Subscribe • Previous Issues Function Calling AI: Transforming Text Models into Dynamic Agents Function Calling, particularly relevant in large language models (LLMs), is a transformative feature that significantly broadens the capabilities of these frontier models. This feature allows AI models to go beyond basic text generation and language understanding by interacting with and executing external functions. AtContinue reading “Expanding AI Horizons: The Rise of Function Calling in LLMs”
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LLM Inference Hardware: Emerging from Nvidia’s Shadow
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”
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”
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”
Securing AI: Addressing the Emerging Threat of Prompt Injection
Subscribe • Previous Issues Mitigating Prompt Injection Risks to Secure Generative AI Apps I’m optimistic about the potential for generative AI, particularly its benefits for companies and knowledge workers. However, in the rapidly evolving landscape of AI, understanding and addressing vulnerabilities like prompt injection is crucial for the safe integration of these technologies into our digital ecosystem. Continue reading “Securing AI: Addressing the Emerging Threat of Prompt Injection”
Generative AI 2023: Why This Year Marks a Major Turning Point
Subscribe • Previous Issues The Promise and Progress of Generative AI One year after ChatGPT’s launch, generative AI is gaining mainstream traction. Large language models (LLMs) like GPT-4 are being adopted across diverse real-world applications, from chatbots to computer programming to medicine and law. The speed of adoption has been remarkable – shortly after the release ofContinue reading “Generative AI 2023: Why This Year Marks a Major Turning Point”
Charting the Graphical Roadmap to Smarter AI
Subscribe • Previous Issues Boosting LLMs with External Knowledge: The Case for Knowledge Graphs When we wrote our post on Graph Intelligence in early 2022, our goal was to highlight techniques for deriving insights about relationships and connections from structured data using graph analytics and machine learning. We focused mainly on business intelligence and machine learning applications,Continue reading “Charting the Graphical Roadmap to Smarter AI”
Best Practices in Retrieval Augmented Generation
Subscribe • Previous Issues Techniques, Challenges, and Future of Augmented Language Models After attending several conferences in the past month, it’s evident that Retrieval Augmented Generation (RAG) has emerged as one of the most popular techniques in AI over the past year, widely adopted by many AI teams. RAG refers to the process of supplementing a largeContinue reading “Best Practices in Retrieval Augmented Generation”
A Comprehensive Approach to Using LLMs
Subscribe • Previous Issues From Proprietary to Open Source to Fleets of Custom LLMs Large language models (LLMs) have proven to be powerful tools for me over the last year. LLMs can be used to build a wide range of applications, from chatbots and content generators to coding assistants and question answering systems. After discussing the journeyContinue reading “A Comprehensive Approach to Using LLMs”
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”