Conversations with the people building AI
You can’t build robust systems with inconsistent, unstructured text output from LLMs. Moreover, LLM integrations scare corporate lawyers, finance departments, and security professionals due to hallucinations, cost, lack of compliance (e.g., HIPAA), leaked IP/PII, and “injection” vulnerabilities. In this episode, Chris…
50 MinutesPractical AI
Today we’re joined by Hugo Larochelle, a research scientist at Google Deepmind. In our conversation with Hugo, we discuss his work on transfer learning, understanding the capabilities of deep learning models, and creating the Transactions on Machine Learning Research journal. We explore the use of large language…
39 MinutesThe TWIML AI Podcast
Large Language Models (LLMs) continue to amaze us with their capabilities. However, the utilization of LLMs in production AI applications requires the integration of private data. Join us as we have a captivating conversation with Jerry Liu from LlamaIndex, where he provides valuable insights into the process of data…
45 MinutesPractical AI
Today we’re joined by Dan Fu, a PhD student at Stanford University. In our conversation with Dan, we discuss the limitations of state space models in language modeling and the search for alternative building blocks that can help increase context length without being computationally infeasible. Dan walks us through the…
28 MinutesThe TWIML AI Podcast
At the recent ODSC East conference, Daniel got a chance to sit down with Erin Mikail Staples to discuss the process of gathering human feedback and creating an instruction tuned Large Language Models (LLM). They also chatted about the importance of open data and practical tooling for data annotation and fine-tuning.…
27 MinutesPractical AI
Today we continue our coverage of ICLR 2023 joined by Dhruv Batra, an associate professor at Georgia Tech and research director of the Fundamental AI Research (FAIR) team at META. In our conversation, we discuss Dhruv’s work on the paper Emergence of Maps in the Memories of Blind Navigation Agents, which won an…
43 MinutesThe TWIML AI Podcast
There are a ton of problems around building LLM apps in production and the last mile of that problem. Travis Fischer, builder of open AI projects like @ChatGPTBot, joins us to talk through these problems (and how to overcome them). He helps us understand the hierarchy of complexity from simple prompting to…
39 MinutesPractical AI
Today we’re joined by Jerry Liu, co-founder and CEO of Llama Index. In our conversation with Jerry, we explore the creation of Llama Index, a centralized interface to connect your external data with the latest large language models. We discuss the challenges of adding private data to language models and how Llama…
41 MinutesThe TWIML AI Podcast
Model sizes are crazy these days with billions and billions of parameters. As Mark Kurtz explains in this episode, this makes inference slow and expensive despite the fact that up to 90%+ of the parameters don’t influence the outputs at all. Mark helps us understand all of the practicalities and progress that is being…
38 MinutesPractical AI
Today we kick off our coverage of the 2023 ICLR conference joined by Christos Louizos, an ML researcher at Qualcomm Technologies. In our conversation with Christos, we explore his paper Hyperparameter Optimization through Neural Network Partitioning and a few of his colleague's works from the conference. We discuss…
33 MinutesThe TWIML AI Podcast
With all the LLM hype, it’s worth remembering that enterprise stakeholders want answers to “why” questions. Enter causal inference. Paul Hünermund has been doing research and writing on this topic for some time and joins us to introduce the topic. He also shares some relevant trends and some tips for getting started…
42 MinutesPractical AI
Today we’re joined by Marti Hearst, Professor at UC Berkeley. In our conversation with Marti, we explore the intricacies of AI language models and their usefulness in improving efficiency but also their potential for spreading misinformation. Marti expresses skepticism about whether these models truly have cognition…
38 MinutesThe TWIML AI Podcast
