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Materials that conduct protons could potentially lead to the development of novel eco-friendly energy solutions.

Artificial Intelligence, DMSE, Energy, Machine learning, Materials science and engineering, Research, School of Engineering, Sustainability, UncategorizedJuly 24, 202439Views0Likes0Comments
MIT engineers have identified new materials that could be more efficient conductors of protons – the nucleus of a hydrogen atom – which could pave the way for a number of climate-protecting technologies. Today's proton-conducting materials require very high temperatures, but lower-temperature alternatives could boost new technologies such as fuel cells that produce clean electricity…

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Researchers from MIT have made significant progress in enhancing the automatic understanding in AI models.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Language, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, School of Engineering, UncategorizedJuly 24, 202435Views0Likes0Comments
As AI models become increasingly integrated into various sectors, understanding how they function is crucial. By interpreting the mechanisms underlying these models, we can audit them for safety and biases, potentially deepening our understanding of intelligence. Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have been working to automate this interpretation process, specifically…

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Using AI and Machine Learning (ML) to Enhance Untargeted Metabolomics and Exposomics: Progress, Obstacles, and The Path Ahead

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 23, 202435Views0Likes0Comments
In recent years, advances in artificial intelligence (AI) and machine learning (ML) have greatly enhanced untargeted metabolomics, a field which allows for an unbiased global analysis of metabolites in the body and can yield crucial insights into human health and disease. Through high-resolution mass spectrometry, untargeted metabolomics identifies key metabolites and chemicals that may contribute…

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Utilizing AI and Machine Learning for Unspecified Metabolomics and Exposomics: Progress, Difficulties, and Upcoming Projections.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 23, 202434Views0Likes0Comments
Metabolomics uses a high-throughput technique to analyze various metabolites and small molecules in biological samples to provide important insights into human health and disease. Untargeted metabolomics is one application that enables a comprehensive analysis of the metabolome, identifying crucial metabolites that indicate or contribute to health conditions. The advent of artificial intelligence (AI) and machine…

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Even though we may anticipate large language models to operate similarly to humans, they do not.

Algorithms, Artificial Intelligence, Computer science and technology, Economics, Human-computer interaction, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, School of Humanities Arts and Social Sciences, UncategorizedJuly 23, 202432Views0Likes0Comments
Large language models (LLMs), such as GPT-3, are powerful tools due to their versatility. They can perform a wide range of tasks, ranging from helping draft emails to assisting in cancer diagnosis. However, their wide applicability makes them challenging to evaluate systematically, as it would be impossible to create a benchmark dataset to test a…

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Scikit-fingerprints: A Highly Developed Python Module for Effectual Molecular Fingerprint Calculations and Incorporation with Machine Learning Processes.

AI Paper Summary, Applications, Artificial Intelligence, Editors Pick, Machine learning, Python, Software Engineering, Staff, Tech News, Technology, UncategorizedJuly 23, 202434Views0Likes0Comments
Scikit-fingerprints, a Python package designed by researchers from AGH University of Krakow for computing molecular fingerprints, has integrated with computational chemistry and machine learning application. It specifically bridges the gap between the fields of computational chemistry that traditionally use Java or C++, and machine learning applications popularly paired with Python. Molecular graphs are representations of…

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A novel artificial intelligence approach accurately interprets 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 23, 202433Views0Likes0Comments
Artificial intelligence (AI) tools have great potential in the field of biomedicine, particularly in the process of segmentation or annotating the pixels of an important structure in a medical image. Segmentation is critical for the identification of possible diseases or anomalies in body organs or cells. However, the challenge lies in the variability of the…

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The AI model is capable of recognizing specific stages of breast tumors that have a high probability of developing into invasive cancer.

Artificial Intelligence, Broad Institute, Cancer, Computer science and technology, Diagnostics, Disease, Electrical Engineering & Computer Science (eecs), Health, Health care, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 23, 202438Views0Likes0Comments
Ductal carcinoma in situ (DCIS), a type of tumor that can develop into an aggressive form of breast cancer, accounts for approximately 25% of all breast cancer diagnoses. DCIS can be challenging for clinicians to accurately categorize, leading to frequent overtreatment for patients. A team of researchers from the Massachusetts Institute of Technology (MIT) and…

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An improved, speedier 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 22, 202438Views0Likes0Comments
While artificial intelligence (AI) chatbots like ChatGPT are capable of a variety of tasks, concerns have been raised about their potential to generate unsafe or inappropriate responses. To mitigate these risks, AI labs use a safeguarding method called "red-teaming". In this process, human testers aim to elicit undesirable responses from the AI, informing its development…

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A fresh approach to artificial intelligence quantifies uncertainty 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 22, 202432Views0Likes0Comments
Segmentation, a practice in biomedicine whereby pixels from a significant structure in a medical image are annotated, can be aided by artificial intelligence (AI) models. However, these models often give only one solution, while the problem of medical image segmentation usually requires a range of interpretations. For instance, multiple human experts may have different perspectives…

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Does ‘fear’ serve as a fundamental factor in developing more flexible, robust, and organic AI systems?

Bio-inspired AI, Biology, Industry, Machine learning, UncategorizedJuly 22, 202436Views0Likes0Comments
Artificial general intelligence (AGI), also known as superintelligence, is the ultimate goal of AI research. It aims to create autonomous systems capable of performing a wide range of tasks as humans do. However, the concept of AGI is still elusive, with critics arguing that current AI systems can never achieve general intelligence. They cite limitations…

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The Neo4j LLM Knowledge Graph Builder: An AI Mechanism that Constructs Knowledge Graphs from Disorganized Data

AI Shorts, AI Tool, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 22, 202437Views0Likes0Comments
Artificial Intelligence (AI) is making strides in the data analysis sphere, with teams of researchers developing new applications to convert unstructured data into usable information. Recently, one such application was introduced, known as the Neo4j LLM Knowledge Graph Builder. This tool leverages powerful machine learning models to transform unstructured data into a comprehensive knowledge graph,…

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