As a means to grift directly, but also for leverage over the tech industry, and possibly the entire economy.
People hate data centers, but if they think AI regulation will crash the economy, will they vote Trump?
791 karma · joined July 25, 2014
As a means to grift directly, but also for leverage over the tech industry, and possibly the entire economy.
People hate data centers, but if they think AI regulation will crash the economy, will they vote Trump?
It's a pretty straightforward problem statement, they didn't really need to outsource the writing.
I had used 2.5-pro for a hefty chunk of development, and found it to work like a somewhat forgetful senior engineer who was new to my project. Very capable, would almost always choose a reasonable option, if not always the best one for the project, and not great at multi-tasking. Generally, made me comfortable not scrutinizing the code line-by-line, but still needed a bit of steering once projects got to a reasonable size.
The next model is a clear step up in the multi-tasking capability at least, with me very rarely having to steer the implementation of a well-defined issue. In terms of code, I found MiMo-V.2.5-pro to be extremely conservative, implementing minimal solutions. The next model seems a little bit more ambitious, in positive ways, making good guesses about gaps/next steps. It also seems to be a fair bit better at design, at least for the little bit I've done, it was good at translating my concepts to practical elements on screen, and cleaned things up nicely as I made suggestions.
I'll keep this in mind as I explore that case.
I think this could be pretty decent in CI? There's a lot of "flakes" I've mediated that this could have handled much more efficiently. Maybe observability as well, triggering elevated logging and other initial measures?
(But I'm also not specifically aware of face blindness as a condition, and had assumed it was generally some form of aphantasia.)
Practically, it means I'm rubbish at remembering people. I've developed some techniques that help, but if someone changes their look significantly, it's very hard for me to identify that it's the same person.
I'm still learning how this has impacted by life, and strategies for working with it. As a simple example, my wife's family was really into cars, so when I got to know them I learned all about cars. When I met my wife, I couldn't identify a single vehicle on the road, except maybe a Hummer, but after 2 years, I could quickly pick out the make and model of 95% of traffic.
Looking back, I can see this is because rather than remember what different cars looked like, I created a taxonomy of ALL cars in my head, and became able to sort any vehicle I saw to fit there somewhere. So when I identified something, I wasn't matching it against previously seen things, but rather eliminating all the things it couldn't be to arrive at the remaining possibility.
Since I have incredible respect for Armin and his work, this is very nice to see, and I hope it wakes some other folk up.
Seemed like something y'all would enjoy here. :)
IBM Bob
On:
IBM Quantum Nighthawk R2
?
It's available at a limited number of airports, and you have to apply 1-3 days in advance each time. Also could be annoying to travellers who have to compete with you for line, seat, or bathroom space.
But maybe more revenue from visitors means better staffing and resources for airports!
If you're building a personal cloud, you also want your AI connected to it, but probably with some degree of management. Aperture already provides a fair amount in this area, and probably with a connector for Cloud in a Bottle, could give your AI safe access.
I say small improvement because my experience is that modern Agents are pretty good, so by the time they've handed it back to me to test it, there are usually only one or two remaining issues that I'll discover as we roll it out to Production.
What Kent completely ignores here, as far a I can tell, is that there is significant value in finding out sooner what the needed features are. Building speculative structure can be a forcing function to establish requirements, because at least you start exposing failure modes. It might be more expensive than waiting, so hopefully you don't do it for most of your requirements, but sometimes it's your best option.
Building the wrong thing is now a much less expensive option, and that means the calculation around YAGNI is different. But it's still a calculation, and for now, each team needs to figure out how it has changed for them.
But it seems trivially easy to run it against local models. Their onboarding guide offers that option, though I have no idea if it changes any functionality.
I also built a couple of harnesses, I wonder if I could swap this for Claude in those...
(Lots of interesting ideas in the blog post, but like all the AI developments these days, hard to be sure what's valuable without extensive experimentation.)
It's a lot easier to become a really successful company if you can keep your inventory costs down. Perhaps by investing in local law enforcement instead, to make sure no one looks too close at said inventory?
Donald Trump is famous for not paying even really cheap contractor bills, because he knew he could get away with it.
https://news.ycombinator.com/item?id=48302822
I'm totally not surprised, except that Trump's admin is actually catching and prosecuting these people.
I assume that means this is just the tip of the iceberg, and the grift is so predominant that they can't help but catch some people.
People, especially in remote jobs, benefit from being organized into groups intentionally, with distinct rituals that enable them to operate effectively while they get to know each other better. Another person needs to design and oversee all that.
While you can provide templates for that structure that allow oversight to scale so that one person can oversee larger groups, that tends to be more effective in non-remote, and more predictable, work environments. Modern software development is very little of that.
I don't have much in-person experience with middle management in contexts outside of software development, and I suspect there are some opportunities to use AI to bring engineers closer to customers.
So good for me.
But there's some really scary stuff in here happening to other people that I'm not even aware of.
Yes, lower classes have access to many more conveniences then they might have had in earlier decades, but they are working far more hours, and their expected lifespan has started decreasing.