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Artificial Intelligence

Construct Salesforce applications powered by generative AI using Amazon Bedrock.

Salesforce Data Cloud and Einstein Model Builder are partnering with Amazon Web Services (AWS) and its Amazon Bedrock service to enable the use of Large Language Models (LLMs) in generative artificial intelligence (AI) applications. This integration was revealed by Salesforce's Daryl Martis and Darvish Shadravan. Salesforce can bring its own LLMs from AWS accounts to…

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Stanford’s AI research offers fresh perspectives on AI model breakdown and data gathering.

The alarming phenomenon of AI model collapse, which occurs when AI models are trained on datasets that contain their outputs, has been a major concern for researchers. As such large-scale models are trained on ever-expanding web-scale datasets, concerns have been raised about the degradation of model performance over time, potentially making newer models ineffective and…

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Progressing with Precision Psychiatry: Utilizing AI and Machine Learning for Customized Diagnosis, Therapy, and Outcome Prediction.

Precision psychiatry combines psychiatry, precision medicine, and pharmacogenomics to devise personalized treatments for psychiatric disorders. The rise of Artificial Intelligence (AI) and machine learning technologies has made it possible to identify a multitude of biomarkers and genetic locations associated with these conditions. AI and machine learning have strong potential in predicting the responses of patients to…

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To enhance the effectiveness of an AI assistant, begin by emulating the unpredictable actions of people.

Researchers at MIT and the University of Washington have developed a model that predicts the behavior of an agent (either human or machine) by accounting for unknown computational constraints that might hamper problem-solving abilities. This model, described as an agent's "inference budget", can infer these constraints from just a few prior actions and subsequently predict…

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This small microchip can protect user information and enhance influential computing on a mobile phone.

A team of researchers from the Massachusetts Institute of Technology (MIT) and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that is resistant to the most common types of cyber attacks. This development could help secure sensitive health records, financial information and other private data while still allowing complicated artificial intelligence (AI) models…

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This small microchip can protect user information while facilitating effective computation on a mobile phone.

Smartphone health-monitoring apps can be invaluable for managing chronic diseases or setting fitness goals. However, these applications often suffer from slowdowns and energy inefficiencies due to the large machine-learning models they use. These models are frequently swapped between a smartphone and a central memory server, hampering performance. One solution engineers have pursued is the use…

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Julie Shah has been appointed as the leader of the Department of Aeronautics and Astronautics.

Julie Shah, the H.N. Slater Professor of Aeronautics and Astronautics, has been appointed as the new leader of the Department of Aeronautics and Astronautics at the Massachusetts Institute of Technology (MIT), effective from May 1. Shah is renowned for her visionary and interdisciplinary leadership, particularly significant for her technical contributions to robotics and artificial intelligence…

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What makes GPT-4o Mini more effective than Claude 3.5 Sonnet in LMSys?

The recent release of scores by the LMSys Chatbot Arena has ignited discussions among AI researchers. According to the results, GPT-4o Mini outstrips Claude 3.5 Sonnet, frequently hailed as the smartest Large Language Model (LLM) currently available. To understand the exceptional performance of GPT-4o Mini, a random selection of one thousand real user prompts were evaluated.…

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Progress and Obstacles in Forecasting TCR Specificity: From Grouping to Protein Linguistic Models

Researchers from IBM Research Europe, the Institute of Computational Life Sciences at Zürich University of Applied Sciences, and Yale School of Medicine have evaluated the progress of computational models which predict TCR (T cell receptor) binding specificity, identifying potential for improvement in immunotherapy development. TCR binding specificity is key to the adaptive immune system. T cells…

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