No Priors Ep. 63 | With Sarah Guo and Elad Gil

ℹ️ EPISODE INFO

Released

May 9, 2024

Duration

29m

Channel

No Priors

Watch on YouTube

▶ Open ↗

📝 EPISODE DESCRIPTION

This week on No Priors hosts, Sarah and Elad are catching up on the latest AI news. They discuss the recent developments in AI like Meta’s new AI assistant and the latest in music generation, and if you’re interested in generative AI music, stay tuned for next week’s interview! Sarah and Elad also get into device-resident models, AI hardware, and ask just how smart smaller models can really get. These hardware constraints were compared to the hurdles AI platforms are continuing to face including computing constraints, energy consumption, context windows, and how to best integrate these products in apps that users are familiar with. Have a question for our next host-only episode, or feedback for our team? Reach out to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil Show Notes: 0:00 Intro 1:25 Music AI generation 4:02 Apple’s LLM 11:39 The role of AI-specific hardware 15:25 AI platform updates 18:01 Forward thinking in investing in AI 20:33 Unlimited context 23:03 Energy constraints

🎤 SPEAKERS

• Sarah Guo

  host

• Elad Gil

  host

🧾 EPISODE SUMMARY

In this episode of No Priors, featuring Sarah Guo and Elad Gil, No Priors Ep. 63 | With Sarah Guo and Elad Gil explores aI’s Next Frontiers: Local Models, Long Context, Energy Limits, Music Sarah Guo and Elad Gil discuss rapid advances across the AI stack, from creative tools like Suno and Udio to small, locally-run language models and Meta’s latest AI products. They examine how platform dynamics play out as Apple, Meta, Snowflake, Databricks, and hyperscalers all jostle over models, data, and distribution. The conversation explores technical directions such as long-context LLMs and specialized hardware, alongside looming constraints like data center energy, nuclear power, and policy. Throughout, they frame massive AI CapEx as comparable to past infrastructure waves and debate which layers—models, platforms, apps—will hold durable value.

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