Machine Dreams

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.

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.

One in four people over 65 will have a stroke. Most will survive, but survival doesn’t mean recovery. While we’ve built data centers in space, stroke patients are still treated with 19th-century physical therapy.

In this episode of Machine Dreams, we sit down with Yotam Drechsler, CEO of BrainQ, who’s building what he calls “NVIDIA for brain recovery.” His AI-powered platform retrains neural networks damaged by stroke, helping patients recover at home through personalized electromagnetic fields and telemedicine.

Yotam explains why AI started in neuroscience but left the brain behind, why the first weeks after stroke matter so much, and what “responsible AI” actually means when patients are elderly, fragile, and trying to regain the ability to button their own shirt. We push back on the fear of AI replacing doctors and ask how you balance innovation with patient safety when families must trust an algorithm with their most precious asset.

This is AI beyond the demo—where the stakes are personal, timelines span decades of R&D, and getting it wrong means more than a bad user review.

AI is moving fast into healthcare, but the brain is not just another system to optimize. It’s fragile, personal, and deeply human.

In this episode of Machine Dreams, we speak with Yotam Drechsler, CEO of BrainQ, about what it really takes to use AI in brain recovery. We talk about stroke, neuroplasticity, why most care still looks like the 19th century, and why responsible AI sometimes means using less of it.

In this episode of Machine Dreams, we sit down with Judah Taub, Co-founder and Managing Partner at Hetz Ventures, fresh off closing the firm’s $140M Fund IV during wartime and a period of global uncertainty. Hetz now manages close to $500M in assets, and Judah has a front-row view into what serious investors are funding in AI and what they are walking away from.

We talk about why Judah sees this moment as the internet in the late 1990s, why “AI bubble” is really two different debates, and what separates durable AI businesses from fast demos. He breaks down the signals he watches, including a sharp test most founders don’t like to hear: does GPT-X make you obsolete, or does it make you stronger? We also unpack why infrastructure and deep software still win in Israel, what “color of revenue” means in practice, and where returns may actually accrue over the next five years as AI fragments into large models beyond language.

If you’re building, investing, or trying to understand where the real money is going in AI, this is the conversation that cuts through the noise.

AI spending isn’t dropping. Investors are just getting smarter about where it goes.

That’s what Judah Taub, founder and managing partner at Hetz Ventures, tells us in this episode of Machine Dreams.

Fresh off a $140 million fourth fund, Judah explains what VCs are funding now, what signals separate real revenue from hype, and the test that can make or break an AI startup.

If you’re building, investing, or trying to understand where the money is going in AI, do NOT miss this one!

We are now 4000+ subscribers strong and that’s only because of you, our dear viewers and subscribers. We’ve had some of the most forward-thinking minds in the AI industry as guests and the feedback on every episode has been remarkably amazing.

As we get ready to publish episode 7 next week, we wanted to share some of our favorite moments (really hard to choose, to be honest) from each episode so far.

AI is often talked about as if it can instantly diagnose illness, replace doctors, and see everything humans miss. In healthcare, that belief can be dangerous.

In this episode of Machine Dreams, we sit down with Moshe Barel, CEO and co-founder of AccuLine, to unpack how AI is actually used in real clinical settings. Moshe has spent more than two decades in cardiovascular medicine and digital health, and his company is building a non-invasive AI-powered system for the early detection of coronary artery disease.

We talk about what AI really does inside medical diagnostics, why human-designed algorithms still matter, how regulation shapes what can safely reach patients, and why most healthcare AI is nothing like ChatGPT. From FDA approval to biased data to the myths that won’t go away, this is a grounded conversation about where AI genuinely helps, where it does not, and what it takes to build systems doctors can trust.