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Unified access to top AI models, supporting GPT4, Claude and more

Hacker News

Unified access to top AI models, supporting GPT4, Claude and more

Hello hackernews, I am looking for feedback for Labophase.com which is a app that focuses on returning results from multiple ai models at the same time. I currently support: GPT4-Turbo, Claude-2, Google PaLM2, Llama2, Mistral, and OpenOrca. Working on supporting Gemini soonTM. I built it to solve a couple of personal pains I experienced. After reaching out to a couple of users in r/localllama, seems that people would have similar approach to address hallucination, availability, and comparing ai models. Initial feedback came in with some surprises that I'm hoping to get feedback from the bigger HN community: 1. Do people prefer a "search" interface over a chatbot interface i.e. (one to many as opposed to one to one interaction with ai)? - My experience is that it's the best defense against hallucinations and misinformation from models because models often hallucinate and fail in different ways and is very obvious when you compare it against other responses. 2. Do a lot of people manage multiple subscriptions and billing to access more than one ai model? 3. Is local setup for accessing the top open source ai models so painful that most people don't bother? --- Note: Labophase is in beta, accounts is not fully working and expect some bugs here and there. Free access will continue until I run out of credits.

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19points
10comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, model, google · 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting
85%85% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source, llama, io · Missing: https docs, excited, just released
47%47% 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 · Strong signals: interface, soon, users · Missing: plus, platform, intuitive
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, google, users · Missing: mobile apps, ios, entrepreneurs
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue
20%20% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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