A complete map of who builds what and how it all connects
The AI ecosystem is a vast, interconnected landscape of companies, technologies, and platforms. From chip makers to cloud providers to application builders - understanding the full picture reveals where value is created and where opportunity lies.
The stack has five layers: Silicon (compute hardware), Cloud (infrastructure platforms), Models (foundation model providers), Tools (development frameworks), and Applications (end-user products). Each layer depends on the ones below it.
NVIDIA, AMD, Google (TPU), AWS (Trainium), Intel, Cerebras, Groq. These companies design the chips that make AI possible. NVIDIA's CUDA ecosystem is the dominant moat.
AWS, Azure, GCP provide GPU clusters, managed services, and APIs. Startups like CoreWeave, Lambda Labs, and Together AI offer specialized GPU cloud.
Anthropic, OpenAI, Google, Meta, Mistral, Cohere build foundation models. Open-source (Llama, Mistral) vs closed-source (Claude, GPT) is the defining tension.
LangChain, LlamaIndex, Weights & Biases, Hugging Face, Vercel AI SDK. These tools make it possible to build AI applications without training models from scratch.
Perplexity (search), Cursor (coding), Jasper (marketing), Harvey (legal), Hippocratic (healthcare). Vertical AI is where most value will be captured.
MCP, A2A, OpenAI function calling. Standards that enable interoperability - the 'HTTP of AI' that connects models to the real world.
The GitHub of AI - hosts 500K+ models, datasets, and Spaces demos
Experiment tracking, model monitoring, dataset versioning for ML teams
Most popular framework for building LLM applications and agent workflows
Frontend-first AI development - streaming, tool use, React components
Run open-source models in the cloud with a simple API call
Fast inference for open-source models, fine-tuning API, GPU cloud
The arms dealer of AI. $3T company because every AI lab needs their GPUs.
Open-source hub - if AI has a center of gravity, it's here.
Reimagining search with AI. $9B valuation. Answer engine, not link engine.
Data + AI platform. Acquired MosaicML. Training models on enterprise data.
Key Takeaway
The AI ecosystem is consolidating around 5 layers. Value flows up from silicon to applications. The biggest opportunity is at the application layer - using foundation models to solve specific industry problems.