AI

AI tools for high lvl researchers who need assistance – not answers

Hacker News

AI tools for high lvl researchers who need assistance – not answers

High-level researchers and published academics don't want hallucinated work and already have the skills to complete their tasks. Current AI platforms and agents are both untrustworthy (hallucinating) or ineffective due to low PDF interactivity (cannot edit drafts, insert quotes, or highlight text in files), which means AI tools become useless at the highest level. We are sad to see academic databases flooded with LLM-assisted papers and an apparent decrease in creativity at the highest level of discovery (we suspect through over-reliance on AI oracles like ChatGPT). We do not believe that Vibing is productive and hope to help minimize Vibe anything. Research is not disposable and should not be treated as another thing to automate; instead, we should build AI tools that help build critical thinking and creativity in humans. So what is Ubik? Ubik is the first AI Research Environment (AiRE): just like an IDE (coding) or a DAW (music production), Ubik is an environment for high-level research and deep knowledge work. Rather than quick/vague generation, Ubik agents can be contextually locked into PDFs added to chat. Like Cursor, all files and AI items can be referenced while prompting using the @ symbol. Search, analyze, and cite papers found in ArXiv and Semantic Scholar. Generate text with citation, and build a knowledge base that amplifies human intelligence instead of replacing it. If you think this sounds like a helpful tool, go check it out and lmk what you think - Ubik will be free until 2026 :3 We are testing our custom-built EVAL suite and currently scoring above 90% on standard PDF EVALs and will be publishing soon <3

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, cursor · Missing: mac, macos, claude
92%92% 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 · Missing: supports, reddit linkedin, podcasting
74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
53%53% 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: platform, soon · Missing: plus, intuitive, reviews
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: answers · Missing: mobile apps, ios, personal
35%35% predicted probability of success on TrustMRR, 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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