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
Jul 18, 2024 • 35min
From Preparation to Recovery: Mastering AI Incident Response
Andrew Burt, co-founder of Luminos.Law and Luminos.ai, discusses AI incident response challenges and preparation. Topics include defining incidents in AI systems, specialized response teams, regulations like SB 1047, contrasting US and European approaches to AI regulation, and the importance of detecting and stopping AI failures.
Jul 11, 2024 • 50min
Unlocking the Power of Unstructured Data
CEO Chang She of LanceDB discusses the challenges and innovations in managing unstructured data for AI, including developing new data formats, optimizing AI training workloads, and enhancing applications with multimodal embeddings and vector search.
Jul 3, 2024 • 51min
Postgres: The Swiss Army Knife of Databases
Ajay Kulkarni and Mike Freedman, co-founders of Timescale, discuss how Postgres has evolved into a versatile platform for AI and vector databases. They explore the innovations in Postgres-like database technology, the significance of streaming post filtering, and the evolution of data formats and database usage, including embedding pipelines for AI applications and handling multimodal data.
Jun 27, 2024 • 44min
Supercharging AI with Graphs
Philip Rathle, CTO of Neo4j, discusses GraphRAG and GQL. Topics include Graph Neural Networks with LLMs, constructing knowledge graphs from various sources, using graphs in AI applications like supply chain risk analysis, benefits in healthcare and customer service, and integrating vector and graph databases for efficient data analysis.
Jun 20, 2024 • 37min
Monthly Roundup: SB 1047, GraphRAG, and AI Avatars in the Workplace
Paco Nathan, founder of Derwen, discusses SB 1047 for regulating AI, GraphRAG techniques, and AI avatars in the workplace. Topics include potential unintended consequences of AI regulation, limitations of integrating symbolic and statistical AI, challenges of AI avatars attending meetings, and advancements in graph analytics and machine learning.
Jun 13, 2024 • 36min
Fine-tuning and Preference Alignment in a Single Streamlined Process
Jiwoo Hong and Noah Lee from KAIST AI discuss their method ORPO, combining supervised fine-tuning and preference alignment in a single step. They highlight the advantages of their approach, such as minimal data requirement, bias prevention, and enhanced adaptability of language models. The Orpo method has received positive feedback from the research community and industry for efficient alignment and scaling models with smaller datasets.
Jun 6, 2024 • 25min
TinyML, Sensor-Driven AI, and Advances in Large Language Models
Pete Warden, founder of Useful Sensors, discusses the development of trustworthy AI for consumer electronics, advancements in Tiny Large Language Models and Sensor-Driven AI, the concept of Dark Compute, using CPUs and sensors for AI applications in consumer devices, and ways to engage in the TinyML and sensor-driven AI community.
May 30, 2024 • 50min
Machine Unlearning: Techniques, Challenges, and Future Directions
Ken Liu, a Ph.D. student at Stanford, discusses the concept of machine unlearning in AI models. They explore challenges like removing specific data points effectively, evaluating generative AI models, and linking privacy-preserving ML techniques with unlearning. The conversation delves into the evolution of unlearning techniques, highlighting the need for benchmarks and advanced methods for implementation.
May 23, 2024 • 39min
Unleashing the Power of AI Agents
Joao (Joe) Moura, founder of crewAI, discusses the simplicity of developing AI agents using large language models. They explore the use of AI agents in various tasks, emphasizing the importance of multi-agent architectures and potential for multimodal AI. The conversation delves into selecting suitable use cases for agent solutions, challenges of software engineering, and AI agents' role in enterprise processes. They also address concerns about prompt injection risks and upcoming features for AI projects.
May 16, 2024 • 42min
Monthly Roundup: Llama 3, Agents, Evaluation Metrics, Cyc, TikTok, and more
Paco Nathan, Founder of Derwen, talks about Llama 3 advancements, open foundation models, evolving AI agents, and the importance of data engineering. They discuss the limitations of leaderboards in evaluating AI models and touch upon the ethical implications of AI development.
