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.

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.

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.

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.

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.

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

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.

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.

Exploring 2024 AI trends like democratized AI hardware, advancements in generative AI models in enterprise settings. Introducing startups in computer vision and NLP, emphasizing importance of quality control in AI systems.

Bryan Cantrill, CTO and Co-founder of Oxide Cloud Computer, leads a startup delivering integrated hardware and software solutions for enterprises seeking cloud computing systems with hyperscaler agility. Oxide specializes in vertically integrated, scale-ready cloud infrastructure tailored for mainstream business needs.Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Google • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes can be found on The Data Exchange web site.