The podcast by and for AI Engineers! In 2025, over 10 million readers and listeners came to Latent Space to hear about news, papers and interviews in Software 3.0. We cover Foundation Models changing every domain in Code Generation, Multimodality, AI Agents, GPU Infra and more, directly from the founders, builders, and thinkers involved in pushing the cutting edge. Striving to give you both the definitive take on the Current Thing down to the first introduction to the tech you'll be using in the next 3 months! We break news and exclusive interviews from OpenAI, Anthropic, Gemini, Meta (Soumith Chintala), Sierra (Bret Taylor), tiny (George Hotz), Databricks/MosaicML (Jon Frankle), Modular (Chris Lattner), Answer.ai (Jeremy Howard), et al. Full show notes always on https://latent.space Sponsorship and business inquiries: [email protected] www.latent.space
This podcast episode dives deep into the world of Together AI, a company dedicated to creating an open and independent AI platform. It explores an array of topics, including the importance of open source and decentralization, the concept of data resampling, data quality, benchmarking challenges, advancements in AI tech...
This podcast episode explores Retool's journey, from its humble beginnings to its current position as a leading provider of low-code tools for developers. Along the way, the founders discuss the challenges and opportunities of building a successful startup, the importance of staying true to their values in lieu of soci...
This podcast episode delves into the key trends and challenges in the AI industry, including the data belligerent war, the ongoing GPU inference war, the rise of serverless VectorDBs, the emergence of new architectures such as state space models and mixture of experts, the evolution of multi-modality in AI, the battle ...
This podcast episode delves into the multimodality in AI, particularly Hugging Face's research and contributions. Experts from Hugging Face discuss the company's research on multimodality, the development of tools like the Transformers library and the Datasets library, and the challenges and advancements in multimodal ...
Reinforcement Learning from Human Feedback (RLHF) is a technique that combines reinforcement learning with human feedback to train language models. It involves using human preferences to guide the training process, with various challenges, including data collection, reward optimization, and preference aggregation. RLHF...
This podcast episode features Steve Ruiz, the creator of TealDraw, a versatile digital drawing tool, and Adam, the creator of Teal Drawing, a tool that allows users to create interactive prototypes using natural language prompts. The podcast discusses the origin, evolution, and applications of TealDraw, as well as the ...
The 2023 NeurIPS conference brought together researchers and experts to discuss the latest advancements in AI, including the focus on utilizing LLMs, the significance of multimodal models, and the need for open-source options. Topics at the conference included using synthetic data for LLM evaluation, KV caching optimiz...
This podcast episode covers various topics in natural language processing and machine learning, including word2vec, reinforcement learning, data filtering, multimodal models, visual reasoning, tree search algorithms, and more. It also examines recent breakthroughs, such as Toolformer, Voyager, and LLMs, as well as ongo...
This podcast episode explores various topics related to AI and computing, including the interaction of data analytics and AI, the concept of streaming browsers, the limitations and potential of AI models, the challenges of building unified models for improving images, the world of AI graphics models and styles, the cha...
This podcast episode features discussions on various topics related to AI coding agents and tools. The speakers introduce Sourcegraph, a coding intelligence startup, and its motivation for creating efficient code search and intelligence tools. They emphasize the importance of code search in enhancing productivity and n...
This podcast episode discusses various topics related to the open source AI community. It covers presentations made by companies and industry experts, the personal journey of Axolotl in fine-tuning language models, the concept of fine-tuning and its importance, challenges in evaluating AI models, the significance of op...
This podcast episode covers various topics related to AI integration in different industries. It addresses challenges and experiences of being acquired from the perspective of the data team, the significance of integrating AI into platforms like Hex, the use of GPT-4 in AI engineering, the value of general models in AI...
This podcast episode delves into a wide range of topics including infrastructure, GPU capacity, open source, TPUs, networking, alternative hardware, Nvidia's dominance, supercomputing, the semiconductor supply chain, and writing content in the AI community. It highlights the importance of efficient infrastructure for t...
This podcast episode covers the highlights of Opening Eye Dev Day, where developers and founders gathered to discuss OpenAI's latest announcements. The topics discussed include the improvements in OpenAI's GPT for Turbo, the stateful API, documentation and capabilities of OpenAI's offerings, UI changes in ChatGPT, the ...
This podcast episode provides a recap of the recent OpenAI event, where they made several key announcements and advancements. The episode discusses the reactions from attendees and covers topics such as the improvements in GPT-4 Turbo, the introduction of stateful APIs and document parsing capabilities, the Assistant A...
In this podcast episode, Michael Rosen, the creator of Smart Lens, a computer vision startup, discusses his journey in the field of computer vision. He talks about attending Apple's WWDC conference and developing a successful classification model using deep learning that surpassed Google Lens. Rosen also explores his w...
This podcast episode explores the journey and challenges of Cube Arden, an embedded analytics product, and discusses the evolution of natural language understanding models in data analysis. It highlights the significance of the semantic layer in providing context and structure to tabular data and discusses the integrat...
In this podcast episode, Jeremy Howard, the founder of Fast AI, discusses the mission of Fast AI which aims to make deep learning accessible to everyone, regardless of their educational background. The conversation explores the development and potential usefulness of language models in various domains, with a focus on ...
This podcast episode explores the world of AI agents and the challenges in developing and deploying them. The hosts discuss Embeu, a company that specializes in building AI agents. They delve into topics such as reasoning, inspecting and debugging AI models, and the importance of benchmarks and scaling laws. The episod...
This podcast episode explores various aspects of AI engineering, including hiring AI engineers, important tools and frameworks, multi-modality in AI, and the upcoming AI Engineer Summit. It discusses the skills and pathways to becoming an AI engineer, highlighting the importance of software engineering experience and A...
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