Oh Jua, it's cool to see that name. They've been on my radar since I applied to (and was rejected by) them earlier this year. I'll be interested to see the research paper once it is published next week, especially since they claim their model surpasses Aurora and Graphcast
Readit Newsgoochphd commented on Swiss startup says its AI weather forecaster beats Microsoft, Google thenextweb.com/news/swiss... · Posted by u/scanny
goochphd commented on Infinite Grid of Resistors mathpages.com/home/kmath6... · Posted by u/niklasbuschmann
I don't get why EE education emphasizes problems of this sort. The infinite grid is an extreme example, but solving weirdly complicated problems involving Kirchoff's laws and Thevenin's theorem was a common way to torture students back in my day...
Here, I don't think it's even useful to look at this problem in electronic terms. It's a pure math puzzle centered around an "infinite grid of linear A=B/C equations". Not the puzzle I ever felt the need to know the answer to, but I certainly don't judge others for geeking out about it.
I was about to say "they still torture students this way" but stopped myself when I remembered I took Circuits 1 and 2 back in 2007. So maybe my knowledge is dated too...
It's a weird butterfly effect moment in my career though. I had an awesome professor for circuits 1, and ended up switching majors to EE after that. Then got two more degrees on top of the bachelor's
goochphd commented on Aurora, a foundation model for the Earth system nytimes.com/2025/05/21/cl... · Posted by u/rmason
Very cool project. There are some presentations by the PI on youtube that I recommend searching for. One of the interesting takeaways I had was that they were able to do better with mesoscale phenomena and extreme weather prediction than the other players (like Graphcast and Pangu and FourCastNet), in part due to their technique for training a higher resolution data space (0.1 deg vs 0.25 or 0.5). I also found it interesting that they were able to show a scaling relationship where performance increased by 5% every time they doubled the model size - and their loss was still improving when they had to cut it off due to cost constraints.
Very cool stuff!
> The GNSS-based Upper Atmospheric Realtime Disaster Information and Alert Network (GUARDIAN) is an ionospheric monitoring yadayadayadascience
That's a pretty impressive number of scrabble points for a project acronym, and I guess bonus points for building that acronym on top of another acronym (GNSS = Global Navigation Satellite System, generic term for America's GPS).
I know government projects have a long, storied history of such wordplay. Anyone have any fun stories on coming up with a really elaborate one? I wonder if chatGPT will unleash a new era of creativity with these...
I love the creativity that goes into naming these projects in the geosciences! I've been a part of several of these projects myself, and have used data and collaborated with teams from many more.
One point of clarification: GNSS is a term that has broader application than you describe, as it encompasses constellations from other countries and political associations as well. For example:
* Galileo - European Union's GNSS system, named after the astronomer * BeiDou - China's GNSS system * GLONASS - Russia's GNSS system * JAXA - Japan's GNSS system
One backronym that I liked from my time doing my PhD was RELAMPAGO, which is a Spanish word for "lightning," but which some group of scientists gave this definition: "Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations". It was a very cool campaign that produced a ton of amazing data, and catalyzed many dissertations (including one of my close friend's).
goochphd commented on Why is it so hard to find a job now? Enter Ghost Jobs arxiv.org/abs/2410.21771... · Posted by u/JSeymourATL
I'm about a year into a mid-effort level job search. I work in a somewhat specialized technical field and am fairly senior (I think in FAANG-ese I'd be an maybe an L7 if I understand their levels correctly). So this means I'm looking for management, director, deputy CTO or CTO positions depending on the company. I have a track record making my company lots of money, and opening up new opportunities worth many multiples of that. So the deck is already stacked against me as most positions are for jr or mid engineers, but I have a proven track record of growing responsibilities and (in my market) fairly recognizable success stories.
The search has been absolutely atrocious. Unlike anything I've ever seen before in 30 years of working in tech.
* I used to be able to simply pull on my network and get a position within 2 or 3 tries. Total job hunt time, under a month.
* The last time I had to go through this was pre-COVID, and I used a mix of my network and cold applications (around 50). I only heard back from 2 of the cold submissions and my network pulled me in to where I am today. Total job hunt time, around 4 months.
* I'm almost exactly 1 year in now, over 700 applications, people in my network can't even get responses for referrals. I've made it to 4 interview funnels, including stupidly exhausting FAANGs, for positions ranging from CTO to consultant filling a contract slot. 2 solid offers, both at least 40-60% below my current market rate. One executive recruiter ghosted me after we started discussing Total Compensation Packages.
I even had a friend post a position at their company, using my resume as the hiring template. Then they personally referred me to that position. I never received a call, and they never received any candidates.
It feels like being personally blacklisted, but it's affecting everybody I know.
The furthest I've gotten has been by hunting down corporate and executive recruiters directly, but I've had two recruiters get laid off halfway through the matching process. One FAANG recruiter has even contacted me hoping I could help them find a position.
Something is broken somewhere. Companies are starving for talent, and talent is starving for companies. The online applications sites are clearly filtering out people, but there appears to be massive churn in the recruiting side as well.
/r/recruitinghell is very representative of things I've seen.
I did notice that hiring activity has picked up since the rollover of the FY. Several 6-7 month old applications stirred somebody to contact me in the last month or so with a "great fit" that turned out to have nothing to do with my skillset.
My story is finally drawing to a close however, I've just negotiated a good position at a new firm and am setting a start date.
That's great that you found a new spot.
I've seen other research and discussion on this topic. Some stats that may be validating for you (and others) to hear:
* There's a 0.08% job application -> offer rate when applying through LinkedIn (LI). An average of 1 in 1,250 applications lead to an offer
* The linked paper on this post finds that 21% of postings are ghost jobs, but I've seen credible estimates that the proportion is as high as 50%
* A Stanford survey found hundreds of fake LI profiles, AI-generated "recruiters" that are interacting with candidates and posting ghost jobs on behalf of big companies
* ~75% of resumes from qualified applicants are never seen by a human
* resumes get on average 6 to 8 seconds of consideration when they are reviewed by a human
* 300,000 jobs are outsourced annually (with respect to the US)
All this to say, you're right, something is fundamentally broken in the labor market, especially the tech labor market. And not that many people are talking about it, except for those of us who have been unfortunate enough to need to look for jobs in the past ~2 years.
In my own case, my previous employer (a startup) ran out of money and laid everyone off last Fall. I was fortunate enough to find a new position, but this job search was the hardest I've faced since 2008 - and it seems worse now than it was this time last year.
goochphd commented on Why is it so hard to find a job now? Enter Ghost Jobs arxiv.org/abs/2410.21771... · Posted by u/JSeymourATL
I once applied for a job that precisely matched my qualifications. It was crazy - the job description could have been written by someone looking at my CV.
I didn't even get an interview. Likely no one did.
It wasn't a ghost job, though. It was a position created for a someone they wanted to hire. Being a public institution, they were required to advertise positions. That didn't mean that they actually wanted any of the candidates who applied.
I once applied to a position like this. It was eerily similar to my background, and when I did a little digging I found that the group lead had even directly cited my research papers in his own research work.
I applied on the site, reached out on LinkedIn to the group lead and the recruiter, and even was able to find emails for those two, which I also messaged as well.
They didn't even bother to send me an automated rejection notice. There was nothing at all, no responses to any messages, no email, nothing. I have to assume that position was posted with someone already in mind that they wanted to hire.
It's disappointing to see how they cannot see what it means for libgen to exist in the broader sense.
Books should be free for all, and we should encourage and educate people to donate back the value they received from them
I don't even mind paying up front anymore. I'm in a position where I can afford it now, though for most of my adult life I've relied on sites like this to make ends meet.
However the only thing I want from publishers is DRM-free e-books (same for music). If you offer a way for me to actually own the digital property I'm buying, I'm going to buy it. If you make it hard or impossible to transfer between my devices, or share with my wife and kids (i.e. how physical media works), you're not getting my money and I'll find another way to get the book.
> name an example from the category
Do you mean synonyms, or something else? Can you give an example of a category and A, B, C please? Thanks.
Yeah for sure. So say your category is "fruits and vegetables". You might say Avocado, Banana, Celery, etc. The goal is to challenge yourself, and it's more of a stretch than you'd think (but a good exercise). Or at least, it was a stretch for me especially at the beginning
Fuck, I recently had Covid and I've been having trouble recalling things. Every other day or so I'll spend 5-10 seconds remembering the name of something. It's possible this happened before I got Covid, though... I don't remember!
This happened to me following a concussion. I worked with a therapist who suggested a "game" that could help my word recall. Every night before sleeping, pick a category and try to name an example from the category for each letter of the alphabet. Choose a different category every night so you're always challenging yourself.
Of course there's no substitute for working with a PT who specializes in post TBI recovery.
I've gained a lot of my recall back (though not at 100%).
This is a phased array device. Angular resolution 20 degrees, range resolution 1 meter. It's not a Doppler radar, so it can detect fixed objects. So if you're using it for people detection, you have to tell it where the fixed objects are. A ceiling mounted unit will see the floor. OK for people counting and such. Range is only 10 meters.
If you just want a motion detector to turn on a light, and IR isn't working for you, there are cheaper microwave detectors.
Of course, indoor settings have a lot of non-stationary objects as well that might not be targets of interest to you, like fans, curtains blowing in the breeze, etc. So you can also develop algorithms to remove those signatures too.
Seeing fixed objects can be beneficial as well, for example, if you have a sensor deployed in a room but you don't know a priori what the room looks like. Longitudinal results and long range statistics can take you pretty far in seeing the room extents and layout and furniture, etc. Though a lidar sweep is better if you can get it