Developers think like architects: coherence, dependencies, edge cases, completion. AI companies often behave like conductors: many products, many experiments, many moving parts. When launch velocity beats closure, docs lag, bugs linger, and trust erodes.

I heard that one in ten school lessons in France is cancelled due to teacher shortages. Imagine if someone invented AI and modernized education.

How do you get rid of stupid questions in your news feed, like: “If C++ is so much faster, why do AI models use Python?” or “What's stopping people from vibe coding their own AI model?” - That can't be serious.

AI could be the force multiplier for the next wave of cancer medicine: in mRNA vaccines, it can rank each tumor’s best neoantigens; in CRISPR, it can design safer guides/editors and predict off-targets. Both fields already use ML—better models could reduce trial-and-error.

Global reset landing tomorrow 10am PST for all paid ChatGPT accounts. Apologies for the slow start with GPT-6.1 Sol, it's now back to running at expected speeds after the massive load spike in the first two days.

This week Claude Sonnet 5.5, GPT-6.1 Sol and Gemini 4 Argon all launched near the top of the Coding Agent Index leaderboard, but each has a different balance of performance and cost The Artificial Analysis Coding Agent Index measures agents (a combination of model and harness) across three agentic coding evaluations. ➤ Claude Sonnet 5.5 (max) in Claude Code takes the top spot at 68, but also has the highest measured cost per task: $14.19 ➤ Gemini 4 Argon (high) in Antigravity CLI scores 64 at $5.84 per task - less than half of Sonnet 5.5’s cost. Note, this uses Google’s promotional pricing, and Argon is not yet publicly available ➤ GPT-6.1 Sol (xhigh) in Codex scores 63 at $1.04, roughly one sixth of Argon’s cost

What people always forget when talking about AI companies

At first, I was skeptical about what this is needed for and what the benefit is compared to the remote connection from Codex or ChatGPT Work. But having a proactive assistant with a memory like this really cannot be underestimated.

Congratulations to Google for achieving an excellent Canonical AA-Omniscience Index score (42) on Artificial Analysis. It did so by driving down hallucinations rather than cranking up accuracy. In other words, it probably abstained more than Opus, Fable, or GPT

I asked my ChatGPT dot to inspect its cloud workspace: • Debian 13.6, Linux 6.18.44 (x86_64) • 9 visible logical CPUs, AMD EPYC 9V74 • 10.45 GB visible RAM • No swap These are workspace specs, not the hardware running the AI model.

Business Premium also offers Dots in the EU. It's a great help in everyday life, even if you don't grant access to your email. The proactive notifications have been on point so far.

Germany is already near the front of the AI-agent shift: 49% of office workers use AI agents. Among IT decision-makers it’s 64%, leaders 63%. Employer-provided AI use jumped 32%→49% in a year. Yet 43% of agent users fear replacement vs. 27% of GenAI-only users.

Working with GPT-6.1 Sol on our newsletter system: it silently changed the DOI confirmation link validity to 48h, even though the task was about a completely different part of the code. A good reminder that code review still matters even with top-tier models.

woah, the biggest upgrade in gemini 4 argon will be hallucination reduction compared to 3.8 flash, google has basically crushed one of gemini’s biggest weaknesses hallucinations now close to being eliminated

Big news: Gemini 4 Argon (High) by @GoogleDeepMind just landed #1 in Text Arena with 1525 pts, and #8 in Code Arena: WebDev with 1679 pts! This release has reshaped the Text Arena Pareto frontier with a blended $8/MToken! Gemini 4 Argon (High) is now the most cost efficient model, see its placement on Pareto frontier below. In the Text Arena, Gemini 4 Argon (High) ranks #1 in Coding, Hard Prompts, Instruction Following, Longer Query, and Creative Writing. It also leads every occupational domain evaluated, with additional #1 spots in English, Non-English, Chinese, and Russian. This model is +20 points above the #2 ranked Claude Opus 4.6 (High), and a huge leap from Google’s previous release, Gemini 3.8 Flash (High) at #11! In Code Arena: WebDev, Gemini 4 Argon (High) gained +96 points from Gemini 3.8 Flash (High), and went from #29 to #8. Congrats to the @GoogleDeepMind team on this impressive frontier release!

Introducing Gemini 4 Argon, our new frontier model, rolling out to cyber defenders starting today, and more widely as soon as possible. I am really excited by the progress we have made here. Argon is priced at $2 in and $10 out during introductory pricing!