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Generative AI’s impact and uses are being investigated by MIT researchers who have received their second series of seed grants.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedJune 29, 202438Views0Likes0Comments
Last summer, MIT President Sally Kornbluth and Provost Cynthia Barnhart invited researchers to submit papers that lay out effective strategies, policy recommendations, and urgent actions within the field of generative artificial intelligence (AI). Among the 75 received proposals, 27 were selected for seed funding. Impressed by the level of interest and the quality of ideas,…

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MIT researchers examining the influence and utilization of generative AI have been given a second round of seed funding.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedJune 29, 202438Views0Likes0Comments
MIT President, Sally Kornbluth, and Provost, Cynthia Barnhart, issued a call for papers last summer regarding “effective roadmaps, policy recommendations, and calls for action” in the field of generative AI. From the 75 proposals they received, 27 were chosen for seed funding. Following the enormous response, a second call for proposals was launched which resulted…

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A fresh set of seed funds has been granted to MIT researchers examining the implications and uses of generative AI in the second phase.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedJune 28, 202436Views0Likes0Comments
MIT President Sally Kornbluth and Provost Cynthia Barnhart launched a call for papers last summer to create policy recommendations and effective strategies in the realm of generative AI. The duo received 75 proposals, out of which 27 were picked for seed financing. Encouraged by the response, a second call was held in fall, resulting in…

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Designing domestic robots to possess a bit of general knowledge.

Aeronautical and astronautical engineering, Algorithms, Artificial Intelligence, Assistive technology, Computer modeling, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Human-computer interaction, Machine learning, Research, Robotics, Robots, School of Engineering, UncategorizedJune 21, 202429Views0Likes0Comments
As robots are increasingly being deployed for complex household tasks, engineers at MIT are trying to equip them with common-sense knowledge allowing them to swiftly adapt when faced with disruptions. A newly developed method by the researchers merges robot motion data and common-sense knowledge from extensive language models (LLMs). The new approach allows a robot to…

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Large language models utilize a surprisingly straightforward method to access some stored information.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedJune 20, 202437Views0Likes0Comments
Large language models (LLMs), such as those which power AI chatbots like ChatGPT, are highly complex. While these powerful tools are used in diverse applications like customer support, code generation, and language translation, they remain somewhat of a mystery to the scientists who work with them. To develop a deeper understanding of their inner workings,…

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Large language models utilize an unexpectedly uncomplicated method to recall certain stored information.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedJune 20, 202433Views0Likes0Comments
Large language models (LLMs) that power artificial intelligence chatbots like ChatGPT are extremely complex and their functioning isn't fully understood. These LLMs are used in a variety of areas such as customer support, code generation and language translation. However, researchers from MIT and other institutions have made strides in understanding how these models retrieve stored…

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Researchers utilize shadows to create 3D scene models, incorporating objects that are normally obstructed from sight.

Artificial Intelligence, Autonomous vehicles, Computer science and technology, Computer vision, Imaging, Light, Machine learning, Media Lab, Research, School of Architecture and Planning, Sensors, UncategorizedJune 18, 202440Views0Likes0Comments
Researchers from MIT and Meta have developed a computational vision technique, named PlatoNeRF, that allows for creating vivid, accurate 3D models of a scene from a single camera view. The innovative technology uses the shadowing in a scene to determine what could lie within obstructed areas. By combining machine learning with LIDAR (Light Detection and…

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Comprehending the visual comprehension of language models.

Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, UncategorizedJune 18, 202434Views0Likes0Comments
Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory (CSAIL) has revealed that language models without image experience still understand the visual world. The team found that even without seeing images, language models could write image-rendering code that could generate detailed and complicated scenes. The knowledge that enabled this process came from the vast…

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