AssemblyAI’s Post

🚀 Exciting news in the world of AI and ML! Researchers have introduced CoLLaVO, a cutting-edge Crayon Large Language and Vision model, aiming to enhance object-level image understanding in Vision Language Models. The findings emphasize the importance of prioritizing basic image understanding for VLMs to excel at VL tasks. This innovative approach could lead to significant advancements in zero-shot performance on various VL benchmarks. Stay tuned for the future of AI and ML with CoLLaVO! #AI #ML #BigData #DataScience #CoLLaVO #Innovation

Take a look at this great creative coding tool from Stanford University called #Spellburst. It merges the best of both worlds from #GenerativeAI and #Processing in a node-based interface. The tool is not out yet, but the research paper is: https://lnkd.in/eKQ5Kw7c #ai #design #creativecoding #art https://lnkd.in/eThyF_dh

An Introduction to #Vision #Language #Modeling Large Language Models (#LLMs), several attempts have been made to extend them to the visual domain https://lnkd.in/gqviRvjd

Have you imagined Running large language models at home in a BitTorrent style? Check out this interesting research paper that I found on Hugging Face. If you're interested in learning more, take a look at my latest blog post where I share my thoughts. #largelanguagemodels #llm #llms #distributedcomputing #distributedsystems #huggingface #researchpaper https://lnkd.in/gwJMmVHj

Delve into the world of Language Model Optimization with our latest insights on Fine-tuning Large Language Models (LLMs). Uncover strategies for enhancing model performance and personalizing them to fit specific applications. Interested in expanding your knowledge about fine-tuning LLMs? Click here to explore more: https://lnkd.in/dawCCcsd #analyticsvidhya #datascience #AVguide

Just delved into a fascinating paper at NEURIPS 2023 on "Tree of Thoughts: Deliberate Problem Solving with Large Language Models” (https://lnkd.in/e3gf688m) which generalizes over the popular Chain of Thought (CoT) approach to prompting language models. Recent study in LLM Reasoning, further expand the original prompt engineering framework to Graph of Thoughts (GoT), an arbitrary graph-based thought transformations. (https://lnkd.in/eqy-uKRG) Interesting progress just within a year. How might these recent studies reshape our approach to reasoning with LLM? #largelanguagemodel #llm #reasoning #artificialintelligence

Increasingly, we understand our world through large language models (LLMs). Those LLMs are usually trained with English data. It's no secret that English is the language of instruction when it comes to technology, but given the revolutionary impact of LLMs on our society, developing Dutch language models is essential. There are now models that are multilingual, but they are not always effective when it comes to 'smaller' languages and nuances. That is why researchers from Vlaams AI Onderzoeksprogramma / Flanders AI Research Program KU Leuven, Ghent University and the Technische Universität Berlin joined forces to develop a state-of-the-art Dutch language model. RobBERT was born! (the model came up with its own name by the way 😁 ) 👌 Various evaluations have shown that the model surpasses other Dutch language models, including on the recently published DUMB benchmark. RobBERT can do more than fill in 'the right words', you can use the model to detect humour and emotion, for the correct use of die and dat. It can be used to expose cyberbullying or to help you write a good resume. Randstad, Statistics Flanders, the Netherlands Forensic Institute NFI, ML6 | Your partner in AI and TechWolf have already used the model.  💣 Since 2019, RobBERT has been downloaded more than a million times for all kinds of applications.  👉 https://pieter.ai/robbert/ Pieter Delobelle Thomas Demeester Thomas Winters

All You Need To Know About The Qwen Large Language Models (LLMs) Series Quick Read: https://lnkd.in/gJhZVpRx Paper: https://lnkd.in/gFZ7tpx6 If you like our work, you will love our newsletter: https://lnkd.in/gTkg4N_D #largelanguagemodel #llm #artificialintelligence #machinelearning

The evolution of Large Language Models (LLMs) over the years has led to advances in Neural Code Intelligence, improving programming efficiency and reducing errors in the software industry. Innovations include Code2Vec’s use of embeddings, CodeBERT’s multimodal data pre-training, Codex’s code generation from natural language prompts, CodeT5’s fine-tuning on various code tasks simultaneously, PLBART’s denoising sequence-to-sequence modeling, and Code Llama’s fine-tuning step for long sequences. These LLMs have fundamentally transformed code understanding, generation, and translation. </div><div class="read-more"><a href="" class="more-link">Continue reading</a>https://lnkd.in/gKwbUPUH

Reading others’ emotions is a skill crucial to humans. Can machines mimic it? I tested IDEFICS, a new open-access visual language model. Used novel images that the model couldn’t have been trained on. Here are prompts & responses. H/T @SanhEstPasMoi @raphaelmilliere ; Images: @NYTimes https://bit.ly/3ReEatM