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Dear friends, In the last couple of days, Google announced a doubling of Gemini Pro 1.5's input context window from 1 million to 2 million tokens, and OpenAI released GPT-4o, which generates tokens 2x faster and 50% cheaper than GPT-4 Turbo and natively accepts and generates multimodal tokens. I view these developments as the latest in an 18-month trend. Given the improvements we've seen, best pra
Agentic Design Patterns Part 1 Four AI agent strategies that improve GPT-4 and GPT-3.5 performance Dear friends, I think AI agent workflows will drive massive AI progress this year — perhaps even more than the next generation of foundation models. This is an important trend, and I urge everyone who works in AI to pay attention to it. Today, we mostly use LLMs in zero-shot mode, prompting a model t
Learn methods like sentence-window retrieval and auto-merging retrieval, improving your RAG pipeline’s performance beyond the baseline. Learn evaluation best practices to streamline your process, and iteratively build a robust system. Dive into the RAG triad for evaluating the relevance and truthfulness of an LLM’s response:Context Relevance, Groundedness, and Answer Relevance. Retrieval Augmented
Generative AI for EveryoneLearn how generative AI works, and how to use it in your life and at work Enroll Now Learn directly from Andrew Ng about the technology of generative AI, how it works, and what it can (and can’t) do Instructed by AI pioneer Andrew Ng, Generative AI for Everyone offers his unique perspective on empowering you and your work with generative AI. Andrew will guide you through
Join our new short course, Finetuning Large Language Models! Learn from Sharon Zhou, Co-Founder and CEO of Lamini, and instructor for the GANs Specialization and How Diffusion Models Work. When you complete this course, you will be able to: Understand when to apply finetuning on LLMs Prepare your data for finetuning Train and evaluate an LLM on your data With finetuning, you’re able to take your o
Learn LangChain directly from the creator of the framework, Harrison Chase Apply LLMs to your proprietary data to build personal assistants and specialized chatbots In LangChain for LLM Application Development, you will gain essential skills in expanding the use cases and capabilities of language models in application development using the LangChain framework. In this course you will learn and get
LEARN GENERATIVE AIShort CoursesTake your generative AI skills to the next level with short courses from DeepLearning.AI. Our short courses help you learn new skills, tools, and concepts efficiently. Available for free for a limited time.
Learn prompt engineering best practices for application development Discover new ways to use LLMs, including how to build your own custom chatbot In ChatGPT Prompt Engineering for Developers, you will learn how to use a large language model (LLM) to quickly build new and powerful applications. Using the OpenAI API, you’ll be able to quickly build capabilities that learn to innovate and create val
Dear friends, Recent successes with large language models have brought to the surface a long-running debate within the AI community: What kinds of information do learning algorithms need in order to gain intelligence? The vast majority of human experience is not based on language. The taste of food, the beauty of a sunrise, the touch of a loved one — such experiences are independent of language. B
Hollywood Embraces Video Gen, New Restrictions on Deepfakes, More Open Source Models, Robot Server The Batch AI News and Insights: Last week I spoke at Coursera Connect, the company’s annual conference in Las Vegas, where a major topic was AI and education.
Get the latest AI news, courses, events, and insights from Andrew Ng and other AI leaders.
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