📰 AI News Daily — 13 Feb 2026

TL;DR (Top 5 Highlights)

• Google DeepMind’s Gemini 3 Deep Think crushes reasoning benchmarks and Codeforces, rolls out via Gemini Ultra and API, with early real-world wins in materials and semiconductor optimization.
• OpenAI’s GPT‑5.3‑Codex‑Spark debuts as a blazing real-time coding model (1000+ tokens/s, 128k context) in research preview, pointing to low-latency, agentic dev workflows.
• Anthropic’s Claude Opus 4.6 lands a 1M-token context and stronger agentic coding, topping major benchmarks and widening access for complex, context-heavy tasks.
• Open models surge: DeepSeek‑V4 and MiniMax M2.5 hit SWE‑Bench highs, while GLM‑5 offers a sparse 744B architecture and 200k local context after compression.
• Creative leap: Kling 3.0 and Seedance 2.0 deliver film-grade, coherent video, pushing AI-generated films toward consistent, long-form storytelling.

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🛠️ New Tools

• ColGREP launches a Rust-based, local multi-vector code search pairing classic grep with semantic retrieval. Integrates with Claude Code, reduces token waste, and runs efficiently on low-power machines.
• Deepagents introduces bring-your-own sandboxes for isolated code execution. Safer agent deployments and flexible environments reduce blast radius and simplify compliance for enterprise automation.
• AI Prompt Linter adds real-time diagnostics, semantic checks, and quick fixes inside IDEs. Treats prompts like first-class code, improving quality and reducing debugging cycles.
• ypi rolls out a recursive coding agent that plans, writes, and improves its own code across steps. Automates multi-phase software tasks and accelerates prototype-to-production loops.
• Lindy Assistant now acts autonomously across 100+ apps via iMessage, no servers or extra hardware. Low-friction automation broadens reach to non-technical teams and personal workflows.
• Developer ecosystem upgrades: LangSmith navigation refresh, LangChain.js Gemini overhaul, VS Code weekly releases, Cline 3.58.0 multi-threaded sub-tasks, mflux 0.16.0 faster local image gen, and Eigent adds MiniMax M2.5.

🤖 LLM Updates

• Google DeepMind – Gemini 3 Deep Think tops ARC-AGI-2, MMMU‑Pro, HLE and Codeforces without tools, hits gold-level math/science, and rolls out via Gemini Ultra and API, with materials and semiconductor breakthroughs.
• OpenAI – GPT‑5.3‑Codex‑Spark delivers ultra-low-latency coding at 1000+ tokens/s with 128k context in research preview. Signals a shift toward real-time, agentic development and tighter IDE feedback loops.
• Anthropic – Claude Opus 4.6 adds a 1M-token context and stronger agentic coding, leading major benchmarks. Expands feasibility of massive-context tasks like monorepo refactors and lengthy legal or scientific reviews.
• DeepSeek‑V4 posts 80.9% on SWE‑Bench, while MiniMax M2.5 reaches 80.2% on SWE‑Bench Verified. Competitive accuracy at lower cost pressures pricing and expands access to high-throughput coding.
• GLM‑5 introduces a 744B sparse architecture and 200k context that runs locally after compression. Blends strong coding with deployment flexibility, narrowing the closed-versus-open gap.
• Lightweight specialists rise: QED‑Nano (4B) matches larger models on theorem proving in natural language, MiMo‑7B boosts agentic behaviors, and Ring‑1T‑2.5 touts gold-tier math with 10x memory efficiency.

📑 Research & Papers

• QED‑Nano (4B) achieves competitive theorem proving entirely in natural language. Demonstrates small models can master symbolic reasoning tasks without toolchains, cutting complexity and compute costs.
• Ring‑1T‑2.5 proposes a trillion-parameter hybrid linear design achieving gold-tier math with 10x memory efficiency. Architectural innovation targets reasoning gains without exorbitant hardware budgets.
• GLM‑5’s sparse 744B design and aggressive compression unlock local 200k context. Points to scalable sparsity as a path to practical, privacy-preserving deployments.
• Researchers report recursive RLMs and multi-draft GRPO-style selection boosting verifiable rewards on hard tasks. Structured self-improvement and robust selection improve reliability over single-shot generation.
• Emerging theory connects scaling-law exponents to language statistics and flags “bliss attractor” failure modes. Better predictive theory aids capacity planning and mitigates degenerate model behaviors.

🏢 Industry & Policy

• Simile raises $100M to build high-fidelity simulations of human behavior. Could reshape testing for social platforms, policy interventions, and robotics training with safer, faster iteration.
• Anthropic closes a major round with a soaring revenue run-rate, scales infrastructure and access, and hires AI Reliability Engineers. Signals intensifying focus on trustworthy, enterprise-grade deployments.
• An Apple Silicon lab upgrades to M3 Ultra Mac Studios with 512GB unified memory, training large models locally on MLX. On-prem performance and privacy become more practical for research teams.
• Microsoft advances grounding systems to keep AI answers current and verifiable. Improved retrieval and citation workflows reduce hallucinations and increase enterprise confidence in production use.
• Open-model competitions (e.g., Code Arena) show GLM‑5 and Kimi‑K2.5 approaching closed performance. Competitive pressure accelerates iteration and keeps costs in check across the ecosystem.

📚 Tutorials & Guides

• Build production apps with Claude Code: a new on-demand course covers integrations, long-term memory, and Skills. Practical recipes shorten onboarding and improve code-assistant ROI.
• Run GLM‑5 locally with 200k context after compression. Step-by-step guidance enables private, large-context workflows without cloud dependencies or extreme hardware.
• Create fully local, private RAG using DeepSeek R1 via Ollama and Elasticsearch. A hands-on path to secure, controllable retrieval systems for sensitive domains.
• LangChain researchers share harness engineering practices from deepagents. Concrete patterns for evaluation and safety trade-offs help teams build more reliable coding agents.

🎬 Showcases & Demos

• Spotify – Honk: an internal Claude-powered system ships features and fixes in real time. Engineers focus on direction while automation handles implementation, showcasing practical agentic development.
• Filmmaking with Kling 3.0 and Seedance 2.0 delivers photoreal textures and coherent sequences. Early reels hint at viable, long-form AI-generated films supplanting parts of traditional pipelines.
• Developer platforms demo instant HTML/CSS/JS game generation with MiniMax M2.5 support. Rapid prototyping compresses idea-to-playable timelines for indie creators and hackathon teams.
• Prime Lab impresses beta users with an agent-based “research agency” for RL experiments. Coordinated agents streamline literature review, experiment design, and iteration speed for ML scientists.

💡 Discussions & Ideas

• Long-horizon agents capable of multi-hour autonomous work are projected by 2026. Focus shifts from raw power to dependable workflows, recovery strategies, and human-in-the-loop controls.
• Open models remain vital for rapid exploration and community iteration, even lagging top closed systems. Accessibility and fine-tuning freedom drive new use cases and reproducible research.
• Robotics splits persist: navigation is mature, manipulation lags. Pushes intensify for deployable real-world RL, better sim-to-real transfer, and safety-aware learning under uncertainty.
• Security debate heats up: can training offensive agents strengthen defense? Advocates argue red-team automation uncovers systemic weaknesses; critics warn of dual-use risks and escalation.
• The “age of simulation” reframes SaaS as agents performing work inside apps. Real-time grounding and verifiable references become essential for accuracy, trust, and compliance.

Source Credits

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