The community experiment compiled roughly 800 Hacker News comments posted between 2016 and 2026 to measure historical expectations against current progress. Out of 826 evaluated statements, 112 met a supermajority consensus among nearly 9,700 participants. The most widely recognized completed tasks centered around automated coding and text writing, several of which were proposed before ChatGPT launched. Meanwhile, milestones related to the Turing test saw voter agreement drop sharply whenever stricter testing conditions were applied.
Key points
Milestones involving automated code generation and text writing represent the most widely…: Milestones involving automated code generation and text writing represent the most widely affirmed artificial intelligence achievements.
Several benchmarks that participants agreed have been met were originally proposed prior…: Several benchmarks that participants agreed have been met were originally proposed prior to the November 2022 release of ChatGPT.
Voter consensus dropped significantly when Turing test evaluations involved stricter cond…: Voter consensus dropped significantly when Turing test evaluations involved stricter conditions like multi-day tests or live Zoom calls.
Sources checked by our analysis pipeline: 1
Oct 3rd, 2026
A few weeks back I was (once more) impressed with a new release of a frontier model, and realized it was still 2026, about three quarters through the year, the same year I discovered coding agents were becoming useful.
It's funny how quickly you get used to the status quo. Using a model for a few days is enough to develop an intuition for its capabilities, and that naturally leads to expectations that would have been unthinkable earlier.
Whenever I hear someone complain about an LLM, I try to picture having the same conversation a year ago. “I let Claude troubleshoot a massive performance regression overnight and told it not to use the profiler because it's too slow, guess what it did?” You let a machine troubleshoot an issue while you were asleep?!
If you use LLMs on a daily basis (and don't keep notes or a blog) it's hard to think back to what you would have been impressed with throughout the years.
Fortunately Hacker News provides a rich archive of statements of the form “wake…
Alphabet's tech giant is positioning itself to close a $10 million acquisition of corporate records from the bankrupt carrier to train artificial intelligence models. Under pressure from a union representing the airline's former workforce, the company agreed to carve out sensitive personal information and bolster record anonymization. The concessions help remove major labor objections ahead of next week's expected approval of the liquidation purchase.
The expanded availability grants developers and advanced subscribers broader access to Google's specialized model following its initial, restricted trial. The deployment is accompanied by early details on upcoming collaborative capabilities designed to enhance how systems operate within the Antigravity environment. This dual announcement highlights the company's push to deliver targeted computational tools directly to enterprise and power users.
Meta's Muse and similar digital assistants have recently been obstructed from scanning platform listings, occasionally forcing traffic to external mirror sites. This pushback aligns with broader terms banning automated checkout bots without human oversight to curb unauthorized data scraping. The shift highlights growing friction between marketplace security and the rise of automated consumer tools.