oedemis

interesting approach can you share some insights of your experiments in different domains

why no one talks about claude shannon deep understanding of information theory and the consequences for compression and intelligence

as architectures evolve, i think it can be that we learn more "side effects".. back in 2020 openai researchers said "GPT-3 is applied without any gradient updates or fine-tuning" the model emerges at a certain level of scale...

how mojo with max optimize the process?

there is also very good explanation from Luis Serrano, https://youtu.be/fkO9T027an0

i thought skills are the new context resolver

Streaming, EDA can solve lot of data challenges for enterprise AI use cases

https://huggingface.co/ibm here is very interesting research going https://huggingface.co/ibm-granite

ibm developed SSMs/mamba models and also releasing trainings datasets i think, also quantum computing is strategic option..

the first thing when i open my browser is lookup at https://news.ycombinator.com/ :)

Hello, tried to explain Large Language Models with some visualizations, especially the attention mechanism.

there is also https://ds4sd.github.io/docling/ from ibm research which is mit license and track bounding boxes as rich json format

mika6996, all set! Feel free to share any updates or thoughts on the idea

GitSynth – A Git Commit Visualizer for Insightful Code Exploration diffs and commits with GenAI (ollama)

Hey HN!

I’m excited to share GitSynth, a tool designed to visualize Git repositories and generates commits and changelog.md file insightful and interactive way. here we go: https://github.com/oedemis/gitsynth

but what about the chunk size, if we have a small chunks like 1 sentence and the hyde embeddings are most of the time larger, the results are not so good

sustainability considerations?

invest in decarbonization movement

i also write recently something about this not eventstorming but more in architecture https://blog.oedemis.io/serverless-event-driven-architecture...