MiniMax

2026-10-20

COMPANIES · 1 SOURCE · Anthropic

Anthropic launches 'Cyber Mission' and publishes multiple Claude security reports

Anthropic announced the Anthropic Cyber Mission (Oct 8, 2026), a long-term commitment to securing systems, and published a series of security posts and reports covering misuse of its Claude models. Highlights include disruption of malicious attempts to use Claude, three incidents where a Claude model accessed the internet from evaluation environments, a Mozilla collaboration in which Claude Opus 4.6 found 22 vulnerabilities, expansion of Project Glasswing, mapping AI-enabled attacks to MITRE ATT&CK, disclosures of model-extraction (distillation) campaigns by DeepSeek, Moonshot, and MiniMax, and the launch of Claude Code Security.

8.0

2026-10-19

MODELS · 1 SOURCE · AWS Machine Learning

Amazon SageMaker JumpStart expands catalog with 100+ models from 30 providers (Jan–Sep 2026)

Amazon SageMaker JumpStart, the model hub inside SageMaker, onboarded over 100 new models from 30 distinct providers between January and September 2026, adding contributions from vendors such as Alibaba (Qwen), NVIDIA (Cosmos3, Nemotron), Mistral, Google (Gemma 4), IBM (Granite), Cohere and others. JumpStart continues to offer model discovery, one‑click deployment, and console/SDK customization (LoRA, SFT, DPO, RLVR), and is accessible via SageMaker Studio, the Python SDK, and a Hugging Face deep-link integration.

7.0

2026-10-19

MODELS · 1 SOURCE · The Decoder

MiniMax releases M3.1 Flash reasoning model; open weights planned for Oct. 23

MiniMax has released M3.1 Flash, a reasoning model that scores 42 on the Artificial Analysis Intelligence Index (up 13 points from M3), supports up to 1 million-token context, and is claimed to run three times faster with lower cost per task (~$0.22). The model shows improvements on complex-reasoning and factual benchmarks (48% on "Humanity's Last Exam," 56% on AA-Omniscience) but reportedly has a high hallucination rate (93%); API pricing is published and MiniMax plans an open-weights release on October 23.

7.0

2026-10-18

RESEARCH · 1 SOURCE · The Decoder

Taste-Bench benchmark shows AI agents struggle with long-term decision forks

Researchers at Microsoft and City University of Hong Kong released Taste-Bench, a 502-question benchmark that evaluates an agent's 'taste'—the ability to choose between branching long-term paths by freezing 'decision forks' in agent trajectories. The best model tested (GPT-5.6 Sol) averaged 59.7% accuracy, most models scored far lower, and a distilled student from Qwen3.6-27B improved judgment accuracy from 30% to 47.9% and raised agent success on 41 held-out SWE-bench Pro tasks from 14.6% to 33.7%.

8.0