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Singularity Review: post #51 — TG.ME

Singularity Review@singularityreview · 2.2K subscribers Open in TelegramOpen

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t.me/singularityreview/51

October 18, 2026

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Week in AI in 7 lines (19 to 25 October) ChatGPT taught Messi a chess opening on a board set up wrong, in an ad in front of 517 million followers. Six AI assistants chased an impossible £350 refund. One sent 187 messages in 15 days. Researchers found about 6,800 "private" Meta AI share links with one search. Just Eat's AI drew a Northern Irish breakfast floating in a glass of cola. Five people with no biology training had an AI design 318,484 proteins against scorpion venom. AI agents left alone on a desert island invented games, then did better on later tasks. An AI helped crack a maths puzzle that had stayed open for 30 years. The thread this week: AI keeps getting more capable, but it still needs a person to check its work. Which story stays with you? Tell us below. Forward this to someone who missed the week. @singularityreview 228·Oct 25

Meta's AI made "private" share links easy to find Muse is Meta's new AI agent. It writes documents, fills in forms and has a share button that makes a link only the people we send it to should see. Researchers at the security firm Claroc found about 6,800 of those links without being sent any. "It took one query," they wrote. Among the pages they opened: a small business loan application, a company revenue review, a bank fraud alert with part of an account number and a full year staff holiday calendar. The trick was simple. Muse put each page's title in the link itself, and opened links end up in public internet lookup records that anyone can search. Meta paused sharing on 20 October, changed the links and switched sharing back on two days later. Why it matters: we are giving AI agents our email, calendars and bank details. "Anyone with the link" can mean more people than we think. Would we share a document an AI made for us? Tell us below. Read the full story 946·Oct 23

ChatGPT taught Messi chess. The board was set up wrong Lionel Messi asked ChatGPT to teach him a chess opening that matched his style. It suggested one called the "GOAT Horns", a nod to his nickname. The ad went up on his Instagram this week, in front of more than 517 million followers. Chess fans spotted the problem within hours. On the board in the ad, each king and queen were standing in each other's places. That one swap changes the game. On the wrong board, the suggested moves let the other side win in four moves. On a correct board, they do not. The post still got about 1.9 million likes in a day, and OpenAI used a fixed board in a later version of the ad. Why it matters: millions of people now learn from chatbots, and they sound sure even when the basics are wrong. We should check the first step ourselves. Would we trust a chatbot as a teacher? Tell us below. Read the full story 1.1K·Oct 23

A food app let AI draw its menus. It put a fry-up in a glass of cola Just Eat has been using AI to make pictures for takeaway dishes that had no photo. It read the menus a little too literally. In Northern Ireland a "breakfast soda" is a soda bread sandwich with bacon, sausage and egg. The AI drew a pint of cola with the breakfast floating in it. Scampi came out as sushi. A "garlic bread plane" became an aeroplane made of bread. A wine with watermelon in its tasting notes got real watermelon chunks in the glass. Customers shared the pictures, and Just Eat has apologised, started removing them and paused the trial. It says every image was checked by a person first. Why it matters: more of what we see before we buy is drawn by AI, not photographed. The funny mistakes are easy to spot. The ones that look normal are not. Would we order from a menu with AI pictures? Tell us below. Read the full story 1.6K·Oct 22 Five people with no biology training asked an AI for an antivenom An investment research firm, Citrini, wanted to know if AI drug discovery was real. With Anthropic, they gave an internal Claude model a 35-page prompt and went home. In 64 hours it designed 318,484 proteins aimed at five scorpion neurotoxins, picked the best, and emailed a lab to ask what it could build. Two labs made 211 designs and tested them. Seventeen bound their toxin. The first 180 came from five human messages. What failed: no design bound more than one toxin, and nobody has tested whether any of them stops the venom. Anthropic does not claim an antivenom. Why it matters: scorpion stings kill more than 3,250 people a year, mostly children, and the treatment is still made by milking venom into horses. The expensive first step just got cheap. Does this change our view of AI in medicine, or is it still a demo? Let us know below. Read the full story 2.2K·Oct 21

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