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Navigating LLM Deployment: Tips, Tricks, and Techniques
Meryem Arik discusses some of the best practices in model optimization, serving and monitoring - with practical tips and real case-studies.
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Manipulating the Machine: Prompt Injections and Countermeasures
Georg Dresler discusses various methods to perform prompt injection to extract system prompts and documents used by GPTs, and ways to integrate countermeasures to protect against stealing information.
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Poetry4Shellz – Avoiding Limerick Based Exploitation and Safely Using AI in Your Apps
Rich Smith provides a case study of a real world LLM based app that is vulnerable to a variety of attack vectors that illustrate the challenges to account for when integrating today's LLM technologies
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Mind Your Language Models: an Approach to Architecting Intelligent Systems
Nischal HP discusses the intricacies of designing and implementing intelligent systems powered by LLMs, drawing upon practical insights gained from real-world deployments.
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Generative Search: Practical Advice for Retrieval Augmented Generation (RAG)
Sam Partee discusses Vector embeddings in LLMs, a tool capable of capturing the essence of unstructured data used by LLMs to gain access to a wealth of contextually relevant knowledge.
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Defensible Moats: Unlocking Enterprise Value with Large Language Models
Nischal HP discusses risk mitigation, environmental, social, and governance (ESG) framework implementation to achieve sustainability goals, strategic procurement, spend analytics, data compliance.
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When AIOps Meets MLOps: What it Takes to Deploy ML Models at Scale
Ghida Ibrahim introduces the concept of AIOps referring to using AI and data-driven tooling to provision, manage and scale distributed IT infra.
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Reach Next-Level Autonomy with LLM-Based AI Agents
Tingyi Li discusses the AI Agent, exploring how it extends the frontiers of Generative AI applications and leads to next-level autonomy in combination with enterprise data.
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Retrieval-Augmented Generation (RAG) Patterns and Best Practices
Jay Alammar discusses the common schematics of RAG systems and tips on how to improve them.
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Large Language Models for Code: Exploring the Landscape, Opportunities, and Challenges
Loubna Ben Allal discusses Large Language Models (LLMs), exploring the current developments of these models, how they are trained, and how they can be leveraged with custom codebases.
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A Bicycle for the (AI) Mind: GPT-4 + Tools
Sherwin Wu and Atty Eleti discuss how to use the OpenAI API to integrate large language models into your application, and extend GPT’s capabilities by connecting it to the external world via APIs.
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