Thinking Machines

At Thinking Machines Lab, we’re passionate about artificial intelligence and making it accessible to everyone. Our mission is to create a future where AI is a tool that anyone can use to achieve their unique goals.

While AI has made incredible strides, there are still significant gaps to fill. The scientific community is playing catch-up with the rapid advancements in AI, and much of the knowledge about these systems is concentrated in top research labs. This limits public understanding and the ability to use AI effectively. We’re here to change that by making AI more understandable, customizable, and capable for everyone.

Our team is made up of scientists, engineers, and innovators who have developed some of the most widely used AI products, like ChatGPT and Character.ai, as well as open-source projects such as PyTorch and Segment Anything. We believe that science thrives when it’s shared, so we’re committed to collaborating with the broader community of researchers and builders. Expect to see frequent technical blog posts, papers, and code from us, as we believe sharing our work benefits everyone and enriches our own research culture.

We’re focused on creating AI that truly works for everyone. This means emphasizing human-AI collaboration, building flexible and personalized systems, and ensuring that AI can adapt to a wide range of human expertise. We see enormous potential for AI to assist in every field, not just programming and mathematics.

To achieve this, we’re prioritizing model intelligence and building robust infrastructure. We believe that the most advanced models will unlock transformative applications, like new scientific discoveries and engineering breakthroughs. Quality infrastructure is key to maximizing productivity and security, so we’re committed to doing things right for the long term.

We also see multimodal capabilities as crucial for more natural communication and deeper integration into real-world environments. Our approach is empirical and iterative, with a strong focus on AI safety. We’ll maintain a high safety bar, share best practices, and contribute to external research on alignment.

Ultimately, we’re here to learn by doing. Products and research go hand in hand, keeping us grounded and focused on solving the most impactful problems. We’ll measure what truly matters—how our systems create genuine value in the real world.

(Tito here; I am posting to promote only… however they are just starting out so give them some time to establish themselves but reach out to them on ‘X’ as the form for employment is not loading right now.)

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Bryan Parras

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