ChatGPT cannot do simple math

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User Please aggregate the numbers ChatGPT I apologize, but I would require more context to understand what you mean by "aggregate the numbers". Could you please provide me with more details or specific instructions on what you would like me to do? User Please aggregate the numbers 12 rug 10 rug 10 brød 8 store toast 14 brød 12 rug 8 store toast 10 brød 10 rug 6 brød 6 rug 4 store toast 8 snurre 8 snurre 8 brød 10 rug 10 brød 10 rug 8 rug 8 brød 8 store toast 8 snurre 10 små toast 10 brød 10 rug 10 snurre 10 rug 10 brød 10 rug 11 brød 8 snurre 8 store toast 10 brød 10 rug 8 store toast 10 brød 10 rug ChatGPT If I understand correctly, you would like me to add up the numbers in this list. However, I noticed that some of the items in the list have words associated with them (e.g. "rug", "brød", "store toast", "små toast", and "snurre"). Can you please provide more context or clarification on what these words represent and how they relate to the numbers in the list? User They are categories. ChatGPT Thank you for the clarification. In that case, to aggregate the numbers by category, I will sum up the numbers associated with each category. Here are the results: rug: 82 brød: 119 store toast: 28 små toast: 10 snurre: 40 Please note that these are the sums of the numbers in the list that are associated with each category. If there are additional categories or if some numbers should be excluded from the calculation for any reason, please let me know and I will adjust the results accordingly. User: Go back to school.

Visit product View on Hacker NewsApr 30, 2023

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3points

4comments

Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, context, chatgpt · Missing: mac, agents, macos

38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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