DeepSeek jolts AI industry: Why AI’s next leap may not come from more data, but more compute at inference
To contextualize DeepSeek’s disruption, let's consider the broader shift in AI being driven by the scarcity of training data.
Google makes its reasoning-optimized Gemini 2.5 Pro model available in public preview
Google LLC today made Gemini 2.5 Pro, an advanced large language model it debuted last month, available in public preview.
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Researchers created an AI reasoning model on par with OpenAI's o1 for less than $50
If the researchers wanted the model to spend more "test-time compute" on a problem, they would simply tell the model to "wait," which extended its thinking time and led to more accurate results.
InfoWorld10d
Databricks’ TAO method to allow LLM training with unlabeled data
Test-time Adaptive Optimization can be used to increase the efficiency of inexpensive models, such as Llama, the company said ...
Less is more: UC Berkeley and Google unlock LLM potential through simple sampling
The current popular method for test-time scaling in LLMs is to train the model through reinforcement learning to generate longer responses with chain-of-thought (CoT) traces. This approach is used in ...
TechSpot13d
Most AI experts say chasing AGI with more compute is a losing strategy
Cheaper, more efficient alternatives to scaling are being explored. OpenAI has experimented with "test-time compute," where AI models spend more time "thinking" before generating responses.