Bigger isn’t always better. In this episode, we break down Microsoft Research’s latest AI breakthrough—Phi-1, a 1.3 billion parameter coding model that outperforms much larger models by focusing on high-quality, textbook-style data. Discover how this approach challenges traditional scaling laws, slashes computational costs, and paves the way for more efficient AI development. Tune in as we explore the future of coding AI and why “textbooks are all you need."

AI isn't taking over jobs as fast as we think—it's all about the economics. In this episode, we dive into MIT’s latest research on computer vision automation and unpack why cost, scale, and deployment matter more than just technical feasibility. From small businesses to AI-as-a-service models, we explore what actually makes automation worth the investment and what that means for the future of work.

Generative AI is evolving beyond standalone models into fully functional agents capable of reasoning, planning, and interacting with the world through tools. In this episode, we explore the architecture of AI agents, how they differ from traditional models, and the role of tools like LangChain and Vertex AI in their development. Discover the future of AI autonomy and what it means for industries and everyday applications.

Discover how multi-agent AI frameworks are redefining the fight against hallucinations in large language models. This episode explores how layered agents, guided by the OVON framework, reduce speculative content through iterative refinement and structured data exchange. Learn about novel KPIs, empirical results, and the potential of agentic AI to enhance trust and transparency in generative AI systems.

Explore how MedAgentBench benchmarks large language models (LLMs) as medical agents, moving beyond chatbots to tackle real-world clinical tasks. This episode unpacks the dataset's 100 clinically derived tasks, its FHIR-compliant interactive environment, and insights into the current state of LLM performance. Learn how AI can reduce administrative burdens and improve healthcare delivery.

Explore how cutting-edge AI transforms remote robotic surgery. Using the Informer model, researchers tackle network-induced issues like jitter and packet loss, ensuring real-time precision for Patient Side Manipulators. Discover the role of predictive AI in overcoming latency challenges, enhancing accuracy, and reshaping surgical possibilities with the Tactile Internet.

Explore the risks of inconsistent multilingual health advice from large language models (LLMs). This episode uncovers disparities in LLM-generated responses across languages, highlighting challenges in cross-lingual consistency, cultural biases, and their implications for equitable healthcare. Learn about groundbreaking evaluation frameworks, key findings, and what this means for the future of AI in healthcare.

Discover how DeepSeek-AI's groundbreaking DeepSeek-R1 models use reinforcement learning to unlock advanced reasoning skills in AI, paving the way toward AGI. From self-evolution to distilled smaller models, this episode explores key breakthroughs, challenges, and their practical implications.