Unverified50% confidenceFactExact time
DeepMind's Thinking Tokens research attempts to insert special placeholder tokens into sequences to allow the model to perform additional internal computation.
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50%
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Long-term
Relevance
9/3/2026
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Related Claims
UnverifiedInference-enhanced models such as DeepSeek-R1 generate a large number of intermediate reasoning tokens before producing the final answer, and these thinking tokens are counted as output token costs.74% similarVerifiedDeepMind's Dreamer series of models performs planning in latent space, improving the sample efficiency of reinforcement learning.71% similarVerifiedDeepMind research has shown that on certain mathematical reasoning tasks, smaller models can surpass models with larger parameter counts by increasing the amount of inference-time computation.71% similarUnverifiedThe DeepSeek model can disable thinking mode by setting the thinking type in extra_body to disable; thinking mode is essentially an engineering implementation of Chain-of-Thought (CoT) technology.71% similarUnverifiedDeepMind's AlphaGeometry, MIT's probabilistic programming language Gen, and IBM's neuro-symbolic AI project are all attempting to combine the perceptual capabilities of neural networks with the reasoning capabilities of symbolic systems.70% similar
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