Can GPT Be Trained for Truth? Exploring Hallucination Reduction

Hacker News

I've been experimenting with ways to encourage ChatGPT to generate more factual outputs. While we know it excels at creative text formats, factual accuracy can sometimes be...well, imaginative. My approach involved using specific prompts to steer it towards factual responses. I'm curious to hear from the HN community: -Have you explored techniques for prompting factual responses in GPT models? -Are there interesting applications for a "factually-focused" ChatGPT? Let's discuss ways to push the boundaries of factual language models through creative prompting

Visit product View on Hacker NewsMay 23, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, chatgpt · Missing: mac, agents, macos

90%90% predicted probability of success on Product Hunt, 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: io · Missing: https docs, excited, just released

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

29%29% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

17%17% 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

9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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