Gas Heatmap
See the cheapest hour to send crypto, across 5 chains
What it does
GasCheck maps average transaction fees by day-of-week x hour-of-day for Bitcoin, Ethereum, BNB Chain, Arbitrum, and Base — see at a glance when fees are cheapest, instead of guessing. Each cell shows the fee rate and what a standard transfer actually costs in USD. Bitcoin fees swing 3-5x in a single day, so timing it right can save real money. L2s like Arbitrum and Base stay flat almost all the time — GasCheck shows that honestly too. No signup, no wallet connection — just open it and check.
Does the same job
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- LBLive Bitcoin Transactions from around the globe in WebGL2013 · earthbit.net · ▲34
I built this over the weekend. Any feedback is appreciated. Please note you will need a WebGL enabled browser. Thank you for checking it out. --UPDATE-- HN Traffic is strangling earthbit. There is sporadic downtime due to the web services I am using, if no transactions appear after a few seconds, then please try again in an hour.
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
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.
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