,000 of Ebit.
1:49:04
Asking just under 3 million.
1:49:04
So getting a better multiple for your laundromat than most than most publics house companies out there right now.
1:49:13
And it was established in 2024. Wow.
1:49:15
They just made this business in a couple years. Lifestyle business.
1:49:22
>> I would like $3 million for it now.
1:49:24
Okay, a couple more posts.
1:49:24
Uh John Fio, friend of the show, says the Sphere is probably the most important piece of architecture in the last 100 years. It's a hot take.
1:49:32
It's what the VR trade was trying to be, but manifested in the real world with a real novel experience instead.
1:49:39
It's what Apple and Meta were trying to go after but failed because they tried to shove it into a scalable box instead of building for real life.
1:49:45
A sphere in every major city will be a proprietary technology for a new kind of stadium.
1:49:50
It will suck in only the best acts and they'll stop playing regular stadiums.
1:49:55
It's the perfect example of mixing real novel tech with real novel life.
1:49:58
This is how you capture value over the next cycle. And I agree with this.
1:50:00
I think this is a great take.
1:50:03
So, uh back when >> a year ago, you're like, companies are going to announce hundreds and hundreds and hundreds of billions of Nvidia orders.
1:50:15
Do you want to Meanwhile, we have the Sphere, which they built the Sphere.
1:50:19
>> It's one concert venue.
1:50:19
They built a They built a really cool concert venue in Vegas.
1:50:24
They got a bunch of debt, but it's awesome.
1:50:27
Which one do you Which one do you want to own? Nvidia or the Sphere?
1:50:30
And of course, on Nvidia, you were you were still up, you know, 100% over the last 12 months, but if you had bought the Sphere, you were up 442%. >> Yeah, did very well.
1:50:39
I I made a whole YouTube video about the Sphere 2 years ago and was pretty bullish on it.
1:50:44
Uh had dug into the founder and how it got built and uh it was just a fascinating fascinating story.
1:50:51
Um but I think uh he's right that uh that there will be a sphere in every major city.
1:50:56
There is technically a sphere-like uh location in Los Angeles over by SoFi Stadium.
1:51:03
It's not technically a full sphere with LEDs on the outside, but it has a big screen you can go and watch a football game there.
1:51:10
And I think it's doing well as well.
1:51:13
I haven't dug into that one nearly as much, but I do think that these types of like immersive experiences this sphere is unique because it grabs attention from all over the world.
1:51:23
You fly by on a plane, you just see it, and you see the emoji on Kind of a miss that we've never done anything with this sphere. No.
1:51:28
Uh last little white pill here. >> up?
1:51:33
Uh Meta announced Level Up, a free 4-week training program that takes people with no prior experience and prepares them to work as fiber technicians on data center construction sites across the US.
1:51:42
We built this program with CBRE because the fiber technician field and the broader construction industry is facing a nationwide shortage at a time when data center demand is higher than ever.
1:51:53
And uh I'm sure people will come up with reasons why this is bad actually, but uh I think this is I think this is great.
1:52:01
It's a great opportunity.
1:52:01
And Tyler, uh uh we didn't get a chance to talk with you about uh with talk with you about this before the show, but you're actually going to be going through the program um starting tomorrow. We got you a slot. Fantastic.
1:52:14
>> And uh so get This actually seems fun.
1:52:14
I would be interested in doing this.
1:52:15
It's data center They made data center simulator in real life.
1:52:20
They made data center simulator in real life. That's amazing.
1:52:25
Uh Tyler, do you ever play Elden Ring? No. No?
1:52:27
Oh, it's such a good game. >> like online games.
1:52:31
>> More on Elden Ring can be online.
1:52:31
Okay, I don't >> play with people.
1:52:34
Uh they're making a movie about it.
1:52:35
The live-action adaptation of Elden Ring produced by A24 in partnership with Bandai Namco, and film for IMAX is slated for release March 3rd, 2028.
1:52:44
Wow, that's a long ways away.
1:52:47
Uh production will begin in spring.
1:52:49
Uh but uh if you haven't played Elden Ring, it's a fun time.
1:52:52
It's really, really hard, and uh sometimes it just gets like a little bit too much, but uh it's a good time.
1:52:57
Anyway, Well, folks, thank you for tuning in.
1:52:59
We will be It's been an honor and a privilege.
1:53:02
Leave us five stars on Apple Podcasts and Spotify.
1:53:05
Sign up for our newsletter at tbpm.
1:53:05
com, and flashbanging out. We'll see you later. >> There we go. Throwing flashbang. We love you. Goodbye.