​[[{“value”:” This post was co-written with Jerry Liu from LlamaIndex. Retrieval Augmented Generation (RAG) has emerged as a powerful technique for enhancing the capabilities of large language models (LLMs). By combining the vast knowledge stored in external data sources with the generative power of LLMs,… Read More »Build powerful RAG pipelines with LlamaIndex and Amazon Bedrock Shreyas Subramanian AWS Machine Learning Blog

​[[{“value”:” As generative artificial intelligence (AI) continues to revolutionize every industry, the importance of effective prompt optimization through prompt engineering techniques has become key to efficiently balancing the quality of outputs, response time, and costs. Prompt engineering refers to the practice of crafting and optimizing… Read More »Evaluating prompts at scale with Prompt Management and Prompt Flows for Amazon Bedrock Antonio Rodriguez AWS Machine Learning Blog

​[[{“value”:” Gregor Betz from Logikon AI, KIT introduces Guided Reasoning. A system with more than one agent is a Guided Reasoning system if one agent, called the guide, mostly works with the other agents to improve their Reasoning. A multi-agent system with a guide agent… Read More »Guided Reasoning: A New Approach to Improving Multi-Agent System Intelligence Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​ Why we are building Tailor Information overload is the biggest issue of our time. We are building Tailor to fix that. I’ve talked with hundreds of folks from different backgrounds and cultures. I asked them how they consume news and information. Everyone told me some version… Read More »Fixing information overload Vittorio Banfi Chatbots Life – Medium

​ 3 text-to-speech examples I’ve randomly encountered online background photo courtesy of BandLab on Unsplash Long before the rise of Bev Standing’s iconic text-to-speech voice all over TikTok and the internet, we’ve heard computers talk. Most people in this day and age have experienced the phenomenon… Read More »Everyday Speech: Examples of TTS out in the wild elaineinthebay Chatbots Life – Medium

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​[[{“value”:” Large Language Models (LLMs) have demonstrated great performance in Natural Language Processing (NLP) applications. However, they have high computational costs when fine-tuning them, which can lead to incorrect information being generated, i.e., hallucinations. Two viable strategies have been established to solve these problems: parameter-efficient… Read More »Enhancing Fact-Checking with LoraMap: A Neuroscience-Inspired Approach to Efficient LoRA Integration Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Machine learning has revolutionized various fields, offering powerful tools for data analysis and predictive modeling. Central to these models’ success is hyperparameter optimization (HPO), where the parameters that govern the learning process are tuned to achieve the best possible performance. HPO involves selecting hyperparameter… Read More »This AI Paper from Cornell and Brown University Introduces Epistemic Hyperparameter Optimization: A Defended Random Search Approach to Combat Hyperparameter Deception Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Hypergraphs, which extend traditional graphs by allowing hyperedges to connect multiple nodes, offer a richer representation of complex relationships in fields like social networks, bioinformatics, and recommender systems. Despite their versatility, generating realistic hypergraphs is challenging due to their complexity and the need for… Read More »HYGENE: A Diffusion-Based Deep Learning Approach for Hypergraph Generation and Modeling Sana Hassan Artificial Intelligence Category – MarkTechPost