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A quicker and more effective method to stop an AI chatbot from providing harmful replies.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, UncategorizedJuly 19, 202434Views0Likes0Comments
Companies that build large language models, like those used in AI chatbots, routinely safeguard their systems using a process known as red-teaming. This involves human testers generating prompts designed to trigger unsafe or toxic responses from the bot, thus enabling creators to understand potential weaknesses and vulnerabilities. Despite the merits of this procedure, it often…

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A novel artificial intelligence approach has been developed to accurately determine the ambiguity in medical imaging.

Artificial Intelligence, Broad Institute, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Health care, Imaging, Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 19, 202430Views0Likes0Comments
In the field of biomedicine, segmentation plays a crucial role in identifying and highlighting essential structures in medical images, such as organs or cells. In recent times, artificial intelligence (AI) models have shown promise in aiding clinicians by identifying pixels that may indicate disease or anomalies. However, there is a consensus that this method is…

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Machine learning divulges the mysteries of high-tech alloys.

Artificial Intelligence, Computer modeling, DMSE, Electrical Engineering & Computer Science (eecs), Machine learning, Materials science and engineering, Metals, Research, School of Engineering, UncategorizedJuly 19, 202434Views0Likes0Comments
Researchers from the Massachusetts Institute of Technology (MIT) are using machine learning to explore the concept of short-range order (SRO) in metallic alloys at atomic levels. The team believes that understanding SRO is key to creating high-performance alloys with unique properties but this has been a challenging area to explore. High-entropy alloys are of particular…

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Machine learning reveals the mysteries behind sophisticated alloys.

Artificial Intelligence, Computer modeling, DMSE, Electrical Engineering & Computer Science (eecs), Machine learning, Materials science and engineering, Metals, Research, School of Engineering, UncategorizedJuly 19, 202446Views0Likes0Comments
The Short-Range Order (SRO), the arrangement of atoms over small distances, plays a crucial role in materials’ properties, yet it has been understudied in metallic alloys. However, recent attention has been drawn to this concept as it is a contributing step towards developing high-performing alloys known as high-entropy alloys. Understanding how atoms self-arrange can pose…

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PredBench: An All-Inclusive AI Standard for Assessing 12 Space-Time Forecasting Approaches across 15 Varied Data Sets via Multi-faceted Analysis.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 18, 202432Views0Likes0Comments
Spatiotemporal prediction, a significant focus of research in computer vision and artificial intelligence, holds broad applications in areas such as weather forecasting, robotics, and autonomous vehicles. It uses past and present data to form models for predicting future states. However, the lack of standardized frameworks for comparing different network architectures has presented a significant challenge.…

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G-Retriever: Progressing Graph Question Answering in Real-Life Situations through RAG and LLMs

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 18, 202436Views0Likes0Comments
Artificial Intelligence has made significant progress with Large Language Models (LLMs), but their capability to process complex structured graph data remains challenging. Many real-world data structures, such as the web, e-commerce systems, and knowledge graphs, have a definite graph structure. While attempts have been made to amalgamate technologies like Graph Neural Networks (GNNs) with LLMs,…

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An improved and quicker method to guard against an AI chatbot providing harmful responses.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, UncategorizedJuly 18, 202435Views0Likes0Comments
Artificial Intelligence chatbots have the capacity to construct helpful code, summarize articles, and even create more hazardous content. To prevent safety violations like these, companies employed a procedure known as "red-teaming" in which human testers crafted prompts intended to elicit unsafe responses from chatbots, which were then taught to avoid these inputs. However, this required…

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A novel artificial intelligence technique successfully identifies ambiguity in medical imaging.

Artificial Intelligence, Broad Institute, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Health care, Imaging, Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 18, 202435Views0Likes0Comments
In biomedicine, the process of segmentation involves marking significant structures in a medical image, such as cells or organs. This can aid in the detection and treatment of diseases visible in these images. Despite this promise, current artificial intelligence (AI) systems used for medical image segmentation only offer a single segmentation result. This approach isn't…

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An improved, quicker method to inhibit an AI chatbot from providing harmful responses.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, UncategorizedJuly 18, 202434Views0Likes0Comments
Researchers from the Improbable AI Lab at MIT and the MIT-IBM Watson AI Lab have developed a new technique to improve "red-teaming," a process of safeguarding large language models, such as AI chatbot, through the use of machine learning. The new approach focuses on the automatic generation of diverse prompts that result in undesirable responses…

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A novel approach in AI successfully identifies ambiguity in medical imaging.

Artificial Intelligence, Broad Institute, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Health care, Imaging, Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 18, 202435Views0Likes0Comments
Researchers from MIT, in collaboration with the Broad Institute of MIT and Harvard and Massachusetts General Hospital, have introduced a new artificial intelligence (AI) tool known as Tyche, which can provide multiple, plausible image segmentation possibilities for a given medical image. Unlike conventional AI tools, which typically offer a single definitive interpretation, Tyche generates a…

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Developing and validating robust systems controlled by artificial intelligence in a systematic and adaptable manner.

Aeronautical and astronautical engineering, Algorithms, Artificial Intelligence, Autonomous vehicles, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Drones, Electrical Engineering & Computer Science (eecs), Machine learning, Mechanical engineering, MIT Schwarzman College of Computing, Networks, Research, Robotics, Robots, Safety, School of Engineering, UncategorizedJuly 18, 202446Views0Likes0Comments
Neural networks have been of immense benefit in the design of robot controllers, boosting the adaptive and effectiveness abilities of these machines. However, their complex nature makes it challenging to confirm their safe execution of assigned tasks. Traditionally, the verification of safety and stability are done using Lyapunov functions. If a Lyapunov function that consistently…

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A novel artificial intelligence approach has been developed to recognize ambiguity in medical imaging.

Artificial Intelligence, Broad Institute, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Health care, Imaging, Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 18, 202438Views0Likes0Comments
Biomedicine often requires the annotation of pixels in a medical image to identify critical structures such as organs or cells, a process known as segmentation. In this context, artificial intelligence (AI) models can be useful to clinicians by highlighting pixels indicating potential disease or anomalies. However, decision-making in medical image segmentation is frequently complex, with…

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