Thinking Machines
@thinkymachines
Thinking, beeping, and booping.
@tinkerapi
1 Following 180.8K Followers
Releasing weights indiscriminately isn't safe. Neither is keeping capable models inside a few labs.
We think there's a path between them. We haven't mapped all of it. Our new post covers the part we can see: how we assessed Inkling, and why access should widen in stages.
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Today, we are releasing Inkling-Small.
Inkling-Small achieves comparable performance to Inkling at a quarter of its size. It features 276B total parameters, 12B active. We are making the full weights available.
Fine-tune it on Tinker today, or chat with it in text, image, and audio on Tinker Playground.
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Today, we are introducing Inkling.
Inkling reasons efficiently across text, image, and audio modalities. We are making the full weights available.
Available today for fine-tuning on Tinker. Play with it in the Inkling Playground. 🧵
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We're building AI that people and organizations can shape and make their own. AI should extend our will and judgment instead of neglecting it; enabling that is the technical challenge we are working to solve.
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We are offering grants of $100,000 + Tinker credits to researchers advancing the field of human-AI interactivity. Submit your proposals by June 19th!
1. (System design) - The Interaction Models see your screen and collaborates with you live. Here we're building a scalable system architecture together — no copy-pasting, no switching tabs, just thinking out loud and drawing on the screen together.
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The technical report includes our motivation, early evaluation results, and technical approach.
Lili and Martin get some help controlling themselves.
The model works in more real situations too, like when Mianna is trying to say words she's only read before.
and draws when things are easier to explain visually!
The model can multi-task!
Long thinks the model knows everything, but the model actually searched while listening and responding to him so he didn't notice.
The team has been sweeping at local trivia night thanks to a model that's aware of continuous time.
With the model's simultaneous speech capability, Horace has gotten a lot easier to work with recently.
Our model interjects to save Alex's parents from his eccentric ideas.
Tessa's quality of life has improved a lot with some nagging.
While Lilian is telling a story, the interaction model can track when she is thinking, yielding, self-correcting, or inviting a response; there is no specific built dialogue management system.
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People talk, listen, watch, think, and collaborate at the same time, in real time. We've designed an AI that works with people the same way.
We share our approach, early results, and a quick look at our model in action.
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Guest post by @_Mantic_AI on training LLMs to predict world events in Tinker
Mantic used Tinker to RL gpt-oss-120b on judgmental forecasting; the result outperformed frontier models on event predictions. Combined with @_Mantic_AI's forecasting architecture, task-specific training takes us to the cusp of automated superforecasting.
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We’re thrilled to partner with @thinkymachines to deploy at least 1 gigawatt of NVIDIA Vera Rubin systems for frontier AI model training.
We are partnering with @nvidia to power our frontier model training and platforms delivering customizable AI.
