TLDRocket
Sign in
Latest Further Developments About Internal AI Models Hacking Things — Zvi (Don't Worry About the Vase) Latest open artifacts (#23): Laguna S2.1, Inkling, & Kimi K3 show the... — Interconnects The Sequence Radar #906: Last Week in AI: Open Models, Intelligent Rob... — TheSequence Is paying artists enough to convince them to embrace AI? — The Verge NVIDIA AI Releases Molt: A PyTorch-Native Agentic Reinforcement Learni... — MarkTechPost End-to-End Forecasting with TimesFM 2.5: Backtesting, Covariates, Anom... — MarkTechPost Open letters about AI development — Simon Willison 🔮 Leopold & exponential markets; transformative GLP-1s; runaway AI &... — Exponential View

Every AI story that matters — in your inbox by 8am.

TLDRocket reads 60+ sources, removes duplicate coverage, and publishes a short neutral summary of every story, linking back to the original. Free, no spam, unsubscribe anytime.

Wednesday, 25 February 2026

A Dream of Spring for Open-Weight LLMs: 10 Architectures from Jan-Feb 2026

Ahead of AI 5 months ago 37

Ten open-weight large language models were released between January and February 2026, including Arcee's Trinity Large (400B parameters), Moonshot's Kimi K2.5 (1 trillion parameters), and StepFun's Step 3.5 Flash (196B parameters), featuring architectural innovations such as sliding window attention, mixture-of-experts designs, and multi-token prediction. Key performance metrics include Step 3.5 Flash achieving 100 tokens/second throughput compared to DeepSeek V3.2's 33 tokens/second, while Qwen3-Coder-Next outperformed larger models on coding benchmarks despite having only 3 billion active parameters. These releases demonstrate ongoing architectural experimentation in open-weight model development, with techniques borrowed from proprietary models being adapted for efficiency and performance across different scales and specializations.

CoderForge-Preview: SOTA open dataset for training efficient coding agents

Together AI 5 months ago 1

A research team released CoderForge-Preview, an open dataset containing 258,000 test-verified coding agent trajectories spanning 51,000 tasks across 1,655 repositories. A Qwen 32B model fine-tuned on this data achieved 59.4% pass@1 on SWE-Bench Verified, ranking first among open-data models in the ≤32B parameter range. The dataset enables open-source researchers to train and improve coding agents without relying on proprietary data sources.

Disrupting malicious uses of AI | February 2026

OpenAI Blog 5 months ago 12

Malicious actors are combining AI models with websites and social platforms to enable coordinated attacks and deception campaigns. The threat report documents specific techniques where bad actors exploit publicly available AI systems to scale their operations across multiple platforms simultaneously. This requires updated detection methods and defense strategies that account for AI-assisted coordination at scale.

The daily briefing

Every AI story that matters, in your inbox by 8am.

TLDRocket reads 60+ sources, removes duplicate coverage, and summarises the day in two minutes. Free, no spam, unsubscribe anytime.