Motaseam Yousef’s Post

Check out this comprehensive blog post on machine learning-enabled optimization for reconfigurable intelligent surfaces-aided 6G networks. The post provides an overview of how machine learning techniques, including reinforcement learning and large language models, can be utilized for network management in 6G environments. It also discusses future challenges and directions in this field. Read the full post here: https://bit.ly/4bZAzXV.

Unlocking AI's Potential: Vellum's LLM Leaderboard Insights Choosing the right large language model (LLM) can significantly impact AI projects. Vellum’s LLM Leaderboard offers a detailed comparison of models based on performance in areas like reasoning, coding, and safety. This transparent evaluation helps companies make data-driven decisions, ensuring they select the best tools for their needs. As LLMs advance, resources like this provide crucial guidance. Discover more here: https://lnkd.in/g3qgyGKA #AI #MachineLearning #LLM #Innovation

Excited to share “BitDelta: Your Fine-Tune May Only Be Worth One Bit” by James Liu et al. This paper introduces BitDelta, which compresses the weight delta between pre-trained and fine-tuned models to 1 bit without losing performance. Challenge: Fine-tuning large language models (LLMs) increases storage and GPU memory demands. Solution: BitDelta quantizes the delta between fine-tuned and base models to 1 bit, significantly cutting memory usage. Impact: This allows using a single high-precision base model with multiple 1-bit deltas, reducing GPU memory requirements by over 10× and enhancing generation latency. Validation: Experiments on models up to 70B parameters (e.g., Llama-2, Mistral) show minimal performance degradation. Read more and explore the code: Paper: https://lnkd.in/gyYbY4X2 #MachineLearning #AI #DeepLearning #LLMs #ModelCompression #BitDelta #Research

🤖 Delve into the latest advancements in machine learning → https://goo.gle/3CkbdqX In this talk from #CCDGN24, Rishiraj Acharya takes us on a deep dive into the world of multimodal search, leveraging the power of Gemini Vision models and Retrieval-Augmented Generation (RAG).

The Prompt Report. Everything you wanted to know about how to chat with your GPT but were afraid to ask. Full of intriguing insights into how #LLMs process information (still a black box). Prompt "engineering" remains a form of medieval alchemy. Hence the importance of programmable frameworks like #DSPy to build reliable and scalable solutions with #GenerativeAI (at least today). https://lnkd.in/eGQAhFGc

The Machine Learning Guide for Predictive Accuracy: Interpolation and Extrapolation ... https://lnkd.in/eGvXR7hv #AI #ML #Automation

icymi 5 main updates from open ai devday 2024 yesterday in sf 1️⃣ realtime api for smoother interactions 2️⃣ vision fine-tuning for custom image analysis 3️⃣ prompt caching to cut costs 4️⃣ model distillation tools for efficiency 5️⃣ structured outputs for reliability wrote a blog here explaining why each is important and different examples - https://lnkd.in/gWhZN_pH

My short presentation in the #EuroHPC User Day+½ HPC ecosystem tools session yesterday summarising the first year of Development Access project(s) for #Scalasca / #Score_P (exa-)scalable parallel performance analysis tools. DeepL Generative AI clearly presented that exa-scale is mind-bogglingly large, but being off by a factor of a million translating numbers between German and English shows it has some way to go to meet the expectations of the EuroHPC audience who immediately spotted the discrepancy. 👉 https://lnkd.in/eZA4qw3V

The mighty #LLMs today can do everything from answering esoteric questions about economics and quantum mechanics, help you code, make music or even play chess at a high level. But did you know they can’t play sudoku? Interesting article on real examples of what #LLMs cannot do. https://lnkd.in/gB4e7EET #GenAI #AI #ML

In a clear and concise introduction to sampling from multivariate distributions, Wencong Yang covers several powerful approaches, from classical statistical methods to cutting-edge generative models.