7 Must-Have Features for Crafting Custom LLMs

Subscribe • Previous Issues Keys to a Robust Fleet of Custom LLMs The rising popularity of Generative AI is driving companies to adopt custom large language models (LLMs) to address concerns about intellectual property, and data security and privacy. Custom LLMs can safeguard proprietary data while also meeting specific needs, delivering enhanced performance and accuracy for improvedContinue reading “7 Must-Have Features for Crafting Custom LLMs”

Unlocking the Future of Efficient AI Model Deployment

Subscribe • Previous Issues Ivy: Streamlining AI Model Deployment & Development In an age where data drives decision-making and automation, deep learning (DL) has become a cornerstone of many industries, influencing everything from healthcare to finance. DL has become pervasive with applications in a wide range of fields, including computer vision, natural language processing, voice applications, andContinue reading “Unlocking the Future of Efficient AI Model Deployment”

Generative AI in Finance: Opportunities & Challenges

Subscribe • Previous Issues The Financial Services Sector’s March into Generative AI During my time as a quant at a hedge fund, I was struck by the asset management industry’s willingness to adopt cutting-edge technologies. Hedge funds are constantly looking for new ways to gain an edge in the increasingly competitive financial markets. They are quick toContinue reading “Generative AI in Finance: Opportunities & Challenges”

Lessons from the FTC’s Probe into OpenAI

Subscribe • Previous Issues What We Can Learn from the FTC’s OpenAI Probe The recent investigation launched by the U.S. Federal Trade Commission (FTC) into OpenAI is a sign of the growing regulatory scrutiny of AI technology and the potential risks it poses. As we build AI models and applications, we must proactively consider the questions listedContinue reading “Lessons from the FTC’s Probe into OpenAI”

Enterprise Generative AI Unfolded

Subscribe • Previous Issues Ten Keys to Accelerating Enterprise Adoption of LLMs By reviewing job postings in the US and analyzing recent reports on enterprise Large Language Models (LLMs) and Generative AI (GAI), I sought to understand the most critical enterprise requirements for these technologies. From this analysis emerged the following pillars, each representing a set ofContinue reading “Enterprise Generative AI Unfolded”

The New Era of Efficient LLM Deployment

Subscribe • Previous Issues Navigating the Intricacies of LLM Inference & Serving According to a recent Stack Overflow survey, 70% of developers use AI tools or plan to do so within the next few months, illustrating the pervasive sentiment of AI optimism within the tech community. The beneficial impacts of these technologies are evident: one-third of theseContinue reading “The New Era of Efficient LLM Deployment”

Decoding Apple’s AI Ambitions

Subscribe • Previous Issues Deciphering Apple’s AI Strategy and Priorities As the world’s most valuable company, Apple’s priority areas and investment strategies draw attention globally.  Curious about the company’s moves in AI, I recently analyzed online job postings from Apple in the US, Europe, and APAC, which I extracted in mid-June 2023. These postings specifically mention [AIContinue reading “Decoding Apple’s AI Ambitions”

Get the Most Out of Your Custom LLMs

Subscribe • Previous Issues Build better Large Language Models with WeightWatcher Companies are beginning to harness Custom Large Language Models (LLMs) and Custom Foundation Models due to their superior performance in specialized fields and applications. These models hold the potential to elevate accuracy, bolster data privacy and security, and deliver a competitive edge. For instance, domain-specific LLMsContinue reading “Get the Most Out of Your Custom LLMs”

What You Need to Know About GPT-4 and PaLM 2

Subscribe • Previous Issues Behind the Curtain: Unpacking GPT-4 and PaLM 2 As AI technology continues to evolve, we are witnessing a shift in the openness of systems. Leading-edge AI models, such as GPT-4 (OpenAI) and PaLM 2 (Google), are trending towards being less open than their predecessors. This shift is being driven by a number ofContinue reading “What You Need to Know About GPT-4 and PaLM 2”

The AI Conference in SF: The Future of AI is Now!

Subscribe • Previous Issues The AI Conference: Bridge the gap between research and practice I am elated to announce my role as Program Chair for The AI Conference, a unique event designed to bridge the gap between research and practical applications. While I have continued to serve as co-chair and program committee member for numerous AI andContinue reading “The AI Conference in SF: The Future of AI is Now!”