Nearly one third of college students drop out every year. According to Elvee's 2026 Higher Education Retention Report, 42% of students say they've felt close to leaving at some point. The drivers aren't just academic. It's burnout, financial pressure, mental health struggles, and trying to balance work with school.

In this episode of Machine Dreams, Raz Dar, CEO of Elvee, explains how AI can identify students at risk of dropping out before it happens. The system analyzes over 100 behavioral signals from learning management platforms like Canvas and Blackboard.

We also talk about how the same technology tracks employee burnout in contact centers, why Elvee avoids demographic data to prevent bias, and what happens when universities actually measure whether their interventions work.

What if universities could know a student was about to drop out before it actually happened?

In this episode of Machine Dreams, Raz Dar, CEO of Elvee, explains how AI can detect early warning signs hidden inside student behavior data—from assignment patterns to engagement levels—and help universities intervene before students fall through the cracks.

Live today on YouTube, Spotify, and Apple Podcasts.

7pm GMT+1. 6pm UK. 1pm EST.

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This episode of Machine Dreams comes with a twist. We’re diving into the Nancy Guthrie kidnapping case, a story that’s dominated headlines and sparked fierce debate about cryptocurrency, crime, and public misconception.

When news broke that the perpetrators demanded millions in Bitcoin, the narrative wrote itself: That crypto is anonymous, untraceable, and built for criminals. But that’s not how Bitcoin works. Katherine Kirkpatrick Bos, General Counsel at StarkWare, breaks down what most people get wrong.

“Bitcoin isn’t anonymous,” she tells us. “It’s pseudonymous.” Every transaction lives on a public ledger forever. In addition, machine learning tools from companies like Chainalysis and Elliptic can trace crypto across wallets and exchanges with precision cash never offered.

In other words, the technology people think helps criminals is actually what catches them.

We also discuss how AI is changing crypto in ways most people don’t realize. Machine learning is now being used to hunt down criminal activity on blockchain networks, tracking patterns humans would miss.

Katherine explains zero-knowledge proofs— a technology that could let companies use AI on sensitive data without ever seeing the actual information. And she breaks down why privacy, long confused with anonymity in crypto, is now the key to getting Wall Street fully on board with blockchain.

Get more in this brand new episode of Machine Dreams.

This episode of Machine Dreams Podcast takes a different turn. The Nancy Guthrie kidnapping has dominated headlines. Perpetrators demanded millions in Bitcoin. Immediately, crypto was blamed as anonymous and untraceable, built for crime.

Katherine Kirkpatrick Bos, General Counsel at StarkWare, explains why that’s wrong and how AI is changing crypto in ways most people don’t realize.

This episode comes with a sizzle like no other. Live today on YouTube, Spotify, and Apple Podcasts.

7pm GMT+1. 6pm UK. 1pm EST.

Get ready!

Most companies believe they’ve approved 30 apps. The truth? Over 500 are running right now.

Your employees aren’t waiting for IT approval. They’re using ChatGPT instead of the Copilot you paid for. They’re uploading sensitive data to free design tools that train on your information. They’re connecting AI agents to Salesforce, HubSpot, and your knowledge base without anyone tracking what those agents can access.

This is shadow AI. And it’s spreading faster than your security team can see it.

Gal Nakash is co-founder of Reco and Forbes 30 Under 30 honoree. He explains why AI agents are now crown jewels for hackers. Compromise one agent and you access every system it touches. He walks through the moment CISOs see their real AI footprint for the first time and realize traditional security assumptions no longer hold.

The companies that survive won’t be the ones blocking AI. They’ll be the ones who assume chaos is permanent and build security that can keep up.

Learn more in this very insightful conversation.

Most companies believe they control their AI tools. They don’t.

Employees are bypassing approved software and using shadow AI apps you’ve never heard of. They’re uploading company data to free tools. They’re connecting AI agents to your systems without asking permission. And every new connection creates a security blind spot that traditional defenses can’t see.

Gal Nakash, co-founder of Reco and Forbes 30 Under 30 honoree, explains why companies that think they run 30 apps are actually running 500. He breaks down how AI agents become crown jewels for hackers, why one compromised agent can unlock your entire system, and what security teams must do differently now that the old rules no longer apply.

This isn’t about blocking AI. It’s about surviving the chaos that’s already here.

New episode of Machine Dreams today. Live soon.

Most AI drug discovery companies fail in clinical trials. Maolac’s success rate? 10 out of 10.

In this episode of Machine Dreams, CEO Maya Ashkenazi Otmazgin explains how her company uses “protein intelligence” to reverse-engineer breast milk’s biological playbook, designing therapeutics that mimic what nature already perfected.

We discuss why biological data is scarce, how Maolac compresses drug timelines without cutting safety corners, and why women’s biology demands different solutions than men’s.

If you’re tired of AI drug discovery vaporware, this conversation is for you.

AI is transforming software. But what happens when it starts transforming biology?

In this episode of Machine Dreams, we sit down with Maya Ashkenazi-Otmazin, founder and CEO of Maolac, to explore how AI is being used to understand and design full proteins, not just small molecules, but the building blocks of human biology itself.

From breast milk as nature’s survival blueprint to the challenges of limited biological training data, this conversation looks at what it really means to use machine learning in drug discovery. We unpack the promise, the risks, and the uncomfortable truth about how slowly biology has advanced compared to tech.

This isn’t hype about curing everything tomorrow. It’s a grounded conversation about where AI in therapeutics actually stands, and what it would take to responsibly move faster.

Full episode live at 7pm GMT+1. 6pm UK. 1pm EST.

Digital humans are no longer a concept. They’re already showing up in how we learn, work, communicate, and interact online.

In this episode of Machine Dreams, we sit down with Ron Friedman, head of content and creative marketing at D-ID, to talk about what AI-powered digital humans actually are, how they’re being used in the real world today, and why they’re becoming the next interface between people and machines.

From business and accessibility to trust, identity, and responsibility, this conversation looks past the demos and into what this shift really means.

In this episode of Machine Dreams, we sit down with Ron Friedman from D-ID to unpack the rise of digital humans — lifelike AI avatars now being used across training, education, customer experience, accessibility, and healthcare.

We talk about what digital humans really are, how they differ from chatbots, and why trust becomes the central challenge once AI stops living in the background and starts looking back at us.

Full episode live at 7pm GMT+1. 6pm UK. 1pm EST.