Thinking Machines Lab Unveils Tinker: An API for AI Model Fine-Tuning
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Exclusive: Mira Murati's Stealth AI Lab Launches Its First Product
Thinking Machines Lab, a heavily funded startup cofounded by prominent researchers from OpenAI, has revealed its first product -- a tool called Tinker that automates the creation of custom frontier AI models. "We believe [Tinker] will help empower researchers and developers to experiment with
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Thinking Machines' first official product is here: meet Tinker, an API for distributed LLM fine-tuning
Thinking Machines, the AI startup founded earlier this year by former OpenAI CTO Mira Murati, has launched its first product: Tinker, a Python-based API designed to make large language model (LLM) fine-tuning both powerful and accessible. Now in private beta, Tinker gives developers and
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Thinking Machines' First Product Lets You Fine-Tune LLMs on Your Laptop | AIM
Tinker is an API service that handles compute and infrastructure needs for fine-tuning models. Thinking Machines, the AI startup founded by the former OpenAI CTO Mira Murati, has announced its first product, Tinker. Tinker is an API that helps developers fine-tune large language models. "It
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Mira Murati's Thinking Machines launches first product, Tinker
Former OpenAI CTO Mira Murati's AI start-up Thinking Machines has launched its first product, Tinker, an API for fine-tuning language models. Mira Murati's Thinking Machines has launched its much anticipated first product - Tinker, "a flexible API for fine-tuning language models". Back in July
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Thinking Machines launches Tinker language model fine-tuning service - SiliconANGLE
Thinking Machines launches Tinker language model fine-tuning service Thinking Machines Lab Inc., the artificial intelligence startup led by former OpenAI executive Mira Murati, today introduced its first commercial offering. Tinker is a cloud-based service that developers can fine-tune, or
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Former OpenAI CTO Mira Murati's startup, Thinking Machines Lab, launches Tinker—an API service designed to democratize and simplify the fine-tuning of large language models for researchers and developers.
Thinking Machines Lab Introduces Tinker: Revolutionizing AI Model Fine-Tuning
Thinking Machines Lab, an AI startup cofounded by former OpenAI CTO Mira Murati, has launched Tinker. This API service automates and simplifies the fine-tuning of custom frontier AI models
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, democratizing AI research by allowing more efficient language model customization.
Source: SiliconANGLE
What Tinker Offers
Tinker is a Python based API that empowers developers and researchers to fine-tune large language models (LLMs) with greater control and accessibility
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. It supports open-source models like Meta's Llama and Alibaba's Qwen for fine-tuning (supervised or reinforcement learning), abstracting away distributed compute and infrastructure complexities1
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Source: VentureBeat
Core Features and Benefits
- Direct Control: Tinker provides low-level Python primitives, allowing users to build custom fine-tuning or RL algorithms without managing GPU orchestration
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. - Efficiency: It leverages Low-Rank Adaptation (LoRA) for cost effective fine-tuning, enabling multiple training jobs to share compute pools efficiently
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. - Scalability: The service supports a wide range of open-weight models, from smaller variants to large Mixture-of-Experts architectures like Qwen-235B-A22B
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. - Simplified Infrastructure: Tinker handles scheduling, resource allocation, and failure recovery, letting users concentrate on their algorithms and data
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Early Adopters and Impact
Tinker has already been adopted by several research institutions, demonstrating its practical utility. Princeton's Goedel Team utilized it for LLM fine-tuning in formal theorem proving, achieving significant results with less data
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. Stanford's Rotskoff Lab improved chemical reasoning models, and Berkeley's SkyRL group experimented with multi-agent RL training loops2
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.
Source: Silicon Republic
Industry experts like Andrej Karpathy and John Schulman have praised Tinker for its balance of algorithmic control and infrastructure abstraction, calling it "the infrastructure I've always wanted"
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.Availability and Future
Currently in private beta with a waitlist, Tinker will eventually transition to usage-based pricing
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. Thinking Machines has also released an open-source 'Tinker Cookbook' for implementing common post-training methods3
. This initiative marks a significant step towards broadening access to advanced AI capabilities, fostering innovation across AI application fields.References
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