Waleed Kadous, Chief Scientist at Anyscale, discusses best practices for building applications leveraging large language models. Topics include heuristics for working with open source models, differences between Code Lama and GitHub Co-pilot, challenges in deploying open source models, using spending data to save data, fine-tuning models in supervised machine learning, and exploring the potential of multimodal models.

CEO of BlockApps and Co-Chair of the Enterprise Ethereum Alliance discusses web3 technologies, transitioning from mining to proof of stake in Ethereum, impact of Proof of Stake and NFTs in the crypto space, intersection of blockchain, AI, and crypto, creation and governance of base models for ML, current happenings in crypto and web3, advantages of blockchain and collapse of VC market

The podcast discusses the evolution of big data and AI technologies, the rise of open source data in the tech industry, the future of AI and machine learning in a decentralized world, simplifying workload and data movement across cloud and on-prem environments, challenges in data management, and the power of networking in open source data.

Malte Pietsch, co-founder & CTO of Deepset, discusses the importance of orchestration frameworks for LLM applications, the usage patterns of the Haystack framework, and optimizing RAG applications with metadata and knowledge graphs. They also explore the evolution of data engineering pipelines, real-time indexing, and the highlights and features of Haystack 2.0.

The hosts analyze takeaways from the inaugural AI conference in San Francisco, discussing the importance of empirical evidence. Experimenting and iterating in AI leads to improved results. The rise of open source and custom foundation models in AI is explored. The use of ensembles in machine learning and highlights from the AI conference are discussed, including generative AI for speech.

Guest Semih Salihoglu, co-creator of Kuzu, discusses the concept of a property graph, differences between property graphs and RDF in graph databases, the need for switching databases, the design and storage techniques of Kuzu, integration with other programming languages, advantages of DuckDB, and compatibility and streaming in real time.

Philipp Moritz and Goku Mohandas of Anyscale discuss retrieval augmented generation (RAG) systems, challenges in evaluation, labeling and classification strategies, optimizing model inference, online software stack, and hyperparameter search in evaluation runs.

Researchers Bill Marcellino and Nathan Beauchamp-Mustafaga discuss the rise of generative AI and its impact on social media manipulation. They explore the use of generative AI for political and security purposes, motivations of nation-state actors, technology asymmetry, scale and control of information propagation, and combatting manipulative content on social media.

Yucheng Low, CEO of XetHub, talks about managing large-scale ML assets and the challenges of data management. They discuss the need for version control, data reproducibility, and efficient solutions. The podcast covers topics such as GDPR impact on data teams, benefits of openness in data management, and distinguishing features of their tool. They also discuss the importance of deduplication, summaries, and visualization tools, and the unique features of Zetahub's user interface for data versioning and collaboration.

The podcast discusses various topics including the revolution of including domain expertise in industrial AI, addressing hallucination in generative AI, retrieval augmented generation for enhancing language models, the challenges of industrial AI and knowledge transfer, the impact of generative AI on jobs, and a call to action to explore the influence and concerns surrounding generative AI.