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”
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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!”
The Future of Prompt Engineering: Getting The Most Out of LLMs
Subscribe • Previous Issues What I Talk About When I Talk About Prompting In recent months, my approach to constructing NLP pipelines and applications has shifted from integrating various libraries to using large language models (LLMs) via their APIs. This transition has resulted in a slight increase in latency and cost (due to the replacement of freeContinue reading “The Future of Prompt Engineering: Getting The Most Out of LLMs”
Unleashing LLMs in Cybersecurity: A Playbook for All Industries
Subscribe • Previous Issues Large Language Models in Cybersecurity Despite the fact that large language models (LLMs) are still in their infancy, organizations across all industries and domains are already showing considerable interest in them. I thought that it would be useful to describe how LLMs will be implemented within companies by focusing on cybersecurity, a specializedContinue reading “Unleashing LLMs in Cybersecurity: A Playbook for All Industries”
Building LLM-powered Apps: What You Need to Know
Subscribe • Previous Issues Building LLM-powered Applications The past few weeks have been exciting for developers interested in deploying AI-powered applications. The field is evolving quickly, and it is now possible to build AI-powered applications without having to spend months or years learning the ins and outs of machine learning. This opens up a whole new worldContinue reading “Building LLM-powered Apps: What You Need to Know”
Alignment in AI: Key to Safe and Beneficial Systems
Subscribe • Previous Issues Get Started on Aligning AI Alignment is a topic that has garnered significant attention and research in the field of AI. It is a critical challenge in AI and machine learning that seeks to ensure that machines behave in ways that are beneficial. More precisely, alignment refers to the idea that an AIContinue reading “Alignment in AI: Key to Safe and Beneficial Systems”
Maximizing the Potential of Large Language Models
Subscribe • Previous Issues The LLM Three-Pronged Strategy: Tune, Prompt, Reward As language models become increasingly common, it becomes crucial to employ a broad set of strategies and tools in order to fully unlock their potential. Foremost among these strategies is prompt engineering, which involves the careful selection and arrangement of words within a prompt or queryContinue reading “Maximizing the Potential of Large Language Models”