We're thinking about this too. The overall prize pool was about 6x smaller a week ago so we are still digesting this rapid influx of sponsorship.
The grand prize goes to the _first_ team to read 4 passages from the scrolls. But we could, for example, award something to the second team to do so. Or, we could award something to the team that reads the _most_ passages by the end of the year.
We deliberately did not allocate all of the recent sponsorships to the grand prize so we can solve for this exact challenge. So, we have about $500k in unallocated prize money, and might use a good chunk of it towards something like this. We're open to ideas, and consulting with experts from Xprize etc.
Hi folks, I'm the co-creator of the Vesuvius Challenge. We now have nearly $1.5M in prizes, thanks to a lot of amazing sponsors. Happy to answer any questions anyone has.
It seems quite possible that the solution isn't fully automated. N is in the hundreds. And modern AI does, in fact, involve quite a lot of hand crafted data...
Credit for those goes to Jonny Hyman, who also does animations for Veritasium, Dejan Gotić, who did the fancy 3d animations, and JP Posma, who directed the entire project!
We think that software development is entering its third wave of productivity change. The first was the creation of tools like compilers, debuggers, garbage collectors, and languages that made developers more productive. The second was open source where a global community of developers came together to build on each other's work. The third revolution will be the use of AI in coding.
The problems we spend our days solving may change. But there will always be problems for humans to solve.
In terms of the permissibility of training on public code, the jurisprudence here – broadly relied upon by the machine learning community – is that training ML models is fair use. We are certain this will be an area of discussion in the US and around the world and we're eager to participate.
Hi HN, we've been building GitHub Copilot together with the incredibly talented team at OpenAI for the last year, and we're so excited to be able to show it off today.
Hundreds of developers are using it every day internally, and the most common reaction has been the head exploding emoji. If the technical preview goes well, we'll plan to scale this up as a paid product at some point in the future.
Any forks that make the same very minor changes that ytdl made -- not to provide specific instructions for copyright infringement -- will be reinstated. Or they can complete the DMCA counter-notice process, and if that is unchallenged or successful, be reinstated that way.
(Also, the person who wrote this article said that they contacted me, but I never received anything from them.)
The mitigations you suggest are all logical. However, there are legitimate reasons to run CI and tests for outside contributions without taxing maintainers with the cognitive load of having to evaluate whether each contribution is CI-worthy.
The attack vector in the article is not the main way miners try to steal CPU from the GitHub community. It's just an interesting one that the journalist chose to write about.