Subscribe • Previous Issues Beyond Nvidia: Exploring New Horizons in LLM Inference The landscape of large language models (LLMs) and Generative AI (GenAI) is undergoing rapid transformation, fueled by surging interest from executives and widespread interest across diverse sectors. Over one-third of CxOs have already embraced GenAI in their operations, and nearly half are actively preparing toContinue reading “LLM Inference Hardware: Emerging from Nvidia’s Shadow”
Author Archives: Ben Lorica
Mimicry or Transformation? Fair Use and Copyright Clash Over AI Training Methods
NYT Sues OpenAI: Copyright Infringement in the Age of AI As a technologist observing the intersection of AI and law, the New York Times lawsuit against OpenAI is a critical juncture. This isn’t merely a legal dispute; it symbolizes the delicate balance between innovation and regulation. My primary concern lies in the potential chilling effectContinue reading “Mimicry or Transformation? Fair Use and Copyright Clash Over AI Training Methods”
Unlocking the Power of Incentives: 2023 Book of the Year
In the fast-moving worlds of artificial intelligence, machine learning, and data science, truly understanding user behavior and motivation is the key that unlocks innovation and progress. This is why Gradient Flow is happy to name economist Uri Gneezy’s Mixed Signals our 2023 Book of the Year 🏆 Weaving together insights from psychology and economics, GneezyContinue reading “Unlocking the Power of Incentives: 2023 Book of the Year”
The AI Conversations That Shaped 2023
Subscribe • Previous Issues Looking Back at the AI Conversations That Defined 2023 To close out 2023, I thought it would be interesting to look back at some of the major AI-related topics that defined the year. Topping the list would be the surprise ousting and subsequent return of Sam Altman as CEO of OpenAI, which sparkedContinue reading “The AI Conversations That Shaped 2023”
Apple’s AI Leap: Bridging the Gap in On-Device Intelligence
Apple Tackles Memory and Computational Demands of Large Language Models. In a recent paper, Apple addresses the substantial computational and memory demands of large language models (LLMs), which present difficulties when attempting to operate them on devices with limited DRAM. These issues are pivotal due to: The prohibitive memory requirements for LLMs that surpass theContinue reading “Apple’s AI Leap: Bridging the Gap in On-Device Intelligence”
Financial Machine Learning
This cheat sheet provides an overview of applications of machine learning in finance, as described in the working paper “Financial Machine Learning” by Bryan T. Kelly and Dacheng Xiu. Return Forecasting Description: Using machine learning models like neural networks to predict future returns on financial assets and portfolios. Examples: Bridgewater Associates, Two Sigma, quant hedgeContinue reading “Financial Machine Learning”
Rails’ Enduring Principles: A Blueprint for AI Tool Creators
Nearly two decades after its debut, Ruby on Rails remains an enduring fixture in the dynamic landscape of web application frameworks. As an open-source framework crafted in Ruby and adhering to the model-view-controller paradigm, Rails has not merely endured; it has flourished, shaping a multitude of frameworks across diverse programming languages. Its groundbreaking methodologies continueContinue reading “Rails’ Enduring Principles: A Blueprint for AI Tool Creators”
From Rails to AI: Lessons in Open Source for the AI Era
Subscribe • Previous Issues Rails’ Enduring Principles: A Blueprint for AI Tool Creators Nearly two decades after its debut, Ruby on Rails remains an enduring fixture in the dynamic landscape of web application frameworks. As an open-source framework crafted in Ruby and adhering to the model-view-controller paradigm, Rails has not merely endured; it has flourished, shaping aContinue reading “From Rails to AI: Lessons in Open Source for the AI Era”
Applications of Generative AI
As highlighted in the slideshow above, companies across various industries are actively exploring the use cases and applications of generative AI (GenAI) and large language models (LLMs). Although still in the early stages of adoption, the level of experimentation and widespread recruitment for GenAI roles suggest a rising enthusiasm. Job postings provide concrete examples ofContinue reading “Applications of Generative AI”
Gemini Cheat Sheet: Google’s State-of-the-Art Multimodal Assistant Explained
This cheat sheet provides an overview of Gemini’s capabilities, development process, early reviews and potential future directions. What is Gemini? Gemini is a natively multimodal foundation model developed by Google that can understand and reason across multiple data modalities such as text, images, audio, video, and more in an integrated fashion. Unlike previous AI systemsContinue reading “Gemini Cheat Sheet: Google’s State-of-the-Art Multimodal Assistant Explained”