Texts in the wild used during pre-training contain lots of biases, such as racial and sexual biases, which are picked-up by the model. During RLHF, the human evaluators are aware of such biases and are instructed to…
This understanding is incomplete in my opinion. LLMs are more than emulating observed behavior. In the pre-training phase tasks like masked language model indeed train the model to mimic what they read (which of course…
Can you provide a link to the comment? R1's technical report (https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSee...) says the prompt used for training is "<think> reasoning process here </think> <answer>…
Agreed. If it's useful, why not scale up the electricity and water supply, and make the latter sustainable.
Though FAANG offers are usually more attractive than startups (considering pay level and stability), some startups could be more selective since they couldn't afford to hire the wrong candidate.
Texts in the wild used during pre-training contain lots of biases, such as racial and sexual biases, which are picked-up by the model. During RLHF, the human evaluators are aware of such biases and are instructed to…
This understanding is incomplete in my opinion. LLMs are more than emulating observed behavior. In the pre-training phase tasks like masked language model indeed train the model to mimic what they read (which of course…
Can you provide a link to the comment? R1's technical report (https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSee...) says the prompt used for training is "<think> reasoning process here </think> <answer>…
Agreed. If it's useful, why not scale up the electricity and water supply, and make the latter sustainable.
Though FAANG offers are usually more attractive than startups (considering pay level and stability), some startups could be more selective since they couldn't afford to hire the wrong candidate.