Results for “LLMs”

350 results

Transcript mentions 248

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Topics & chapters 36

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AI summaries 66

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Columbia CS Professor: Why LLMs Can’t Discover New Science

a16z82 views
Vashan Vishal argues that current LLMs are not AGI because they only navigate existing 'Bayesian manifolds' derived from training data, rather than creating new scientific paradigms.summaryHe introduces a formal model where LLMs perform Bayesian inference on a compressed matrix of token distributions, explaining phenomena like in-context learning and the effectiveness of chain-of-thought through entropy resummaryDefinition of AGI: AGI is defined as the ability to create new science, math, or paradigms (like Einstein's relativity) that go beyond the training distribution, whereas current LLMs only refine and navigate existing knotakeaway

What's in America's Code? Reaganism with Horacio Rozanski

Ronald Reagan Presidential Foundation & Institute11 views
Booz Allen Hamilton's report 'What's in America's Code?' reveals that Chinese LLMs introduce more vulnerabilities and political bias into generated code than American models, driven largely by their significant cost advasummaryChinese LLMs introduce significantly more code vulnerabilities than American models, particularly when coding for American or national security applications, despite not containing explicit 'back doors'.takeawayThe primary driver for using Chinese LLMs in the US is cost, with models like DeepSeek being 10-20 times cheaper than US alternatives like Anthropic or OpenAI, creating an adoption pressure on startups.takeaway

What's in America's Code? Reaganism with Horacio Rozanski

Ronald Reagan Presidential Foundation & Institute36 views
Booz Allen Hamilton's report reveals that Chinese LLMs introduce significantly more code vulnerabilities than American models, particularly when used for national security applications, and inject political bias into gensummaryChinese LLMs introduce more vulnerabilities than American models, especially when coding for national security applications; however, these are not intentional backdoors but rather systemic differences in secure coding ptakeawayCybersecurity is shifting towards AI-driven attacks where LLMs can control thousands of attack vectors simultaneously (e.g., drone swarms), requiring defense mechanisms that specifically counter AI behaviors rather than takeaway

Why Scale Will Not Solve AGI | Vishal Misra - The a16z Show

a16z54 views
The guest argues that current LLMs are fundamentally limited to correlation-based pattern matching (Shannon entropy) and Bayesian updating, lacking the causal reasoning and plasticity required for AGI.summaryLLMs function as compressed representations of a massive probability matrix, performing Bayesian updating where new evidence updates the posterior distribution of the next token, but they do not retain learning between stakeawayHuman intelligence differs from LLMs in two key ways: humans have lifelong plasticity (continual learning) and use causal simulation (Kolmogorov complexity) rather than just correlation (Shannon entropy).takeaway

WTF is Artificial Intelligence Really? | Yann LeCun x Nikhil Kamath | People by WTF Ep #4

Nikhil Kamath50 views
Yann LeCun argues that current Large Language Models (LLMs) are insufficient for achieving human-level intelligence because they lack a physical world model and persistent memory, functioning only as 'System 1' reactive summaryLLMs are limited to discrete data (text) and cannot understand the continuous, high-dimensional physical world (video/images), making them incapable of true reasoning or physical interaction.takeaway“The smartest LLMs are not as smart as your house cat.”quote