An Ideal Laboratory for Self‑Improving Agents Settlers of Catan looks disarmingly simple—collect wood, sheep, brick, wheat, and ore, then build roads and settlements. Yet the game’s soul is negotiation and long‑term planning under uncertainty, exactly the kind of challenge that has tripped up many reinforcement‑learning systems. Dice inject randomness, opponents conceal their intentions, and every trade reshapes […]| NATURAL 20
TLDRMIT researchers have developed “self-adapting language models” (SEAL) that can improve their own abilities by generating their own training data and updating their internal parameters. This allows models to better learn from new information, adapt to tasks on the fly, and move closer to becoming long-term autonomous AI agents. It’s a major step toward models […]| NATURAL 20
TLDR AI and automation have been nibbling away at human work for seventy years. Humanoid robots and super-smart software will push that trend into overdrive. If jobs disappear, societies must replace wage income with new forms of economic agency like shared ownership and stronger democratic power. Waiting too long risks both a broken economy and […]| NATURAL 20