You're talking about a different model — this post is about ChatGPT. text‑davinci‑003 still fails on all of the Hofstadter/Bender questions that I've tried. The prompt you're suggesting does not seem to produce a hallucination in ChatGPT:
MACHINE LEARNING
-
Challenge of incorporating all known trivia into training data
By
–
Expecting it to fully integrate every piece of trivia seems unfair — a lot of people would rate the first answer as reasonable. It’s fundamentally difficult to get training data that incorporates everything the model knows, rather than what the human demonstrator knows.
-
GPT-3 improvement shows not just pattern-matching, still hallucinates details
By
–
The point isn’t that it’s perfect, just that it’s not narrowly pattern-matching on this specific list of questions — there’s clear improvement vs. GPT-3 across many questions that contain false assumptions. It does still hallucinate details in other ways.
-
Tokenization issue: model struggles with letter sequences
By
–
This feels like a tokenization issue — in general, it doesn’t see text as sequences of letters, and struggles with tasks that assume it does.
-
Reinforcement Learning as Backpropagation Through Time
By
–
Reinforcement learning is backpropagation through time.
-
GPT-3 succeeds on trick questions, pre-training unchanged since 2021
By
–
No. It also succeeds on questions I’ve written myself that trick GPT-3, as in this screenshot. The pre-training data hasn’t been updated since 2021, and OpenAI specifically denies (in this thread) training on the Hofstadter/Bender questions.
-
Domino MLOps Platform: Hybrid Multi-Cloud Data Science Solution
By
–
What did the truck say? Domino is the only hybrid and multi-cloud MLOps platform. Unleash data science, not cloud spend. Follow us to #ReInvent2022 booth #2938 for more info, and to win prizes! https://t.co/I7YNKEJaZT pic.twitter.com/5oNDRyWaJG
— Domino Data Lab (@DominoDataLab) 30 novembre 2022What did the truck say? Domino is the only hybrid and multi-cloud MLOps platform. Unleash data science, not cloud spend. Follow us to #ReInvent2022 booth #2938 for more info, and to win prizes! https://
domino.buzz/3hOw8Ip -
Los Angeles Open-Source ML Meetup December 1st Event
By
–
Calling all Los Angeles makers! We invite you to join us for an evening of open-source and ML scalability on December 1, 2022. Come hang out and talk with data science enthusiasts. Register: https://
meetup.com/los-angeles-ar
tificial-intelligence-deep-learning/events/289694346/
… -
Freddie Mac Modernizes AI ML Infrastructure with DataRobot
By
–
Join us at #AISummit New York for a discussion on how @FreddieMac modernized their #AI and #ML infrastructure, leveraging DataRobot to rapidly deliver meaningful value to the business. Sign up https://
datarobot.com/events/ai-summ
it-new-york/
… -
DeepMind Reduces Math Reasoning Errors Using Process-Based Supervision
By
–
DeepMind Studies Process- vs Outcome-based Model Supervision, Significantly Reducing Reasoning Errors on Math Word Problems https://
syncedreview.com/2022/11/30/dee
pmind-studies-process-vs-outcome-based-model-supervision-significantly-reducing-reasoning-errors-on-math-word-problems/
…