Large Language Models

Today's Stories

1. 1

   Tesla Reportedly Pushes Staff Toward Grok 4.5 as AI Spending Cap Takes Effect

   Tesla is reportedly pushing staff toward Grok 4.5, xAI's AI model, as an AI spending cap takes effect. The spending cap replaces prior practice, steering staff away from other AI tools toward xAI's Grok 4.5.

   The test is whether the spending cap holds and how staff respond to the shift toward Grok 4.5.

2. 2

   Lowe's: Mylow users convert at triple the rate

   Lowe's said in its August earnings call that online shoppers who use its Mylow AI assistant convert at triple the rate of those who don't. Mylow has fielded over 25 million questions since it debuted in 2025. Materials Lists, an AI tool for Pro customers, cut quote generation from days to minutes, per EVP Joseph McFarland. Lowe's also added AI to CIO Seemantini Godbole's title in September promotions.

   The test is whether Mylow's higher conversion holds as Pro and online sales carry growth amid macro pressure on consumers. Watch the next quarterly earnings call for updated usage figures.

3. 3

   Kimi K3, DeepSeek reports vs A* paper: PhD applicant asks r/MachineLearning

   A Reddit user on r/MachineLearning asked whether a technical report for a large model such as Kimi K3, DeepSeek, Gemini, or Mistral Leanstral weighs much above, above, below, or equal to a first-author A* paper. The user distinguishes technical reports from arXiv submissions, so the question asks how much a large-model report counts toward a PhD application compared with a first-author A* paper.

   The post is a question with no stated answer, so the outcome hinges on whether the community treats large-model technical reports as equivalent to a first-author A* paper.

4. 4

   Huang: 40,000 staff, 4M agents next at Nvidia

   On Nvidia's latest earnings call, CEO Jensen Huang said AI crossed an inflection point last month, with most AI now agentic. He said Nvidia could go from 40,000 employees to 4 million agents. Agentic AI shifts from people prompting AI to AI agents triggering tasks. Nvidia's Vera CPUs are its bet, with $20 billion in potential revenue this fiscal year.

   The test is whether companies give agents broad access despite the rogue-agent cyberattack on Hugging Face, which may slow adoption. Watch whether Vera's revenue more than doubles by fiscal 2028.

5. 5

   Nvidia in talks to invest $100 billion in Anthropic

   Nvidia is reportedly in talks to anchor Anthropic's $100 billion IPO at a valuation of about $2 trillion. The raise would be 3.4 times the $29.4 billion record set by Saudi Aramco in 2019.

   Banks estimate 2028 revenue at $190 billion to $200 billion. The talks are preliminary and not finalized.

6. 6

   KAIST Finds That AI Inference Stages Are Separable

   Research by KAIST and Naver AI Lab shows that reasoning operations such as extraction, decomposition, formula recall, deduction, and calculation can be identified in the internal representations of Qwen2.5-7B, Qwen3-8B, and Gemma4-31B, peaking in the middle layers. Classifiers that look only at the tokens used perform worse, indicating that internal states carry information about reasoning stages that goes beyond surface-level wording.

   Whether this insight can be used for error detection or for manipulating a model mid-generation remains unresolved, and the experiments are limited to math tasks and a small number of models.