ML team lead
I have a Master's in Machine learning, and I'm specializing in LLM and Gen AI. I am an inventor at heart, so I usually have many innovative ideas to improve things or combine technologies in a new way. In the past, I founded my own startup and was CTO for about a decade, so if you're looking for someone with experience in startups and leadership, I'm your guy.
LLM's have reached a point now where it's possible to query their billions of parameters and uproot information in a hierarchical structure, which is the structure of information itself, human knowledge and the physical world. Basically objects are made of objects etc But the features that humans use to describe our world, whether with language or drawing, are not the features that ML & AI algorithms use, which are merely data points, pixels on an image, or a vague assembly of such pixels. It is a fight against the infinite complexity of life and Nature itself. Humans use objects, (real) features, and in a hierarchical way: a cat is a head and a body. A head is eyes, whiskers, ears, An eye is a cornea and an iris... etc. Today algorithms process trillions of data points and 'only' produce a statistical result, not real features, and will always do so no matter how much data is used (unless they incorporate our approach). Humans, on the other side, can classify with certainty billions of different (visually) cats by verifying they tick a few boxes, ie the 'real life' features we all know make a cat (pointy ears, whiskers, fur, etc). Our approach deems to create a knowledge graph of such real life features (what we usually refer to more generally as 'objects'), which in turn, can be used to improve current algorithms' performance. For instance, it is easy to imagine how it allows to verify if all the proper features of an object are present in an image because it tells us exactly what we should be looking for, what matters. Therefore, it will improve, say, object recognition, with direct applications in robotics, AV, guided systems of all sorts, medical diagnostics and even real language understanding. There are other applications but one of them is to improve LLM's themselves, by reducing the training time and their size by incorporating our concept into new architectures to avoid having to re-learn the whole human knowledge every time.
🔐 Exclusive Access: Only 1,000 slots available for Coral model use. 💡 Spotlight Your Idea: Showcase in this limited-entry event. 💰 Win Big: Cash prizes and Cohere credits up for grabs. 🌐 Collaborate Globally: Team up with AI enthusiasts worldwide.
Join us for an exhilarating 4-days hackathon centered around Falcon LLMs, a cutting-edge language model. The hackathon is sponsored by GAIA, the leading startup acceleration program, providing participants with the opportunity to apply for the next cohort and build innovative companies in Saudi Arabia.
Discover RAG: Enhance LLMs with fresh, trusted data using Retrieval-Augmented Generation (RAG). Vectara's Power: Explore Vectara, the all-in-one platform for innovative AI integration. Get Started: Dive into the week-long Hackathon Challenge and craft RAG-based applications. Choose Your Challenge: Opt for Customer Support, Legal Space, Financial Services, or Healthcare to showcase your skills. Join us in taking AI innovation to new heights.