Subscribe • Previous Issues The Future of Analysts: Orchestrating AI for Strategic Insights I’ve written a couple of posts examining the significant challenges confronting startups in the AI landscape, particularly those involved in training foundation models like Large Language Models (LLMs). In one post, I highlighted Meta’s release of the world’s largest “open weights” foundation model—a notableContinue reading “Rethinking Analyst Roles in the Age of Generative AI”
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The Case Against SB 1047
California SB 1047 (California Safe and Secure Innovation for Frontier Artificial Intelligence Models Act) is a proposed California state bill that aims to regulate the development and deployment of large, advanced AI models by imposing safety and testing requirements on developers. The bill is now in the hands of Governor Gavin Newsom, who will eitherContinue reading “The Case Against SB 1047”
Pipe SQL: Google’s Answer to SQL’s Limitations
As a long-time SQL user, I still turn to it whenever I need to work with tabular data, preferring it over dataframe libraries like Pandas. SQL’s syntax is easier to recall and aligns well with set theory concepts, making it intuitive for those familiar with basic mathematical logic. The presence of an optimizer further enhancesContinue reading “Pipe SQL: Google’s Answer to SQL’s Limitations”
Cerebras Inference: First Impressions
As someone who has closely followed the AI hardware landscape for years, I’ve long been particularly bullish on Cerebras among the startups building specialized AI chips. Their founding team, composed of chip industry veterans with a proven track record of delivering cutting-edge hardware, has consistently impressed me. I’ve had the pleasure of seeing them keynoteContinue reading “Cerebras Inference: First Impressions”
GraphRAG Goes Medical: Introducing MedGraphRAG
GraphRAG represents an emerging set of techniques that merge knowledge graphs with large language models to enhance retrieval-augmented generation. However, the absence of standardization has led to a variety of implementations, each with its own unique strengths and challenges. In a previous post, I explored a system developed by Nvidia and Blackrock that integrates RAG/VectorRAG,Continue reading “GraphRAG Goes Medical: Introducing MedGraphRAG”
Unpacking Model Collaboration: Ensembles, Routers, and Merging
Generative AI models are constantly evolving, and so are the strategies we use to improve their performance. Retrieval-Augmented Generation (RAG) and its advanced iterations, such as GraphRAG and Mixture of Memory Experts, represent approaches that incorporate external knowledge to enhance model capabilities. Combining the strengths of different models has proven to be highly effective. ApproachesContinue reading “Unpacking Model Collaboration: Ensembles, Routers, and Merging”
Boosting LLMs: The Power of Model Collaboration
Subscribe • Previous Issues Unpacking Model Collaboration: Ensembles, Routers, and Merging Generative AI models are constantly evolving, and so are the strategies we use to improve their performance. Retrieval-Augmented Generation (RAG) and its advanced iterations, such as GraphRAG and Mixture of Memory Experts, represent approaches that incorporate external knowledge to enhance model capabilities. Combining the strengths ofContinue reading “Boosting LLMs: The Power of Model Collaboration”
Advancing RAG: Best Practices and Evaluation Frameworks
As I’ve noted in previous posts, RAG and GraphRAG have become popular techniques for many AI teams, and for good reason. They enhance large language models (LLMs) by connecting them with external knowledge. This grounding in factual information is key for improving accuracy and reducing hallucinations. Personally, I’ve found RAG and its variants to beContinue reading “Advancing RAG: Best Practices and Evaluation Frameworks”
AI and Technology in the 2024 DNC Platform
Building on the discussions from my previous article analyzing the Republican platform’s stance on Crypto and AI, the Democratic National Committee (DNC) 2024 platform presents a distinctly contrasting vision for AI development and regulation. In terms of scope and depth, the 2024 DNC platform comes in at a comprehensive 41,000+ words, while the 2024 RNCContinue reading “AI and Technology in the 2024 DNC Platform”
The Reality Check: Why AI Projects Stumble and How to Succeed
A new survey from RAND sheds light on the root causes of failure for AI projects and offers insights into how they can succeed. AI is often touted as the next frontier in technology, promising to revolutionize industries and drive unprecedented efficiencies. Yet, the stark reality is that many AI projects fail. With the rapidContinue reading “The Reality Check: Why AI Projects Stumble and How to Succeed”