SetupScore
Multi-source reviews: Expert consensus over one opinion
What it does
You read 5 monitor reviews. Two love it, one hates it, two are meh. Now what? SetupScore fixes this. Our pipeline ingests expert reviews, Reddit discussions, YouTube videos, and customer feedback — then uses NLP-based extraction to score products across sources, flag recurring issues, and map where reviewers agree or clash. One opinion is a data point. We give you the dataset.
Does a similar job
all alternatives →
- WCWatch ChatGPT debate itself on a given topic2023 · opinionate.io · ▲94
- HIHorsebot3k - Intelligent Amazon Review Analysis2011 · ▲10
We found that evaluating products based on ratings alone often is not helpful, and some products have too many reviews to efficiently read. Also, for many products, we discovered that finding where the well-written and thoughtful reviews fell was more important than the content. So, for Startup Weekend Kansas City last weekend, we created an app (Horsebot3k) which parses Amazon to identify the better written reviews, and what topics people like and dislike. We got the app fully working over the weekend, and won first place! Check it out at http://horsebot3k.com We also have a 90 second…
- OVOpen Video Game Data: A new approach to evaluating games2023 · ▲7
> Introduction Our idea is to offer an alternative to well-known sites like Metacritic and OpenCritic, but with a different approach. Instead of being a score aggregator, we will be a list aggregator. Metacritic brings together reviews from multiple review sites in one place, providing a final score of 0-100 based on a weighted arithmetic average, where some critics carry more weight than others. An alternative to Metacritic is OpenCritic, where all critics are weighted equally in the final average. However, both still work with numeric scores. > Why relying on scores can be problematic? -…
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 19d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
