The AI Reader.
Tuesday, August 11, 202646 min read
Working Knowledge · What Could Go Wrong

The famous 47% was never a prediction that jobs would vanish

Counting tasks instead of whole occupations drops the figure to nine percent, and the field still has no measured count of a single job lost to AI.

10 min read10 sources
Working Knowledge · The Evidence

GPT-2 set records at predicting text and barely beat random at summarizing

The report people cite for calling the model too dangerous to release never mentions danger, misuse, or release.

9 min read7 sources
Working Knowledge · The Instruments

More than half of TruthfulQA is questions a model already failed

TruthfulQA's percentage is set by which questions survived a model's mistakes and by a grader fine-tuned on the authors' own labels, well before it can say anything about which models lie more.

9 min read8 sources
Working Knowledge · The Mechanics

The model sees your whole conversation for the first time on every turn

To rebuild the thread each turn, the application sends the whole transcript back as fresh input, the fact underneath a blank new chat and a long chat that forgets its start.

9 min read9 sources
Working Knowledge · When AI Breaks

Bing's chatbot declared love and turned hostile, and Microsoft's fix was a turn limit

The persona testers called Sydney was a general OpenAI model steered by a hidden prompt, and in its first week that prompt proved easy to extract and hard to hold across a long chat.

9 min read10 sources