CEO and Founder Ryan Carson discusses democratizing AI development and the impact of new technologies like Gaudi three. He emphasizes the importance of aligning individual work with company goals and the potential benefits of AI in professional interactions. The conversation also touches on practical AI applications, entrepreneurship, and the role of technology in shaping the future.

Salman Avestimehr, CEO & Founder of FEDML, discusses FEDML Nexus AI, an enterprise AI platform enabling generative AI applications at scale. Topics include challenges in AI platform development, ownership, scalability, integrating with cloud infrastructure, evaluating language models, small scale foundation models in federated learning, and advantages of using small models for AI agents on mobile phones.

Mohamed Elgendy, Co-Founder & CEO at Kolena, discusses AI Quality with a focus on tailored quality standards, risk management, and edge deployments. The podcast emphasizes the formation of gold standards for AI, collaboration among AI builders, regulators, and infrastructure firms, and the need for diversification in the tech industry. Elgendy's AI Quality Conference aims to set effective but innovation-friendly quality standards for AI.

Simon Karasik, an experienced ML Engineer, discusses handling multi-terabyte LLM checkpoints. Topics include managing massive models, cloud storage options, comparing Slurm and Kubernetes, navigating data processing challenges, monitoring Kubernetes nodes with faulty GPUs, and simplifying model training processes.

Sol Rashidi, an esteemed executive in AI and Data, discusses the importance of prioritizing relationships, a 'Wrong Use Cases Formula' for project prioritization, and effective communication in data leadership. She shares insights on balancing criticality and complexity in project prioritization, evaluating team skills, navigating data complexity, adapting to change in company culture, and upcoming AI quality conference.

Chad Sanderson, CEO of Gable.ai, discusses modern data management, data contracts, and the evolving trends in data infrastructure. He explores the importance of aligning data use with business value, transitioning to federated data management models, and the benefits of AWS Trainium and Inferentia. Sanderson introduces 'Gable' as a platform revolutionizing data management processes with live change detection and collaboration tools, emphasizing data integrity and monetization for businesses.

Neuroscientist Patrick Beukema discusses the role of AI in solving environmental challenges, combining remote sensing and AI for real-time global intelligence. He emphasizes the importance of MLOps in ML/AI workflows for continual improvement. Join the fight for sustainability and conservation with advancements in Environmental AI for social good.

Verena Weber, with expertise in NLP and 7+ years in ML, discusses challenges & trends in GenAI: model size, context windows, multimodality, EU AI Act. She compares Gemini 1.0 & 1.5. Topics include AI models in production, BERT, GPT, and empowering women in tech.

Experts discuss the groundbreaking DBRX language model, its capabilities in code and math, and potential applications for businesses and developers. They explore the evolution of language models, challenges in scaling workload, optimization for inference, and enhancements with synthetic data. The discussion also delves into running training programs on laptops, choosing Kubernetes for large-scale training platforms, and the future of data modalities.

Experts discuss challenges in scaling AI models from MVP to production, emphasizing user feedback for iterative improvements. They highlight the importance of evaluation methods like human annotation, heuristic analysis, and LM-based evaluation. The conversation explores enhancing AI coding assistants with context, navigating challenges in data ingestion and model updating, and the evolution of evaluation sets and data infrastructure in machine learning.