> Michael England, a spokesman for the National Science Foundation, said the decision to dismantle the network, known as the Ocean Observatories Initiative, “aligns with N.S.F.’s wider strategy to have a nimbler approach to prioritizing support for evolving scientific priorities and emerging technologies as well as a deliberate approach to smart life cycle management within its portfolio of research infrastructure.”
1) it's not hard to do your own research. If you're here, I assume you know how.
2) does that answer satisfy you? The bullshitty word salad doesn't surprise me. With this administration I expect incompetence and double speak and am rarely disappointed. I wonder why at this point in time you choose to give them so much leeway.
> 1) it's not hard to do your own research. If you're here, I assume you know how.
What an awful take. The point of news shouldn't be "assume I'm right and the readership takes my word for it". It should help the reader come to a conclusion, because it's news and not opinion. If you have to go do your own research not to dig deeper but because the article failed to even cover the basic arguments, it has utterly and completely failed.
There is no such thing as a complete piece of information and it is unreasonable to expect every published piece of every bit of information to contain all required context to understand it. I'm not defending the Yale article's basic miss on the information, but rather your laziness on looking for more information when something came across your purview.
If someone said to you "hey, I heard they're pulling back on measuring ocean currents, isn't that shitty?" Would you get defensive and start yelling at them about not providing the "other side"? No, you'd say "whoa, I better figure out what's going on here" and make it a point to dig more, not sit there and bitch and moan about incomplete information. Yale.edu isn't a news service, it has no obligation to "both sides" a story for you.
Furthermore, what even would be the point of anyone regurgitating that hopeless pile of words the NSF's chief barfed out (apart from illustrating that's all they have as an explanation)? You mistakenly gave the administration the benefit of the doubt here when you really had no business doing so.
> 1) it's not hard to do your own research. If you're here, I assume you know how.
Assume the opposite direction. If you don't bring the data, then you're not doing your part to convince others on your position. Assumption of "default data" is a significant contributor in the breakdown of communications.
> 2) does that answer satisfy you?
No, in fact it leaves open more questions than before. From the article provided (https://archive.is/fZ9CN):
>> The $48 million annual budget for the observation network was small compared with the value of the data it collected for understanding the oceans and the climate, Dr. McLean said.
- Why didn't aligned charities step in to plug the gap? Billions flow through charities each year, and yet none have stepped in? One or 2 stepping in and still not being able to plug the gap, I can accept. None at all?
- If the data is that important, then there should be multiple efforts in collecting it, not just one. Why did everything get lumped into a single basket?
I'm not sure what your background is, but as a staff level engineer, I can assure you they do not. They in fact seem to lack any understanding of architectural intent within a sufficiently large code base. This seems obvious since they can't fit the entire code base in their context at once.
We have many folks (not engineers) at our company using LLMs to open PRs, and every one of these PRs has profound architectural design problems.
> They in fact seem to lack any understanding of architectural intent within a sufficiently large code base. This seems obvious since they can't fit the entire code base in their context at once.
Nonsense. The goalpost is "this is as good as a senior engineer". A senior engineer can easily understand architectural rationale. Don't dismiss my argument because it's inconvenient to yours.
I've been using it mostly to bat away yak shaving rabbit holes one can get into when working on a large and complex project. I work mostly on platform work, which is generally nebulous in its feedback loop and testing. Relegating AI to refactoring and building tools to help me research keeps me focused on solving the actual main problem I'm trying to solve, reduces context switching. I really don't understand people who use it to bat out their main focus. I simply don't trust it at that level.
I was surprised that incident didn’t seem to get as much attention since that was a pretty major data corruption bug, but I guess it was a much smaller scope of impacted repos/customers than a lot of these availability issues?
Wrapping my face in tinfoil: across the board, Amazon, Microsoft, GitHub, Anthropic and OpenAI, I’m seeing a lot of top-level service issues that sound an awful lot like code hitting production that hasn’t been fully tested.
Breaking buttons on the website is one thing, kinda, but Enterprise used to mean a certain degree of robustness and seriousness in product management.
Devs are expected to ship slop 10x faster. The AI tools genuinely help a bit, like maybe 2x, but the 10x "improvement" comes from not thinking about anything else than shipping your assigned features, not testing your code carefully, not getting proper code reviews, not dogfooding your stuff, and releasing carelessly.
Merge queues are not as frequently used… ~2000 PRs affected over 4 hours. I reckon that’s on the order of 10 commits per tenant. It’s a feature with low traction, probably because it creates more problems than it solves.
while external merge queues offer a ton more features, i wouldn't describe any of them as 'perfect' based on the simple fact the UX is bolted on. github continues to display their native UI components for merging, and users are forced to interact via arcane commands in comments or external CLIs/webpages. not ideal!
So I guess I should just give up on my dream of having a useful AI assistant for day to day "human" tasks. We're just hell bent on replacing humans in jobs.
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