TAU and Google Israel launch three-year AI research program with $1M from Google.org
Tel Aviv University (TAU) and Google Israel are launching a three-year program to advance research in artificial intelligence. Google.org is providing $1 million in funding to kickstart the initiative.
The collaboration brings together leaders from academia and industry, including Avinatan Hassidim, Prof. Tova Milo, Prof. Yossi Matias, Prof. Ariel Porat, and Prof. Yishay Mansour. The focus is clear: accelerate high-impact AI research while strengthening the local research ecosystem.
Who's involved
The program features senior voices across research and leadership from TAU and Google Israel. Their combined track record spans academic leadership, large-scale research operations, and applied AI.
What this program could support
While full details weren't provided, programs of this type typically emphasize practical outputs and collaboration. Expect opportunities that help researchers build, test, and share work with both academic and industry impact.
- Seed grants for multi-year projects and student fellowships
- Joint research between TAU and Google-affiliated researchers
- Seminars, workshops, and visiting scholar exchanges
- Open datasets, benchmarks, and reproducibility practices
- Responsible AI reviews and human-centered evaluation
- Compute access and tooling to speed experimentation
Why it matters for scientists and research teams
A three-year window gives labs enough time to run meaningful studies, publish, and iterate. Funding paired with industry partnership can shorten the path from idea to deployment, especially on data-heavy or compute-intensive work.
For early-career researchers, this kind of program can provide mentorship, visibility, and smoother access to collaborators. For labs, it's a chance to align research threads with concrete use cases without compromising scientific standards.
How to position your work
- Frame proposals around measurable outcomes: datasets released, benchmarks improved, or evaluation protocols adopted
- Build in reproducibility from day one: clear code, data cards, and experiment tracking
- Prioritize safety, fairness, and transparency alongside performance
- Show a path to integration: potential pilots, partners, or public resources
Next steps
Watch for formal calls, timelines, and application instructions from TAU and Google. Announcements will likely appear on official channels and newsletters.
Helpful resources for upskilling
If you're aligning your lab's roadmap with industry-grade AI practice, these curated paths can save time.
- AI courses by job role for targeted skill building
- Courses sorted by leading AI companies to mirror current tooling and methods
Bottom line: a focused, multi-year TAU-Google Israel effort with fresh funding is good news for AI research. Keep your proposal tight, your evaluation honest, and your outputs useful to both science and society.
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