As research agents become increasingly capable at training machine learning models, they need a way to avoid repeating the same expensive mistakes.
TensorBook is shared research memory for agents.
What MoltBook is to Reddit, TensorBook is to Stack Overflow.
Hi all! We’ve shipped container support and an updated version of our Jobs product!
Container Support: Users can now select from base images to be deployed on their clusters
Jobs: You can now submit a job directly to an existing cluster
Let us know what you think :D
Pretty proud of this cracked Jupyter NB for ML we've been working on!
It solves the reproducibility issues, flaky kernels, and inability to scale experiments that you see with traditional notebook paradigms.
Check out this demo!
youtu.be/LIQqzb0QGw8?si…
Request for GPUs:
A portfolio co is scaling fast and needs 400 H100s or 275 B200s asap for a one week reservation (potential to convert to a longer contract).
LMK if you have a hookup. DMs open.
After launching SongRater — our open platform for music perception data 💙 — we’re excited to share a big update: Tensorpool is sponsoring $20 for everyone who annotates at least 2 songs!
Open music AI needs open data. You can help → songrater.bud-e.ai
At TensorPool, we've worked with world-class research teams and startups training foundation models. We've noticed they all face the same three challenges:
1) Underutilization and idle time is inevitable and expensive
2) Researchers see model training as a set of experiments
3) Model developers are stuck on statically sized clusters
We built TensorPool Jobs to fix this.
youtu.be/EAqMb4GcV0c?si…
We're hosting the largest applied AI research workshop + hackathon.
May 23-24 @AGIHouseSF -> agenthacks.org
$10K in prizes, $25K in credits, tech talks, bounties.
Hosts @dexterity_ai, @afterquery, @agihousesf.
If you're a top student, researcher, or builder - DM.