Research towards AI models that can generalise, scale, and accelerate science Next week marks the start of the 11th International Conference on Learning Representations (ICLR), taking place 1-5 May in Kigali, Rwanda. This will be the first major artificial intelligence (AI) conference to be hosted in Africa and the first in-person event since the start …
ContentsIntroductionLLM Training PipelinePretrainingPost-Training: Supervised Fine-TuningPost-training: Reinforcement Learning with Human FeedbackWhy Hallucinations?Model InterrogationUsing Web SearchConclusion Introduction In a YouTube video titled Deep Dive into LLMs like ChatGPT, former Senior Director of AI at Tesla, Andrej Karpathy discusses the psychology of Large Language Models (LLMs) as emergent cognitive effects of the training pipeline. This article is inspired by his explanation …
Responsibility & Safety Published 25 May 2023 Authors Toby Shevlane New research proposes a framework for evaluating general-purpose models against novel threats To pioneer responsibly at the cutting edge of artificial intelligence (AI) research, we must identify new capabilities and novel risks in our AI systems as early as possible. AI researchers already use a …
Contents1. Introduction2. The Transformer2.1. The Self-Attention Mechanism2.2 The Multi-Headed Self-Attention3. The Vision Transformer4. The Result4.1 What does the ViT model learn?5. So, is ViT the future of Computer Vision?References 1. Introduction Ever since the introduction of the self-attention mechanism, Transformers have been the top choice when it comes to Natural Language Processing (NLP) tasks. Self-attention-based …
Vision Transformers (ViT) Explained: Are They Better Than CNNs? Read More »
Impact Published 7 June 2023 Authors Daniel J. Mankowitz and Andrea Michi New algorithms will transform the foundations of computing Digital society is driving increasing demand for computation, and energy use. For the last five decades, we relied on improvements in hardware to keep pace. But as microchips approach their physical limits, it’s critical to …
“You don’t have to be an expert to deceive someone, though you might need some expertise to reliably recognize when you are being deceived.” When my co-instructor and I start our quarterly lesson on deceptive visualizations for the data visualization course we teach at the University of Washington, he emphasizes the point above to our …
The Dangers of Deceptive Data–Confusing Charts and Misleading Headlines Read More »
Since the launch of the Gemini 2.0 Flash model family, developers are discovering new use cases for this highly efficient family of models. Gemini 2.0 Flash offers stronger performance over 1.5 Flash and 1.5 Pro, plus simplified pricing that makes our 1 million token context window more affordable. Today, Gemini 2.0 Flash-Lite is now generally …
Start building with Gemini 2.0 Flash and Flash-Lite Read More »
Retrieval-Augmented Generation (RAG) is a powerful technique that enhances language models by incorporating external information retrieval mechanisms. While standard RAG implementations improve response relevance, they often struggle in complex retrieval scenarios. This article explores the limitations of a vanilla RAG setup and introduces advanced techniques to enhance its accuracy and efficiency. ContentsThe Challenge with Vanilla …
As part of our aim to build increasingly capable and general artificial intelligence (AI) systems, we’re working to create AI tools with a broader understanding of the world. This can allow useful knowledge to be transferred between many different types of tasks. Using reinforcement learning, our AI systems AlphaZero and MuZero have achieved superhuman performance …
MuZero, AlphaZero, and AlphaDev: Optimizing computer systems Read More »
Imagine a world where your coffee maker knows exactly when to brew your perfect cup, your car negotiates traffic like a seasoned pro, and your virtual assistant manages your schedule with uncanny efficiency. Welcome to the age of AI agents – the silent revolution that’s reshaping our world faster than you can say “Hey Siri.” …
