Building LLM-Based Applications with Azure OpenAI with Jay Emery - #657

Building LLM-Based Applications with Azure OpenAI with Jay Emery - #657

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.

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Bridging the Patient-Physician Gap with ML and Expert Systems w/ Xavier Amatriain - #316

Bridging the Patient-Physician Gap with ML and Expert Systems w/ Xavier Amatriain - #316

Today we’re joined by return guest Xavier Amatriain, Co-founder and CTO of Curai, whose goal is to make healthcare accessible and scaleable while bringing down costs. In our conversation, we touch on ...

11 Marras 201939min

What Does it Mean for a Machine to "Understand"? with Thomas Dietterich - #315

What Does it Mean for a Machine to "Understand"? with Thomas Dietterich - #315

Today we have the pleasure of being joined by Tom Dietterich, Distinguished Professor Emeritus at Oregon State University. Tom recently wrote a blog post titled "What does it mean for a machine to “un...

7 Marras 201938min

Scaling TensorFlow at LinkedIn with Jonathan Hung - #314

Scaling TensorFlow at LinkedIn with Jonathan Hung - #314

Today we’re joined by Jonathan Hung, Sr. Software Engineer at LinkedIn. Jonathan presented at TensorFlow world last week, titled Scaling TensorFlow at LinkedIn. In our conversation, we discuss their m...

4 Marras 201935min

Machine Learning at GitHub with Omoju Miller - #313

Machine Learning at GitHub with Omoju Miller - #313

Today we’re joined by Omoju Miller, a Sr. machine learning engineer at GitHub. In our conversation, we discuss: • Her dissertation, Hiphopathy, A Socio-Curricular Study of Introductory Computer Scien...

31 Loka 201943min

Using AI to Diagnose and Treat Neurological Disorders with Archana Venkataraman - #312

Using AI to Diagnose and Treat Neurological Disorders with Archana Venkataraman - #312

Today we’re joined by Archana Venkataraman, John C. Malone Assistant Professor of Electrical and Computer Engineering at Johns Hopkins University. Archana’s research at the Neural Systems Analysis Lab...

28 Loka 201946min

Deep Learning for Earthquake Aftershock Patterns with Phoebe DeVries & Brendan Meade - #311

Deep Learning for Earthquake Aftershock Patterns with Phoebe DeVries & Brendan Meade - #311

Today we are joined by Phoebe DeVries, Postdoctoral Fellow in the Department of Earth and Planetary Sciences at Harvard and Brendan Meade, Professor of Earth and Planetary Sciences at Harvard. Phoebe ...

25 Loka 201936min

Live from TWIMLcon! Operationalizing Responsible AI - #310

Live from TWIMLcon! Operationalizing Responsible AI - #310

An often forgotten about topic garnered high praise at TWIMLcon this month: operationalizing responsible and ethical AI. This important topic was combined with an impressive panel of speakers, includi...

22 Loka 201930min

Live from TWIMLcon! Scaling ML in the Traditional Enterprise - #309

Live from TWIMLcon! Scaling ML in the Traditional Enterprise - #309

Machine learning and AI is finding a place in the traditional enterprise - although the path to get there is different. In this episode, our panel analyzes the state and future of larger, more establi...

18 Loka 201933min

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