> For the complete documentation index, see [llms.txt](https://lwm.mit.edu/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://lwm.mit.edu/course-materials/ai-panorama.md). # AI Panorama A recurring, overview presentation broadly surveying the capabilities of AI, introducing an accessible framework for understanding its direct applicability to research. {% hint style="warning" icon="clipboard-question" %} **Community Survey: complete below to have your questions answered during the course!**

{% endhint %} #### No Sign-Up Necessary: See Session Dates Below to Attend For questions, please reach out to **** {% hint style="info" %} ## Session Dates (Luria Auditorium, 76-156 from 12-2PM) * Friday, September 25, 2026 * Friday, October 23, 2026 * Friday, November 6, 2026 * Friday, December 4, 2026 {% endhint %} #### The Framework AI is fundamentally a tool to find structure in data. It lets us examine thousands of images, or hundreds of gene measurements, or dozens of cell lines in parallel to reveal underlying patterns the human eye along couldn't see. Every application of computation in science helps point us towards a new line of inquiry, or prompts us to ask new questions, guiding future research steps. This presentation outlines a framework for understanding the capabilities and limitations of AI in its ability to help us answer five useful research questions, all based on finding structure in data: 1. What **patterns** are we missing? 2. What can we **predict**? 3. What might **explain** the result? 4. What new can we **design**? 5. What can we learn by **bringing evidence together**?