Today in AI ·

Dream Labs #Robotics #FoundationModels #Funding

Dream Labs opens Dream-1 robot model API

Dream Labs emerged from stealth with $90 million in seed funding and a public API for Dream-1. The company says the model can control previously unseen bimanual robots without robot-specific demonstrations or fine-tuning, potentially reducing deployment work.

Read at Dream Labs
Cloudflare #Cloudflare #AIModels #DataExtraction

Cloudflare previews Clairic for structured data extraction

Cloudflare introduced Clairic in preview on Workers AI on October 19, with open weights planned. The model extracts, computes, estimates and forecasts values from unstructured inputs, offering developers a specialized alternative for structured-data tasks.

Read at Cloudflare
GitHub #GitHubCopilot #Governance #DeveloperTools

GitHub adds REST controls for Copilot model policies

GitHub made REST endpoints for retrieving and updating Copilot model policies generally available on October 19. Controls span enterprises, teams, apps and organizations, enabling administrators to automate model availability and delegation.

Read at GitHub
Hugging Face #PyTorch #LocalAI #AppleSilicon

PyTorch 2.15 preview improves AI workloads on Macs

Hugging Face detailed FP8 support, faster language-model decoding and new Metal kernels in the PyTorch 2.15 release candidate on October 20. The MPS improvements target local AI performance and memory use, with macOS 15 and Python 3.11 now required.

Read at Hugging Face
Hugging Face #AIAgents #Training #OpenSource

Hugging Face publishes a curriculum for training AI agents

Hugging Face published an agent post-training curriculum on October 20 covering supervised fine-tuning, distillation, reinforcement learning, environments and harnesses. It connects lessons, examples and tooling to help developers train agents across complete multi-step workflows.

Read at Hugging Face

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60-second Shorts and long-form deep dives on how real AI systems are built, how they break, and how to fix them: caching, RAG, agents, security and decision models.

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Five stages, from the edge of the network to the security of your agents.

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  1. 1 Foundations Edge & Caching Why far servers feel fast, where edge rendering backfires, and how one cache expiry can take down an AI app. 2 episodes · 2 coming 0 of 2 done
  2. 2 Core Decision Models When a typed decision beats generated text, and how to route between a decision model and an LLM. 3 episodes · 1 coming 0 of 3 done
  3. 3 Advanced Agents in Production Context, memory, cost guardrails and the workspace an autonomous coding agent needs. 9 episodes · 5 coming 0 of 9 done
  4. 4 Hands-on Hands-On: Coding Agents from Your Phone Step-by-step tutorials: build and ship real apps from the Claude app, with the prompts and the code for every step. 3 episodes · 2 coming 0 of 3 done
  5. 5 Hands-on AI Coding Agent Tips One practical tip per Short for Claude Code and the other coding agents, each one tested in a real run. 2 episodes 0 of 2 done
  6. 6 Extra Code Stories Picture-led stories from the history of programming, and what they say about where coding goes next. 2 episodes 0 of 2 done
  7. 7 Advanced AI Security Stolen tokens, poisoned tools and the other ways an AI system gets turned against its users. 4 episodes · 2 coming 0 of 4 done

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