Here’s a concise, practical overview of who funds AI and tech‑innovation startups and where to look depending on stage and need.

1. Top venture capital firms (early → growth)

• Seed / early-stage: Y Combinator (accelerator/seed), Andreessen Horowitz (a16z), Sequoia Capital, Accel, Benchmark, Greylock, Index Ventures, First Round Capital, Lightspeed Venture Partners, Union Square Ventures.
• Growth / later-stage: Bessemer Venture Partners, Insight Partners, Tiger Global, Coatue, General Catalyst, TCV.

2. Firms and funds specialized in AI / deep tech

• a16z (has AI-focused funds), Data Collective (DCVC — deep tech, AI), Khosla Ventures (deep tech), Playground Global (hardware + AI), Granite Ventures, Radical Ventures (AI-focused), Element AI (investor/incubator historically — check current status). Many generalist VCs also have AI-focused partners or thematic funds.

3. Corporate venture capital and strategic investors

• Google Ventures (GV), Intel Capital, Microsoft M12, Salesforce Ventures, Samsung NEXT, Qualcomm Ventures, NVIDIA’s investment programs, SoftBank Vision Fund. These are good for strategic partnerships, distribution, or cloud/GPU credits.

4. Accelerators & incubators

• Y Combinator, Techstars (many city programs and corporate partnerships), 500 Global (formerly 500 Startups), Plug and Play Tech Center, NVIDIA Inception (program for AI startups), AWS Activate, Google for Startups, Microsoft for Startups. They provide funding, mentorship, credits and go‑to‑market help.

5. Angel investors & seed networks

• AngelList syndicates, Clubhouse/Founders’ angel groups, regional angel networks (e.g., Tech Coast Angels, New York Angels), independent angel investors experienced in AI/ML. Good for pre‑seed/seed checks.

6. University / research commercialization funds and labs

• University tech-transfer offices, research incubators (Stanford StartX, Berkeley SkyDeck, MIT Sandbox/Delta V) — often strong for deep‑tech spinouts.

7. Public / government funding and grants

• U.S. SBIR/STTR programs (federal R&D grants), NSF programs (e.g., NSF SBIR/STTR, I‑Corps), state economic development grants and innovation competitions — helpful for early prototype and research funding without equity dilution.

8. Industry‑specific or application‑focused funds

• Healthcare AI: GV, Deerfield, Oak HC/FT.
• Robotics / hardware: Playground Global, Shasta Ventures.
• Climate / energy + AI: Lowercarbon Capital, Energy Impact Partners.

9. Non‑dilutive resources & credits

• Cloud credits and programs from AWS, Google Cloud, Microsoft Azure, NVIDIA (Inception) — useful to reduce runway needs before raising capital.

How to pick the right investors

• Match stage (pre‑seed, seed, Series A/B/C) — some firms only invest at certain stages.
• Domain expertise and network — pick investors who know AI/ML and can open partnerships/customers.
• Check typical check size, follow‑on reserve, and portfolio overlap.
• Strategic vs. purely financial — corporate VCs may bring customers but also strategic constraints.

Quick next steps / resources

• Use AngelList, Crunchbase, PitchBook (paid), or Signal by CB Insights to filter investors by stage, ticket size, and sector.
• Apply to relevant accelerators (YC/Techstars) and corporate startup programs (AWS Activate, NVIDIA Inception).
• For US founders, consider SBIR/STTR for non‑dilutive early funding.

If you want, I can:

• Give a prioritized list of likely-fit investors based on your startup’s stage, domain (e.g., generative AI, computer vision, robotics), and location.
• Draft a short investor outreach email or one‑page investor intro.