All tags
Person: "petergostev"
not much happened today
kimi-k3 moonshot vllm baseten modal together-ai ollama dell nvidia mixture-of-experts model-scaling numerical-stability model-architecture open-models model-distribution model-licensing agentic-ai vision scaling-efficiency open-source-infrastructure commercial-restrictions ai-security kimi_moonshot jensenhuang natolambert petergostev artificialanlys
Moonshot released the Kimi K3 open-weights model, a 2.8T-parameter MoE with 104B active parameters, 896 experts, and 1M-token context featuring native visual understanding. The release includes open-source infrastructure like FlashKDA, MoonEP, and AgentENV, enabling large-scale agentic post-training and serving. The technical report highlights a ~2.5× scaling-efficiency improvement over K2 with innovations in numerical stability and MoE routing. Licensing is source-available with commercial-use restrictions, signaling a trend towards open-weight models with business carve-outs. Distribution was broad and immediate via platforms like vLLM, Baseten, Modal, Together, and Ollama Cloud. Separately, NVIDIA launched the Open Secure AI Alliance to build an ecosystem combining open and closed frontier models for AI security, emphasizing defense against attackers already equipped with strong AI.
not much happened today
gpt-5.2-codex gpt-5.3-codex openai langchain baseten ollama openrouter agent-orchestration context-pipelines coding-agents pricing-models multi-agent-systems workflow-optimization model-agnostic-orchestration prompt-engineering memory-optimization anthony_maio mason_drxy hwchase17 sydneyrunkle naroh teknuim vtrivedy dbreunig zachtratar theo petergostev cheatyyyy
AI Twitter Recap highlights the shift from model-centric AI to context pipelines and agent orchestration as key performance drivers. Notably, gpt-5.2-codex and gpt-5.3-codex showed significant benchmark improvements through prompt and middleware tuning. The ecosystem around open harnesses like Hermes, deepagents, and Flue is rapidly evolving, with innovations in multi-agent coordination and model-agnostic orchestration. Developer workflows are adapting to coding agents such as Codex and Claude Code, with emerging challenges in pricing models due to high token usage in agentic workloads. The practical takeaway is that agent performance depends on the synergy of model × harness × memory/context strategy, not just model weights alone.
GPT-Image-2
gpt-image-2 qwen3-1.7b codex openai hugging-face figma canva adobe nous-research image-generation multilingual-models model-integration benchmarking agent-infrastructure multi-process-systems fine-tuning scientific-reasoning healthcare-ai hierarchical-decomposition clementdelangue lewtun gdb nickaturley mark_k petergostev tekninum mayank_022
OpenAI launched GPT-Image-2, enhancing image generation with improved text rendering, layout fidelity, editing, multilingual support, and "thinking" capabilities. It supports generating slides, infographics, diagrams, UI mockups, and QR codes, and integrates with tools like Figma, Canva, Adobe Firefly, and Hermes Agent. Benchmarks show GPT-Image-2 leads image generation tasks with a +242 Elo advantage. Hugging Face released ml-intern, an open-source agent automating post-training research loops, improving scientific reasoning and healthcare benchmarks significantly. Hermes is evolving into a richer local/open agent platform with enhanced multi-process orchestration capabilities.