Resources & links.

Direct access to Claude Haiku 4.5, Sonnet 4.6, and Opus 4.7 with prompt caching and batch processing

Access GPT-5.5 Instant, GPT-5.5 Pro, DALL-E 3, Whisper, and text-embedding-3 models

Free tier includes Gemini 3.5 Flash (launched I/O 2026); paid tier unlocks Gemini 3.1 Pro with 2M token context

LPU-based hardware delivers industry-leading inference speeds on open models

Single OpenAI-compatible endpoint for Claude, GPT, Gemini, Llama, and more

Access Qwen 3.7 Max ($2.50/M input) and open Qwen 3 models — also available via OpenRouter at qwen/qwen3.7-max

Run and fine-tune Llama, Mistral, and other open models with a simple API

One-line API for thousands of community models including Stable Diffusion and Flux

Free serverless inference on 100,000+ models from the HF Hub

Composable chains, retrieval, agents, and integrations for every major LLM

Best-in-class RAG pipelines with support for 100+ data source connectors

Unified API with streaming, tool calling, and structured outputs for all major providers

First-party SDK with full type safety, streaming, tool use, and prompt caching support

Type-safe agent framework with dependency injection and model-agnostic design

Forces LLM responses into validated Pydantic models with automatic retry on failure

End-to-end robot learning: data collection, training, and deployment for SO-ARM100, OpenArm, and LeRobot Humanoid platforms (Apache 2.0)

Assign roles to agents and let them collaborate on complex tasks autonomously

Build cyclic, stateful agent workflows as graphs with fine-grained control

Customizable conversational agents that work together to solve tasks

Pre-built integrations with GitHub, Slack, Gmail, Jira, and 100+ apps for agents

Minimal ~1,000 line codebase for code-first agents that write and execute Python

One command to run Llama, Mistral, Gemma, and 100+ models locally with GPU support

PagedAttention memory management for up to 24× throughput improvement over HuggingFace

Serverless vector DB with built-in hybrid search (dense + sparse) for RAG applications

High-performance Rust-based vector database with filtering and payload support

Built-in vectorization modules for text, images, and multimodal data

Simplest vector DB to get started with — runs locally in pure Python, no setup needed

Connects Claude or Copilot to your .pbix file — AI reads tables/relationships and writes DAX directly. Privacy note: table names, column names, and query results flow to the LLM; use Enterprise plans or local models for sensitive data.

Open protocol by Anthropic enabling AI models to access local and remote data sources

Official collection of reference MCP servers for GitHub, Slack, Postgres, filesystem, and more

Connect Claude and other AI models to 6,000+ apps with no-code automation triggers

Drag-and-drop workflow builder with native Claude and OpenAI modules

Elo-based leaderboard from millions of human preference votes across all major models

YAML-based test suites for evaluating prompt quality, safety, and regression testing

Systematic framework for measuring model performance with hundreds of pre-built evals

One-line integration to log requests, track costs, and monitor latency across LLM providers

Traces MCP tool calls in real time — shows which table names, column names, and query results leave your machine when using Power BI MCP, Cursor, or other AI dev tools

Host, discover, and share ML models, datasets, and demos with 1M+ model repos

Active discussion of papers, industry news, and research with 3M+ members

Researchers, founders, and engineers sharing papers, demos, and takes as they happen

Focused forum for long-form AI safety research posts from leading researchers

The primary venue for AI research papers before peer review — hundreds published daily

Every ML paper linked to its implementation, with live benchmark leaderboards

In-depth articles by researchers explaining complex ML concepts and recent advances

Constitutional AI, interpretability, model cards, and frontier safety research from Anthropic

The 'Flamingo Book' — covers testing at scale, code review, version control, and team culture; essential context for the AI-era second-order effects Bender describes at Google I/O 2026

Original source of the 'AI as amplifier' finding — DORA data shows AI lifts elite performers most; teams with weak practices see minimal gains or regression

Best single video for engineers entering AI — no maths required, covers tokenization → fine-tuning → alignment in one session

The definitive visual explanation — watch the 4-part series in order for the clearest mental model of how LLMs actually learn

Essential for understanding the AI investment landscape in mid-2026 — covers Anthropic S-1, Trump EO dynamics, Claude's 640% YoY growth, and AI robotics strategy

The most product-dense Google I/O in history — watch from 1:20:00 for the Project Astra and Antigravity agent demos that define the 2026 agentic AI playbook

Short-form practitioner video on AI agents from Eduardo Ordax (AWS) — hosted on LinkedIn rather than YouTube, so no embed preview is available on this site