The app, "SnackPass", faces a similar issue. Coffee shops spend time fulfilling mobile orders, placed in advance to avoid waiting in line, resulting in a delay for in-person orders.
While I was unable to view the entire article (paywalled), I suspect that some kind of priority queue that weights an order's priority by the user's distance to the store may be useful to solve the waiting issue.
I got an error when passing a prompt with about 20k tokens to the Llama 4 Scout model on groq (despite Llama 4 supporting up to 10M token context). groq responds with a POST https://api.groq.com/openai/v1/chat/completions 413 (Payload Too Large) error.
Is there some technical limitation on the context window size with LPUs or is this a temporary stop-gap measure to avoid overloading groq's resources? Or something else?
It's not so much an insistence, more just where the industry is at. Those freewheel hubs are loud because that's generally the lightest, most efficient design - lots of teeth for immediate drive engagement, no extra grease that would lessen said engagement, no extra material for sound dampening.
Clutch mechanisms are available, but these are slightly less efficient and generally more expensive.
Basically... People love spending lots of money for the absolute highest quality components. How will other riders know how fancy your hubs are unless it broadcasts that fact to the world?
Photopea is fantastic, fast, looks and works exactly like Photoshop, and maintains some features removed from Photoshop, such as the ability to generate normal maps.
The data availability statement in this article undermines its entire premise.
> We did not publish our raw data along with the manuscript because it could be understood that we are publicly shaming authors who did not want to share their data. As for the raw data that were received during this study, we informed our study participants that those raw data will be deleted after being examined and that all data and communication will be treated with strict confidence.
There's a big difference between explicitly denying to share data for justified ethical reasons, and saying you will share the data and then failing to follow through.