In this article we will explore why 128K tokens (and more) models can’t fully replace using RAG. We’ll start with a brief reminder of the problems that can be solved with RAG, before looking at the improvements in LLMs and their impact on the need to use RAG. Illustration by the author. RAG isn’t really …
A note from Google and Alphabet CEO Sundar Pichai: Information is at the core of human progress. It’s why we’ve focused for more than 26 years on our mission to organize the world’s information and make it accessible and useful. And it’s why we continue to push the frontiers of AI to organize that information …
Part 1: Leverage linear regression and decision trees to impute time-series gaps. Source: DALL-E. Missing data in time-series analysis — sounds familiar? Does missing data in your datasets due to malfunctioning sensors, transmission, or any kind of maintenance sound all too familiar to you? Well, missing values derail your forecast and skew your analysis. So, …
Missing Data in Time-Series: Machine Learning Techniques | by Sara Nóbrega | Dec, 2024 Read More »
Acknowledgements Genie 2 was led by Jack Parker-Holder with technical leadership by Stephen Spencer, with key contributions from Philip Ball, Jake Bruce, Vibhavari Dasagi, Kristian Holsheimer, Christos Kaplanis, Alexandre Moufarek, Guy Scully, Jeremy Shar, Jimmy Shi and Jessica Yung, and contributions from Michael Dennis, Sultan Kenjeyev and Shangbang Long. Yusuf Aytar, Jeff Clune, Sander Dieleman, …
Python code to create folders and Word documents for research papers in biomedical sciences — all in one go with only two inputs Photo by Maksym Kaharlytskyi on Unsplash I am a researcher with over seven years of experience working in public health and epidemiological research. Every time I am about to start a new …
Technologies Published 4 December 2024 Authors Ilan Price and Matthew Willson New AI model advances the prediction of weather uncertainties and risks, delivering faster, more accurate forecasts up to 15 days ahead Weather impacts all of us — shaping our decisions, our safety, and our way of life. As climate change drives more extreme weather …
Implementing Speculative and Contrastive Decoding Large Language models are comprised of billions of parameters (weights). For each word it generates, the model has to perform computationally expensive calculations across all of these parameters. Large Language models accept a sentence, or sequence of tokens, and generate a probability distribution of the next most likely token. Thus, …
Research Published 5 December 2024 Advancing adaptive AI agents, empowering 3D scene creation, and innovating LLM training for a smarter, safer future Next week, AI researchers worldwide will gather for the 38th Annual Conference on Neural Information Processing Systems (NeurIPS), taking place December 10-15 in Vancouver, Two papers led by Google DeepMind researchers will be …
5. Univariate sequential encoding It is time to build the sequential mechanism to keep track of user choices over time. The mechanism I idealized works on two separate vectors (that after the process end up being one, hence univariate), a historical vector and a caching vector. The historical vector is the one that is used …
Technologies Published 14 May 2024 Announcing our novel watermarking method for AI-generated text and video, and how we’re bringing SynthID to key Google products Generative AI tools — and the large language model technologies behind them — have captured the public imagination. From helping with work tasks to enhancing creativity, these tools are quickly becoming …
Watermarking AI-generated text and video with SynthID Read More »
