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Sohn 2023 | Patrick Collison in conversation Sam Altman

Sohn 2023 | Patrick Collison in conversation Sam Altman

42 segments available

At the 2023 Sohn Investment Conference on May 9, 2023, Stripe CEO Patrick Collison spoke with OpenAI CEO Sam Altman about the future of AI and more. Introduced by Sohn Conference Foundation Chair Graham Duncan. This session is presented by Sohn 2023 Corporate Sponsor: Tegus

Segments Timeline

1
0:00 - 0:18
0:18 duration67 words

The Right Sam

Patrick Collison humorously reflects on his previous interview with Sam Bankman-Fried, emphasizing the importance of having the right conversation partner this time, Sam Altman. This light-hearted introduction sets the stage for a deeper discussion on pressing topics in the tech world.

"Patrick, over to you. All right. Thank you, Graeme. Um, and, uh, and thank you, Sam, uh, for being with us. Uh, last year, I actually interviewed Sam Bankman Freed, which was, uh, which was clearly th..."

2
0:18 - 0:51
0:33 duration121 words

Worldcoin's Future

Collison and Altman discuss the launch of Worldcoin, highlighting the challenges faced in the U.S. regarding cryptocurrency regulations. Altman notes the irony of the U.S. being a difficult environment for crypto companies, raising questions about the future of digital currencies in America.

"Uh, so, um, so we we'll start out with the topic on, uh, on everyone's mind. Uh, so, uh, when will we all get our world coin? Uh, I think if you're not in the US, you can get one in a few weeks. If yo..."

3
0:51 - 1:39
0:47 duration150 words

ChatGPT's Role in Daily Life

Sam Altman shares his most common use case for ChatGPT, which is summarization. He discusses how the tool has become essential for managing emails and Slack messages, hinting at the potential for future plugins to enhance its functionality.

"ever. I don't know. All right. Um, so, uh, which is a crazy thing to think about that like this is, you know, think whatever you want about crypto and the ups and downs, but the fact that the US is th..."

4
1:39 - 2:36
0:56 duration180 words

The Future of AI Capabilities

Collison and Altman explore the potential limitations of current AI architectures. They discuss the possibility of reaching a plateau in AI development and the factors that could hinder progress, such as data and computational constraints.

"know, testing something just you actually want to get you where chat GBT is purely, you know, an instrumental tool for you? Summarization by far. Uh I I've gotten like I don't know how I would still k..."

5
2:36 - 3:24
0:48 duration160 words

The Importance of Expert Feedback

Altman emphasizes the need for smart experts to provide feedback in the development of AI models. He discusses the implications of this requirement for the future workforce, particularly for graduate students in the field.

"possibility. If we end up in the world where we asmtote soon, what do you think kind of exposed we will, you know, look back on the reason as having been too little data, not enough compute, what's wh..."

6
3:24 - 4:08
0:43 duration136 words

Nuclear Secrets and AI

The conversation shifts to the classification of nuclear secrets and its relevance to AI safety. Altman argues that while classification is important, it is not a complete solution to preventing disasters, drawing parallels between nuclear technology and AI.

"we're we're now training on kind of order of all of the internet's tokens and you can't grow that, you know, another two orders of magnitude. Uh I guess you could counter with yeah the synthetic data ..."

7
4:08 - 5:00
0:52 duration148 words

Learning from Past Technologies

Altman cautions against drawing too many parallels from past technologies when considering AI. He suggests that while there are similarities between nuclear materials and AI supercomputers, each technology has unique challenges that must be addressed.

"the plan. Mhm. If um so one of the big breakthroughs in I guess uh GPD 3.5 and four is RHF. Uh um you know if you Sam uh personally sat down and did oral all of the RLHF would the model be significant..."

8
5:00 - 5:54
0:53 duration165 words

Global Regulatory Agency for AI

The discussion turns to the idea of establishing a global regulatory agency for AI, akin to the IAEA for nuclear materials. Altman argues for the necessity of such an organization to ensure safety and accountability in AI development.

"And h how many how many like how should one think about the question of how many smart grad students one needs like is one enough or do you need like 10,000? It's we're studying this right now. We we ..."

9
5:54 - 6:49
0:54 duration170 words

Challenges of International Cooperation

Collison and Altman discuss the difficulties of achieving international cooperation on AI regulations, particularly with countries like China. They acknowledge the complexities of diplomacy and the need for a collaborative approach to ensure global safety.

"of required the power of nations and we made the IAEA which I think was a good decision on the whole and a whole bunch of other things too. So like yeah, I think probably anything you can do there to ..."

10
6:49 - 7:38
0:49 duration136 words

Open Source AI Models

Altman reflects on the rapid advancements in open source AI models, predicting that they will become increasingly capable. He contrasts this with the progress of closed-source models developed by hyperscalers, emphasizing the importance of community-driven innovation.

"AI supercomputers do have some similarities and this is a place where we can draw more than usual parallels and inspiration. But I would caution people to to overlearn the lessons of the last thing. U..."

11
7:38 - 8:51
1:12 duration195 words

Economic Value of AI Models

The conversation explores the economic implications of AI models, with Altman suggesting that while smaller open source models may suffice for many applications, larger models will be necessary for groundbreaking discoveries in fields like medicine and physics.

"this would be a capabilities threshold, but that's harder to measure. any any system cape over that threshold I think should submit to audits um full visibility to that organization be required to pas..."

12
8:51 - 9:43
0:52 duration189 words

Facebook's AI Strategy

Collison questions whether Facebook should open source its AI models, particularly LLaMA. Altman critiques Facebook's past AI strategy but expresses optimism about their potential to become a significant player in the AI landscape.

"So one of the there's also I think there there there's like a bunch of unusual things about this is why it's dangerous to learn from any technological analogy of the past. There's a bunch of unusual t..."

13
9:43 - 10:56
1:12 duration207 words

Future Discoveries Impacting AI Safety

Altman discusses the potential for new discoveries to significantly alter the probability of AI-related risks. He emphasizes the importance of ongoing research and the need to remain vigilant about the implications of advancements in AI technology.

"closed source models and there will be the progress that the open source community makes and it'll be you know a few years behind or whatever a couple years behind maybe um but I think we're going to ..."

14
11:02 - 12:10
1:08 duration176 words

AI Safety and Interpretability

Collison emphasizes the importance of understanding AI model internals for safety and alignment. He critiques the current reliance on Reinforcement Learning from Human Feedback (RLHF) and advocates for deeper mechanistic interpretability. This segment addresses the need for more technical work in AI safety to ensure robust and reliable AI systems.

"many super economically valuable things, yes, the smaller open source model will be sufficient. But you actually just touched on the one thing I would say, which is like help us invent super intellige..."

15
12:10 - 13:12
1:02 duration197 words

The Need for Technical AI Safety Work

In this segment, Collison expresses concern over the lack of sufficient interpretability work in AI safety. He calls for more technical researchers to focus on making AI systems safe and aligned, rather than merely discussing philosophical concerns. This highlights the urgency for actionable solutions in AI safety.

"Um yeah I mean a lot like I think that's most of the new work between here and super intelligence will move that probability up or down. Okay. Is there anything you're particularly paying attention to..."

16
13:12 - 14:35
1:22 duration258 words

Funding AI Interpretability Research

Collison suggests that philanthropic efforts should focus on funding small groups or individuals working on AI interpretability. He believes that providing financial support to emerging researchers can significantly advance the field. This segment discusses the importance of nurturing talent and innovation in AI safety.

"And do you think sufficient interpretability work is happening? No. Um why not? You know, a lot of people say they're very worried about AI safety. So that seems, you know, superficially surprising. M..."

17
14:35 - 15:39
1:03 duration203 words

Bridging the Skill Gap in AI Research

Collison addresses the skill bottleneck in AI research, noting that talented individuals can transition into AI roles relatively quickly. He shares insights from OpenAI's program that successfully trains new researchers, emphasizing the potential for rapid growth in the field. This segment highlights the importance of developing new talent in AI.

"single people or small groups of people that are very technical that want to push forward a technical solution. um and are you know maybe in grad school or just out or in undergrad or whatever I I thi..."

18
15:39 - 16:40
1:00 duration192 words

The Rise of Conversational AI

Collison predicts a future where conversational AI agents become commonplace, potentially outnumbering human friends for the next generation. He discusses the implications of this shift on social interactions and the need for societal norms to differentiate between AI and human interactions. This segment explores the evolving landscape of AI companionship.

"program at OpenAI that does exactly this, and I'm astonished how well it works. It seems that pretty soon we'll have um uh agents that you can converse with in very natural form, low latency, full dup..."

19
16:40 - 18:07
1:27 duration253 words

A Society of Integrated AIs

Collison envisions a future where multiple AIs coexist with humans, contributing to societal infrastructure. He contrasts this with the fear of a singular superintelligence, suggesting that a diverse array of AIs could be more manageable. This segment discusses the potential for harmonious integration of AI into daily life.

"is important is that we we we establish a societal norm soon that you know if you're talking to an AI or a human or a sort of like weird AI assisted human situation. Um but people people seem to have ..."

20
18:07 - 20:01
1:54 duration317 words

AI's Impact on Economic Growth

Collison speculates on how AI will significantly alter real economic growth and capital efficiency. He argues that AI could lead to better capital allocation in sectors like healthcare, potentially revolutionizing industries. This segment examines the economic implications of AI advancements.

"of AIs integrated along with humans and yeah there have been movies about this for like a long time like there's like you know C3PO or whatever you want in Star Wars like people know it's a AI. It's s..."

21
20:01 - 22:32
2:30 duration482 words

OpenAI's Research and Commercialization Strategy

Collison outlines OpenAI's dual focus on groundbreaking research and commercialization. He believes that developing consumer products can enhance their platform, while maintaining a commitment to being a leading research organization. This segment highlights OpenAI's strategic vision for the future of AI.

"I I would take the other side of that. Again, we don't know. But I I would say that like human cap capital allocation is so horrible that if we know exactly what to do, even if it's expensive, you you..."

22
22:12 - 23:03
0:50 duration145 words

The Impact of GPT on AI Development

Altman reflects on the transformative impact of the GPT paradigm as a significant breakthrough for OpenAI. He discusses the importance of combining various research efforts to achieve meaningful contributions to the AI field.

"um and building the org that can make these repeated breakthroughs. Uh they don't all work. You know, we like went we've gone down some bad paths, but we have figured out more than our fair share of t..."

23
23:03 - 24:03
0:59 duration156 words

Google's Response to AI Challenges

In response to a question about Google's strategy, Altman praises their focus and adaptability in the face of emerging AI technologies. He believes that while AI will change search, it won't eliminate it, especially with Google's proactive approach.

"starts tomorrow. Um, if you were CEO of Google, how would you do? I think Google's doing a good job. Um, I think they they they have had like quite a lot of focus and intensity recently and are really..."

24
24:03 - 25:01
0:58 duration154 words

The State of AI Research in China

Collison and Altman discuss the output of machine learning research from China, noting the disparity between the volume of published papers and their impact. They ponder the reasons behind this phenomenon and the visibility of significant research contributions.

"Um, how much important ML research comes out of China? I would love Sorry, go ahead. I would love to know the answer to that question. Like how much does it come out of China that we get to see? Not v..."

25
25:01 - 26:10
1:08 duration166 words

Optimizing AI Training and Inference Efficiency

The conversation shifts to the efficiency of AI training versus inference. Altman expresses a preference for improving inference efficiency, highlighting its potential impact on overall computational resource management in AI models.

"I just feel confused. Um, would you prefer OpenAI to um to, you know, figure out a 10x improvement to training efficiency or to inference efficiency? It's a good question. Um it sort of depends on how..."

26
26:10 - 27:31
1:20 duration215 words

Anticipating the Next GPT Moment

Altman reflects on the significance of GPT-2 and speculates about upcoming breakthroughs that could have a similar impact. He expresses hope for new developments that could emerge within the next year.

"there a GPT2 moment happening now um there's a lot of things we're working on that I think will be GPT2 like moments uh if they come together but nothing there's nothing like released that I could poi..."

27
27:31 - 28:14
0:43 duration122 words

The Future of AI Co-Pilots

Collison shares his vision for an AI co-pilot that could manage various digital tasks, enhancing productivity by integrating with communication tools and personal organization systems.

"some kind of Siri plus sort of thing. Yeah. Yeah. And you mentioned you know curing cancer. uh is there an obvious application of these techniques and technologies to science that again you think we h..."

28
28:14 - 29:30
1:16 duration223 words

AI's Role in Accelerating Scientific Discovery

The discussion turns to AI's potential applications in science, with Collison suggesting that AI could significantly enhance the efficiency of scientific research and discovery, both through improved tools and innovative problem-solving approaches.

"same a similar system could go off and start to read all of the literature, think of new ideas, do some limited tests in simulation, email a scientist and say, "Hey, can you run this for me in the wet..."

29
29:30 - 30:10
0:39 duration117 words

The Future of AI Reasoning in Science

Collison contemplates the future of AI in scientific reasoning, discussing the potential for AI models to make significant scientific advancements independently, while acknowledging the complexities involved.

"you know currently easy to work with I I really don't know. I I this is like, you know, most areas I I am willing to like kind of give some rough opinion. In this one, I never have un I don't I don't ..."

30
30:10 - 33:06
2:55 duration512 words

Innovating Beyond Traditional Corporate Structures

Altman reflects on OpenAI's unique capital structure and the challenges it presents. He argues that while innovation in corporate structures can be tempting, the focus should remain on product and scientific innovation.

"more work. Um uh you know, OpenAI has a um has done a super impressive job of fundraising and has a very unusual capital structure uh for you know the nonprofit and the Microsoft deal and like all all..."

31
32:44 - 34:00
1:15 duration258 words

The Elusive Nature of Founders Like Elon Musk

In this segment, Collison reflects on the rarity of visionary founders like Elon Musk, questioning why more companies like SpaceX and Tesla haven't emerged. He explores the cultural and capital-related factors that may hinder the emergence of similar innovators in today's landscape.

"Um, and I understand why. Like it's also great for companies that like only ever have to raise a few hundred thousand or a million dollars and get to profitability. But I think we over pivoted in that..."

32
34:00 - 35:06
1:06 duration177 words

The Future of Funding Models

Collison shares insights on the evolution of funding models in the tech industry, suggesting that new structures may emerge to better support high-risk innovations. He highlights the importance of adapting funding approaches to foster groundbreaking projects that require significant upfront investment.

"never met another person that I think I can that can be developed easily into another Elon. He is sort of this like strange N of one character. Um I'm happy he exists in the world of course but you kn..."

33
35:06 - 36:34
1:27 duration230 words

Investing in Long-Term Projects

Collison proposes a bold idea for nurturing talent in tech: providing financial support to a select group of innovators for long-term projects. He envisions a model that allows individuals to explore their ideas without immediate financial pressure, fostering creativity and innovation.

"the you know there's a finite or essentially finite uh set of um of funding models in the world uh And each has a particular set of incentives and for the most part a particular sociology uh and you k..."

34
36:34 - 37:40
1:06 duration208 words

The Role of Mentorship in Innovation

In this discussion, Collison emphasizes the value of mentorship and long-term relationships in fostering innovation. He reflects on his experiences working with trusted colleagues over many years and how these relationships contribute to successful ventures.

"this. You still need like the Elon like people to to do it. Um, and like one project I've always been tempted to do, um, is say, "Okay, we're going to identify the, let's say, 100 most talented people..."

35
37:40 - 39:12
1:31 duration351 words

Identifying Future AI Beneficiaries

Collison speculates on which non-AI companies will benefit most from AI advancements in the coming years. He suggests that innovative investment vehicles could leverage AI for superior performance, highlighting the transformative potential of AI across various sectors.

"That's kind of the university model, I guess. Uh and I don't mean that as like a this already exists. You know, you're just, you know, reinventing the bus or something. H I mean that like it's it's ma..."

36
39:12 - 40:44
1:32 duration256 words

Microsoft's AI Transformation

Collison discusses Microsoft's potential to transform itself through AI, analyzing the company's readiness and strategic approach to integrating AI technologies. He considers how Microsoft's existing infrastructure positions it to capitalize on AI advancements.

"time, worked with for a long time. I think that's really valuable. Like in the case of OpenAI, uh I had known Greg Brockman for a long time. I met Ilia for maybe only like a year before, even a little..."

37
40:44 - 42:58
2:13 duration314 words

The Complexity of AI Overfitting

In this segment, Collison addresses concerns about AI models, particularly GPT-4, and the potential for overfitting. He reflects on the challenges of understanding AI training processes and the implications for model performance and reliability.

"have been taking it more seriously than others? Um what do you think the likelihood is that we will come to realize that GPT4 is somehow significantly overfit on the problems uh you know in the domain..."

38
42:58 - 44:41
1:42 duration325 words

Regulating Synthetic Biology

Collison raises critical questions about the regulation of synthetic biology, drawing parallels to AI safety. He emphasizes the need for global coordination to prevent potential pandemics caused by synthetic pathogens and discusses the challenges of monitoring and regulating this emerging field.

"thinking all this AI safety stuff how if at all do you think synthetic biology should be regulated? I mean, I would like to not have another synthetic path to gym cause a global pandemic. I think we c..."

39
45:01 - 46:14
1:13 duration259 words

The Slow Path of Clinical Trials

In this segment, Collison critiques the lengthy clinical trial processes that hinder rapid vaccine deployment, using the COVID-19 vaccine timeline as an example. He identifies this as a critical area for improvement within the biomedical ecosystem to ensure timely responses to health crises.

"Um and so I think the particular thing like if it is true that uh co was engineered uh I think you know instances of that set of slight modifications to already existing uh infectious diseases we can ..."

40
46:14 - 48:00
1:45 duration310 words

The Abundance Agenda: A Call for More Resources

Collison and Altman discuss the concept of an 'abundance agenda,' advocating for increased resources across various domains to achieve societal goals. They explore how self-imposed restrictions can limit progress, particularly in energy transitions and technological advancements.

"Yeah, I I I I very much agree with that. and and and clinical trials um uh like that that was the you know the the limiting step uh in uh in co and I I think it's you know it's at this point been wide..."

41
48:00 - 51:07
3:07 duration548 words

Overcoming Friction in Innovation

Collison addresses the challenges faced by innovators today, including regulatory hurdles and societal skepticism. He argues that these barriers create friction that stifles creativity and entrepreneurship, making it harder for new ideas to flourish and be implemented.

"different domains um more more kind of the Henry Adams curve realized uh and they frequently observe that permitting in the broadest sense all sorts of you know well-intentioned but self-imposed restr..."

42
51:07 - 52:38
1:30 duration261 words

The Decline of Young Founders in Tech

In this closing segment, Collison reflects on the absence of young founders in the tech industry compared to previous decades. He raises concerns about the educational system and societal attitudes towards entrepreneurship, questioning what has changed and how it affects innovation.

"used to or believe less. when we first met whatever it was uh 15 or so years ago, uh Mark Zuckerberg was preeminent in the technology industry and in his 20s and you know not that long before then uh ..."