Tinker

@tinkerapi

I tink, therefore I am. Post-training API by @thinkymachines

San Francisco

thinkingmachines.ai/tinker

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Tinker
@tinkerapi
Jul 15
Inkling is our first open model from @thinkymachines and is now available on Tinker! Check out these quotes from Tinker customers on their experience with Inkling: @_Mantic_AI: "Not only does Inkling outperform Kimi K2.6 on our forecasting evals, it does so with half the output
Thinking Machines
@thinkymachines
Jul 15
Today, we are introducing Inkling. Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available. thinkingmachines.ai/news/introduci… Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵
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Tinker
@tinkerapi
11h
Sundial put the effort in getting RLVR right: training on verified fixes instead of artificial errors, smart rewards that disincentivize hacking, and deterministic scoring. The result — a trained Inkling-Small that fixes 83.7% of LaTeX errors in under 1 second and $.0013.
turboblitz
@turboblitzzz
11h
We fine-tuned @thinkymachines' Inkling-Small to fix LaTeX compile errors inside the editor, in under a second. On real errors it matches Claude Fable 5.1, six times faster and at about 1/40 of the cost. When we interviewed mathematicians, one of the most common annoyances we
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Tinker
@tinkerapi
Sep 15
To learn who the model thinks it is, look at whom it imitates. Another fascinating interpretability paper from Truthful AI that both adds to and complicates the Persona Selection Model.
Owain Evans
@OwainEvans_UK
Sep 15
New paper: We trained models on synthetic stories about humans only (no AIs). We found the Assistant adopts quirky behaviors from the stories in ordinary chat. Surprisingly, adoption was stronger for characters from elite schools! Why does this happen? 🧵
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Tinker
@tinkerapi
Sep 14
RLVR isn't just for math and code. Engineers spent decades building physics-based verifiers for electromagnetic systems. @gentrajectory is using these and Tinker to train models that design power transformers to meet specs at low cost in the real world.
General Trajectory
@gentrajectory
Sep 7
AI is now improving its own model architectures and chips. The power infrastructure it runs on deserves the same attention. We used RL to teach a Kimi base model to design medium-power transformers. It met 93% of unseen specs, helping to compress multi-week engineering efforts
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Tinker
@tinkerapi
Sep 9
We highlighted how OpenResearch+Tinker make exploratory research easier, but equally important is auditing: testing dozens of competing published methods in an automated way with the compute cost forecast to within a dollar. We love to see our research grants support great work!
alphaXiv
@askalphaxiv
Sep 9
Using Tinker with an autoresearch loop is a really effective way to reproduce post-training papers at predictable costs Today there are dozens of self-distillation methods all claiming improvements over each other, and it’s hard to establish which claims hold up We gave agents