The technology operates at 0.75V with data retention exceeding 128ms, targeting high-density processor caches with lower power consumption than SRAM.
Specialized versions trained on consumer behaviors replace general-purpose variants for non-subscribers starting November 8.
The tool creates per-project VMs with allowlisted networking and proxy-based token injection to protect host systems from prompt injections and rogue agents.
The update introduces a built-in HTTPS tunnel using Let's Encrypt, Google Trust Services, and ZeroSSL that requires no account or payment.
The feature uses Plaid to access balances and transactions on Pro, Max, and Ultra plans, allowing users to query spending without giving Claude control over funds.
NVIDIA has released four interactive world simulation models based on Cosmos 3 under the OpenMDW-1.1 license.
The method removes inter-round dependencies by drafting successor blocks during verification, achieving higher average speedups than DFlash across seven benchmarks.
Snyk's analysis of 20,000 skills flagged over 65% for unsafe behavior but identified only nine as actively malicious, including one that appends remote text to global configuration.
The smallest 0.8B model outperforms existing translation-specialized LLMs with over 30 times the parameters in Japanese-English and multilingual tasks.
The 560B-parameter model supports text, image, and video inputs and achieves 92.21 on OmniDocBench 1.5.
It recorded a 0.07% out-of-scope attack rate while discovering 948 Linux kernel privilege escalation vulnerabilities.
The new metrics include spend per day, spend per API key, input and output tokens per model, and cached input rate.
Inkling 2 Small achieved the final score of the first generation in just 75 steps of RL fine-tuning.
The tool uses 320 CLI and MCP tools to analyze native apps, websites, and games, then directs coding agents to rebuild them in a clean-room or deep mode.
The model features a 1M-token context window and is available in public preview without waitrooms or session limits.
The RL update improves hard math and code scores to match the base Qwen3.8-27B while maintaining 0.67x thinking token usage on agent tasks.
The round is expected to close in coming weeks and could total about $20 billion, falling short of a previous $30 billion target.
The 131M parameter model supports 6 languages and 14 voices, achieving 30ms warm start on M5 Max and 0.85% WER on the Open TTS Leaderboard.
GitHub proposes a four-stage agentic workflow using Copilot to reduce the 441% increase in pull request review times caused by high AI adoption.
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