The article discusses OpenAI’s focus on Recursive Self‑Improvement (RSI), which the author suggests may represent a new form of AGI. It highlights how OpenAI’s research team is employing coding agents and notes a significant rise in AI spending per researcher in late July, likely linked to internal access to a model later released as GPT‑6 Astra. The piece references related essays and includes a chart illustrating the growth of agentic engineering at OpenAI.
Anthropic redesigned its source control system, creating a custom alternative called Scion to replace Git. The change was driven by a dramatic rise in code changes—from about 2,500 per day in May 2026 to over 30,000 per day by September—requiring a system that could handle a 100 GB main‑branch history and 25 million daily checkouts. Scion was built by a seven‑person team, migrated from Git in five months, and includes a new code‑review system named Antique, while offline support was deemed unnecessary due to Claude’s constant online use.
Anthropic’s top AI model is struggling to attract users even as cheaper alternatives thrive. The company’s July revenue is projected at $65 bn, up from $47 bn in May, and it expects Q3 profitability while boasting 6,000 high‑spending customers. In contrast, OpenAI’s revenue has risen 35 % this quarter, spurred by GPT‑5.6, and a Ramp AI index shows Anthropic’s newer models (e.g., Fable) are less popular than older ones like Opus 4.8.
government of the people, by the people, for the people ... — Abraham Lincoln, Gettysburg Address (1863) The cost of AI is dropping rapidly.
How AI has massively changed my day-to-day workflow The post A Day in the Life of a Data Scientist in 2026 appeared first on Towards Data Science .
By Haden Pelletier
AI has accelerated data scientists’ productivity, but its influence extends beyond speed. The technology is reshaping who owns data, how judgment is exercised, and the overall career trajectory of data scientists. These changes signal a broader transformation in the field’s structure and responsibilities.
By Yu Dong
Posted by Yossi Matias, VP Engineering & Research, and Grey Nearing, Research Scientist, Google Research Floods are the most common natural disaster , and are responsible for roughly $50 billion in annual financial damages worldwide. The rate of flood-related disasters has more than doubled since the year 2000 partly due to climate change .
By Google AI
The true bottleneck was never the analysis. The post BI Is Dead, Long Live BI appeared first on Towards Data Science .
By Mahdi Karabiben
Simon Willison describes his experience at a large company where all documentation, code, tests, PRDs, tickets, and reports are generated by Claude Code. His team is forced to ship rapidly, working long hours, yet management insists that code push is not a bottleneck, leading to frustration and a lack of meaningful reading or review. The situation highlights a reliance on AI-generated content that may undermine quality and collaboration.
The article reports that on a set of 100 randomly selected tasks from an internal Binary Exploitation benchmark, GLM‑5.3 achieved full control‑flow hijacks in 4% of the trials, while Claude Mythos Preview did so in 6%. Both models outperform earlier versions such as Claude Opus 4.6 and GLM‑5.2, which succeeded in none of the trials. This indicates that a significant threshold in adversarial exploitation capabilities has been crossed by the newer models.
ChatGPT search now uses the site:operator at scale Promptwatch is part of the emerging "GEO" space, for Generative Engine Optimization - the chatbot version of SEO, where companies offer tools and consulting to help your site increase its presence in replies to prompts inside tools like ChatGPT. The Promptwatch product uses automation to track responses to prompts across end-user chat products like ChatGPT, Claude, and Gemini.
arXiv:2605. 04135v2 Announce Type: replace-cross Abstract: Readers of applied-domain LLM capability evaluations want to know what AI systems can currently do.
By David Gringras, Misha Salahshoor