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MIT Sloan, Teaching & Learning Technologies
Приєднався 30 сер 2023
Teaching & Learning Technologies, part of Sloan Technology Services (STS), connects MIT Sloan to research-driven best practices, resources, and trainings in instructional technology and design-helping our community make an impact in the classroom and beyond. Learn more: mitsloanedtech.mit.edu/about/
Generative AI as a New Innovation Platform
Dive into the world of generative AI with Michael Cusumano, Sloan Management Review Distinguished Professor of Management and Deputy Dean for Faculty at the MIT Sloan School of Management. In this video, inspired by his October 2023 column for Communications of the ACM, Cusumano explores the emergence of generative AI as a new innovation platform. Discover the transformative potential of this new technology, from its foundational models to its expansive applications across industries. Whether you're deeply embedded in the tech world, a strategic thinker in business, or simply fascinated by AI technologies, this video can help you gain a deeper understanding of how generative AI is shaping our digital future.
Note: Google changed the name of their generative AI chatbot from Bard (mentioned in the video) to Gemini in February, 2024.
For more MIT Sloan resources on teaching with generative AI, visit our Resource Hub: mitsloanedtech.mit.edu/ai/.
Note: Google changed the name of their generative AI chatbot from Bard (mentioned in the video) to Gemini in February, 2024.
For more MIT Sloan resources on teaching with generative AI, visit our Resource Hub: mitsloanedtech.mit.edu/ai/.
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Unpacking NVIDIA's Dominance in the Generative AI Ecosystem
Переглядів 81710 місяців тому
Dive into the world of generative AI and NVIDIA with Michael Cusumano, Sloan Management Review Distinguished Professor of Management and Deputy Dean at MIT Sloan School of Management. Based on his recent column in Communications of the ACM (January 2024), Cusumano takes us on a journey from NVIDIA's humble beginnings to its current status as a behemoth in AI and machine learning. He examines th...
Getting Started with ChatGPT's Advanced Data Analysis Feature
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Join Chuck Downing, a PhD student at MIT Sloan, as he dives into the capabilities of ChatGPT's Advanced Data Analysis features. This tutorial showcases how to enable and use Advanced Data Analysis, from reading and describing datasets to generating advanced data visualization and regression analyses. Downing demonstrates the process using the World Bank's carbon emissions dataset, highlighting ...
MIT Sloan's Rama Ramakrishnan Shares Primer on ChatGPT
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Rama Ramakrishnan, Professor of the Practice in Data Science and Applied Machine Learning at the MIT Sloan School of Management, guides us on an exploration of the AI model ChatGPT. The video traces the evolution of ChatGPT from its predecessors, GPT-3 and GPT-3.5. It demystifies the complex mathematical and neural network foundations that enable the model to predict and generate text based on ...
Welcome to MIT Sloan's Teaching with Generative AI Resource Hub
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In this video, Eric So, Sloan Distinguished Professor of Global Economics & Management at MIT Sloan, welcomes you to the school's Teaching with Generative AI Resource Hub. Discover MIT Sloan's AI teaching resources and join the conversation: mitsloanedtech.mit.edu/ai/.
What a lovely explanation! I am so proud to be a graduate of this magnificent college!
Really really interesting! I also find that if I ask ChatGPT for its sources for certain information, it sometimes understands that I am feeling doubtful about its answer, and it has often corrected itself, given me the (new) sources, with an apology.
Amazing explanation!
As explained at around 3:52 , chathpt would take out the next word after sampling.. which would mean that got should generate wrong sentences many time.. which is not the case. Could you explain this
Sampling is done in probabilistic manner, so you are more likely to get words that have higher probability (but not always the one with maximum probability). This also means that there is a likelihood of picking a word that is incorrect, but since the probability associated with this choice is comparatively very low, its chances of being picked are also low.
Excellent explanation of evolution from GPT to Chatgpt...thank you
Fascinating!