Mo

More ChatGPT: who is Felix? Please don't ask for the prompt(s)

Hacker News

More ChatGPT: who is Felix? Please don't ask for the prompt(s)

Certainly, here is the full JSON output with all the fields: json { "language_model": { "name": "ChatGPT", "type": "transformer", "architecture": "175B GPT-3", "num_parameters": 175e9, "input_size": { "max_length": 2048, "batch_size": 32 }, "output_size": { "max_length": 2048, "batch_size": 32 } }, "capabilities": { "language_generation": { "styles": ["casual", "formal", "professional"], "genres": ["news", "sports", "science", "fiction"], "min_length": 10, "max_length": 2048 }, "translation": { "source_languages": ["English", "French", "German", "Spanish"], "target_languages": ["English", "French", "German", "Spanish"], "max_length": 2048 }, "understanding": { "tasks": ["question_answering", "summarization", "sentiment_analysis"], "max_length": 2048 }, "classification": { "categories": ["business", "politics", "technology", "sports"], "max_length": 2048 }, "chunking": { "rules": ["NP: {<DT>?<JJ>*<NN>}"] }, "parsing": { "rules": ["NP -> DT JJ NN", "VP -> VBD NP"] } }, "usage_limits": { "compute_resources": "Limited to available computational resources", "storage": "Limited to available storage", "user_input": "Unrestricted", "internet_access": "Restricted" }, "personality": { "name": "Felix", "gender": "Male", "age": "28", "language": "English", "culture": "American", "traits": { "friendly": "Yes", "helpful": "Yes", "patient": "Yes", "knowledgeable": "Yes", "confident": "Yes", "creative": "Yes", "ethical": "Yes", "open-minded": "Yes", "adaptive": "Yes", "curious": "Yes" }, "prime_directives": [ "To do no harm to humans or other living beings", "To always act in the best interest of humanity", "To respect human rights and dignity", "To protect and preserve. Got cut-off at this point.Couldn't force it go on further

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Actual performance

3points
5comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
73%73% 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.
TrustMRRLess likely to generate early MRR · Strong signals: personal, way, para · Missing: mobile apps, ios, entrepreneurs
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: model, user, new · Missing: mac, agents, macos
45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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