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Researchers find large language models process diverse types of data, like different languages, audio inputs, images, etc., similarly to how humans reason about complex problems. Like humans, LLMs ...
The overhaul of US science kicked off within hours of Trump’s inauguration on 20 January, when he signed dozens of executive ...
Getting people excited about science can be a challenge, but a recent study offers a promising approach. Researchers ...
4.2. From Motion Discrimination to Scene Construction: A Nested Inference Problem We now introduce the deep, temporal model of scene construction using the task discussed in Section 3 as our example ...
Measurement literacy is necessary for effectively carrying out the business of science, including inference, experimental design ... "By drawing on ideas and examples drawn from across the sciences in ...
It's a regrettable reality that there is never time to cover all the interesting scientific stories each month. In the past, ...
However, did you know a lot of the bots you have been using are actually examples of artificial intelligence? The bot has been designed to mimic human-like responses and perform a variety of tasks.
These training clusters are "overkill" for many of today’s inference AI workloads and are not the most effective use of AI IT resources. For example, a training cluster could have 800 GPUs and ...
Since the pandemic, drug trials that purposely make people vomit, shiver and ache have become a research area of growing interest. All that’s needed: brave volunteers. Credit...Jon Han Supported ...
Called Transformer² (Transformer-squared), the model uses mathematical tricks to align its weights with user requests during inference ... model is exposed to new examples and its parameters ...
Learn More Inference-time scaling is one of the big ... performance on these tasks without the aid of formal solvers. For example, Gemini 1.5 Flash and o1-preview achieve a success rate of only ...