Data Archives - Page 6 of 14

Improving software testing by utilizing generative AI

Alumni/ae, Artificial Intelligence, Data, Electrical Engineering & Computer Science (eecs), Faculty, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Startups, UncategorizedJune 15, 202471Views 0Likes 0Comments

Generative AI, which can create text and images, also has extensive potential in creating realistic synthetic data for various applications. Being able to produce synthetic data can assist organizations, particularly in situations where real-world data is lacking or sensitive. For instance, it can help in patient care, rerouting of flights due to adverse weather, or…

Improving software testing with the use of generative artificial intelligence.

Alumni/ae, Artificial Intelligence, Data, Electrical Engineering & Computer Science (eecs), Faculty, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Startups, UncategorizedJune 15, 202463Views 0Likes 0Comments

Generative AI has the capability to produce realistic synthetic data that could help organizations in various sectors such as healthcare, aviation, and software development efficiently carry out operations. For the last three years, MIT spinout DataCebo has been offering the Synthetic Data Vault (SDV), a generative software system that can design synthetic data, useful in…

Improving software testing through the use of generative artificial intelligence.

Alumni/ae, Artificial Intelligence, Data, Electrical Engineering & Computer Science (eecs), Faculty, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Startups, UncategorizedJune 14, 202465Views 0Likes 0Comments

Generative AI, recognized mainly for its ability in creating text and images, is now used by companies to create synthetic data for various scenarios aiding in patient treatment, plane rerouting, and software improvements especially in situations that lack real-world data or require sensitive data. DataCebo, an MIT spinoff, has invented a generative software system called…

The startup speeds up advancements in achieving computing at the speed of light.

Alumni/ae, Artificial Intelligence, Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Electronics, Innovation and Entrepreneurship (I&E), Machine learning, MIT $100K competition, Photonics, School of Engineering, Startups, Sustainability, Sustainable computing, UncategorizedJune 14, 202469Views 0Likes 0Comments

Enhancing software testing through the application of generative AI.

Alumni/ae, Artificial Intelligence, Data, Electrical Engineering & Computer Science (eecs), Faculty, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Startups, UncategorizedJune 14, 202467Views 0Likes 0Comments

Generative AI, in the past few years, has gained significant popularity because of its capacity to develop realistic text and images. However, the created text and images form only a portion of the data generated today. Every interaction we have with a medical system, software application, or the effect of any environment, such as a…

Startup advances the journey towards computing at the speed of light.

Alumni/ae, Artificial Intelligence, Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Electronics, Innovation and Entrepreneurship (I&E), Machine learning, MIT $100K competition, Photonics, School of Engineering, Startups, Sustainability, Sustainable computing, UncategorizedJune 13, 202474Views 0Likes 0Comments

In today's digital era, the demand for ever-increasing computing power has been overwhelmingly huge, driven primarily by advancements in artificial intelligence. However, the constant innovation in computing technology is facing obstacles, primarily due to the limitations in the shrinking size of transistors used in chips. This imposes a strict limit on Moore's Law and Dennard's…

Improving software testing through the application of generative AI.

Alumni/ae, Artificial Intelligence, Data, Electrical Engineering & Computer Science (eecs), Faculty, Innovation and Entrepreneurship (I&E), Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Startups, UncategorizedJune 13, 202466Views 0Likes 0Comments

Generative AI is increasingly being utilized to generate synthetic data, enhancing organizations' abilities to deal with situations where actual data may be limited or sensitive. Over the past three years, DataCebo, an MIT spinoff initiative, has been offering a generative software system known as the Synthetic Data Vault (SDV) to enable organizations to create synthetic…

The progress towards approaching light-speed computing is being expedited by a startup.

Alumni/ae, Artificial Intelligence, Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Electronics, Innovation and Entrepreneurship (I&E), Machine learning, MIT $100K competition, Photonics, School of Engineering, Startups, Sustainability, Sustainable computing, UncategorizedJune 13, 202474Views 0Likes 0Comments

The progress towards computing at light-speed is being fast-tracked by a startup.

Alumni/ae, Artificial Intelligence, Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Electronics, Innovation and Entrepreneurship (I&E), Machine learning, MIT $100K competition, Photonics, School of Engineering, Startups, Sustainability, Sustainable computing, UncategorizedJune 12, 202469Views 0Likes 0Comments

Researchers utilize extensive language models to assist robots with navigation.

Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Data, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, Robotics, Robots, School of Engineering, UncategorizedJune 12, 202461Views 0Likes 0Comments

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a language-based navigational strategy for AI robots. The method uses textual descriptions instead of visual information, effectively simplifying the process of robotic navigation. Visual data traditionally requires significant computational capacity and detailed hand-crafted machine-learning models to function effectively. The researchers' approach involves converting a…