rish-b

4 ms·

1. 1.▲
   Is the new gpt-3.5-turbo model worse?(refuel.ai)

   19 points by rish-b 3y ago|0 comments
2. 2.▲
   by rish-b 3y ago

   A common reason is to reduce cost and latency. Larger models typically require GPUs with more memory (and hence higher costs), plus the time to serve requests is also higher (more matrix multiplications to be done).
3. 3.▲
   Falcon 40B (potentially the most capable open-source LLM) is now open-source(tii.ae)

   69 points by rish-b 3y ago|1 comments
4. 4.▲
   Large Language Models Are Few-Shot Health Learners(arxiv.org)

   53 points by rish-b 3y ago|47 comments
5. 5.▲
   by rish-b 3y ago

   This is such an interesting direction for LLM research (especially because it's easy to imagine applicability in industry as well). If all it takes is ~1k high-quality examples (of course, quality can be tricky to define) to tune an LL