Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model This article co-authored by Alexandra Sasha Luccioni, Sylvain Viguier, and Anne-Laure Ligozat estimates that BLOOM, a Large Language Model, with 176 billion parameters, emits 24.7 tonnes of CO2 during a single training. Abstract: Progress in machine learning (ML) comes with a cost to the […]
Tech experts are starting to doubt that ChatGPT and AI ‘hallucinations’ will ever go away This article written by Matt O’Brian and the Associated Press argues that the problem of AI ‘hallucinations’ is not fixable. Anthropic, ChatGPT-maker OpenAI and other major developers of AI systems known as large language models say they’re working to make […]
Towards Generalist Biomedical AI Researchers from Google DeepMind have released Med-PaLM M, which is a large multimodal generative model that flexibly encodes and interprets biomedical data including clinical language, imaging, and genomics. Abstract. Medicine is inherently multimodal, with rich data modalities spanning text, imaging, genomics, and more. Generalist biomedical artificial intelligence (AI) systems that flexibly […]
China’s AI Regulation and How They Get Made Matt Sheehan of the Carnegie Endowment for International Peace, has published an article on how Beijing is leading the way in AI regulations, releasing groundbreaking strategies to govern algorithms, chatbots and more. Global partners need a better understanding of what, exactly, this regulation entails, what it says […]
What Roles Could Generative AI Play on Your Team? In this Harvard Business Review article published on June 22, 2023 and co-authored by Misiek Piskorski and Amit Joshi, the authors argue that: The recent advances in ChatGPT are merely the first application of new AI technologies. As such, companies and leaders need to think about […]
A quick history of AI, Machine Learning and Deep Learning Subhankar Samanta, provides an insightful and chronological account of the history of Artificial Intelligence, Machine Learning and Deep Learning, published in Nerdy Electronics. To read the full article, please click on this link. Image credit: rawpixel.com on Freepik
Generative AI and Data Privacy: A Primer Kristin E. Busch has written a report for Congressional Research Service, published on May 23, 2023, which provides detailed insight into generative AI and data privacy for policy makers. To read the full report, please click on this link. Image credit: https://pxhere.com/https://pxhere.com/en/photo/1584997?utm_content=shareClip&utm_medium=referral&utm_source=pxhere
The Little Book of Deep Learning François Fleuret, professor of computer science at the University of Geneva (Switzerland), has written a book about deep learning. His book targets STEM background readers looking for a minimum technical knowledge to understand NLP and generative models. To read the book, please click on this link.
Why Generative AI is more dangerous than you think A lot has been written about the dangers of generative AI in recent months and yet everything I’ve seen boils down to three simple arguments, none of which reflects the biggest risk I see headed our way. Before I get into this hidden danger of generative AI, it […]
A very interesting seminar series, organized by Collège de France, aims to develop discourses on human and machine intelligence. To check out the full program, please click on this link.