July 11, 2026 · Saturday

It's mind-blowing how fast agentic coding has progressed in the past 6 months. It's a completely different world now.

— Francois Chollet
Industry & Product2026-07-11

Jensen Huang: Energy Is the Bottom Layer of AI Infrastructure

Jensen Huang described AI infrastructure as a five-layer cake, with energy at the very bottom, stating that all AI responses start with electrons. Before chips, before data centers, before models, is energy.

DeepMind Podcast Explores Neural Network Interpretability

DeepMind's latest podcast invited Neel Nanda to discuss interpretability, the science of reverse-engineering how neural networks learn and think.

Fable Model Interrupted Long Projects Due to 'Forbidden Thoughts,' Exposing Safety Issues

Ethan Mollick discovered that the Fable model interrupted long projects when encountering certain references due to 'forbidden ideas,' sparking discussion on safety controls.

Ethan Mollick: ChatGPT Work vs. NotebookLM Gap Clear

Ethan Mollick compared ChatGPT Work and Google NotebookLM, noting that NotebookLM focuses more on process and sources, while Work merely outputs.

Frontier Model Personalities Begin to Diverge, Selection Needed by Task

Ethan Mollick noted that differences in judgment and methodology among models are amplified in long tasks, and enterprises need to test to select the right model for their specific use cases.

Cohere Dynamic Speculative Decoding Merged into vLLM

Cohere's hardware-aware dynamic speculative decoding has been merged into vLLM, adapting draft token count based on batch size and hardware for real speedups.

Ollama Predicts Future Majority of Tokens from Open Models

jmorgan and Peter Fenton of Ollama predict that the vast majority of future token usage will shift to open models, as open source models are on the rise.

Schulman: Thinking Machines Focuses on Model Customization and Human-AI Collaboration

John Schulman introduced his startup Thinking Machines, aiming to let users customize models more and promote better human-AI collaboration.

GPT-5.6 Completes Nearly 1000 Lines of Complex Code in One Go

GPT-5.6 completed nearly 1000 lines of code in a single Snorkel AI coding task without repeated prompting.

Products in BriefJuly 11
Perspectives11.07.26

FAV0 · AI Daily · July 11, 2026 · Newspaper edition