As artificial intelligence agents become more advanced, it could become increasingly difficult to distinguish between AI-powered users and real humans on the internet. In a new white paper, researchers from MIT, OpenAI, Microsoft, and other tech companies and academic institutions propose the use of personhood credentials, a verification technique that enables someone to prove they are a real human online, while preserving their privacy.
Generative AI represents a seismic shift in the way we approach creative tasks. A comprehensive understanding of these technologies enables organizations to leverage the power of the technology to increase productivity, improve customer service, enhance user experiences, develop content, create synthetic data, enable new discoveries, and so much more!
To ensure that professionals have continual training and access to the latest knowledge, MIT xPRO has created the six-week online course: Driving Innovation with Generative AI.
Ask a large language model (LLM) like GPT-4 to smell a rain-soaked campsite, and it’ll politely decline. Ask the same system to describe that scent to you, and it’ll wax poetic about “an air thick with anticipation" and “a scent that is both fresh and earthy," despite having neither prior experience with rain nor a nose to help it make such observations.
As organizations rush to implement artificial intelligence (AI), a new analysis of AI-related risks finds significant gaps in our understanding, highlighting an urgent need for a more comprehensive approach.
Generative AI represents a seismic shift in the way we approach creative tasks. A comprehensive understanding of these technologies enables organizations to leverage the power of the technology to increase productivity, improve customer service, enhance user experiences, develop content, create synthetic data, enable new discoveries, and so much more!
Add to calendarAmerica/New_YorkDriving Innovation with Generative AI09/29/2025
Generative AI represents a seismic shift in the way we approach creative tasks. A comprehensive understanding of these technologies enables organizations to leverage the power of the technology to increase productivity, improve customer service, enhance user experiences, develop content, create synthetic data, enable new discoveries, and so much more!
Become an essential part of your organization’s generative AI journey by equipping yourself with the knowledge and skills necessary to navigate the intricate world of generative AI. This six-week course leverages industry case studies, hands-on work with generative AI tools, and the latest thinking from 12 faculty members from MIT CSAIL.
As artificial intelligence models become increasingly prevalent and are integrated into diverse sectors like health care, finance, education, transportation, and entertainment, understanding how they work under the hood is critical. Interpreting the mechanisms underlying AI models enables us to audit them for safety and biases, with the potential to deepen our understanding of the science behind intelligence itself.
Neural networks have made a seismic impact on how engineers design controllers for robots, catalyzing more adaptive and efficient machines. Still, these brain-like machine-learning systems are a double-edged sword: Their complexity makes them powerful, but it also makes it difficult to guarantee that a robot powered by a neural network will safely accomplish its task.
