I think it's reasonable to be turned off by a slick-looking website, but I imagine it's because the intended audience of the website is the general (dog-owning) public, likely for the purposes of soliciting participants.
This project is a research project out of the University of Washington, led by several of the professors there. I believe the lab is the Healthy Aging and Longevity Institute.
They share a list of academic publications that have resulted from the project, and their Team page lists the full names a sizable large number of people.
Their FAQ indicates that the cost of the DNA Kit and other things are covered by the project funding. [1]
What made you think that it's engaging in fraud? I'm genuinely curious.
I'm not involved in the project but just from looking at the site for several minutes, it seems to be a fairly reasonable research project.
Or did you say "fraud" less to mean "these are people who are stealing money and e.g., hoarding it away" and more to mean "these are people engaging in a research project I disapprove of"?
> SWE-Bench has recently modified their submission requirements, now asking for the full working process of our AI model in addition to the final results -their condition to have us appear on the offical leaderboard. This change poses a significant challenge for us, as our proprietary methodology is evident in these internal processes. Publicly sharing this information would essentially open-source our approach, undermining the competitive advantage we’ve worked hard to develop. For now, we’ve decided to keep our model’s internal workings confidential. However we’ve made the model’s final outputs publicly available on GitHub for independent verification. These outputs clearly demonstrate our model’s 30% success rate on the SWE-Bench tasks.
It seems to me that there's a natural tension in emerging fields of science and engineering between establishing clear guidelines and regulations early on to minimize harms, or instead allowing practitioners to experiment, tinker, build and create outcomes that may be potentially harmful.
What are some frameworks for how to think about navigating this tension in emerging scientific or engineering fields?
Some ones I'm mulling over:
1. Rate of innovation: In rapidly evolving fields, imposing strict regulations too early can hinder innovation and progress. In such cases, it might be better to minimize restrictions early on to allow practitioners to explore new ideas. Then, as the field matures, regulations and standards can be gradually introduced.
2. Adaptive regulation: Implement a flexible regulatory framework that can be updated as new information becomes available.
3. Self-regulation: In some cases, maybe we should expect and encourage the industry to use self-regulation via developing guidelines and codes of conduct. This may be one way to try and strike a balance between responsible innovation while minimizing bureaucratic obstacles.
I took a class with Professor Ousterhout. He would end every Friday's lecture with a "Thought for the Weekend", such as this one.
It was very entertaining and charming to hear him discuss his personal and professional life, and lessons he's learned throughout them often occasionally have very little to do with computer science.
I don't remember all of his "Thoughts for the Weekend", but I do remember one story he told about wishing he had apologized sooner to resolve some conflict he was in. That was a bit of wisdom that stuck with me from the class, beyond any of the computer science topics we covered.