Latest from MIT Tech Review – Why Big Tech’s bet on AI assistants is so risky

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Since the beginning of the generative AI boom, tech companies have been feverishly trying to come up with the killer app for the technology. First it was online search, with mixed results. Now…

Latest from MIT : A more effective experimental design for engineering a cell into a new state

A strategy for cellular reprogramming involves using targeted genetic interventions to engineer a cell into a new state. The technique holds great promise in immunotherapy, for instance, where researchers could reprogram a patient’s T-cells so they are more potent cancer killers. Someday, the approach could also help identify life-saving cancer treatments or regenerative therapies that…

Latest from MIT : Is AI in the eye of the beholder?

Someone’s prior beliefs about an artificial intelligence agent, like a chatbot, have a significant effect on their interactions with that agent and their perception of its trustworthiness, empathy, and effectiveness, according to a new study. Researchers from MIT and Arizona State University found that priming users — by telling them that a conversational AI agent…

Latest from Google AI – DynIBaR: Space-time view synthesis from videos of dynamic scenes

Posted by Zhengqi Li and Noah Snavely, Research Scientists, Google Research A mobile phone’s camera is a powerful tool for capturing everyday moments. However, capturing a dynamic scene using a single camera is fundamentally limited. For instance, if we wanted to adjust the camera motion or timing of a recorded video (e.g., to freeze time…

Latest from Google AI – Re-weighted gradient descent via distributionally robust optimization

Ramnath Kumar, Pre-Doctoral Researcher, and Arun Sai Suggala, Research Scientist, Google Research Deep neural networks (DNNs) have become essential for solving a wide range of tasks, from standard supervised learning (image classification using ViT) to meta-learning. The most commonly-used paradigm for learning DNNs is empirical risk minimization (ERM), which aims to identify a network that…

Latest from MIT Tech Review – This robotic exoskeleton can help runners sprint faster

A wearable exoskeleton can help runners increase their speed by encouraging them to take more steps, allowing them to cover short distances more quickly. While previous studies have focused on how wearable exoskeletons can help people reduce the energy they expend while running, the new study, published today in Science Robotics, examines how wearable robots…

Latest from MIT : Re-imagining the opera of the future

In the mid-1980s, composer Tod Machover came across a copy of Philip K. Dick’s science fiction novel “VALIS” in a Parisian bookstore. Based on a mystical vision Dick called his “pink light experience,” “VALIS” was an acronym for “vast active living intelligence system.” The metaphysical novel would become the basis for Machover’s opera of the…

Latest from MIT : From physics to generative AI: An AI model for advanced pattern generation

Generative AI, which is currently riding a crest of popular discourse, promises a world where the simple transforms into the complex — where a simple distribution evolves into intricate patterns of images, sounds, or text, rendering the artificial startlingly real.  The realms of imagination no longer remain as mere abstractions, as researchers from MIT’s Computer…