The Data Exchange with Ben Lorica
Ben Lorica
A series of informal conversations with thought leaders, researchers, practitioners, and writers on a wide range of topics in technology, science, and of course big data, data science, artificial intelligence, and related applications. Anchored by Ben Lorica (@BigData), the Data Exchange also features a roundup of the most important stories from the worlds of data, machine learning and AI. Detailed show notes for each episode can be found on https://thedataexchange.media/ The Data Exchange podcast is a production of Gradient Flow [https://gradientflow.com/].
Episodes
Mentioned books
May 9, 2024 • 43min
LLMs for Data Access: Unlocking Insights with Text-to-SQL
Guest Gunther Hagleither discusses text-to-SQL technology for data analytics, adoption challenges, RAG integration for better SQL, and future advancements in text-to-SQL systems.
May 2, 2024 • 54min
2024 Artificial Intelligence Index
Nestor Maslej discusses the 2024 AI Index Report, covering topics like benchmarks surpassing human capabilities, advancements in agentic AI research, debate between closed and open large language models, comparison of AI landscape in China and the US, complexities of synthetic data and responsible AI, and AI's impact on scientific problem-solving.
Apr 25, 2024 • 46min
DBRX and the Future of Open LLMs
Hagay Lupesko, Senior Director of Engineering at Databricks MosaicAI, discusses the innovative open LLM DBRX, bridging quality and cost efficiency. Topics include data control, collaboration in the AI community, model training, serving and optimizing, sustaining open source models, future plans for DBRX, hybrid RAG, tool utilization, knowledge graphs, and engagement opportunities with the open-source project.
Apr 18, 2024 • 37min
Monthly Roundup: New LLMs, GTC 2024, Constraint-Driven Innovation, Model Safety, and GraphRAG
Paco Nathan, Founder of Derwen, discusses updates on large language models and advancements in efficiency and scalability. Topics include Constraint-Driven Innovation, GTC 2024 highlights, and lessons from AI workload security exploits. Exciting discussions on model improvements, generative AI tools, and the importance of data engineering for AI safety.
Apr 11, 2024 • 36min
Automating Software Upgrades: How to Combine AI and Expert Developers
Steve Pike, Co-founder of Infield.ai, discusses automating software upgrades by blending AI and expert developers to address challenges like security fixes and bug updates. The conversation touches on the importance of combining automation with human expertise, utilizing data sources like GitHub, and the role of AI in speeding up software development processes.
Apr 4, 2024 • 44min
Generative AI in the Industrial Sphere
Chetan Gupta, Head of AI Research at Hitachi, shares insights on applying generative AI in industrial settings. Topics include challenges of implementing AI, generating synthetic data for defect detection, automating fault tree creation, ensuring reliable AI behavior, and using generative AI for process transformation in industries.
Mar 28, 2024 • 58min
The Intersection of LLMs, Knowledge Graphs, and Query Generation
Semih Salihoglu, Associate Professor at University of Waterloo and co-creator of Kuzu, discusses using Large Language Models (LLMs) for query generation in SQL and Cypher. Topics include automation of data warehouses, metadata impact on RAG System, developing graph database engines with multi-database support, integration of knowledge graphs for question answering, and logic-based reasoning with LLMs.
Mar 21, 2024 • 36min
Unlocking the Potential of Private Data Collaboration
The podcast delves into data collaboration and secure computation challenges in various industries. Topics include synthetic data sets, secure multi party computation, NPC and Python integration in warehouses, and custom language models
Mar 14, 2024 • 34min
Frontiers of AI: From Text-to-Video Models to Knowledge Graphs
Exploration of AI developments like text-to-video models and knowledge graphs. Discussions on productionizing AI, Google's Gemini, foundation model enhancements, AMD's software innovations, and knowledge graph augmentations of language models.
Mar 7, 2024 • 43min
Adaptive, Specialized, and Accessible: Where AI Systems Are Heading Next
The podcast explores the advancements and challenges in AI systems, focusing on real-time learning, data limitations, and ethical considerations. It delves into the evolution of AI towards sensory inputs, the complexities of open source AI models, and the implications of foundation AI models in innovation and legal practices. Additionally, it discusses tax automation, book promotions, and the potential of AI in various fields.
