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Research: The use of randomness in AI can enhance equity when distributing limited resources.

Algorithms, Artificial Intelligence, Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedJuly 24, 202437Views0Likes0Comments
Machine learning (ML) models are increasingly used by organizations to allocate scarce resources or opportunities, such as for job screening or determining priority for kidney transplant patients. To avoid bias in a model's predictions, users may adjust the data features or calibrate the model's scores to ensure fairness. However, researchers at MIT and Northeastern University…

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DigiXT Prism AI – An Essential Efficiency Booster for Commercial Users

Data, Generative AI, UncategorizedJuly 19, 202433Views0Likes0Comments
Prism AI, featured as part of the DigiXT suite, is an advanced artificial intelligence solution designed to facilitate analytics and business reporting. It acts as a "co-pilot" for various roles: business users, data engineers, and scientists. By addressing key challenges such as insights generation, effective visualization, and collaboration, Prism AI is building the bridge towards…

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Methods for evaluating the dependability of a multi-functional AI model prior to its implementation.

Algorithms, Artificial Intelligence, Computer science and technology, Data, Human-computer interaction, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedJuly 16, 202433Views0Likes0Comments
Foundation models, or large-scale deep-learning models, are becoming increasingly prevalent, particularly in powering prominent AI services such as DALL-E, or ChatGPT. These models are trained on huge quantities of general-purpose, unlabeled data, which is then repurposed for various uses, such as image generation or customer service tasks. However, the complex nature of these AI tools…

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MIT ARCLab declares the laureates of the first-ever Award for AI advancements in Space.

Aeronautical and astronautical engineering, Artificial Intelligence, Cleaner industry, Contests and academic competitions, Data, Lincoln Laboratory, Satellites, School of Engineering, Space exploration, Spaceflight, Sustainability, UncategorizedJuly 12, 202440Views0Likes0Comments
The number of satellites orbiting the Earth has grown exponentially in recent years, both due to lower costs and a rise in demand for services that satellites can provide, such as broadband internet and climate surveillance. However, this increase in activity also raises concerns around safety, security, and the environment, necessitating enhanced methods for monitoring…

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When should you rely on an AI model?

Artificial Intelligence, Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Technology and society, UncategorizedJuly 12, 202440Views0Likes0Comments
MIT researchers have developed a technique for improving the accuracy of uncertainty estimates in machine-learning models. This is especially important in situations where these models are used for critical tasks such as diagnosing diseases from medical imaging or filtering job applications. The new method works more efficiently and is scalable enough to apply to large…

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“They have the ability to envision influencing the world they reside in.”

academics, Algorithms, Analytics, Apps, Artificial Intelligence, astronomy and planetary science, Climate change, Collaboration, Computer science and technology, Data, Digital technology, Education, Environment, Global, Human-computer interaction, Internet, K-12 education, Machine learning, Media Lab, MIT Schwarzman College of Computing, nasa, Office of Open Learning, Open access, Programming, Social Media, Space, Special events and guest speakers, STEM education, teaching, Technology and society, UncategorizedJuly 9, 202449Views0Likes0Comments
A group of New England Innovation Academy students have developed a mobile app that highlights deforestation trends in Massachusetts as part of a project for the Day of AI, a curriculum developed by the MIT Responsible AI for Social Empowerment and Education (RAISE) initiative. The TreeSavers app aims to educate users about the effects of…

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Researchers from MIT present a generative artificial intelligence for databases.

Algorithms, Artificial Intelligence, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, Programming, Programming languages, Research, School of Engineering, School of Science, UncategorizedJuly 8, 202432Views0Likes0Comments
GenSQL, a new AI tool developed by scientists at MIT, is designed to simplify the complex statistical analysis of tabular data, enabling users to readily understand and interpret their databases. To this end, users don't need to grasp what is happening behind the scenes to develop accurate insights. The system's capabilities include making predictions, identifying anomalies,…

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The MIT-Takeda Program concluded with 16 research papers, a patent, and almost 24 projects successfully completed.

Artificial Intelligence, Awards, Classes and programs, Collaboration, Data, Drug development, Electrical Engineering & Computer Science (eecs), Faculty, Graduate, Health care, Health sciences and technology, honors and fellowships, Jameel Clinic, Machine learning, Medicine, MIT Schwarzman College of Computing, Pharmaceuticals, postdoctoral, School of Engineering, Special events and guest speakers, Students, SuperUROP, UncategorizedJune 19, 202444Views0Likes0Comments

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Improving software testing through the application 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 17, 202434Views0Likes0Comments
Generative AI, renowned for its capability to autonomously produce text and images, plays a crucial role in creating realistic synthetic data from diverse scenarios, helping organizations optimize operations. A notable initiative in the field is the Synthetic Data Vault (SDV), developed by DataCebo, an MIT spinoff. This generative system aids organizations in creating synthetic data…

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Improving software testing through the utilization 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 16, 202433Views0Likes0Comments
Generative AI has vast potential in creating synthetic data that can mimic real-world scenarios, which in turn can aid organizations in improving their operations. In line with this, DataCebo, a spinout from MIT, has developed a generative software system referred to as the Synthetic Data Vault (SDV), which has been employed by thousands of data…

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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 16, 202436Views0Likes0Comments
Generative AI, which can create text and images, is becoming an essential tool in today's data-driven society. It's now being utilized to produce realistic synthetic data, which can effectively solve problems where real data is limited or sensitive. For the past three years, DataCebo, an MIT spinoff, has been offering a Synthetic Data Vault (SDV)…

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