TheDeviousPanda t1_je5ddm3 wrote on March 29, 2023 at 3:12 PM

Reply to [D] The best way to train an LLM on company data by jaxolingo

It’s going to be a lot easier to just take something like GPT-4 and feed in your data directly and ask questions.

TheDeviousPanda t1_j6vv0my wrote on February 2, 2023 at 6:23 AM

Reply to [D] Apple's ane-transformers - experiences? by alkibijad

I hate to do this to you, but I have been in your position and I have answers to all your questions.

Yes, yes
A lot
Yes, very

TheDeviousPanda t1_izio2gc wrote on December 9, 2022 at 11:45 AM

Reply to [R] Large language models are not zero-shot communicators by mrx-ai

This is just literally not true -every model on beta.openai.com and chatGPT answers this question correctly. Contrived experimental setup or I’m just completely misunderstanding the paper.

TheDeviousPanda t1_ivj5gk6 wrote on November 8, 2022 at 10:27 AM

Reply to [D] It it possible to save my conversations with customers in order to continuously train & develop a ML program that can compose original responses for me? by Salubriously_Moist

Before you go fine tuning LLMs on your conversations I would check any privacy policy in the communications you are using. Using the other party’s messages for an LLM that will be exposed to other people opens you up to some risk.

TheDeviousPanda t1_ium7iy4 wrote on November 1, 2022 at 12:23 PM

Reply to comment by laprika0 in [D] Machine learning prototyping on Apple silicon? by laprika0

Scikit learn numpy pandas xgboost etc, totally fine to do on CPU which is great on MacBooks. Pytorch tensorflow jax? Forget it. If anyone in lab asks for help debugging on their local machine bc cluster is down, I just ignore it. Impossible to do prototyping on Mac.

TheDeviousPanda t1_isrcx1c wrote on October 18, 2022 at 3:17 AM

Reply to [D] Machine Learning conferences/journals with a mathematical slant? by vajraadhvan

I do not recall seeing any highly mathematical papers at ICML this year. What you are proposing might be better received at a conference like AISTATS, perhaps.

TheDeviousPanda t1_irdcat4 wrote on October 7, 2022 at 4:29 AM

Reply to [D] When are you qualified to review other AI research papers? by tempestwing0101

The primary factor in determining the quality of a review is not the maturity of the reviewer but in my opinion the time that is invested into reviewing the paper. AI research papers are not so complex; generally undergraduates that I have worked with are able to fully understand a paper when given sufficient time. By contrast, the average review you can expect to get at a conference will be from a reviewer who has spent maybe 30 minutes on your paper.

I would encourage you to read the papers that you have been assigned in depth and try to give good reviews. Assuming that there is some discussion period where you can see other reviews on the same paper, you will get some indirect signal on the quality of your review.