No Priors: Artificial Intelligence | Technology | Startups

Big tech earnings and the current AI debates, with Sarah Guo and Elad Gil

Mar 7, 2024

42:14

Snipd AI

This podcast episode dives into the latest developments in AI models, Google's entry into the competitive space, the intersection of biology and robotics, NVIDIA's high earnings, ROI in AI investments, and the challenges in US chip production. The hosts discuss AI application in 2024, effective AI tools, and the virtuous tech cycles in the industry.

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Quick takeaways

Google enters AI competition with Gemini 1.5, focusing on agent-centric companies and partnerships.

NVIDIA's high earnings impact AI landscape, reflecting growth in AI applications and need for US chip production.

Deep dives

Exciting Advances in Model World

Emerging hand models, Google's Gemini with a million token context window, biological models needing longer context windows for proteins, impressive progress by Mistral with rapid model development, notably launching 'Le Big Model' and partnering with Microsoft Azure.

Evolution of Human Capital Waves in AI

00:48

Expanding Capabilities of General MLMs

02:41

Long-term investment lens in AI impact on companies

01:01

Introduction

3min

Enhancing AI Capabilities and Challenges at Google

6min

Advancements in Biology and Robotics

5min

AI Impact on Business Growth and ROI

25min

Dynamic Evolution of AI Field and Competitive Landscape Exploration

2min

Exploring the Impact of AI on Business and IT Budgets

2min

Host-only episode discussing NVIDIA, Meta and Google earnings, Gemini and Mistral model launches, the open-vs-closed source debate, domain specific foundation models, if we’ll see real competition in chips, and the state of AI ROI and adoption.

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Show Notes:

(0:00) Introduction

(0:27) Model news and product launches

(5:01) Google enters the competitive space with Gemini 1.5

(8:23) Biology and robotics using LLMs

(10:22) Agent-centric companies

(14:22) NVIDIA earnings

(17:29) ROI in AI

(20:43) Impact from AI

(25:45) Building effective AI tools in house

(29:09) What would it take to compete with NVIDIA

(33:23) The architectural approach to compute

(35:42) the roadblocks to chip production in the US

(38:30) The virtuous tech cycles in AI

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