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 discusses various aspects of AI research, including the evolution of models such as Raker Core, the career journey of the speaker, the challenges faced by compute providers, the importance of marketing and PR in research, the qualities of a good AI programmer, architectural decisions in transformer...
This podcast episode explores the recent developments in Databricks' text to image model, the challenges faced in building and managing custom machine clusters for GPU training, the significance of evaluating datasets and models in natural language understanding and reasoning tasks, and the potential of coding agents a...
This podcast episode explores the emergence of the AI Engineer role and its evolving landscape in the field of AI engineering. It discusses the skills and responsibilities of AI Engineers, as well as the differences between AI Engineers and ML Engineers. The episode also emphasizes the importance of collaboration betwe...
This podcast episode explores the role of AI engineers in working with language models and discusses the challenges and rewards of implementing fallbacks and prompts in AI applications. It also discusses the tendency to reach for standardization and abstractions early in new technology cycles and the difficulty of dete...
This podcast episode explores the role of language models in the finance industry and their potential to enhance individuals' reasoning abilities. It discusses the importance of domain expertise, the limitations of large context windows, and the challenges of ensuring accuracy and reliability in information retrieval a...
This podcast episode explores various projects and benchmarks aimed at evaluating the performance of language model agents in realistic web-based tasks. It discusses the challenges faced by language models in navigation, filtering, math, and social scenarios, highlighting the gap between language models and humans. The...
In this episode of the Latent Space Podcast, Mark Huang from Gradient shares insights into their efforts to expand the context window of large language models, particularly Llama 3. He explains their innovative approach, which employs a curriculum learning method utilizing datasets like SlimPajamas and UltraChat. The d...
This podcast episode explores various topics in deep learning, including variational autoencoders (VAEs), diffusion models, generative models, adversarial machine learning, attention maps, context extension, large language models, and self-pre-training. It discusses the concepts, challenges, applications, and potential...
This podcast episode explores the world of NSFW AI chatbots and the challenges and opportunities they present in the adult industry. The guest, Jesse Silver, discusses the concept of fan platforms like OnlyFans and the need for automation in order to save creators time and increase their income. The conversation covers...
This podcast episode explores the creative side of generative AI, focusing on WorldSim, WebSim, and HumanSim. The episode consists of a demo of WorldSim, a talk on WebSim, and an interview on Simulative AI. The speakers highlight the capabilities of language models, the CLI interface for interacting with Claude's simul...
This podcast episode explores various topics related to AI engineering, machine learning, and the development of large language models. The discussions cover the evolution of recommendation systems, the emergence of tools like Instructor and FLITE, the potential of AI-powered workflows, the challenges and realities of ...
This podcast episode delves into the journeys and motivations behind the founding of Ought, a non-profit research lab focused on developing AI tools for reasoning, and Elicit, a company that provides an AI research assistant. Andreas, the co-founder and CTO of Elicit, shares his fascination with AI since childhood and ...
This podcast episode explores various topics in the AI industry, including the Four Wars of the AI Stack, the competition between multi-modality and dedicated modality companies, advancements in GPT-4 and the upcoming release of GPT-5, the potential impact of Apple entering the AI race, the trend towards vertical agent...
This podcast episode explores various topics related to artificial intelligence (AI) engineering. It discusses the origin and success of the AI Engineer Summit, an event that brings together technical engineers working with AI. It also introduces the upcoming World's Fair of AI, a major event in the AI community. The e...
This podcast episode explores the career journey of David Luan, the CEO and co-founder of Adept, and discusses the history and challenges of developing GPT. It also delves into the Brain Credit Marketplace at Google, the approach of Adept in building reliable AI products for enterprise customers, the growing awareness ...
This podcast episode delves into the evolving field of audio generation, its potential impact on music-making, and the promise it holds for democratizing music creation through Suno, a music generation platform. By exploring the use of transformer-based models, the challenges of capturing the full range of audio behavi...
This AI Podcast episode explores the latest advancements and trends in artificial intelligence, including long inference for text LLMs, emerging alternative architectures for LLMs, Mixture of Experts (MOEs), model merging, online LLMs, text-to-video generation with Sora, generative models, the Grok hardware, Gemini's l...
This podcast episode explores the complexities, applications, and future of deep learning frameworks, particularly PyTorch. It delves into the challenges of supporting diverse hardware configurations, the potential of Mojo and MLX, and the rise of new frameworks. It emphasizes the importance of usability, reliability, ...
This podcast episode explores the various aspects of artificial intelligence (AI), from model design and packaging to usage optimization and accessibility. The genesis of Replicate, a platform for publishing and running machine learning models, is discussed, along with its pivotal role in fostering a vibrant community ...
This podcast episode explores the journey of Bernhardsson, co-founder of Modo, from his time at KTH and Spotify to founding his own company. It highlights the importance of developer productivity in the context of data teams and the challenges in using traditional cloud computing infrastructure. The episode introduces ...
Follow this podcast in Podwise
Sign in to get AI summaries, transcripts and mind maps for any episode, including new ones.
