Ibrahim Haddad, Ph.D.’s Post

Last week, our team was in San Jose and presented at The Linux Foundation Gen AI & ML Summit. 🔥 For us, this was an exciting opportunity to interact with LLM practitioners and talk about LLM evaluation. 100s of people visited our booth and learned more about Deepchecks LLM Evaluation solution. 🚀 🌟 Learn more about Deepchecks LLM evaluation here: https://lnkd.in/dwx-JeGZ #llmops #llms #machinelearning #opensource #openai

Great selection of AI on IBM Z topics during SHARE Orlando event from March 4 to 6. Whether you are sysprog, application developer, data scientist, or IT manager, you will find relevant content for your projects and daily tasks. Join our top speakers to learn more about how AI on IBM Z can help you make your applications and operations more intelligent.

Motokolearn is a Motoko package meant to facilitate on-chain training and inference of machine learning models where having a GPU is not a requirement.

The AI community is all about science, innovation & execution… 🔥 Less than 24 hout after Meta’s announcement on LLaMa-2… 🌋 Update to LLaVA, including support for LLaMA-2, LoRA training, 4-/8-bit inference, higher resolution (336x336), Also release LLaVA Bench for benchmarking visual chat with results from Bard and Bing-Chat. ⬇️ 🚀 Major update for LLaVA, open-source large multimodal model. 📊 Introducing LLaVA-Bench, a benchmark for open-ended visual chat, comparing with commercial chatbots like Bard and Bing-Chat. 🦙 LLaVA based on RLHF-tuned LLaMA-2-Chat now available, offering longer context windows. ✅ Latest release supports and verifies training with RTX 3090 and RTX A6000, improving accessibility for large multimodal model training. 🌐 Project Page: llava-vl.github.io 💡 Demo: llava.hliu.cc 🔗 GitHub: https://lnkd.in/giJ6yi9h

Thrilled to share: My neural network, "Grand Hopfield NetMaster," now solves any N-Queens problem in screensaver mode, reminiscent of an old PC. It cracked a 48x48 puzzle from a random setup, without recursion, using PyTorch tensors and the Pygame interface. More info inside -> https://lnkd.in/dTNuhBi3 #open_to_work #meta #windows #ai

🎓 Just wrapped up the 3rd workshop with Elite Global Excellence on "Parallel Computing Platform and CUDA Software for Big Data Simulation" 🚀 Thanks to Dr. Eka and Dr. Nelli from Great Polytechnic University, Russia, for an enlightening journey! Ready to dive into the realms of Parallel Computing! 💻🌐 #TechEnthusiast #BigDataSimulation #WorkshopComplete #AlwaysLearning

The TinyML-Kenya Educator Series is going great!🔥 Today, we looked at Computer Vision tasks and learned how to use the Edge Impulse platform to train a #machinelearning model to detect faces. Here is a link to the public project: https://lnkd.in/dZHwsWMx The presentation slides can be found in this GitHub repository: https://lnkd.in/d9RQ7da4

Exciting news! Arduino has just made machine learning even more accessible with the introduction of TensorFlow Lite Micro in the Arduino Library Manager. Now you can easily run various TensorFlow Lite Micro examples. Check out this article to learn more and get started with machine learning using Arduino. 🔬🚀 #MachineLearning #Arduino #TensorFlowLiteMicro Read more: https://lnkd.in/dR-KW6vq

🔬 Exciting News! Check out this amazing blog post on "A Platform for Scientific Challenges: Open Source and Collaborative"! 🌟 Discover CodaLab Competitions, an open source platform designed to help data scientists and research teams organize and crowd-source solutions for machine learning problems through competitions and challenges. 🚀 This platform provides a multitude of useful features, including multiple phases, code and result submissions, multi-score leaderboards, and the ability to run jobs within Docker containers. 🤖 It's incredibly flexible and can handle large-scale experiments, allowing organizers to upload massive datasets and provide their own CPU or GPU compute workers. 💪 Read all about it in the blog post here: [link](https://ift.tt/Zd786pD) Stay ahead in the world of scientific challenges and open collaboration with CodaLab Competitions! 🌐 #ScientificChallenges #OpenSource #Collaboration #DataScience #MachineLearning