Subscribe • Previous Issues Building Trust: Enhancing AI with Private Information Retrieval As AI co-pilots, virtual assistants, and agents become integral to our daily routines, I’ve been reflecting on how these tools handle our most sensitive queries and requests. Whether it’s confidential medical consultations, private legal advice, or personalized mental health support, how can we trust thatContinue reading “Protecting User Privacy in the Age of Generative AI”
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Unlocking Business Value by Optimizing AI Workflows
Subscribe • Previous Issues Overcoming AI Scaling Challenges with Ray Compiled Graph By Ben Lorica and Dean Wampler. Imagine a startup developing AI-powered customer service chatbots, agentic workflows, or retrieval-augmented generation (RAG) applications. As their user base grows, they suddenly face skyrocketing costs and deteriorating response times. This scenario is playing out across industries as companies grappleContinue reading “Unlocking Business Value by Optimizing AI Workflows”
Structure Is All You Need
Subscribe • Previous Issues Enhancing AI Retrieval Systems with Structured Data I’ve previously written about GraphRAG, a form of Retrieval-Augmented Generation (RAG) that combines the power of vector embeddings with knowledge graphs (KG). While traditional RAG relies solely on vector-based similarity searches to retrieve relevant information, GraphRAG introduces knowledge graphs to represent and traverse relationships between entities,Continue reading “Structure Is All You Need”
Custom AI Platforms: The Features Driving Innovation
Subscribe • Previous Issues How Tech-Forward Organizations Build Custom AI Platforms: A Feature Breakdown In my previous article, “Why Digital-First Companies Are Building Their Own AI Platforms”, I explored why many tech-forward companies are opting to build their own AI platforms rather than relying on off-the-shelf solutions. The piece sparked considerable interest, with readers eager to exploreContinue reading “Custom AI Platforms: The Features Driving Innovation”
Rethinking Analyst Roles in the Age of Generative AI
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”
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”
Why Digital-First Companies Are Building Their Own AI Platforms
Subscribe • Previous Issues 10 Advantages of Custom AI Platforms Despite the abundance of AI services & platforms in the market, many tech-forward companies are taking a different route: building their own custom AI platforms. This raises a crucial question: why craft a bespoke AI platform when so many options already exist? The classic “buy vs. build”Continue reading “Why Digital-First Companies Are Building Their Own AI Platforms”
Lessons from the Frontlines of AI Training
Subscribe • Previous Issues Inside the Data Strategies of Top AI Labs In the AI arms race, data remains the ultimate fuel, and the hunger for it is insatiable. Indeed, as someone who monitors this space closely, I can tell you that scaling laws continue to be the North Star for top AI labs. The equation isContinue reading “Lessons from the Frontlines of AI Training”
What is an AI Alignment Platform?
Subscribe • Previous Issues A Unified Approach to Managing AI Risks By Andrew Burt, Mike Schiller, & Ben Lorica. Artificial intelligence has a problem. In the last decade, companies have begun to deploy AI widely and have come to rely on a host of different tools and infrastructure. There are tools for data collection, cleaning, and storage.Continue reading “What is an AI Alignment Platform?”
Why Your Generative AI Projects Are Failing
Subscribe • Previous Issues Generative AI: Navigating the Challenges of Enterprise Adoption As we reach the halfway mark of 2024, it’s a prime opportunity to evaluate how companies are progressing in their efforts to leverage the power of generative AI. To mark this occasion, I’ve combed through numerous surveys and spoken with people from several companies acrossContinue reading “Why Your Generative AI Projects Are Failing”