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Interactive Visualization of GraphRAG

Hacker News

Interactive Visualization of GraphRAG

Hi HN, I've built a demo to query quarterly earnings call transcripts from a select few S&P 100 companies using Microsoft's new GraphRAG framework. One of the key advantages of GraphRAG over traditional vector retrieval methods is its transparency and explainability. Unlike vectors, which are often obscure and not human-readable, the graphs generated by GraphRAG are easily interpretable. In this demo, the graphs are used off-the-shelf without any domain-specific fine-tuning. Check out the graphs here: https://bit.ly/46d757b Try out the demo here: https://bit.ly/3WfyvEX

Visit productView on Hacker NewsJul 22, 2024
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, visual, using · Missing: mac, agents, macos
72%72% 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
59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
58%58% 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
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · 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 · Strong signals: active · 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 · Missing: web3, chat, crypto
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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