SingleStore Developers’ Post

Highly recommend watching this! You want to follow Pavan Belagatti if you need practical tips on building Generative AI 👑

Happy the share my recent article on Quantization: Run Memory efficient LLMs. #GenAI #LLMs #technology #AI

Don't miss out on mastering AI interactions on Wednesday, July 24th at 12:00 PM! Learn expert techniques in prompt engineering for large language models in this quick lunch & learn online session with Douglas Day. Link in bio for more details and to get tickets. #AI #LanguageModels #PromptEngineering #TechEvent #LearnFromExperts datalab

#LFMs are bound to replace #LLMs ? Explained by itself: "A Liquid Foundation Model (LFM) is a type of machine learning model that is designed to handle sequential data. It's called "liquid" because it can adapt and change its structure based on the data it's processing, much like a liquid can change its shape to fit its container. This model is particularly useful in natural language processing tasks, where the order of the data (words in a sentence, for example) is important. It can remember information from earlier in the sequence and use it to inform its understanding of later data. In essence, it's a flexible and adaptable model that can learn from and make predictions based on sequences of data." https://lnkd.in/eXqWY7Ng

Did not see much different between "BitNet: Scaling 1-bit Transformers for Large Language Models" in pytorch and the int2 quantization method. 🤔 I guess BitNet allow users to train in 1bit weight + 2bit activation And quantization can do 1bit weight + 2bit activation after calibration #LLM #AI #ML #DeepLearning #1bit

Discover how Mixture of Experts (MoE) is revolutionizing large language models (LLMs) by enhancing performance and efficiency. Learn about the innovative architecture of MoE, its benefits, and insights from experiments with models like GPT-4 and Mixtral 8x7B, showcasing how specialized expert networks drive the next generation of AI technology. Read the full article here: https://lnkd.in/gaXeT-xJ #generativeai #largelanguagemodels

In our newest video, we dive into an intriguing aspect of AI technology: 🗜️ Prompt Compression 🗜️ This innovative approach reduces the sizes of AI prompts, maintaining effectiveness while optimizing data use. It is ideal for developers looking to make AI communications more efficient. What do you think? Watch and join the discussion! https://lnkd.in/d8YESrcJ

Ready to become an LLM Scientist? Follow this roadmap to unlock your potential and master the art of Large Language Models. Begin Your Generative AI Journey with us now: https://hubs.la/Q02JYY6M0 #LLM #DataScience #Roadmap

𝗖𝘂𝘁 𝗟𝗟𝗠 𝗰𝗼𝗺𝗽𝘂𝘁𝗲 𝗯𝘆 𝟱𝟬% 𝘄𝗶𝘁𝗵 𝗠𝗶𝘅𝘁𝘂𝗿𝗲-𝗼𝗳-𝗗𝗲𝗽𝘁𝗵𝘀 💫 ↓ Highlights: ➲ Transformer-based language models tend to evenly distribute computation across input sequences ➲ With Mixture-of-Depths (MoD) additional computation is dynamically allocated to specific, more complex segments of sequences ➲ MoD reduces computation by 50% during post-training sampling ➲ It maintains accuracy comparable to baseline models ➲ MoD accelerates processing speed by up to 50% in specific tasks Link to Google DeepMind paper in comments. ‘𝗩𝗶𝗲𝘄 𝗺𝘆 𝗯𝗹𝗼𝗴’ ↑ for more Generative AI insights. #generativeai #artificialintelligence #deepmind

If you missed #tinyAI Forum on Generative AI on the Edge last week, we have you covered! The video recording of Prof. Song Han's (Associate Professor, MIT EECS) presentation: "Visual Language Models for Edge AI 2.0" is now available on tinyML YouTube channel https://lnkd.in/gMCJ5ASs This talk presents edge AI innovations across the full stack: Song first presented VILA (CVPR’24), a visual language model with multi-image reasoning and in-context learning capabilities. With strong zero shot learning capabilities, VILA 2.7B is deployable on Jetson Orin Nano. Followed by AWQ (MLSys’24), a 4-bit LLM quantization algorithm that boosts model efficiency, and TinyChat, an inference library that powers visual language model inference. VILA, AWQ and TinyChat enable advanced visual reasoning on the edge and bring new opportunities for edge AI applications. And Don't forget to register and attend our annual tinyML Summit, April 22-24. https://lnkd.in/g46W-pwD #tinyml #ml #artificialintelligence #genai #generativeai #machinelearning #ai Davis Sawyer Evgeni Gousev Olga Goremichina Tinoosh Mohsenin Danilo Pietro Pau Max Petrenko Gian Marco Iodice Daniel Situnayake