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Click anywhere to start. This is a simple tool to measure your reaction time. The average (median) reaction time is 273 milliseconds, according to the data collected so far. In addition to measuring your reaction time, this test is affected by the latency of your computer and monitor.

2025年3月26日 · With test-time compute, the relationship between compute and capability intensifies—the same model can deliver different levels of intelligence depending on allocated thinking time. This makes deployment compute's importance even stronger: it now determines both how many AI systems can operate simultaneously and how intelligent each instance ...

2025年2月6日 · we dive into test-time compute and discuss five+ open-source methods for its effective scaling for deep step-by-step models' reasoning.

2024年8月6日 · In this work, we analyze two primary mechanisms to scale test-time computation: (1) searching against dense, process-based verifier reward models; and (2) updating the model's distribution over a response adaptively, given the prompt at test time.

What Is Test-Time Compute? In the world of Artificial Intelligence (AI) and machine learning, particularly within the domain of Large Language Models (LLMs), test-time compute refers to the computational resources utilized during the inference phase—the process where a model generates outputs in response to user prompts or queries. Unlike the ...

2024年12月13日 · In test-time compute, MCTS is used to explore and evaluate multiple potential decisions or outputs by building a search tree dynamically during inference. It balances exploration (testing less familiar options) and exploitation (focusing on the most promising options) to identify near-optimal solutions efficiently.

2025年3月25日 · TAO uses test-time compute and reinforcement learning to improve models using data that enterprises already have, such as input examples, making it straightforward to improve any deployed AI application in quality and reduce cost by using smaller models. TAO is a highly flexible method that shows the power of test-time compute for specialized ...

2025年1月8日 · In this post, we will discuss one such approach: by altering the LLM training objective, we can reuse existing data along with more test-time compute to train models to do better. The predominant principle for training models today is to supervise them into producing a certain output for an input.