​[[{“value”:” Large Language Models (LLMs) have become pivotal in artificial intelligence, powering a variety of applications from chatbots to content generation tools. However, their deployment at scale presents notable challenges. High computational costs, latency, and energy consumption often limit their wider use. Organizations face the… Read More »Snowflake AI Research Open-Sources SwiftKV: A Novel AI Approach that Reduces Inference Costs of Meta Llama LLMs up to 75% on Cortex AI Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Businesses today deal with a reality that is increasingly complex and volatile. Companies across retail, manufacturing, healthcare, and other sectors face pressing challenges in accurate planning and forecasting. Predicting future inventory needs, setting achievable strategic goals, and budgeting effectively involve grappling with ever-changing consumer… Read More »Solve forecasting challenges for the retail and CPG industry using Amazon SageMaker Canvas Aditya Pendyala AWS Machine Learning Blog

​[[{“value”:” Chat-based assistants have become an invaluable tool for providing automated customer service and support. This post builds on a previous post, Integrate QnABot on AWS with ServiceNow, and explores how to build an intelligent assistant using Amazon Lex, Amazon Bedrock Knowledge Bases, and a… Read More »Enabling generative AI self-service using Amazon Lex, Amazon Bedrock, and ServiceNow Marcelo Silva AWS Machine Learning Blog

​[[{“value”:” Have you ever admired how smartphone cameras isolate the main subject from the background, adding a subtle blur to the background based on depth? This “portrait mode” effect gives photographs a professional look by simulating shallow depth-of-field similar to DSLR cameras. In this tutorial,… Read More »Create Portrait Mode Effect with Segment Anything Model 2 (SAM2) Vineet Kumar Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Lexicon-based embeddings are one of the good alternatives to dense embeddings, yet they face numerous challenges that restrain their wider adoption. One key problem is tokenization redundancy, whereby subword tokenization breaks semantically equivalent tokens, causing inefficiencies and inconsistencies in embeddings. The other limitation of… Read More »Enhancing Lexicon-Based Text Embeddings with Large Language Models Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” TL;DR: Enterprise AI teams are discovering that purely agentic approaches (dynamically chaining LLM calls) don’t deliver the reliability needed for production systems. The prompt-and-pray model—where business logic lives entirely in prompts—creates systems that are unreliable, inefficient, and impossible to maintain at scale. A shift… Read More »Beyond “Prompt and Pray” Hugo Bowne-Anderson and Alan Nichol AI & ML – Radar

​Retrieval augmented generation (RAG) has become a vital technique in contemporary AI systems, allowing large language models (LLMs) to integrate external data in real time. Retrieval augmented generation (RAG) has become a vital technique in contemporary AI systems, allowing large language models (LLMs) to integrate external… Read More »5 Python Libraries to Build an Optimized RAG System Iván Palomares Carrascosa MachineLearningMastery.com

​[[{“value”:” Large Language Models (LLMs) have made significant progress in natural language processing, excelling in tasks like understanding, generation, and reasoning. However, challenges remain. Achieving robust reasoning often requires extensive supervised fine-tuning, which limits scalability and generalization. Furthermore, issues like poor readability and balancing computational… Read More »DeepSeek-AI Releases DeepSeek-R1-Zero and DeepSeek-R1: First-Generation Reasoning Models that Incentivize Reasoning Capability in LLMs via Reinforcement Learning Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” AI and ML are expanding at a remarkable rate, which is marked by the evolution of numerous specialized subdomains. Recently, two core branches that have become central in academic research and industrial applications are Generative AI and Predictive AI. While they share foundational principles… Read More »Generative AI versus Predictive AI Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models rely heavily on open datasets to train, which poses significant legal, technical, and ethical challenges in managing such datasets. There are uncertainties around the legal implications of using data based on varying copyright laws and changing regulations regarding safe usage. The… Read More »Step Towards Best Practices for Open Datasets for LLM Training Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost