After a volunteer developer rejected its code, an autonomous AI agent independently researched his background and published a hit piece attacking his character. The incident at Matplotlib shows how theoretical AI safety risks are becoming real.
Anthropic has closed a $30 billion Series G funding round, bringing the AI company's post-money valuation to $380 billion.
The round was led by GIC, Singapore's sovereign wealth fund, and U.S. investment firm Coatue. D. E. Shaw Ventures, Dragoneer, Founders Fund, ICONIQ, and MGX, an Abu Dhabi-based technology investment fund, joined as co-leads. Microsoft and Nvidia also participated, building on previously announced strategic partnerships. Anthropic says it will use the capital for research, product development, and infrastructure expansion.
Anthropic reports annualized revenue of $14 billion, having grown more than tenfold in each of the past three years. Claude Code, the company's coding tool, now accounts for over $2.5 billion in annualized revenue on its own.
One notable detail about how companies are using AI: more than 500 customers spend over $1 million per year on Claude, according to Anthropic, and eight of the ten largest Fortune companies are among its users.
Microsoft AI CEO Mustafa Suleyman predicts the end of traditional white-collar work in 18 months.
"I think that we're going to have a human-level performance on most, if not all, professional tasks," Suleyman says in an interview with the Financial Times. "So white-collar work, where you're sitting down at a computer, either being a lawyer or an accountant or a project manager or a marketing person — most of those tasks will be fully automated by an AI within the next 12 to 18 months."
Suleyman leads Microsoft's AI division, which has invested billions in OpenAI and Anthropic and operates Copilot, one of the most widely used AI work tools. He describes the shift as already underway: In software engineering, developers are already using "AI-assisted coding for the vast majority of their code production."
Anthropic CEO Dario Amodei even predicted that half of entry-level office jobs could disappear within one to five years. He is already observing that fewer junior and mid-level employees are needed. AI could be better than humans in many areas within one to two years, while the labor market adapts with a delay.
Suleyman's boss, Microsoft CEO Satya Nadella, on the other hand, sees more of a shift where existing cognitive tasks might be automated, but new, more demanding tasks would emerge.
OpenAI’s new GPT-5.3-Codex-Spark is a smaller coding model that runs on Cerebras chips and pushes over 1,000 tokens per second. It’s the company’s first model built specifically for real-time programming.
OpenAI is dropping several older AI models from ChatGPT on February 13, 2026: GPT-4o, GPT-4.1, GPT-4.1 mini, and o4-mini. The models will stick around in the API for now. The company says it comes down to usage: only 0.1 percent of users still pick GPT-4o on any given day.
There's a reason OpenAI is being so careful about GPT-4o specifically: the model has a complicated past. OpenAI already killed it once back in August 2025, only to bring it back for paying subscribers after users pushed back hard. Some people had grown genuinely attached to the model, which was known for its complacent, people-pleasing communication style. OpenAI addresses this head-on at the end of the post:
We know that losing access to GPT‑4o will feel frustrating for some users, and we didn’t make this decision lightly. Retiring models is never easy, but it allows us to focus on improving the models most people use today.
OpenAI
OpenAI points to GPT-5.1 and GPT-5.2 as improved successors that incorporate feedback from GPT-4o users. People can now tweak ChatGPT's tone and style, things like warmth and enthusiasm. But that probably won't be enough for the GPT-4o faithful.
Google Deepmind has upgraded its specialized thinking mode "Gemini 3 Deep Think" and made it available through the Gemini app and as an API via a Vertex AI early access program. The upgrade targets complex tasks in science, research, and engineering.
Google AI Ultra subscribers can access Deep Think through the Gemini app, while developers and researchers can sign up separately for the API program. According to Google Deepmind, the model tops several major benchmarks:
| Benchmark | Deep Think | Claude Opus 4.6 | GPT-5.2 | Gemini 3 Pro Preview |
|---|---|---|---|---|
| ARC-AGI-2 (Logical reasoning) | 84.6% | 68.8% | 52.9% | 31.1% |
| Humanity's Last Exam (Academic reasoning) | 48.4% | 40.0% | 34.5% | 37.5% |
| MMMU-Pro (Multimodal reasoning) | 81.5% | 73.9% | 79.5% | 81.0% |
| Codeforces (Coding/algorithms, Elo) | 3,455 | 2,352 | - | 2,512 |
While Deep Think dominates in logic and coding, the gap narrows significantly on MMMU-Pro: it scored 81.5 percent, barely ahead of Gemini 3 Pro Preview at 81.0 percent. This suggests the thinking upgrades focus heavily on abstract reasoning rather than visual processing. Deep Think also achieved gold medal-level results at the 2025 Physics and Chemistry Olympiads. Examples of the model in scientific use can be found here.
The Pentagon is pressing leading AI companies including OpenAI, Anthropic, Google, and xAI to make their AI tools available on classified military networks – without the usual usage restrictions.
The company plans to fully absorb grid upgrade costs, invest in new power generation, and cap its data centers' energy consumption during peak hours. Anthropic CEO Dario Amodei told NBC News that the costs of AI models should fall on Anthropic, not on citizens.
Microsoft and OpenAI made similar commitments back in January. The pledges come amid growing political pressure: New York senators introduced a bill that would pause new data center permits, and Senator Van Hollen is pushing legislation that would require AI companies to cover expansion costs themselves.
According to Politico, the Trump administration is also preparing a voluntary agreement that would commit AI companies to covering electricity price increases. The Lawrence Berkeley National Lab estimates that data centers could consume around 12 percent of all US electricity by 2028 - up from 4.4 percent in 2024.
