What do tech pioneers think about the AI revolution?

The Panelists

Regina Barzilay (MIT): Professor for AI and Health, known for breakthroughs in early breast cancer detection and antibiotic discovery.
David Silver (Google DeepMind): Principal Research Scientist, led the team behind AlphaGo (which defeated the world champion at the game Go) and works on Artificial General Intelligence (AGI).
Paolo Pirjanian (Embodied): Founder/CEO building emotionally intelligent robots to assist with child development and care.

Key Discussion Topics

1. AI in Medicine (Regina Barzilay)

Motivation: Regina shifted her work to oncology after her own breast cancer diagnosis in 2014, realizing there was a lack of basic AI technology in patient care compared to the advanced tech at MIT just a subway stop away.
Early Detection: She developed an AI model that could detect cancer on mammograms up to two years earlier than human radiologists by identifying subtle patterns in the tissue that are too confusing for the human eye.
Antibiotic Discovery: Her team used AI to screen thousands of molecules to find a new antibiotic effective against drug-resistant bacteria (like MRSA and E. coli). The AI identified a molecule that didn’t look like anything humans would have created.
Barriers to Adoption: Despite mature technology, AI isn’t widely used in hospitals due to regulation and billing structures. In the US, doctors are paid based on time spent; if AI makes them faster, they ironically lose money, reducing the incentive to use it.

2. Reinforcement Learning & AGI (David Silver)

Reinforcement Learning: Described as a method similar to how humans and animals learn via trial and error. The AI is given a “reward” (a positive number for good actions, negative for bad), which drives its learning process.
AlphaGo: Defeating a human at Go was harder than Chess because Go relies on intuition and creativity—traits previously thought to be uniquely human. The AI had to “imagine” how the game would play out 300 moves ahead.
Artificial General Intelligence (AGI): The goal is to create systems that aren’t just “narrow AI” (good at one task) but can learn diverse skills (like a human who can be a chef, a scientist, and a tennis player).
AI & Culture: He views AI as a powerful tool for creators (e.g., writers and musicians) rather than a replacement for human culture, citing Will.i.am’s excitement over AI music tools.

3. Social Robots & Care (Paolo Pirjanian)

Therapy for Children: His robots serve as “training wheels” for children with autism, helping them practice social skills like eye contact and turn-taking in a safe environment before applying them to human interactions.
Elderly Care: He predicts that within the next decade, robots will provide assistive care for the elderly, helping with cooking, walking, and combating social isolation/loneliness.
Job Displacement: When asked if robots will take all our jobs, he jokingly answered “Yes,” before pivoting to the serious potential for AI to change everything in our lives.

Q&A Highlights

On Regulation:
- David: Supports regulation but notes it cannot be “one size fits all”—medical AI needs different rules than chatbots.
- Regina: Concerned that over-regulation is causing suffering by delaying life-saving technologies.
- Paolo: Warns that regulation is difficult because AI is a strategic national asset; slowing it down locally might give adversaries an advantage (an “arms race”).
On Sports: David mentions a collaboration with Liverpool Football Club using AI to improve tactical decision-making.
On Human Learning: A young audience member asked if humans will stop learning. The panel was optimistic:
- David: Envisions AI as a personalized tutor that knows exactly how to teach you.
- Regina: Believes AI removes the “drudgery” (like fixing grammar or coding syntax), allowing humans to focus on higher-level ideas and become more prolific, similar to how calculators aided scientists like Einstein.

“In any system of energy, Control is what consumes energy the most. No energy store holds enough energy to extract an amount of energy equal to the total energy it stores. No system of energy can deliver sum useful energy in excess of the total energy put into constructing it. This universal truth applies to all systems.

Narrow AI is a “machine” that is able to perform one single task and it’s not specialized. On the other hand the general AI is a machine that is able to perform many tasks and learn from them at the same time, however, nowadays it’s just a concept used to tailor and train current AI models to provide a human-like output, pointing out that it’s not intended to replace human work but boost it.

it’s fascinating to see tech pioneers weigh in on the AI revolution! As someone who’s been following AI developments closely, I’m intrigued by how collaborative AI systems could transform businesses. I recently came across SmythOS, which seems to be pioneering some exciting multi-agent AI technology.

I’m an AI engineer with over 4+ years of experience working on a wide range of projects. My focus is on building smart, AI-driven solutions that help businesses improve their performance. I’ve worked in industries like healthcare, real estate, aerospace, and e-commerce, where I’ve helped clients by creating everything from chatbots and sound classifiers to complex data analysis platforms. What sets me apart is my ability to take challenging problems and build AI models that provide real, practical solutions.

Whether it’s improving email automation, creating systems to analyze scientific studies, or developing tools for real-time decision-making in space tech, I love using AI to make things more efficient. I’m skilled in Python, NLP, machine learning, Gen AI and API development, and I always aim to build systems that not only work but are also scalable and easy to maintain. I’m always excited to collaborate with individuals or organizations looking to leverage AI to drive growth and innovation.

While a fascinating talk, every one of them is looking at the question of how it will handicap us in terms of their own desires to learn which developed in a world without these technologies. If we know one thing about humans it’s that if you don’t find a way to create struggle, you get weaker and die. That is why we have gyms now that we don’t have to hunt for our food and we see what not having to hunt for our food did to obesity, mental health, and the general health of our species. AI is wonderful and has huge potential and yet if we don’t limit it such that it doesn’t write all our code, all our books, all our music, all our relationships, all our struggles, we will perish.