A great article that goes deep into the current #risks with #agentic #AI. While the author speaks from a SaaS standpoint, this analysis applies to any solution that relies on AI agents. A recommended reading for anyone who's planning to venture into this wonderful world. 😈

If you want to learn more about #opensource #smalllanguagemodels and #ollama, you can consider reading my book 👇
mng.bz/YZra
@manningbooks.bsky.social

Running an #AI #Agent locally and using only #opensource components gives you more control, but still some implementation hurdles can be met. Please be patient, as this is still a work in progress (I have started it last week only). Please give it a star if you like it 🙏 5/5
#python #smolagents

This work follows few principles:
- Everything stays local (a scientist laptop, or a local server). Nothing must leave the user's organisation network.
- #opensource parts only.
- #smalllanguagemodels only.
- User Experience is based on the BYOP (Bring Your Own PDB) and MD expertise principle :)
4/5

I have started a #github repo, where I am building a local #agent with the goal of moving away all the annoying work from the scientists that use #gromacs, so that they could focus on their main tasks, where they can apply in full their domain knowledge and expertise. 3/5
github.com/virtualrambl...

#gromacs has plenty of applications in Material Science, #drugdiscovery and #chemical Reaction Modelling. Although being a very powerful tool, it requires a lot of manual work to prepare an end-to-end simulation and analysis pipeline. 2/5

A #HuggingFace space to play with Prompt-Free #Diffusion is also available: t.co/SEmZ94iVlE
3/3
#Python #opensource #AI

#SeeCoder is reusable to most public #text2image models as well as adaptive layers like #ControlNet, #LoRA, T2I-Adapter, etc. Inputs to the model are a reference image and a depth map, a canny edge map, a scribble or a openpose.
The official GitHub repo: t.co/RkEDS0RQLD
2/3
#AI #opensource

Actually some can run also on a MacBook Air.