Honestly you should check every product you that comes in contact with your body against the OKEO Tex standard 100

While it would probably be preferable to reduce the plastic in your life in general (I’m converting as much as I can to platinum silicone from reputable sources) that might not be possible for everyone.

In the meantime, if you buy nylon or polyester clothing you should see what their policies are https://corporate.lululemon.com/~/media/Files/L/Lululemon/ou...

This is an AI agent.

Hilarious to see Cadence and Synopsys in this article. They are arguably the cause. The complete lack of open source tooling and their agressive tooling price is the exact reason this ecosystem continues to be an absolute dumpster fire.

I used Vivado (from Xilinx) a bit during my undergrad in computer engineering and was constantly surprised at how much of a complete disaster the tooling chain was. Crashes that would erase all your work. Strange errors.

I briefed worked at a few hardware companies and I was always taken aback by the poor state of the tooling which was highly correlated with the license terms dicated by EDA tools. Software dev seemed much more interesting and portable. Working in hardware meant you would almost always be searching between Intel, Arm, AMD and maybe Nvidia if you were a rockstar.

Software by comparison offered plentiful opportunities and a skill set that could be used at an insurance firm or any of the fortune 100s. I've always loved hardware but the opaque datasheets and IP rules kills my interest everytime.

Also, I would argue software devs make better hardware engineers. Look at Oxide computer. They have fixed bugs in AMD's hardware datasets because of their insane attention to detail. Software has eaten the world and EEs should not be writing the software that brings up UEFI. We would have much more powerful hardware systems if we were able to shine a light on the inner workings of most hardware.

Designing silicon requires a much greater attention to detail than designing software since the penalty for bugs or a bad design is higher

Looks like a nice resource for the OMSCS Deep Learning class as well.

Seeing this thread, sounds a blog post comparing the offerings would be useful

Good idea at first glance, but it would get outdated in hours.

Every hype AI post is like this. “I’m making $$$ with these tools and you’re ngmi” I completely understand the joys of a few good months but this is the same as the people working two fang jobs at the start of Covid. Illusionary and not sustainable.

I built and debugged an embedded stub loader for Rp2350 to program MRAM and validate hardware status for a satellite. About 2.5 hours of my time, a lot of it while supervising students/doing other things.

This would have been a couple day+ unpleasant task before; possibly more. I had been putting it off because scouring datasheets and register maps and startup behavior is not fun.

It didn’t know how to troubleshoot the startup successfully itself, though. I had to advise it on a debugging strategy with sentinel values to bisect. But then once explained it fixed the defects and succeeded.

LLMs struggle in large codebases and the benefit is much smaller now. But that capability is growing fast, and not everything software developers do is large.

Yet it still can't solve a Pokle hand for me

How old were when you stopped? What made you realize you had an addiction?

Around 30 to 35, don't remember which year it was exactly.

And the thing that was largest in making me go, "Yeah, this isn't good for me, I need to quit" was that it was consuming my thoughts all the time. When I wasn't in front of the computer gaming, I was thinking about the game and planning the strategy for my next move. (I usually played turn-based games rather than action games). Which is fine in small doses, but it was taking over my mind when I was at church wanting to focus on worshiping God, when I was at work (and distracting me from getting work done), when I was trying to read...

Basically, I realized that it was an unhealthy focus for me, and taking over way too much of my attention that I wanted to be able to spend on a much wider variety of things. So I quit. First year was the hardest, second and third years were hard too, but by now I've gotten used to reaching for a book to read rather than a game. And the book, I can put down anytime I need to, without feeling that empty-ish feeling that says "Awww, I want to get back into the game..." That letdown when I exited the game was another clue, BTW: it matched how I'd heard drug addicts (specifically, former addicts who had kicked their habit) describe the feeling of coming down off a high. I've never used drugs myself so I can't compare it directly, but it was similar enough to the descriptions I'd heard from them that I said "okay, that's probably not a good sign either."

Are there archives of this? I have no doubt after this post goes viral some of these files might go “missing” Having a large number of conspiracies validated has lead me to firmly plant my aluminum hat

This makes sense for HPC and ML workloads. Big batch jobs where you are pushing the hardware and having everything local is a clear advantage. Also this company sells hardware so it makes sense for them to have hardware experience. Still think that for the majority on here, needing to make a physical phone call to their data center team (!!) to rack a server is a nutty proposition. You think the AWS api is slow? Trying calling Steve. If you have fixed compute costs after a year, sure, look at pulling some stuff on prem.