​[[{“value”:” Retrieval Augmented Generation (RAG) is a state-of-the-art approach to building question answering systems that combines the strengths of retrieval and foundation models (FMs). RAG models first retrieve relevant information from a large corpus of text and then use a FM to synthesize an answer… Read More »Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and AWS CloudFormation Sandeep Singh AWS Machine Learning Blog

​[[{“value”:” In recent years, we have seen a big increase in the size of large language models (LLMs) used to solve natural language processing (NLP) tasks such as question answering and text summarization. Larger models with more parameters, which are in the order of hundreds… Read More »Faster LLMs with speculative decoding and AWS Inferentia2 Syl Taylor AWS Machine Learning Blog

​[[{“value”:” Information retrieval systems have powered the information age through their ability to crawl and sift through massive amounts of data and quickly return accurate and relevant results. These systems, such as search engines and databases, typically work by indexing on keywords and fields contained… Read More »Catalog, query, and search audio programs with Amazon Transcribe and Knowledge Bases for Amazon Bedrock Nolan Chen AWS Machine Learning Blog

​ The clock strikes 3 AM. A potential buyer is browsing your website, eager to make a purchase, but they have a question. Your support team is fast asleep, and the sale slips away. Sound familiar? Today’s consumers expect instant gratification, and companies are feeling… Read More »Can Chatbots Reduce Business Costs Dramatically? Expert Opinion and Insights Master Of Code Global Chatbots Life – Medium

​[[{“value”:” Large Language Models (LLMs) have revolutionized problem-solving in machine learning, shifting the paradigm from traditional end-to-end training to utilizing pretrained models with carefully crafted prompts. This transition presents a fascinating dichotomy in optimization approaches. Conventional methods involve training neural networks from scratch using gradient… Read More »This AI Paper Introduces a Verbalized Way to Perform Machine Learning and Conducts Several Case Studies on Regression and Classification Tasks Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Home Table of Contents Exploring Probabilistic Search: The Power of the BM25 Algorithm Probabilities in Search: The Probability Ranking Principle (PRP) The Probability Ranking Principle (PRP) Using Matching Score to Compute Relevance The Okapi BM25 Algorithm The BM25 Score Connection between BM25 Score and… Read More »Exploring Probabilistic Search: The Power of the BM25 Algorithm Puneet Mangla PyImageSearch

​Food security, healthcare and exploring the cosmos are among the ways students of a new pan-African Master’s program aspire to apply AI Food security, healthcare and exploring the cosmos are among the ways students of a new pan-African Master’s program aspire to apply AI  Read More  

​[[{“value”:” Reinforcement learning (RL) is a specialized branch of artificial intelligence that trains agents to make sequential decisions by rewarding them for performing desirable actions. This technique is extensively applied in robotics, gaming, and autonomous systems, allowing machines to develop complex behaviors through trial and… Read More »ARCLE: A Reinforcement Learning Environment for Abstract Reasoning Challenges Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Ensuring the safety of increasingly powerful AI systems is a critical concern. Current AI safety research aims to address emerging and future risks by developing benchmarks that measure various safety properties, such as fairness, reliability, and robustness. However, the field remains poorly defined, with… Read More »AI Safety Benchmarks May Not Ensure True Safety: This AI Paper Reveals the Hidden Risks of Safetywashing Aswin Ak Artificial Intelligence Category – MarkTechPost