Today we’re joined by Jay Emery, director of technical sales & architecture at Microsoft Azure. In our conversation with Jay, we discuss the challenges faced by organizations when building LLM-based applications, and we explore some of the techniques they are using to overcome them. We dive into the concerns around security, data privacy, cost management, and performance as well as the ability and effectiveness of prompting to achieve the desired results versus fine-tuning, and when each approach should be applied. We cover methods such as prompt tuning and prompt chaining, prompt variance, fine-tuning, and RAG to enhance LLM output along with ways to speed up inference performance such as choosing the right model, parallelization, and provisioned throughput units (PTUs). In addition to that, Jay also shared several intriguing use cases describing how businesses use tools like Azure Machine Learning prompt flow and Azure ML AI Studio to tailor LLMs to their unique needs and processes.
The complete show notes for this episode can be found at twimlai.com/go/657.
Ensuring LLM Safety for Production Applications with Shreya Rajpal - #647
What’s Next in LLM Reasoning? with Roland Memisevic - #646
Is ChatGPT Getting Worse? with James Zou - #645
Why Deep Networks and Brains Learn Similar Features with Sophia Sanborn - #644
Inverse Reinforcement Learning Without RL with Gokul Swamy - #643
Explainable AI for Biology and Medicine with Su-In Lee - #642
Transformers On Large-Scale Graphs with Bayan Bruss - #641
The Enterprise LLM Landscape with Atul Deo - #640
BloombergGPT - an LLM for Finance with David Rosenberg - #639
Are LLMs Good at Causal Reasoning? with Robert Osazuwa Ness - #638
Privacy vs Fairness in Computer Vision with Alice Xiang - #637
Unifying Vision and Language Models with Mohit Bansal - #636
Data Augmentation and Optimized Architectures for Computer Vision with Fatih Porikli - #635
Mojo: A Supercharged Python for AI with Chris Lattner - #634
Stable Diffusion and LLMs at the Edge with Jilei Hou - #633
Modeling Human Behavior with Generative Agents with Joon Sung Park - #632
Towards Improved Transfer Learning with Hugo Larochelle - #631
Language Modeling With State Space Models with Dan Fu - #630
Building Maps and Spatial Awareness in Blind AI Agents with Dhruv Batra - #629
AI Agents and Data Integration with GPT and LLaMa with Jerry Liu - #628
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