OpenUK’s Post

Best book, in my view, since "The Coming Wave" discussing artificial intelligence. CxOs, leaders, everyone in tech, parents and students (over 18) should all consider. We are very quickly entering a very new world... This interview of Eric Schmidt provides a high level overview but the book itself is dramatically better and worth the full read.

🚀 Exciting News! 🚀 I'm thrilled to announce that our paper on "Automated Detection and Classification of PCB Defects Using Deep Learning" has been published via IEEE! 📝 In this research, we explored the efficacy of various CNN algorithms for the efficient detection and classification of PCB defects. Throughout this journey, I'm immensely grateful for the unwavering support and guidance of my mentor, Dr. Sachin Sharma. His expertise and encouragement have been instrumental in shaping our research endeavors. #DeepLearning #PCBDefectDetection #IEEE #Research #Innovation #ArtificialIntelligence #MachineLearning #ComputerVision #AcademicResearch

Curious how LLMs will change deep scientific research? At Undermind, we're building tools that radically rethink the "google search" paradigm - replacing it with deep agent-like search by LLMs that can find incredibly complex resources, solving your real problems directly. Here's a great blog post explaining how it's different, by Aaron Tay: https://lnkd.in/ddNTPMtS

💥💥💥 Flow Matching Guide and Code Yaron Lipman, Marton Havasi, Peter Holderrieth, Neta Shaul, Matt Le, Brian Karrer, Ricky T. Q. Chen, David Lopez-Paz, Heli Ben-Hamu, Itai Gat Abstract Flow Matching (FM) is a recent framework for generative modeling that has achieved state-of-the-art performance across various domains, including image, video, audio, speech, and biological structures. This guide offers a comprehensive and self-contained review of FM, covering its mathematical foundations, design choices, and extensions. By also providing a PyTorch package featuring relevant examples (e.g., image and text generation), this work aims to serve as a resource for both novice and experienced researchers interested in understanding, applying and further developing FM. 👉 https://lnkd.in/eMjU98me #machinelearning

New Medium Article: Top Important Computer Vision Papers for the Week from 24/06 to 30/06 Every week, researchers from top research labs, companies, and universities publish exciting breakthroughs in various topics such as diffusion models, vision language models, image editing and generation, video processing and generation, and image recognition. This article provides a comprehensive overview of the most significant papers published in the Fourth Week of June 2024, highlighting the latest research and advancements in computer vision. Whether you’re a researcher, practitioner, or enthusiast, this article will provide valuable insights into the state-of-the-art techniques and tools in computer vision. ➡ Do not miss the 60% discount on To Data & Beyond yearly subscription: https://lnkd.in/gmwFUqYr ➡ Check out my new ebook: LLM Roadmap from Beginner to Advanced Level: https://lnkd.in/dp7_CssN

Search for incredibly complex topics and find every paper. This AI tool completely automates systematic and thorough literature search using language models. Claims are results in 10-50x more accurate and comprehensive compared to Google Scholar. https://lnkd.in/gbCRFkBz

Grateful to have participated in the MedPRAI24 conference, where I had the opportunity to present my paper titled “Evaluation of Fine-Tuning Llama-2 for Domain-specific Question Answering.” This paper was a valuable practice and a great experience in scientific writing. A big thanks to Dr. Wadhah Tareq for his support. This paper investigates the fine-tuning of Llama-2 (7B model) Large Language Model using Parameter-Efficient Fine-Tuning (PEFT) techniques on a new text corpus. By applying "QLoRA" to optimize memory usage, we had only 34 million trainable parameters instead of 7 billion. Will share the paper link once it’s published. The project including the code, datasets, and experiments, can be found on GitHub here: [ https://lnkd.in/ddf-8kVv ]. #MedPRAI24 #MedPRAI2024 #ScientificWriting #AI #Research #LLM

There are so many people trying to predict where science, technology and the future will intersect. Writers of science fiction books & movies can give inspiration for innovators in these areas, but they can also miss when creating these new ideas. Wireless communications, artificial intelligence, and sleek vehicles are great examples where some of these hit the mark. Let's read about some areas where sci-fi went off the rails a bit. What are some examples that are top of mind to you? #scifi #inspiration #neverhappened #vectorone https://lnkd.in/ey5qYxnm

I’m so excited to dive into the new book by my former PhD supervisor - the brilliant Francis Nyamnjoh! Our understandings of emerging technologies, like AI, is already deeply influenced by our imaginations and visions of the future. I believe that allowing academic insights and creative story-telling perspectives to blend can offer a much richer understanding about the role these technologies play in our lives. Cannot wait to explore the ideas in this book!

Very interesting to run into a direct (plagiarized) copy of my own paper (Using a Cognitive Architecture to consider antiblackness in design and development of AI systems - https://lnkd.in/eNWsQYGu) in the "Journal of Artificial Intelligence General Science (JAIGS). What's more they have a completely diff citation list (I would guess to inflate citation counts). A good reminder of folks to pay attention outchea. (It even appears that the main contact of the journal is the "author" of the copied article! https://lnkd.in/ePfZDNFZ)