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Ex-OpenAI CTO’s startup wants to make AI models more consistent
Thinking Machines Lab, led by former OpenAI CTO Mira Murati, shared details on its research to make AI models deliver more consistent responses.
The US-based startup, which recently raised US$2 billion in seed funding, published a blog post exploring how randomness in large language models arises during inference, especially in the orchestration of GPU kernels.
Researcher Horace He suggested that better control of this process could make AI outputs more reproducible, which may be important for enterprises, scientific research, and reinforcement learning.
The company did not specify whether these techniques will be part of its first product, expected to launch in the coming months.
It also announced plans to regularly publish research and code as part of a new series called “Connectionism,” providing rare insight into ongoing work at a company that has attracted significant attention in the AI sector.
🔗 Source: TechCrunch
🧠 Food for thought
Implications, context, and why it matters.
AI determinism research addresses a core enterprise adoption barrier
- Thinking Machines Lab’s focus on making AI models produce consistent responses tackles a fundamental business problem that has limited enterprise adoption of AI systems.
- The company’s research into controlling GPU kernels to reduce randomness in AI responses could significantly improve reinforcement learning training, which they plan to use for customizing AI models for businesses 1.
- This technical approach addresses the practical reality that enterprises need predictable, reproducible results from AI systems, rather than the varied responses that current models like ChatGPT typically produce when asked the same question multiple times 1.
- Their commitment to publish research openly contrasts with OpenAI’s evolution toward more closed development, potentially positioning Thinking Machines Lab to attract researchers and developers who prefer transparent collaboration 1.
Recent Thinking Machines Lab developments
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