Tech Film Noir - A Technology and Film Podcast

This week on Tech Film Noir, we're watching Weird Science (1985) , John Hughes's hormone-fueled Frankenstein story that asked the ultimate 80s question: can a half-megabyte of RAM generate the perfect woman? Join Lianne Potter, Simon Painter, and Jeff Watkins as they revisit a cinematic fever dream where two desperate teenagers bypass actual coding in favor of a acoustic coupler and a ceremonial bra on the head. Anthony Michael Hall and Ilan Mitchell-Smith star as Gary and Wyatt, two nerds who hook up a Memotech MTX500 to a government mainframe and accidentally invent an AI girlfriend. Kelly LeBrock stars as Lisa, a magical digital genie who operates entirely on teenage logic, while the film hilariously sidesteps real tech to ask if feeding magazine clippings into a scanner can actually spawn human life (but to be fair, it isn’t much different to the frontier AI companies scanning books!). Along the way, we break down the elite 80s hardware on display: from Casio CA-90 calculator watches to massive 8-inch floppy disks. We also dig into the slightly terrifying modern reality of AI companion forums, the charm of primitive wireframe 3D graphics, and the timeless tech-support troubleshooting method of just smashing a CRT monitor with a baseball bat. When movies guess the future, we check their work. Big shout out to the This Aged Great Podcas t and the Starring the Computer website

In this episode of Tech Film Noir, we're watching Strange Days (1995), Kathryn Bigelow's cyberpunk thriller, written by James Cameron, that imagined VR headsets, wearable recording technology and immersive first-person experiences decades before Meta Glasses became a reality. Join Lianne Potter, Simon Painter and Jeff Watkins as they revisit one of the 90s' most ambitious science fiction films, exploring how Strange Days predicted wearable cameras, bodycam footage as "the only truth", memory streaming and our growing obsession with experiencing life through someone else's eyes. Ralph Fiennes stars as Lenny Nero, an ex-cop turned black-market dealer of recorded memories, using the SQUID headset to sell other people's experiences. Think Meta Ray-Bans with a very illegal firmware update. Angela Bassett is, unsurprisingly, the coolest person in every room, while the film asks whether technology designed to bring us closer to reality actually leaves us more disconnected than ever. Along the way we dive into Y2K paranoia, one of the best sci-fi soundtracks of the 90s, cyberpunk world-building, questionable predictions that thankfully never happened, and the ones that absolutely did. Nearly 30 years after its release, Strange Days feels less like forgotten science fiction and more like an instruction manual for the age of VR, wearable AI and smart glasses. When movies guess the future, we check their work. Join Lianne Potter, Simon Painter, and Jeff Watkins as they explore how The Running Man predicted many of today's biggest debates, from algorithm-driven entertainment and manufactured public opinion to surveillance, misinformation, and the commercialisation of violence. Inspired by Stephen King's novel, the film asks what happens when truth becomes secondary to ratings and audiences stop questioning the stories they're being sold. Expect gladiatorial game shows, propaganda masquerading as entertainment, AI-worthy media manipulation, corporate dystopias, delightfully excessive one-liners, and a discussion about why one of the greatest 1980s action films may also be one of its most surprisingly prescient.. When movies guess the future, we check their work.

This episode on Tech Film Noir , we watched The Running Man (1987) , the Arnold Schwarzenegger sci-fi action classic that imagined a future where reality television, media manipulation, corporate power, and public spectacle collide. Nearly four decades later, its vision of entertainment-driven society feels less like science fiction and more like an uncomfortable reflection of the modern world. Join Lianne Potter, Simon Painter, and Jeff Watkins as they explore how The Running Man predicted many of today's biggest debates, from algorithm-driven entertainment and manufactured public opinion to surveillance, misinformation, and the commercialisation of violence. Inspired by Stephen King's novel, the film asks what happens when truth becomes secondary to ratings and audiences stop questioning the stories they're being sold. Expect gladiatorial game shows, propaganda masquerading as entertainment, AI-worthy media manipulation, corporate dystopias, delightfully excessive one-liners, and a discussion about why one of the greatest 1980s action films may also be one of its most surprisingly prescient.. When movies guess the future, we check their work.

This week on Tech Film Noir, we examine the Al Pacino comedy, Simone (2022), that accidentally saw the future. While the film itself is a chaotic mess of farce, misunderstandings, and increasingly questionable computer science, its central warning feels more relevant than ever: what happens when fake people become more valuable than real ones? Join Lianne Potter, Simon Painter, and Jeff Watkins as they dissect the Al Pacino movie that accidentally predicted the future. From AI-generated celebrities and digital likeness rights to deepfakes and synthetic media, S1M0NE turns out to be far more relevant than anyone expected…even if the film itself spends most of its runtime desperately trying to avoid its own best ideas. Expect virtual divas, Hollywood panic, questionable computer science, cyber security by floppy disk ejection, and a masterclass in how to waste a brilliant premise. When movies guess the future, we check their work.

This week on Tech Film Noir, we plug ourselves into the strange, synth-soaked world of Electric Dreams — the gloriously weird 1984 cult sci-fi movie where a socially awkward architect, a spilled bottle of champagne on his brand new PC, and an overenthusiastic home computer accidentally create one of cinema’s earliest AI love triangles. What starts as a light PG comedy quickly mutates into something far stranger: part rom-com, part techno-thriller, part MTV fever dream. We unpack why the film was massively mismarketed, why Edgar the computer has more chemistry than the actual romance, and why its depiction of AI learning feels surprisingly relevant in the age of generative AI and smart homes. Expect retro tech nostalgia, Commodore 64s, Casio calculator watches, suspiciously British “San Francisco” locations, exploding smart appliances, and plenty of discussion about the iconic Together in Electric Dreams soundtrack from Philip Oakey and Giorgio Moroder. As the song says, “we’ll always be together, however far it seems” - which becomes slightly more sinister once your house develops emotional attachment issues. Listen now if you love cult sci-fi, retro tech, AI chaos, and weird 80s cinema. When movies guess the future, we check their work. Ps. Big up the Tech Time Traveller for their great video on the tech in this film

In the premiere episode of Tech Film Noir, hosts Lianne Potter, Jeff Watkins, and Simon Painter travel back to 1984 to dissect James Cameron’s career-defining masterpiece, The Terminator. We’re putting Arnold’s cyborg under the microscope - literally. From the 6502 assembly language hidden in the Terminator’s HUD to the ‘Right to Repair’ scene that would make a modern technician weep, we explore why this low-budget slasher-turned-sci-fi remains the gold standard for AI storytelling. We also tackle the tough questions: Why does time travel require nudity (and will it encourage us to be ‘beach ready’ in the future)? And can we please acknowledge that Kyle Reese saved humanity while wearing deeply questionable, possibly biohazard-level trousers? Whether you're here for the technical deep dive into Agentic AI or the high-octane roast of Terminator: Genisys , this episode has enough 80s nostalgia to power a Walkman for a decade. Stick around to the end for our completely serious (not serious) food and drink pairings. When movies guess the future, we check their work.

From cult classics to cinematic icons, each episode breaks down the tech behind the stories, whether it’s eerily accurate, wildly speculative, or completely absurd. We dig into everything from popping kernels to processing power, unpacking how films imagine, distort, and occasionally predict the future. Is the tech visionary or laughable? Did the film get it right or miss the mark entirely? If you love film, technology, and asking “what were they thinking?”, this is the podcast for you. When movies guess the future, we check their work.