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The Economic Times
ET@Davos: Andrew Ng, founder of DeepLearning.AI
In this episode of ET@Davos, ET's Executive Editor Sruthijith KK sits down with AI pioneer Andrew Ng, Founder of DeepLearning.AI, for a critical conversation on India's tech future. Ng delivers a stark warning: the nation's massive IT services industry faces existential disruption. While dismissing AGI hype as overblown, he insists AI-powered ...
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New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs acce
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More than 100 years ago, electricity changed everything. Now the same thing is about to happen with artificial intelligence. Watch Andrew Ng’s full talk from the Stanford MSx Future Forum: http://stanford.io/2pzQM2z | Stanford Graduate School of Business
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New short course: Evaluating AI Agents! Evals are important for driving AI system improvements, and in this course you'll learn to systematically assess and improve an AI agent’s performance. This is built in partnership with Arize AI and taught by John Gilhuly, Head of Developer Relations, and Aman Khan, Director of Product. I've often found evals to be a critical tool in the agent development process - they can be the difference between picking the right thing to work on vs. wasting weeks of e
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New short course: Attention in Transformers: Concepts and Code in PyTorch. Last week we released a course on how LLM transformers work. This week, go deeper and learn about the technical ideas behind the attention mechanism, and see how to code it in PyTorch. This course is built with Josh Starmer, Founder and CEO of StatQuest. The attention mechanism was a breakthrough that led to transformers, the architecture powering large language models like ChatGPT. Transformers, introduced in the 2017 pa
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Had an insightful conversation with @geoffreyhinton about AI and catastrophic risks. Two thoughts we want to share: - It's important that AI scientists reach consensus on risks-similar to climate scientists, who have rough consensus on climate change-to shape good policy. - Do AI models understand the world? We think they do. If we list out and develop a shared view on key technical questions like this, it will help move us toward consensus on risks. I learned a lot speaking with Geoff. Let’s al
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Build better RAG by letting a team of agents extract and connect your reference materials into a knowledge graph. Our new short course, “Agentic Knowledge Graph Construction,” taught by Neo4j Innovation Lead Andreas Kollegger, shows you how. Knowledge graphs are an important way to store information accurately but they are a lot of work to build manually. In this course you’ll learn how to build a team of agents that turn data– in this case product reviews and invoices from suppliers–into struct
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