Stay ahead on AI.
All in ONE place.

The accessible source details point to this update: Bringing GPT-Rosalind to academic research labs. Because the full article could not be reliably extracted or rewritten, this TLDR stays conservative and is based on headline-level information plus limited source context from openai.com.

Google Quantum AI has demonstrated "magic state cultivation" on its Willow processor, achieving a fold reduction in errors compared to uncultivated states and a record logical fidelity of 99.99%. Published in Science, the breakthrough addresses a bottleneck identified since 2004, where creating error-corrected magic states could consume up to 95% of a quantum computer's capacity. The team, led by Craig Gidney, Noah Shutty, and Cody Jones, also demonstrated switching between color codes and surface codes on real hardware.

Anthropic has granted METR, an AI safety nonprofit, employee-like access to evaluate its models and safety practices. Six METR staff received company hardware, office space, and access to internal tools comparable to Anthropic's own risk assessment teams. METR will independently publish risk assessments without Anthropic veto rights, though Anthropic can require redactions in narrow predefined categories. Anthropic is also working with SecureBio and Accenture as evaluators, and is in early discussions with Hugging Face, under a three-tier access framework.

Google has updated Circle to Search on Android to detect text message scams. Users can activate the feature by long-pressing the home button or navigation bar, then drawing a circle around a suspicious message. Circle to Search will generate an AI Overview with guidance, insights, and suggested next steps. If red flags are detected, users are advised to delete the message and block the sender's number, helping people avoid phishing links and protect personal information.

Microsoft has completed pre-training MAI-Base-2, a Mixture-of-Experts foundation model with 80 billion active and 2.8 trillion total parameters. Trained on 16,000 GB200 GPUs over 38 days, it outperforms every open-weight model tested and is 4 to 12 times more FLOPs-efficient than DeepSeek-V4-Pro-Base. Built on organic data without model distillation, Microsoft plans to license weights to enterprise partners via Foundry. MAI-Base-2 is currently undergoing post-training.

Krea has opened the beta for Krea 3, a new image editing model that delivers end-to-end 2K edits in under 8 seconds. The model matches the quality of Nano Banana Pro and GPT Image 2.5, and supports bounding box control with precise multi-turn edits designed for iterative creative workflows. A full release with additional benchmarks is planned for the following week, with LoRAs and style references already available for early experimentation via direct message.

OpenAI engineer Tibo announced that the company has deployed a series of infrastructure changes and added more compute to significantly reduce the disruptive 'Selected model is at capacity. Please try a different model' error. When capacity issues do occur, the system will now automatically retry and continue on its own rather than blocking the request entirely. OpenAI is asking users to report any remaining occurrences so the team can investigate further.

Rivian CEO RJ Scaringe announced at TechCrunch Disrupt that the company plans to integrate third-party AI agents from companies like Anthropic, OpenAI, and Meta into its electric vehicles. Rivian recently launched its own in-car AI assistant and built a proprietary agentic framework that routes voice commands to local or cloud-based models. Scaringe emphasized safety guardrails, noting agents won't control brakes or steering. Rivian is hosting an AI and Autonomy Day in December to share more details.

NVIDIA released three new open models in its Nemotron 3.5 family for agentic AI. The billion-parameter Super VL delivers frontier multimodal accuracy at 5x faster throughput than comparable models, supporting instruction following, tool use, and visual document understanding. Bolt 74B-A9B 24GB runs local agentic workloads on NVIDIA RTX hardware using bit quantization, while Bolt E4B 4GB targets conversational and physical edge agents. Partners including Salesforce, CrowdStrike, Perplexity, and Atlassian are already integrating or customizing Super VL.