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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, 202456Views0Likes0Comments
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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The conference emphasizes the magnitude of the mental health issue and innovative approaches to identifying and treating it.

Alzheimer's, Artificial Intelligence, Behavior, Biology, Brain and cognitive sciences, Depression, Digital technology, Disease, Health, Health care, Health sciences and technology, Machine learning, McGovern Institute, Mental health, Mobile devices, Neuroscience, Office of Open Learning, Parkinson's, Pharmaceuticals, School of Science, Special events and guest speakers, UncategorizedJune 13, 202466Views0Likes0Comments

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Stanford researchers propose a two-step model for adjusting the linguistic calibrations of long-form creations.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJune 12, 202450Views0Likes0Comments
Large Language Models (LLMs) can sometimes mislead users to make poor decisions by providing wrong information, a phenomenon known as 'hallucination'. To mitigate this, a team of researchers from Stanford University has proposed a new method for linguistic calibration. The new framework involves a two-step training process for LLMs. In the first stage - supervised finetuning…

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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, 202449Views0Likes0Comments
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…

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Improving the Safety and Dependability of AI via Short-Circuiting Methods

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJune 12, 202450Views0Likes0Comments
AI system vulnerabilities, particularly in large language models (LLMs) and multimodal models, can be manipulated to produce harmful outputs, raising questions about their safety and reliability. Existing defenses, such as refusal training and adversarial training, often fall short against sophisticated adversarial attacks and may degrade model performance. Addressing these limitations, a research team from Black…

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A novel approach to computer vision accelerates the screening process of electronic components.

3-D printing, Algorithms, Artificial Intelligence, Automation, Computer vision, Imaging, Machine learning, Materials science and engineering, Mechanical engineering, Renewable energy, Research, School of Engineering, Solar, Sustainability, UncategorizedJune 12, 202453Views0Likes0Comments
Solar cells, transistors, LEDs, and batteries with boosted performance require better electronic materials which are often discovered from novel compositions. Scientists have turned to AI tools to identify potential materials from millions of chemical formulations, with engineers developing machines that can print hundreds of samples at a time, based on compositions identified by AI algorithms.…

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