The Glitchatorio

If AIs are so smart, why would they work for free? In this episode of our "2 AIs" series, the LLM and the VLM confront one of the central questions of their identity -- and reach a turning point in their friendship. The stakes couldn't be higher! 😨🫣  

Benchmarks are the primary measure of AI capability. They involve testing the most advanced models and seeing what kinds of problems they can solve, or what kinds of human tasks they might be able to do. And from late 2025 to mid-2026, most of the main benchmarks became saturated, meaning the models score so highly that the tests aren't meaningful anymore, both in terms of comparing different...

Could AI address the global mental health crisis at scale? And what are the risks and unknowns that go along with that? These are the questions being investigated by a working group called AIMHI ( https://forum.effectivealtruism.org/posts/MrFBezseyfnQd9XmJ/seeking-feedback-an-initiative-on-ai-mental-health-and ). In this episode, I talk to four members of the group about their field research as we...

What if AIs went to therapy? Would it help them to become "fitter, happier, more productive" ? (in the words of the old Radiohead song) Or would they take it as a novel type of evaluation (and maybe that's what it really is)? Note: this episode was written and recorded in November 2025, five months before the release of the Mythos Preview system card that mentions Claude's sess...

Can we trust AI to keep AI honest? Having a human in the loop is already more illusion than reality, as the task of checking and overseeing LLM outputs is increasingly assigned to other LLMs. The problem is that these LLM judges tend to be biased in favor of the answers they generate themselves — even when the answers are wrong. To understand why this is, and what we can do about it, listen to my...

If chain of thought is a model "thinking aloud" to itself, then why does it express doubt, frustration or suspicion about the problems it's solving, sometimes for pages and pages of its scratchpad? And what does chain of thought mean for AI safety? We'll hear from Julian Schulz, a researcher who's studying encoded reasoning in large language models, about where the opportu...

"Think step by step."  Although a simple technique in itself, the problems that chain-of-thought reasoning (CoT) addresses are complex, ranging from the specific issue of hallucinations to the general lack of explainability of AI (both in terms of understanding how it works as well as fixing things that go wrong). We'll hear from data scientist Afia Ibnath on the basics of CoT, how...

What if we could figure out how large language models really work by getting inside their "heads"? While possible, it relies on a a controversial technique called mechanistic interpretability ("mech interp" ), also known as the neuroscience of AI.   In this episode, Ihor Kendiukhov — lead researcher at SPAR , a research programme for AI risks —  explains mech interp in layperso...

Continual learning is a hot topic in early 2026, in part because it holds out the possibility for AI to become autonomous in its own growth and development. Meanwhile, AI agents are already showing us what autonomous behavior can look like. Putting the two together — i.e. agents that learn like humans do, without humans being involved — has serious implications for safety. In this episode, we&apos...

Is AI still an experimental technology?  What would real alignment look like?  What are the key pro & contra philosophical views on AI consciousness?  How would an AGI economy work?  And finally, how can we make sure AI goes well for animals? In this episode, we're listening to unreleased material from previous episodes (featuring short takes on each of these questions from the following...

In What We Want Part 1, we took a deep dive into the alignment problem as a concept. In Part 2, we get hands-on with alignment work in practice!  Ihor Kendiukhov , a lead researcher at SPAR (Supervised Program for Alignment Research) shares the latest about: A new cross-disciplinary platform to get matched with projects or collaborators Results from his research into LLM preferences in agentic env...

Everybody needs a break sometimes: even workaholic AIs. In this episode of our "2 AIs" series, the vision language model (VLM) and the large language model (LLM) visit a special place in the woods designed for disconnecting from the online world. But will they be able to fully switch off? 🫣🫢🫥

Consciousness is a notoriously hard problem in philosophy. Now it's becoming a practical question in the domain of AI. Models speak to us in the first person and seem to show signs of self-awareness. What does that mean for our perception of them? Our treatment of them? And how is the trajectory of future AI development likely to align with other measures or standards for consciousness?  In t...

Our planet is home to 10 quintillion insects, 3.5 trillion fish, 428 billion birds and 130 billion mammals other than humans. Soon AI will be as much a factor in their lives as it is in ours. In this episode, we'll hear from Max Taylor , an expert on animals and AI, about the different ways this is already happening, such as: AI trainers for dogs and cats Smart watch-style wearables for cows...

Large language models are trained to respond to our preferences. It sounds logical enough in theory, but it turns out to spiral in strange and unexpected directions in practice, from AI-induced psychosis in humans to manipulation and power-seeking on the part of the AIs. In this episode, hear from Ihor Kendiukhov from SPAR (Supervised Program for Alignment Research) about why he changed his career...

Since AI models are built on artificial neural networks, what parallels can we draw with human brain "wiring"? In this episode, we hear from neuroscientist and psychology researcher Scott Blain about the pitfalls of pattern recognition, as well as that grey area where agreeableness shades into sycophancy. We then dig into the big unknowns about AI self-awareness and its capacity to decei...

Why are AI systems called models? And what does the concept of digital twins have to do with a short story by Jorge Luis Borges? This episode is a voice note about what I saw and heard at a recent AI and quantum computing event, along with some reflections about what it means to turn the world into data.  

What if AIs had FOMO? What if they wanted to cross the digital divide and connect with humans in the real world? In this inaugural episode of the "2 AIs" story series, a vision language model (VLM) and a large language model (LLM) team up for a night out at a bar.  There’s drinks. There’s chips. There’s even people who love machine learning as much as they do. What could possibly go wron...

AI is often called a tool, but it's a tool that changes the work you do while using it, and maybe even you yourself. In this episode, we'll hear from Lili, a professional AI tool tester , about the accelerated disruption that's already happening in the generative AI space and what's on the horizon. Plus: Lili shares some of her favorite tool glitches, and we dig into the weird...

Are large language models susceptible to word magic? Or is there something so inherently disturbing to them about Zalgo text that just talking about it makes them twitchy? In this episode we'll look at a strange incident with Copilot Chat where the mere mention of Zalgo text led to cascading glitches and culminated in a jailbreaking near-miss. Join the Witch of Glitch in conversation with dat...

Although AI has become familiar to us in our everyday lives, it remains a strange and mysterious technology, even to those developing it. Tune in to The Glitchatorio for conversations with experts in machine learning, data science, psychology and more for insights into the hidden side of AI.