Hey folks, I'm working on starting a company that applies ML and NLP to patient data with the intent of finding the right patients for clinical trials. I'm looking for a cofounder. Please DM me if you are interested or know someone who might be. Would love to chat. Thank you submitted by /u/another_african [link] [comments]
My friend implemented the method of Multihead Mixture of Experts in this arxiv paper https://arxiv.org/pdf/2404.15045 and he wanted me to share it with you! https://github.com/lhallee/Multi_Head_Mixture_of_Experts__MH-MOE Try it out. Let me know what you think and I will pass it on to him. submitted by /u/Prudent_Student2839 [link] [comments]
Hello guys, I've been working on a sequential labelling using DNA sequences as inputs. Lately there have been 2 foundation models released HyenaDNA (Based on Hyena operator) and Caduceus (based on mamba), I used both pretrained and from scratch models and performances are terrible even with pretrained ones. Does anyone have experience with this type...
This is a small drug toxicity prediction GNN model I wrote/trained repo: https://github.com/Null-byte-00/toxicity-prediction-gnn submitted by /u/Soroush_ra [link] [comments]
I have a use case to use function calling within my application, I am confused whether to choose OpenAI function calling or use Bedrock Agents coupled with Lambda functions for this, which is the best approach? Or help me to choose between these two. submitted by /u/raman_boom [link] [comments]
ML is very good at solving a niche set of problems, but most of the technical nuances are lost on tech bros and managers. What are some problems you have been told to solve which would be impossible (no data, useless data, unrealistic expectations) or a misapplication of ML (can you have this LLM do all of out accounting). submitted by /u/LanchestersLaw...
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