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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, 202433Views0Likes0Comments
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…

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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, 202435Views0Likes0Comments
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…

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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, 202432Views0Likes0Comments
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…

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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, 202436Views0Likes0Comments
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…

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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, 202437Views0Likes0Comments
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…

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Implementing AI for individuals facing challenges to find solutions.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedJune 10, 202436Views0Likes0Comments
While at MIT Media Lab in 2010, Karthik Dinakar and Birago Jones developed a machine learning tool destined to help content moderation teams at tech companies like Twitter and YouTube. The project excited many, leading to a demonstration at a White House cyberbullying summit. However, the system tripped over unconventional wording in teenage vernacular, revealing…

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Implementing AI to aide individuals encountering challenges.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedJune 10, 202437Views0Likes0Comments
In 2010, while studying at MIT Media Lab, Karthik Dinakar and Birago Jones developed a tool to assist in content moderation for social media platforms like Twitter and YouTube. The project, aimed at identifying concerning posts and potential cyberbullying, sparked enough interest to receive an invitation to a cyberbullying summit at the White House. However,…

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