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From Cloud to Edge: AI Gets Personal
7 segments available
What if generative AI models could run directly on your smartphone, creating images, video, and voice instantly—without relying on the cloud? In this episode, Jennifer Li, General Partner at a16z, explains why on-device AI is poised to take center stage in 2025. Thanks to smaller, more efficient models and increasingly powerful devices, AI-powered experiences will become faster, more seamless, and more private. From real-time voice agents to AR-powered cameras and smarter wearables, Jennifer explores how this shift unlocks new consumer and B2B applications. She also dives into the challenges, economics, and players that stand to benefit from this evolution. Timecodes: 00:00: The Rise of On-Device AI 00:56: Smartphone Compute Power 01:59 Advantages of On-Device Models 03:33: Real-Time Applications 05:23: Economic Implications 06:47: Future Trends and Players 07:43: Looking Ahead to 2025 Resources: Find Jennifer on X: https://x.com/JenniferHli Check out all 50 Big Ideas: https://a16z.com/big-ideas-in-tech-2025/ Stay Updated: Let us know what you think: https://ratethispodcast.com/a16z Find a16z on Twitter: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Subscribe on your favorite podcast app: https://a16z.simplecast.com/ Follow our host: https://twitter.com/stephsmithio Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.
Segments Timeline
The Rise of On-Device AI
Jennifer Li discusses the increasing prevalence of on-device generative AI models, emphasizing their potential to run directly on smartphones. She highlights the advancements in smartphone compute power, comparing it to computers from 10-20 years ago, and explains how smaller models can effectively generate images, voice, and video on these devices.
"the generative models that are creating image voice video will become more prevalent on the infrastructure side and also on the device compute power side it's a perfect setup for the smaller models to..."
Advantages of On-Device Models
In this segment, Jennifer Li outlines the advantages of running AI models on devices, including improved user experience through real-time applications. She emphasizes the importance of speed and efficiency, noting that on-device processing enhances privacy and reduces reliance on cloud computing, ultimately transforming user interactions with technology.
"a computer 10 or 20 years ago thanks to moral law smaller sizes of 2 billion 8 billion parameter models that's enough compute for for them to run on device um and it can generate and create very robus..."
Unlocking New Applications
Jennifer explores the potential applications of on-device AI models, particularly in real-time voice agents and augmented reality. She discusses the exciting developments in conversational AI and how these technologies can enhance user experiences, making interactions more fluid and engaging.
"and also the disadvantages as consumers and day-to-day users uh we are already spoiled by uh real time and very uh performant very sleek and and realtime applications if you're talking to a chatbot if..."
Reimagining AR Experiences
This segment focuses on how on-device AI can revolutionize augmented reality experiences. Jennifer explains how generative AI can interact with smartphone cameras to create immersive environments, allowing users to visualize changes in their physical spaces, thus enhancing the way we interact with our surroundings.
"the models on device then the last part is just privacy uh users do care about you know if my meeting notes is taken locally I probably will use this meeting notaker much more often than uh knowing so..."
Economic Implications of On-Device AI
Jennifer discusses the economic implications of running AI models on devices rather than in the cloud. She addresses the cost benefits and challenges associated with this shift, emphasizing how it could change developer efficiency and the overall economics of AI applications.
"what type of real time exchanges you want to have with your AI companion your support agents or any sort of life coach I think we do need to think about the modality and and the latency in a much more..."
Key Players in the On-Device AI Landscape
In this segment, Jennifer identifies key players that stand to benefit from the rise of on-device AI models. She highlights the interest from hardware manufacturers and model developers, discussing how this shift could impact the entire supply chain and lead to new opportunities in the tech industry.
"physical world and not just using the camera for capture but also using it as a projector definitely and let me ask you about economics then because a lot of the models that exist today do rely on inf..."
Looking Ahead to 2025
Jennifer shares her vision for the future of on-device AI by 2025, focusing on the integration of generative models in mixed reality applications. She expresses excitement about the potential for enhanced consumer experiences and the maturity of foundational model technology, setting the stage for innovative developments in the coming years.
"hybrid mode uh so I would encourage teams who are thinking of uh leveraging this technology uh sort of consider it more holistically super interesting and as we think about that world are there any pl..."