"#AI excels at learning through association, but fails when a problem requires a form of symbolic reasoning that cannot be implicitly learned from the correlation between game states and outcomes - a tangible, catastrophic failure mode"
Another example why #neurosymbolic reasoning is necessary for #AGI
https://arstechnica.com/ai/2026/03/figuring-out-why-ais-get-flummoxed-by-some-games/
Google Just Achieved Mathematical AGI
The code has been cracked. Google’s latest model has successfully solved "unsolvable" International Mathematical Olympiad problems with 100% accuracy, signaling a shift from pattern matching to true logical reasoning.
#GoogleAI #AGI #Mathematics #DeepMind #TechBreakthrough #FutureTech #TechNews #Tech #Technology #science #innovation #news
https://www.technology-news-channel.com/google-just-achieved-mathematical-agi/
RE: https://mathstodon.xyz/@tao/115722360006034040
On the Measure of Intelligence (2019) https://arxiv.org/abs/1911.01547 is more relevant every day.
Two views of intelligence: Intelligence as a collection of task-specific 𝐬𝐤𝐢𝐥𝐥𝐬, or intelligence as 𝐬𝐤𝐢𝐥𝐥-𝐚𝐜𝐪𝐮𝐢𝐬𝐢𝐭𝐢𝐨𝐧 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲, relative to priors, experience, and generalization difficulty.
Isaac Newton’s skill in doing calculus was low compared to that of the average mathematician today. However, Newton was able to develop the entirely new skill of calculus, starting only with the priors and experience available in the 17th century.
Newton had a dual capacity:
1. The ability to learn how to stand on the shoulders of giants.
2. The ability to see further than those who came before him.
"AI community still gravitates towards benchmarking intelligence by comparing the skill exhibited by AIs and humans at specific tasks [...] solely measuring skill at any given task falls short of measuring intelligence, because skill is heavily modulated by prior knowledge and experience: unlimited priors or unlimited training data allow experimenters to "buy" arbitrary levels of skills for a system, in a way that masks the system's own generalization power." – Francois Chollet (2019)
lol, I just realized that every #AI coding model knows my GitHub handle 😆
Mom, Dad! I made it!
Interesting paper that was recently updated today engaging Heidegger's philosophy with contemporary Machine Learning techniques. I hope to take more time to engage with this paper over the next couple of days. Still, it is encouraging to see such consideration connecting AGI concerns with philosophical principles. Exploring how contemporary design principles lead more to tool use, than AGI.
https://arxiv.org/abs/2602.19028
I haven't watched iRobot in a while… but I vaguely remember this didn't end too well...
https://x.com/ShaanVP/status/2023611833668825483
If you want to know why people don't trust #OpenAI or Microsoft or Google to fix a broken faux-#AGI #chatbot #LLM, consider that using suicidal teens for A/B testing was regarded as perfectly fine by a Silicon Valley "health" startup developing "#AI"-based suicide prevention tools.
(Aside: This is also where we get when techbros start doing faux-utilitarian moral calculus instead of just not doing obviously unethical shit.)
Análisis crítico sobre la trayectoria de la Superinteligencia Artificial en 2026. Evaluación de hitos tecnológicos vs. narrativa comercial. 🧠👾 🔗 https://www.glitchmental.com/2026/01/ai-2026-superinteligencia-debate.html #AI #TechEthics #AGI #GlitchMentalMX
Finally, after an epic battle against Gitea CI:
The definitive answer to the question, "Is AI intelligent yet?"
Geloof de hypemachine niet. Met hun boek #TheAICon willen Emily M. Bender en Alex Hanna de AI-bubbel doorprikken en tonen hoe we ons kunnen verzetten tegen de #AI-zwendel van Big Tech.
“Het narratief dat dit alles onvermijdelijk is, is nergens op gebaseerd. Het dient enkel de belangen van de mensen en bedrijven die deze technologieën verkopen.”
Ik had het genoegen om te spreken met @emilymbender & @alex.
I can't understand what it is about the calendar flipping to a new year that is supposed to induce rationality, but it seems to mark a reset for at least a month or so. Suddenly and ironically, many are calling out the AI bubble. Ha! The #AGI promises without a hint of delivery and the weaknesses of #GenAI in general have all been clear to realists and pragmatists for at least a few years.
1/
#AGI for me will forever be Adventure Game Interpreter and tied to Sierra On-Line. Now, all you prompt jugglers can get out of my lawn.
The Parable of the Talking Dog - Terrence Sejnowski
“One of my favorite stories is about a chance encounter on the backroads of rural America when a curious driver came upon a sign: “TALKING DOG FOR SALE.” The owner took him to the backyard and left him with an old Border Collie. The dog looked up and said:
“Woof. Woof. Hi, I’m Carl, pleased to meet you.”
‘Large Language Models and the Reverse Turing Test’
Terrence Sejnowski (Nov 2022 v9)
A brilliant and enjoyable essay on Large Language Models, human cognition, and intelligence
“A road map for achieving artificial general autonomy is outlined with seven major improvements inspired by brain systems.”
Sejnowski is the Francis Crick Professor at the Salk Institute for Biological Studies where he directs the Computational Neurobiology Laboratory
