Tuhin, specializes in model deployment and monitoring at any scale, joins the show to talk about self-hosting open access models. They discuss trends in tooling and usage of open access models, common use cases for integrating self-hosted models, and the influence of generative AI on the ecosystem.

Nathaniel Simard, creator of burn, joins the podcast to discuss Rust as a deep learning framework. They explore Rust's capabilities, motivations behind using it, challenges in supporting deep learning, working with GPU libraries, importing models & training tools. They discuss the potential of Burn and suggest starting with the burn.dev website for more information.

Emily Freeman and James Q Quick discuss the impact of AI on developers, including the need to embrace AI and learn its strengths and limitations. They also explore the challenges and benefits of adopting AI in different contexts and delve into the implications of a new technology for controlling website copy. The speakers reflect on the definitions and future of open source, the challenges of proving AI-generated code, and the under-hyped aspects of AI. They emphasize the uncertain future of AI and the need for responsible usage, as well as the potential of AI in addressing coding problems.

This episode of the podcast explores the lifecycle of generative AI models, discussing model optimization, serving, and deployment. It also highlights the revolution in microelectronics, the availability of open access models on Hugging Face, and the process of selecting and running a model for deployment. The speakers emphasize the importance of code reuse and provide tips for exploring and deploying generative models.

Dominik Klotz from askui joins Daniel and Chris to discuss the automation of UI, and how AI empowers them to automate any use case on any operating system. Along the way, the trio explore various approaches and the integration of generative AI, large language models, and computer vision. Join the discussionChangelog++ members save 6 minutes on this episode because they made the ads disappear. Join today!Sponsors:Statsig – Build faster with confidence. Startups to Fortune 500s rely on Statsig to make data-driven decisions. Ship smarter and faster with the unified platform for feature flags, experimentation, and analytics. Our listeners get free white-glove onboarding, migration support, and 5 million free events per month. Changelog News – A podcast+newsletter combo that’s brief, entertaining & always on-point. Subscribe today. Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs. Featuring:Dominik Klotz – GitHub, LinkedInChris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XShow Notes: askui.com askui on GitHub askui on LinkedIn askui on Twitter/X Something missing or broken? PRs welcome!

Demetrios from the MLOps Community discusses fine-tuning vs retrieval augmented generation, OpenAI Enterprise, MLOps Community LLM survey results, and orchestration and evaluation of generative AI workloads. They also talk about recent events in the MLOps community, the shift towards practical implementations of generative AI, misconceptions in fine-tuning language models, the correlation between OpenAI and startup size, the importance of diverse speakers at conferences, and upcoming events and sponsors.

Mike, an AI code optimization expert, joins the hosts to discuss practical code optimizations using AI "translation" of slow to fast code. They explore the use of Language Model Driven Learning (LLMs) and Meta's Code Llama for automating code optimization. They also discuss the state of code generation models in open source and closed source ecosystems, dealing with code hallucinations, and exciting advancements in AI-driven developer tools.

The podcast explores the new AI app stack, including model 'middleware' for caching and control and app orchestration. They discuss the importance of understanding the ecosystem and tooling around large language models. They also explore AI playgrounds and the use of vector databases and embeddings. They break down the components of the new generative AI stack and emphasize the importance of AI engineering. The hosts reflect on their exploration of the infrastructure components and the value of the conversation.

In this Fully Connected episode, Daniel and Chris kick it off by noting that Stability AI released their SDXL 1.0 LLM! They discuss its virtues, and then dive into a discussion regarding how the United States, European Union, and other entities are approaching governance of AI through new laws and legal frameworks. In particular, they review the White House’s approach, noting the potential for unexpected consequences. Join the discussionChangelog++ members save 2 minutes on this episode because they made the ads disappear. Join today!Sponsors:Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs. Typesense – Lightning fast, globally distributed Search-as-a-Service that runs in memory. You literally can’t get any faster! Changelog News – A podcast+newsletter combo that’s brief, entertaining & always on-point. Subscribe today. Featuring:Chris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XShow Notes: Announcing SDXL 1.0 GitHub, Hugging Face, urge EU to relax open-source AI rules White House: Blueprint for an AI Bill of Rights LEARNING RESOURCE! Patterns for Building LLM-based Systems & Products Something missing or broken? PRs welcome!

There’s so much talk (and hype) these days about vector databases. We thought it would be timely and practical to have someone on the show that has been hands on with the various options and actually tried to build applications leveraging vector search. Prashanth Rao is a real practitioner that has spent and huge amount of time exploring the expanding set of vector database offerings. After introducing vector database and giving us a mental model of how they fit in with other datastores, Prashanth digs into the trade offs as related to indices, hosting options, embedding vs. query optimization, and more. Join the discussionChangelog++ members save 3 minutes on this episode because they made the ads disappear. Join today!Sponsors:Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs. Typesense – Lightning fast, globally distributed Search-as-a-Service that runs in memory. You literally can’t get any faster! Changelog News – A podcast+newsletter combo that’s brief, entertaining & always on-point. Subscribe today. Featuring:Prashanth Rao – Website, GitHub, LinkedIn, XChris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XShow Notes:Vector databases blog posts from Prashanth: (Part 1): What makes each one different? (Part 2): Understanding their internals (Part 3): Not all indexes are created equal Something missing or broken? PRs welcome!