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Season One Wrap
Send us a textThree months ago we set out to make complex tech feel simple for smart people. Today, we close Season 1 with a bonus episode that’s a candid debrief on what worked, what didn’t, and the practical concepts you told us made a difference at work and in everyday life. We answer listener questions and Hugh fails to answer Hannah’s trivia questions (in a throwback to Episode 1).We start with reflections on learning the craft of podcasting while defining our mission and chemistry. Favourite episodes resurface—especially the outages deep dive—because they blend clear systems thinking with human stories and real fixes. Hannah share she learnt the most from our episode on LLMs (which was definitely the hardest episode for Hugh to prep for). From there we jump into listener Q&A and tackle the acronyms that clutter meetings: VPN as an encrypted tunnel that blocks man-in-the-middle attacks, URL as these days a synonym for “web address”, and HTTP versus HTTPS as the protocol that is the backbone of the modern web. We keep the momentum with SQL and CSV as the backbone of analytics, plus LAN and WAN to map your home, office, and global networks. Along the way we bust a persistent myth: Wi‑Fi isn’t “wireless fidelity”; it’s simply a name that stuck (and one that was invented in Australia!).Cloud computing takes centre stage as we lay out how AWS, Azure, and Google Cloud grew from internal platforms into the engines of modern startups. We talk trade-offs: price, performance, managed services, and the undeniable friction of switching providers. Then we answer a deceptively simple question: how do different programming languages “talk”? The practical path is APIs and shared contracts, with compilers and files as the quiet glue that lets JavaScript front ends call Java services and microservices cooperate at scale. For fun, we tip our hats to tech lore—from YouTube’s dating-app origin to Bluetooth’s Viking name—and why trivia can be both marmite and memorable (and why a Vegemite analogy isn’t the same!).We’re lining up more expert interviews and deeper dives into data centres, energy use, Bitcoin mining economics, quantum timelines, and chip fabrication. If season one made you a little bit smarter, help us reach tens of thousands more learners: follow, share with a friend, and leave a review so we can shape season two around your biggest questions.Like, Subscribe, and Follow the Tech Overflow Podcast by visiting this link: https://linktr.ee/Techoverflowpodcast
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31:41
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31:41
Inside Waymo’s Robotaxis with Nick Pelly
Send us a textA taxi pulls up with no one in the front seat. Would you get in? We invited Waymo director Nick Pelly to take us from that first uncanny moment to the engineering that makes a driverless ride feel calm, confident and, by the data, far safer than most humans behind the wheel.We walk through the full autonomy stack in plain English: how cameras, radar and LiDAR fuse into a single view of the world; how perception, prediction and planning work together to thread through double‑parked vans, nudge through gridlock and still behave like a good road citizen. Nick explains why Level 4 autonomy is about design domain as much as capability, why hardware still matters, and how redundancy handles blocked sensors, grime or failures without drama. We dig into machine learning at scale, from training on diverse city data to tens of billions of simulated miles, and how teams tune precision and recall so the car avoids both missed hazards and needless hard braking.Beyond the ride, we zoom out to the business and the city. Phoenix offered a launchpad to build the marketplace, charging and fleet operations; San Francisco demanded handling a busy city and human‑like judgement; London beckons with dense streets and weather. We explore what happens as adoption grows: fewer parking lots, smoother traffic, motorway platoons, even intersections that need fewer lights when vehicles coordinate. Nick also shares his focus area—reliability and freeway fail‑safes—designing for worst‑case scenarios so the system exits danger gracefully at speed; this episode was recorded a week before Nick and the team announced highway driving!If you’re curious about autonomous vehicles, safety, AI, urban mobility or just want to know what “robotaxi” really means, this conversation turns buzzwords into something you can picture—and maybe soon, ride. Enjoy the episode, then follow and share the show, and leave a quick review to help us bring you an even bigger season two.Like, Subscribe, and Follow the Tech Overflow Podcast by visiting this link: https://linktr.ee/Techoverflowpodcast
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43:13
Hacking, Part #2: Pay 2.5 Bitcoin and We Will Unlock Your Computers
Send us a textEver joined a “Guest Wi‑Fi” that looked legit, rushed through an email on the way to the airport, or reused a password because it was easier? Those small shortcuts are exactly where hacks begin. We open the curtain on how attacks actually work and, more importantly, the simple habits that stop them.We break down malware in clear terms: old‑school viruses that ride dodgy attachments, worms that replicate on their own, and Trojans disguised as free software. Then we step into the street‑level reality of man‑in‑the‑middle attacks using rogue hotspots, why HTTPS and a reputable VPN matter, and how attackers can read or even alter your traffic if you don’t encrypt. On the application side, we demystify SQL injection with concrete examples and show how basic engineering hygiene prevents catastrophic data leaks.Credentials get a full audit: why password reuse fuels credential stuffing, how to build unique, strong passphrases with a password manager, and when to choose authenticator apps over SMS to defeat SIM‑swap. We also explore passkeys, the passwordless future that uses cryptography tied to your device and makes phishing far harder. From there, we move into company defences: phishing simulations, penetration testing, red team versus blue team drills, and unglamorous but vital basics like patching and tested backups. A crazy ransomware story reminds us that backups and culture beat panic every time -- and Hugh's friend still has 2.5 Bitcoin from the attack (with a fantastic twist at the end).Along the way, we talk economics of cyber crime, why you only need to be harder to breach than your peer group, and how ethical hackers and bug bounty programmes improve resilience. Subscribe for more practical tech explainers, share this with someone who needs a security refresh, and leave a quick review so others can find the show. What’s the one security habit you’ll change today?Like, Subscribe, and Follow the Tech Overflow Podcast by visiting this link: https://linktr.ee/Techoverflowpodcast
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37:22
Hacking. Part #1: How A Retail Giant Fell to Ransomware
Send us a textA fake contractor calls the help desk, a password gets reset, and suddenly a national retailer has hackers inside. We open the door on the human side of hacking—how believable stories and helpful habits become the first domino—then trace the technical steps that turn a small foothold into a system‑wide crisis.We walk through the anatomy of the Marks & Spencer breach: social engineering as the entry point, slow‑burn privilege escalation, and the moment attackers reached the Active Directory—the store of who can do what. From there, it’s a short hop to ransomware detonation and double extortion, where every machine is unusable and stolen customer data adds pressure to pay. Along the way, we translate hashing, brute force, and admin access into plain English, and we talk candidly about what detection looks like when it actually works: least privilege that’s enforced, behavioural alerts that catch odd access patterns, and teams empowered to say no.The hardest lesson lands in recovery. Backups that live on the same network get encrypted or deleted; backups that are never rehearsed don’t restore on time. We break down air‑gapped, immutable backups, how to test restores, and why a clean rebuild is sometimes the only safe path. We also connect this case to higher‑stakes incidents at pipelines and hospitals, showing why attackers chase critical bottlenecks and how zero‑trust identity, MFA, network segmentation, and vendor risk controls blunt that leverage. It’s a story about culture as much as code: small process choices—like verifying contractors—change outcomes.If this breakdown sharpened your thinking, follow the show, leave a quick review, and share it with a teammate who owns identity, help desk, or backups. Your support gets us to series two—and might just get Hannah to Melbourne.Like, Subscribe, and Follow the Tech Overflow Podcast by visiting this link: https://linktr.ee/Techoverflowpodcast
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AI, Without The Hype: ChatGPT and LLMs. Part #2
Send us a textFinally, a podcast that explains how AI, LLMs, and ChatGPT work without any hype, fluff, or hyperbole. This episode is aimed at smart people who aren’t in tech and just want to be able to understand the basics. Join host Hannah Clayton-Langton as she discusses the topic with former Google VP and OG AI expert, Hugh Williams.We start by separating AI, machine learning, and LLMs, then explain why generative systems are not search. Instead of retrieving pages, an LLM synthesises new text using patterns learned from trillions of tokens. That leap was unlocked by transformers, the architecture that parallelises processing and models relationships between words through attention. Add weeks of GPU-heavy training in massive data centres and you get astonishing next-word prediction with long-range context.Then comes the human layer. We talk through reinforcement from human feedback that nudges models toward helpful, safe behaviour, and the safety heuristics that block harmful queries or intercept trivial ones. We also get candid about limits: hallucinations that produce confident nonsense, bias from data and raters, weak arithmetic unless the system calls an external tool, and uneven image generation that’s improving fast. Along the way we share practical tips: how to compare outputs across models, when to fact-check with a second system, and why grounding responses in reliable sources matters.If you’ve heard about trillion-token training runs, NVIDIA GPUs, and “stochastic parrots” but want a clear, human explanation, this one’s for you. You’ll learn how LLMs actually work, why they feel so capable, and how to use them at work like a fast intern whose drafts still need your judgement. Enjoy the deep dive, and if it helps you explain AI to a friend, subscribe, leave a review, and share your favourite takeaway with us.Like, Subscribe, and Follow the Tech Overflow Podcast by visiting this link: https://linktr.ee/Techoverflowpodcast
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39:24