MIT PhD student Behrooz Tahmasebi and advisor Stefanie Jegelka have modified Weyl's law to incorporate symmetry in assessing the complexity of data, potentially enhancing machine learning. Their work, presented at the Neural Information Processing Systems conference, demonstrates that models satisfying symmetries can produce predictions with smaller errors and require less training data, partic...
A multinational company's Hong Kong office lost HK$200 million ($25.6 million) in a sophisticated scam using deepfake technology, featuring a digitally recreated version of the CFO instructing an employee to transfer funds. This incident highlights the challenges posed by deepfakes, which utilize AI tools to create convincing fake videos, making it difficult to discern real from fabricated cont...
A new study by the ITIF calls for governments to adopt AI to drive energy efficiency across industries, citing examples such as farmers using AI to reduce fertilizer and water usage, and factories deploying it to increase energy efficiency. The study's author emphasizes the need for policymakers to not hold back beneficial uses of AI, especially in regulated areas like healthcare.
Learn how to calculate your data team's return on investment (ROI) with the Data ROI Pyramid, which focuses on capturing the value of data team initiatives such as customer churn dashboards and data quality initiatives. The pyramid also emphasizes reducing data downtime as a key strategy to increase ROI.
Hacker-for-hire firm, Appin Technology, and its subsidiaries have allegedly been involved in cyber-espionage, using legal threats to silence publishers reporting on their activities. Anti-censorship voices are now fighting back against their aggressive censorship campaign.
The article discusses the benefits of retrieval augmented generation (RAG) for improving the precision and relevance of AI models. It emphasizes the importance of monitoring retrieval and response evaluation metrics to troubleshoot poor performance in LLM systems.
The article discusses the Retrieval Augmented Generation (RAG) pattern for generative AI workloads, focusing on the analysis and detection of embedding drift. It explores how embedding vectors are used to retrieve knowledge from external sources and augment instruction prompts, and explains the process of performing drift analysis on these vectors using Principal Component Analysis (PCA).
Generative AI is revolutionizing product design by making complex tools more accessible through natural language commands, benefiting both expert and novice users. Tailoring AI models with domain-specific data improves performance, giving companies a competitive edge in delivering differentiated offerings.
GeForce NOW celebrates 4 years with Diablo IV and Overwatch 2 joining the cloud gaming library, along with other new games. The battle for Sanctuary heats up in Diablo IV, while Overwatch 2 offers epic team-based action, all available on GeForce NOW.
Data is crucial for maximizing the value of AI and solving business problems efficiently. Amazon SageMaker Canvas revolutionizes data preparation for security analysts, allowing them to effortlessly access foundation models, extract value, and remediate cybersecurity risks.
Resilience is crucial for generative AI workloads to meet organizational availability and business continuity requirements. Generative AI solutions involve new roles, tools, and considerations such as prompt validation and data pipelines.
AI technology has the ability to transform food images into recipes, allowing for personalized food recommendations, cultural customization, and automated cooking execution. This innovative method combines computer vision and natural language processing to generate comprehensive recipes from food images, bridging the gap between visual depictions of dishes and symbolic knowledge.
Improving content discovery on media platforms is crucial for user engagement. Implementing Retrieval Augmented Generation (RAG) with your own data using Knowledge Bases for Amazon Bedrock can solve semantic and user intent challenges, allowing you to create a movie chatbot that generates relevant answers based on retrieved context.
Amazon Titan Text Embeddings is a text embeddings model that converts natural language text into numerical representations for search, personalization, and clustering. It utilizes word embeddings algorithms and large language models to capture semantic relationships and improve downstream NLP tasks.
Automate detecting document tampering and fraud at scale using AWS AI and machine learning services for mortgage underwriting. Develop a deep learning-based computer vision model to detect and highlight forged images in mortgage underwriting using Amazon SageMaker.