Stay informed with our curated collection of articles, research, and expert perspectives on artificial intelligence
Harvard Business Review
An exploration of how agentic AI is transforming human-AI collaboration, from AI-powered travel planning to virtual caregivers and supply-chain specialists that can optimize inventories in real-time.
Read MoreStephen Wolfram
A comprehensive explanation from first principles of how modern AI models work, following the timeline from early neural networks to today's large language models and ChatGPT.
Read MoreDale Markowitz
A direct and intuitive explanation of what large language models are and how they work, providing a great introduction to the technology behind modern AI systems.
Read MoreJay Alammar
A visual and technical overview of the transformer architecture that powers modern language models, making complex concepts accessible through clear illustrations.
Read MoreGoogle Research
Research exploring how transformer models reason through problems, using graph algorithms to better understand their capabilities and limitations.
Read MoreChip Huyen
An explanation of RLHF, which makes language models behave in more predictable and human-friendly ways—one of the most important aspects of systems like ChatGPT.
Read MoreGoogle Research
Research on how multiple language model agents can collaborate to solve complex tasks that require processing long contexts and specialized knowledge.
Read MoreChip Huyen
A practical guide discussing the key challenges in building LLM applications, how to address them, and what types of use cases make the most sense for deployment.
Read MoreDAIR.AI
A comprehensive guide for writing effective LLM prompts, with specific examples for popular models and techniques to get the best results from AI systems.
Read MoreGoogle Research
Research on how AI can assist scientists in making discoveries, automating routine tasks, and suggesting novel approaches to complex scientific problems.
Read MoreGeorgetown University Library
A practical overview of when generative AI tools like ChatGPT and Elicit can be helpful in research and writing, and when to be more cautious with their use.
Read MoreMcKinsey
Research showing that while almost all companies invest in AI, just 1% believe they are at maturity. The biggest barrier to scaling is not employees—who are ready—but leaders, who are not steering fast enough.
Read MoreAndreessen Horowitz
An assessment of where value is accruing, and might accrue, at the infrastructure, model, and application layers of generative AI in the market.
Read MoreWharton AI
Generative AI is nowhere near being able to operate without intensive human oversight....
Read MoreSequoia Capital
If 2024 was the primordial soup year for AI, the building blocks are now firmly in place. AI's potential is now congealing into something real and tangible.
Read MoreOpenAI & University of Pennsylvania
Research predicting that around 80% of the U.S. workforce could have at least 10% of their work tasks affected by large language models, with implications for job transformation.
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