OpenAI Puts September Revenue Run Rate at $50 Billion, Below $68 Billion Measure
1. OpenAI Told Investors Annualized Revenue Was About $50 Billion at the End of September, Below the Previously Circulated $68 Billion Measure OpenAI told investors that its annualized revenue reached roughly $50 billion at the end of September, clarifying a key financial measure as the company faces pressure to support its $852 billion
2. Anthropic Updates Claude Policy, Banning Sustained, Needless Abuse and Tightening Rules on Weapons, Surveillance and Political Propaganda Anthropic has updated its usage policy for the first time in more than a year, setting clearer limits on how Claude may be used for weapons, surveillance, political campaigns and autonomous hardware.
3. Long-WAM Extends Robots’ Visual History to 19.2 Seconds, Raising RoboCasa GR-1 Success From 63.3% to 78.7% Robots need visual history to judge motion and determine how far a task has progressed, but processing more video can delay their next action.
In Brief
- Google Unveils a Cross-App Gemini Agent for Enterprise Work Google’s cloud-based agent can work across Workspace, Slack, and Microsoft 365 while maintaining context across devices. It is currently available to enterprise customers in private preview.
- Anthropic Launches Cyber Program for Critical Infrastructure and Open-Source Software Anthropic’s Cyber Mission will provide frontier models, engineers, and threat research to infrastructure defenders, while its free OSS Scanner will periodically inspect participating open-source projects. Anthropic cautions that scanner reports are model-generated without human review and may be invalid.
- Arena Raises $200 Million at a $3.1 Billion Valuation Arena, a crowdsourced AI-model evaluation platform that began as a UC Berkeley research project, raised a Series B led by Lightspeed Venture Partners and Khosla Ventures. The company says it reached $100 million in annualized revenue in June and has added an alignment leaderboard.
- USA Today Seeks More Than $250 Million From OpenAI USA Today Co. and several of its local newspapers sued OpenAI, alleging that it copied hundreds of thousands of articles without permission to train AI models. OpenAI had not responded to The Verge’s request for comment.
- Fired OpenAI Researchers Contest Misconduct Allegations Jasmine Wang, Tomek Korbak, and Mikita Balesni denied mishandling sensitive information and said their dismissals could discourage safety work and external collaboration. OpenAI said an investigation found a pattern of policy violations and denied that the firings were retaliation for raising safety concerns.
- Anthropic Commits $150 Million to a Federal AI Science Initiative Anthropic will provide Claude products, API credits, training, and technical support to the Genesis Mission, a US federal initiative involving more than 15 agencies. The three-year commitment is intended to support several hundred research projects, including work in fusion energy and quantum computing.
- Google Releases an Offline AI Meeting-Notes App for Macs Google AI Edge Foresight transcribes and summarizes meetings, answers questions, and references local files without sending audio or notes to the cloud, according to Google. The free experimental app uses EmbeddingGemma 2 and is optimized for Apple Silicon Macs.
- OpenAI Says It Disrupted Two “False Front” Influence Operations OpenAI reported disrupting two AI-enabled influence operations that used purported journalists and a think tank to distribute geopolitical messaging.
- OpenAI Withdraws Three Mathematics Manuscripts OpenAI updated its mathematics repository with six new Lean formalizations, 19 modifications, and three withdrawals. The withdrawn manuscripts concerned Weil classes, Kuga–Satake correspondences, and the rational Hodge conjecture.
- STEPQuant Cuts Recurrent-State Serving Memory by Up to 68.7% Researchers introduced STEPQuant, a post-training quantization method for the persistent states used by linear-attention models. They report that its six-bit configuration preserved near-FP32 accuracy, compressed recurrent states by more than fivefold, and reduced total serving memory by as much as 68.7% in an SGLang implementation.