AI News
New insights into training dynamics of deep classifiers
MIT researchers uncover the structural properties and dynamics of deep classifiers, offering novel explanations for optimization, generalization, and approximation in deep networks.
Overhaul, which taps AI to secure physical supply chains, raises $73M in equity and debt
Businesses dependent on the physical supply chain face a number of potential roadblocks. Customers expect fast deliveries with visibility into each step, but costs — including transportation and raw materials costs — are rising thanks to inflation and other factors. Meanwhile, there’s a talent shortage, particularly in areas like logistics and operations management, and technical […] Overhaul, which taps AI to secure physical supply chains, raises $73M in equity and debt by Kyle Wiggers originally published on TechCrunch
Microsoft’s computer vision model will generate alt text for Reddit images
Two years ago, Microsoft announced Florence, an AI system that it pitched as a “complete rethinking” of modern computer vision models. Unlike most vision models at the time, Florence was both “unified” and “multimodal,” meaning it could (1) understand language as well as images and (2) handle a range of tasks rather than being limited […] Microsoft’s computer vision model will generate alt text for Reddit images by Kyle Wiggers originally published on TechCrunch
Large language models are biased. Can logic help save them?
MIT researchers trained logic-aware language models to reduce harmful stereotypes like gender and racial biases.
Robot armies duke it out in Battlecode’s epic on-screen battles
The long-running programming competition encourages skills and friendships that last a lifetime.
Integrating humans with AI in structural design
A process that seeks feedback from human specialists proves more effective at optimization than automated systems working alone.
MIT-Takeda Program heads into fourth year with crop of 10 new projects
The program leverages MIT’s research expertise and Takeda’s industrial know-how for research in artificial intelligence and medicine.
Efficient technique improves machine-learning models’ reliability
The method enables a model to determine its confidence in a prediction, while using no additional data and far fewer computing resources than other methods.
Helping companies deploy AI models more responsibly
MIT spinout Verta offers tools to help companies introduce, monitor, and manage machine-learning models safely and at scale.
3 Questions: Leo Anthony Celi on ChatGPT and medicine
The chatbot’s success on the medical licensing exam shows that the test — and medical education — are flawed, Celi says.
Solving a machine-learning mystery
A new study shows how large language models like GPT-3 can learn a new task from just a few examples, without the need for any new training data.
Automating the math for decision-making under uncertainty
A new tool brings the benefits of AI programming to a much broader class of problems.
MIT Solve announces 2023 global challenges and Indigenous Communities Fellowship
More than $1 million in funding available to selected Solver teams and fellows.
Putting clear bounds on uncertainty
Computer scientists want to know the exact limits in our ability to clean up, and reconstruct, partly blurred images.
MIT researchers develop an AI model that can detect future lung cancer risk
Deep-learning model takes a personalized approach to assessing each patient’s risk of lung cancer based on CT scans.
Gaining real-world industry experience through Break Through Tech AI at MIT
A new experiential learning opportunity challenges undergraduates across the Greater Boston area to apply their AI skills to a range of industry projects.
2022-23 Takeda Fellows: Leveraging AI to positively impact human health
New fellows are working on health records, robot control, pandemic preparedness, brain injuries, and more.
Engineering in harmony
AeroAstro major and accomplished tuba player Frederick Ajisafe relishes the community he has found in the MIT Wind Ensemble.
Forecasting potential misuses of language models for disinformation campaigns and how to reduce risk
OpenAI researchers collaborated with Georgetown University’s Center for Security and Emerging Technology and the Stanford Internet Observatory to investigate how large language models might be misused for disinformation purposes. The collaboration included an October 2021 workshop bringing together 30 disinformation researchers, machine learning experts, and policy analysts, and culminated in a co-authored report building on more than a year of research. This report outlines the threats that language models pose to the information environment if used to augment disinformation campaigns and introduces a framework for analyzing potential mitigations. Read the full report here.
Program teaches US Air Force personnel the fundamentals of AI
MIT researchers developed and studied a customized AI training program for users with varied backgrounds, which could be delivered across large organizations.
