Unreal Intelligence

karlsorochinski

A podcast focused on humanizing AI—exploring its history, real-world value, societal impact, and the rapid evolution shaping our future. Unreal Intelligence is built with AI as a true force multiplier. I use AI to support research, assist in writing, and validate the accuracy of the ideas presented. Episodes are delivered using a voice clone, and that choice is intentional—this podcast doesn’t just talk about AI, it demonstrates it in practice. Transparency is non-negotiable. There’s no attempt to obscure where or how AI is used. Instead, this podcast embraces openness as a core principle: showing what’s possible while staying grounded in honesty and authenticity. Inspired by the spirit of Rush’s The Spirit of Radio—that even with all the machinery behind modern creation, what matters most is staying open-hearted and honest—Unreal Intelligence aims to prove that technology doesn’t replace humanity, it amplifies it.

Episodes

  1. 23h ago

    AI Made Me Do It

    Remember when Walgreens closed stores and blamed shoplifting — and then their own CFO admitted “maybe we cried too much”? The real reason was cost-cutting; the crime was the cover story. In this episode I argue that “AI did it” has become 2026’s version of that exact move: a plausible, external, un-arguable reason that lets leadership announce layoffs without owning the decision underneath.  We follow the money. The 2023 tech-layoff wave — over a quarter-million jobs — was the post-COVID over-hiring correction, and almost nobody blamed AI. Two years later the same cuts, at the same kinds of companies, get relabeled “AI-driven efficiencies.” I break down what’s actually driving most cuts (over-hiring, expensive capital, and the permanent shareholder demand to protect margin) — while keeping myself honest about the narrower, real ways AI genuinely is reshaping work.  Then the part that matters: what the cover story costs you. It feeds the fear of the three-in-four workers who already don’t feel their jobs are safe, and it burns the trust you can’t buy back. I close with a simple framework — separate the decision from the tool — plus a Monday-morning playbook for reading your own company when the AI-layoff memo lands. This isn’t AI-hype or AI-doom. It’s about telling the truth when jobs go away.

    22 min

  2. Jul 6

    Will This Fable Be A Cautionary Tale?

    Anthropic shipped Fable 5 — its most powerful public model to date — on June 9th. Three days later the U.S. government switched it off. By June 30th it was back. Everyone read that shutdown-and-return as the system working. I read it as a preview of the question nobody’s actually asking: not “is this model safe for the public,” but “is it safe in the hands of the people who get to decide what ‘safe’ even means?”  I walk it straight. First, what actually happened — the verified timeline, the Amazon researchers who bypassed Fable 5’s guardrails and got it to demonstrate exploiting a software vulnerability, and Anthropic’s fair counter that the same behavior shows up on weaker models and the technique is now blocked 99%+ of the time. The real story isn’t the jailbreak; it’s the cycle — ship, panic, intervene, re-release — that every frontier model now runs. Then the heart of it: I steelman government control honestly (someone should be able to hit the brakes on a genuinely dangerous capability) before flipping it — the exact tool declared too dangerous for you was fine for the state. That’s not safety. That’s concentration risk wearing a safety costume, and any leader who’s audited a single-point-of-failure already knows the questions to ask.  Finally, the receipt from history: Cambridge Analytica. One quiz app, ~270,000 downloads, up to 87 million profiles harvested (70.6 million in the U.S.), psychographic microtargeting in the 2016 campaigns — and it ran on crude 2014-era tech. Now hand that same intent a frontier model: not 1000x more data, 1000x more precision, individually optimized and continuously tested on you specifically. The trust question stops being abstract. Are we writing a good story here? Only time will tell — but the ending depends on the governance we build now, not on how smart the model gets.

    22 min

  3. Jun 29

    Safe or Sorry?

    In one week this June, the United States took its two most powerful AI models off the table — and China gave its best one away for free. Same week, two countries, two opposite bets on the future. This episode is about the phrase we all grew up on — “better safe than sorry” — and why it may be the most expensive instinct we have right now.  I walk it straight, no spin. First, the week America hit the brakes: a June 12–13 export-control order forced Anthropic to suspend Fable 5 and Mythos 5 — even for its own foreign-national employees — after a reported jailbreak of its top cybersecurity model, plus the June 2 executive order standing up a voluntary, 30-day pre-release review with the power to anoint “trusted partners.” I steelman the security case honestly — frontier cyber-capability really is dual-use — before asking the uncomfortable question: when pulling a model becomes a tool of policy, what does that do to the appetite to push the frontier at all?  Then, the opposite bet: Zhipu AI’s GLM 5.2 — 753B parameters, a usable 1M-token context, released under an unrestricted MIT license at roughly one-sixth the cost of the closed frontier ($1.40/$4.40 vs Claude Opus 4.8’s $5/$25 and GPT-5.5’s $5/$30), at near-parity on real benchmarks. That cost gap isn’t a tech footnote — it’s a margin advantage that flips every build-vs-buy spreadsheet, which makes open-vs-closed a P&L question, not a philosophy one. Finally, the oldest lesson there is: politically-driven pauses don’t stop a technology, they relocate it — and the economic ownership goes with it. Security is real, so govern the genuinely dangerous, narrowly. But don’t confuse throttling innovation with keeping people safe. Mistake control for security and you get neither: safe AND sorry.

    22 min

  4. Jun 22

    Pay Me Now or Pay Me Later

    Somewhere in your company right now, an AI agent is writing code nobody is reading. That's not a technology problem — it's an invoice you're signing without knowing the amount. This episode is about the three bills coming due across the entire industry: the AI-generated code that looks cheap until you have to maintain it, the "clean" data nobody actually agrees on, and the accountability vacuum that opens up the moment you treat a tool like it can own a decision. Karl walks through the real cost of each — from GitClear's data showing copy-pasted code surging while refactoring collapses, to the hundred-times cost difference between LLMs and classical ML on structured tasks — and gives you one concrete Monday-morning move before these invoices start compounding interest. Knight Capital. Zillow. Klarna. McDonald's. The pattern is the same every time. You can pay now or pay later. Later is where the zeros get added. Subscribe so you don't miss what's next.

    22 min

  5. Jun 15

    Power Tools on a Sinking Ship: How Corporations Are Misusing AI

    Everyone’s buying AI to fix email overload — and nobody’s asking why we have this many emails in the first place. This week I’m going after the most expensive open secret in corporate tech: most enterprise AI deployment is theater. Companies are pouring billions into licenses pointed at surface-level text work while the broken processes underneath keep generating the noise. MIT’s research says 95% of GenAI pilots fail to deliver ROI. The models aren’t the problem. The thinking is.  I walk through the two human failure modes wrecking AI initiatives — overtrust and refusal. On the overtrust side: the Air Canada chatbot ruling that made “the AI said it” legally your problem, the lawyers sanctioned for ChatGPT-invented case law, the Bard demo error that wiped $100 billion off Alphabet, and why hallucination is an architectural feature you manage, not a bug you wait out. On the refusal side: the skeptics in your org who won’t touch the tool — and why losing your most experienced people from the AI loop creates the worst possible risk distribution.  Then the fix: treat AI like a smart, fast, occasionally-wrong junior co-worker embedded in redesigned workflows — never an oracle bolted onto broken processes. I close with a four-step Monday-morning playbook: one measured pain point, one named human owner, real outcome tracking, and a gentle on-ramp for your skeptics. Process first, AI second, supervision always.

    24 min

  6. Jun 8

    Beyond ChatGPT: The AI Blind Spot Costing Science-Driven Companies Millions

    Beyond ChatGPT: The AI Blind Spot Costing Science-Driven Companies Millions

    24 min

  7. Jun 1

    Who am I to argue?

    A senior director just handed her go-to-market strategy to a chatbot. Didn't push back once. When Karl asked why, she said seven words that should worry every leader using AI right now: "Who am I to argue with it?" That's the real crisis. Not hallucinations. Not job loss. Deference. Smart, experienced people outsourcing their judgment because the model sounds more confident than they feel. This episode makes the case that deference is the single biggest threat to value creation in enterprise AI — and it's already inside your org. You'll walk away with: - Why confident-sounding output is a feature of how these models are trained, not evidence they're correct - The "argument rule" — a one-line process change that measurably improves AI output quality without slowing anyone down - The inversion drill: how to get the model to critique its own work before you ship anything that matters Your judgment is the asset. The model is the variable. Don't let that flip. New episodes weekly. Subscribe wherever you listen.

    25 min

  8. May 25

    The 5% Problem: Why Your AI Agents Aren’t Paying Off

    Ninety-five percent of corporate AI projects are returning basically nothing. Not a little — nothing. And the MIT research behind that number isn't an indictment of the technology. It's an indictment of how companies pick, scope, and measure AI work. Karl's position: the failure is organizational design wearing an AI costume. The models are fine. The deployment isn't. You'll walk out with a six-step checklist for building agents that actually pay off, a clear framework for why "find the dollar before the use case" changes your prioritization completely, and an honest look at why broad mandates like "transform customer service with AI" aren't projects — they're wishes. If you've got a pilot that looked good in the demo and went quiet in real work, this episode is the postmortem you didn't know you needed. Follow Unreal Intelligence so you don't miss the next one.

    23 min

  9. May 19

    Your AI Ban Is Your Biggest Security Risk

    A bank blocked ChatGPT at the firewall, sent the all-staff email, and felt good about it. Six months later, forty percent of their knowledge workers were using it anyway — on personal phones, pasting in whatever they needed, completely invisible to the security team. The ban didn't stop the AI. It stopped the company from seeing it. That's the argument Karl makes in this episode: a blanket AI ban isn't a control. It's a blindfold. And it may be the single biggest security gap in your company right now. You'll come away knowing exactly how to pull a shadow usage report and what to do with the number you find. You'll understand what enterprise AI contracts actually give you that a personal account never will — and why that difference matters legally, not just technically. And you'll get five concrete moves to replace your ban with something that creates real visibility and real governance. More usage, less risk. That's not a contradiction. It's the whole point. If you've got a ban in place — or you're about to put one in — this one's worth your commute.

    28 min

  10. Feb 19

    Unreal Intelligence - The History of AI

    EKA Technology, LLC brings you Unreal Intelligence a podcast on the history, use and trends in AI

  • 10 Episodes

About

A podcast focused on humanizing AI—exploring its history, real-world value, societal impact, and the rapid evolution shaping our future. Unreal Intelligence is built with AI as a true force multiplier. I use AI to support research, assist in writing, and validate the accuracy of the ideas presented. Episodes are delivered using a voice clone, and that choice is intentional—this podcast doesn’t just talk about AI, it demonstrates it in practice. Transparency is non-negotiable. There’s no attempt to obscure where or how AI is used. Instead, this podcast embraces openness as a core principle: showing what’s possible while staying grounded in honesty and authenticity. Inspired by the spirit of Rush’s The Spirit of Radio—that even with all the machinery behind modern creation, what matters most is staying open-hearted and honest—Unreal Intelligence aims to prove that technology doesn’t replace humanity, it amplifies it.

Information

  • Creator
    karlsorochinski
  • Years Active
    2K
  • Episodes
    10
  • Rating
    Clean
  • Copyright
    © Copyright 2026 All Rights Reserved
  • Show Website
    Unreal Intelligence