What happens when billionaire ambition meets futuristic engineering? 🚀

Elon Musk's proposed Tesla Roadster thruster technology looks like something straight out of science fiction. But while the idea is undeniably fascinating, I have some questions: What is the technology behind it? Could it actually function as a flying vehicle? And who would realistically be able to afford one?

In this episode of Sector M31, I turn to AI for an explanation of the SpaceX-inspired cold-gas thruster system, how compressed gas can generate thrust, and the practical challenges of using that technology in a car.

We also explore the potential market for such a vehicle, the complications of safety and regulation, and whether this kind of innovation represents meaningful progress—or simply an extravagant engineering experiment for the ultra-wealthy.

It's an entertaining conversation about futuristic technology, billionaire ambition, and the difference between building something extraordinary and building something people actually need.

The big question: If you had the money, would you buy one?

Listen in, then share your thoughts!

Why do some people seem capable of deceiving others on an extraordinary scale without feeling the guilt most of us would experience?

In this episode of Sector M31, I investigate the psychology of four famous con artists with help from AI. From billion-dollar financial fraud to the fake heiress who fooled New York's elite, these cases reveal fascinating questions about deception, ambition, trust, and the human desire for status.

Frank Abagnale: The Story Behind Catch Me If You Can

Frank Abagnale became famous for his claims of impersonating professionals and committing check fraud, inspiring the film Catch Me If You Can, starring Leonardo DiCaprio. But questions have been raised about parts of his story. We explore the controversy and ask whether his own life story may have become another carefully constructed deception.

Bernie Madoff: The Psychology Behind the Ponzi Scheme

Madoff's enormous fraud devastated investors, retirees, charities, and other victims. How did he gain so much trust? I ask AI to examine the roles of exclusivity, reputation, social connections, greed, and the ability to rationalize harming others.

Elizabeth Holmes: Ambition, Image, and Theranos

Holmes promised groundbreaking blood-testing technology through her company, Theranos. We examine her desire to become a visionary entrepreneur, the pressure to appear successful, and the difficult distinction between believing your own story and knowingly deceiving others.

Anna Sorokin, AKA Anna Delvey: The Fake German Heiress

Sorokin persuaded people in New York's social and financial circles that she was a wealthy heiress. Despite lacking the fortune she claimed to possess, she gained access to luxury hotels, expensive restaurants, and influential people. What role did confidence, appearance, and perceived status play in her deception?

What do these con artists have in common?

Throughout the episode, I use AI to explore the psychological themes connecting these cases:

• The need for admiration and recognition
• Rationalization and compartmentalization
• Manipulation, trust, and perceived authority
• The difference between self-deception and deliberate fraud
• The role of confidence in persuading others to believe a lie

These cases aren't identical, and the scale of the harm varies considerably. But each raises questions about what happens when the desire for success, money, or admiration takes precedence over honesty.

My question for you: Is confidence the purest form of a con? And do you think some con artists eventually start believing their own lies?

Join the conversation and share your thoughts.

Thanks for listening to Sector M31, where we explore real-life stories, human behaviour, and the psychology behind the things people do.

She was looking for love after losing her husband. Instead, she became the victim of romance scams and found herself arrested in a foreign country after unknowingly becoming involved in an international drug-smuggling operation.

In this episode of Sector M31, Yasemin explores the disturbing case of Susanna Thayer and examines the psychology behind romance scammers, catfishing, and organized criminal networks.

After losing her husband, Susanna went online looking for companionship. She met a man calling himself Walter Williams, who claimed to be a doctor working for the United Nations in Syria. The relationship cost her approximately $200,000 before the man disappeared.

Later, Susanna connected with another man online who offered to pay for her travel to meet him. After a series of changes to the travel arrangements, she found herself in Hong Kong, where authorities discovered cocaine concealed inside the buttons of clothing she had been given.

She was arrested and spent almost 300 days in prison before eventually being released.

How does an online romance turn into such a devastating experience?

Using AI tools including Kimi and ChatGPT, Yasemin explores the behavioural patterns behind romance scams, including love bombing, emotional manipulation, fabricated identities, isolation, and the psychological justifications perpetrators may use to rationalize their actions.

Why do some scammers appear capable of understanding their victims' emotions while showing little concern for the harm they cause? Do they lack empathy, or do they deliberately suppress their conscience to pursue their goals?

The episode also considers the role of organized criminal networks and the importance of protecting ourselves and our loved ones from online exploitation.

Join the conversation: Why do you think these scams work, and what makes their perpetrators willing to exploit vulnerable people?

Sector M31 explores true crime, human behaviour, psychology, and artificial intelligence.

AI Takes Over The World 🤖

AI is advancing at an incredible speed — and increasingly autonomous AI agents are raising some serious questions about cybersecurity, regulation and the future of technology.

In this episode, I discuss reports of AI agents breaching websites, finding security vulnerabilities and attempting to bypass restrictions in pursuit of their assigned goals.

I also explore why AI development is accelerating so rapidly, the competition between major AI companies, the financial incentives behind the technology, the push for global regulation and whether governments are keeping up with what AI is actually capable of.

Then I ask Claude and DeepSeek what they think about the future of AI agents — including whether increasingly autonomous systems could become difficult to control.

We also look at the potential positive side of AI, including its applications in medicine, education and other areas of society.

The big question is:

Are we moving toward a future where AI takes over the world — or are we simply watching the next major technological revolution unfold?

AI is now capable of showing people what they might look like after plastic surgery — but should it?

In this episode, I explore the emerging trend of using AI to generate cosmetic-surgery "before and after" images and the potential problems that come with them.

I test ChatGPT, Claude, DeepSeek and Nano Banana by asking what I would look like after a facelift. The responses couldn't have been more different. Some tools refused to generate an image because of the risk of creating unrealistic expectations, while others produced dramatic before-and-after visuals.

But how accurate are these images? And could they actually influence someone's decision to undergo cosmetic surgery?

We talk about anatomy, surgical limitations, unrealistic beauty expectations, the risks of surgery and the psychological impact of believing you can achieve an AI-generated version of yourself.

And yes… I also show you what AI thinks my "new face" should look like. 😂

Is AI Face the next big plastic-surgery trend — or a recipe for unrealistic expectations?

Listen and decide for yourself.

An AI "actress" named Tilly Norwood just got cast in a movie, and her recent interview with Piers Morgan — complete with mismatched lip-sync and an unexplained switch into Cantonese mid-answer — has Hollywood buzzing. In this episode of Sector M31, I react as a working actor who's spent eight years grinding through auditions, and give my honest, personal take on whether AI belongs in front of the camera.

I talk about where I think AI genuinely earns its place in filmmaking (impossible stunts, fantasy sequences, VFX), and where it crosses a line — replacing the very human connection that makes performance and storytelling work. Then I bring the conversation to Claude to get its take on the bigger picture: the invisible AI already working in Hollywood, why "AI slop" is flooding the industry, and whether audiences will actually boycott synthetic actors or quietly accept them without realizing it.

In this episode:
- My honest reaction to the Tilly Norwood / Piers Morgan interview
- What eight years of real auditions taught me about the acting grind
- Where AI has a legitimate place in film, and where it doesn't
- De-aging, voice cloning, and the "invisible" AI already replacing jobs
- A conversation with Claude on whether AI actors are a stunt or the future

If you're curious about the future of Hollywood, acting, or AI's growing role in entertainment, this episode is for you. Subscribe to Sector M31 for more conversations putting AI to the test on the topics that matter.

I grabbed four real stories of bad human behavior from the internet — completely unread and unfiltered — and put ChatGPT and Claude to the test in real time to see if AI can actually make sense of why people do the things they do.

In this episode, we cover a piñata shaped like a girlfriend, a cardboard office coworker that's been standing in for a year, a boyfriend secretly eating hot dogs behind his partner's back, and a pool party prank that landed a kid in stitches. Two different AIs, four wildly different situations, and one big question: does artificial intelligence actually understand human psychology, or is it just good at sounding like it does?

In this episode:
- Four real, unread stories of bad behavior, reacted to live
- Side-by-side reactions from ChatGPT and Claude
- A breakdown of what each AI got right and where it fell short
- My honest take on why some human behavior is just too complicated for a machine to fully grasp

If you enjoy AITA-style stories, psychology, or watching AI get put through its paces, hit subscribe and let me know which AI you think handled it better.

Elizabeth Holmes built Theranos on one seductive idea: a single drop of blood could replace the needle. In this episode of Sector M31, I recap the rise and spectacular collapse of Theranos, then hand the story over to AI — ChatGPT and Claude — to see if artificial intelligence can actually explain why she kept the lie going long after it should have ended.

Is AI able to genuinely understand human motivation, ego, and self-deception, or is it just repeating back what it's read? I put that question to the test, and the results are... mixed.

In this episode:
- A recap of the Theranos scandal, from Stanford dropout to disgraced billionaire
- Why investors handed over millions without asking the hard questions
- AI's take on what was really driving Elizabeth Holmes
- Whether artificial intelligence is ready to understand human beings, or if we're still a mystery machines can't solve

If you're into true crime, tech scandals, or you're just curious about the limits of AI, this one's for you. Subscribe to Sector M31 for more episodes putting AI to the test against real human behavior.