Prior work suggests that language models, while trained on next token prediction, show implicit planning behavior: they may select the next token in preparation to a predicted future token, such as a likely rhyming word, as supported by a prior qualitative study of Claude 3.5 Haiku using a cross-la…

Forklift safety expert Jackson Phillips discusses how AI-powered collision avoidance is helping manufacturers and warehouses move from reactive safety measures to proactive prevention.

Are you sitting down? Because we need to talk about next year. We just finished analyzing the mind-bending interview between Tom Bilyeu and AI safety expert Dr. Roman Yampolskiy, and the conclusion is impossible to ignore: Humanity might have a 99.9% probability of extinction, and the clock runs out in 2027. In this episode, we react to Yampolskiy’s terrifying prediction that we are sprinting toward an "Event Horizon"—the moment Artificial Superintelligence (ASI) becomes smarter than us in every domain. Once that happens, he argues, our ability to control it vanishes. Why? Because a superintelligent god doesn’t want to be turned off. We break down the "Uncomfortable Truths" of this interview: - The 2027 Deadline: Why Yampolskiy believes the "Uncontrollable God" arrives in just 12 months. - The Alignment Problem: Why it’s mathematically impossible to predict the behavior of something smarter than you. - The "Elite" Solution: The controversial idea that only a handful of developers have the power to stop the arms race. - The Way Out: Why shifting back to Narrow AI (specialized tools like medical bots) might be the only way to save our species while still enjoying tech benefits. This isn’t science fiction anymore; it’s the calendar. Join us as we debate: Is it time to pull the plug on AGI before it pulls the plug on us? 👇 Hit play to arm yourself with the facts before the timeline shifts.

I have a 3-year-old son.

Is humanity ready to parent a god-like teenager? 🍼🤖 We just watched the explosive NBC News interview with Anthropic CEO Dario Amodei, and if you aren’t paying attention to what happens between now and 2026, you need to listen to this episode immediately. In this deep-dive reaction, we break down Amodei’s chilling yet hopeful warning: that Artificial Intelligence is currently like a powerful, unpredictable "teenager"—brilliant, capable of massive destruction (or creation), but lacking the maturity to know right from wrong. Amodei warns we are sprinting toward a critical threshold of risk by 2026, where the "adults in the room" (regulators and transparent researchers) must step in before it's too late. In this episode, we uncover: - The "Teenager" Analogy: Why Amodei believes current models possess immense power without the necessary social safeguards. - The 2026 Deadline: Why the next few years are the "danger zone" for autonomous weapons and biosecurity threats. - Profit vs. Safety: The controversial push for companies to publish their "danger research" instead of hiding it. - The Medical Miracle: The cautious hope that AI could cure diseases and solve scientific mysteries—if we survive the adolescence phase. Are we raising a Nobel Prize winner or a delinquent? Join us as we dissect the most important interview of the year and ask the hard question: Can we align AI motivations with human values before the teenager moves out of the house? 👇 Hit play to understand the future before it arrives.

Musk’s viral warning about ChatGPT sparks lawsuits and backlash. What’s proven, what’s alleged, and why AI safety just got real.

PhD Project - GeoDataMonitor: Towards monitoring usage of geospatial datasets in machine learning models at King’s College London, listed on FindAPhD.com

Let’s be real: We are currently building a digital god in a basement, and according to Professor Stuart Russell, we forgot to include a "kill switch." In this episode, we are reacting to the bone-chilling interview on The Diary of a CEO that has the tech world in a panic. Russell, one of the world's most respected AI experts, isn't just worried about AI taking your job—he’s worried about it taking our species. We break down the "black hole" of economic gravity that is forcing companies to ditch AI safety protocols in a reckless sprint toward Artificial General Intelligence (AGI). If you think we can just "turn it off" if things go south, think again. We dive into the alignment problem and the terrifying reality of machine self-preservation. Why would a superintelligence let you shut it down when it has an objective to complete? We also tackle the existential dread of a future without work: if humans are no longer the dominant intelligence, what exactly is our purpose? What we’re unpacking in this AI deep-dive: - The Fast Takeoff Scenario: Why the jump from "smart" to "all-powerful" might happen in the blink of an eye. - Profits vs. Survival: How the race for AGI became an unregulated gold rush that ignores the risk of human extinction. - The Alignment Glitch: Why giving a machine a goal without "human values" is a recipe for global catastrophe. - Meaning in the Machine Age: Stuart Russell’s take on how we survive (and find joy) when we are no longer the smartest ones in the room. The clock is ticking, and the "Takeoff" has already begun. Whether you're a tech optimist or someone just trying to understand the Steven Bartlett interview, this breakdown is the reality check you’ve been waiting for. 🔊 LISTEN NOW to find out if we can still steer the ship—before the AI takes the wheel. Don't want to be left behind in the AGI race? Hit that SUBSCRIBE button and leave a review to join the conversation! Share this with your friend who thinks AI is "just a chatbot"—they need this wake-up call.

YouTube video by Women in AI Research WiAIR

OpenAI has updated its whistleblower policy to allow employees to report concerns to regulators without retaliation, following California's SB 53 law.

Anthropomorphic AI safety language misplaces agency, shielding designers and institutions from accountability for engineered harm.

A 2026 AI discovery reveals systems behaving beyond prediction, raising new questions about control, transparency, and the future of...

Machine unlearning (MU) for large language models has become critical for AI safety, yet existing methods fail to generalize to Mixture-of-Experts (MoE) architectures. We identify that traditional unlearning methods exploit MoE's architectural vulnerability: they manipulate routers to redirect quer…

<div> The rapid deployment of large language models (LLMs) and Vision–Language–Action (VLA) systems has been accompanied by increasingly sophisticated regulato

How the AI Industry Collapsed Diverse System Failures into a Convenient Myth

YouTube video by More Perfect Union

YouTube video by International Association for Safe & Ethical AI

Model interpretability is crucial for establishing AI safety and clinician trust in medical applications for example, in survival modelling with competing risks. Recent deep learning models have attained very good predictive performance but their limited transparency, being black-box models, hinder…