This episode is sponsored by Oracle. OCI is the next-generation cloud designed for every workload – where you can run any application, including any AI projects, faster and more securely for less. On average, OCI costs 50% less for compute, 70% less for storage, and 80% less for networking. Join Modal, Skydance Animation, and today’s innovative AI tech companies who upgraded to OCI…and saved.

Try OCI for free at http://oracle.com/eyeonai

What if you could fine-tune an AI model without any labeled data—and still outperform traditional training methods?

In this episode of Eye on AI, we sit down with Jonathan Frankle, Chief Scientist at Databricks and co-founder of MosaicML, to explore Tau—Databricks’ breakthrough tuning method that’s transforming how enterprises build and scale large language models (LLMs).

Jonathan explains how Tau uses reinforcement learning and synthetic data to train models without the need for expensive, time-consuming annotation. We dive into how Tau compares to supervised fine-tuning, why Databricks built their own reward model (DBRM), and how this system allows for continual improvement, lower inference costs, and faster enterprise AI deployment.

Whether you're an AI researcher, enterprise leader, or someone curious about the future of model customization, this episode will change how you think about training and deploying AI.

Explore the latest breakthroughs in data and AI from Databricks: https://www.databricks.com/events/dataaisummit-2025-announcements

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AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.

What if your blood could reveal the future of your health - years before symptoms ever appear?

In this episode of Eye on AI, Craig Smith sits down with Ash Anwar, co-founder of Molecular You, to explore how AI and advanced biomarker analysis are transforming how we detect and prevent disease.

From a real-life case where stage 1 pancreatic cancer was caught early, to the science behind tracking 250+ dynamic biomarkers, Ash breaks down how Molecular You is shifting healthcare from reactive treatment to proactive longevity.

They dive into the limitations of genetic testing, the power of machine learning models trained on clinical data, and how personalized action plans are helping individuals take control of their health in real time.

If you're curious about the intersection of AI, diagnostics, and the future of preventive medicine—this is a conversation you won't want to miss.

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(00:00) How AI Can Predict Disease Before It Happens
(02:02) Meet Ash Anwar: From Scientist to Health Tech Leader
(06:31) What Is Molecular You and How It Works
(09:43) Why Biomarker Tracking Over Time Is a Game-Changer
(15:46) How Molecular You Detected Stage 1 Pancreatic Cancer
(23:15) Biomarkers vs Genetics: What Really Matters
(28:11) The AI Models Behind Early Disease Detection
(32:37) How the Product Works for Clinics and Consumers
(35:05) Who They Compete With and What Makes Them Different
(37:34) Research vs Product: The Cancer Risk Challenge
(43:43) How Often Should You Get Tested?

AGNTCY - Unlock agents at scale with an open Internet of Agents. Visit https://agntcy.org/ and add your support.

What does it really take to turn cutting-edge AI research into a successful foundation model company?

In this episode of Eye on AI, we sit down with Anjney Midha, General Partner at a16z, to unpack how he helps scientists and researchers transform their breakthroughs into scalable, real-world AI businesses.

From his early backing of Anthropic to launching Mistral and Black Forest Labs, Anjney shares a behind-the-scenes look at how AI infrastructure companies are born.

We dive into the critical challenges of model reliability, evaluation beyond academic benchmarks, and the rise of hybrid architectures combining transformers with diffusion and LSTMs.

If you're building in AI or investing in it, this is the roadmap to what's next.

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(00:00) Turning AI Research into Real Companies

(02:08) Anjney’s Journey into Venture Capital

(05:44) The Birth of Anthropic

(08:26) Backing Mistral and Stable Diffusion

(13:16) Are Transformers Really Enough?

(18:36) Why AI Evaluation Is Broken

(22:10) Making AI Models More Interpretable

(28:38) The Real Potential of AI Agents

(32:43) How a16z Spots AI Breakthroughs

(37:45) Investing Like It’s the 1970s

(43:31) What AI Voice Tech Needs Right Now

(46:32) Models vs Products

(51:17) What’s Holding Back AI Agents

(55:41) Anjney Startup Investing Strategy