. Might be a little harder to hire the H1-B's through tata than it used to be. I'll be curious to see how this impacts these major contracting firms that have really abused the system.

I would say this psychosis descends to most levels of management. We have SVP's, VP's, and Senior Directors who all think the AI can just do all the work for us. I've heard that one SVP keeps asking why her son studying computer science can make all these wonderful things with AI in such a short time but we take so much longer to build and deploy things.

I will admit that AI has been a boon in my role. It's easy to point it at some messy project and ask questions until I understand what it is doing or why it looks wonky. It can also help craft mongo or sql queries faster than me based on the schema and description I provide. But, it cannot be trusted outright yet. And, I have to go back and double check the work constantly. If I just trusted it to do the work and deployed what it produced my company could find itself in legal trouble, and I would wind up being fired.

I'm not knocking the arts at all but I question how you measure the value returned and the quality of the art? Art is highly subjective. I've seen pieces of art that to me look like a toddler did them, but other people are just entranced by them. I can be absolutely entranced by some musical or theater performances and others I find just off putting. So how do you judge the value? How do you actually measure the return?

In terms of the money being paid out it sounds very similar to grant money to me. I've worked with multiple arts groups that apply for a receive grant money on a regular basis to put on art shows or theater productions. One of my friends has told me about artists she knew who received grant money and the art they produced which left me wondering how that was art... (again art is subjective). The main difference I see is that this is paid out monthly for the duration instead of a lump sum dispersement.

Finally does that $1.20 spent account for the overhead of running the program? Most charitable organizations are considered to be doing a good job if they keep their overhead to $0.20 to $0.35 per dollar spent. So if that $1.20 is only what is spent then the actual costs have to be $1.40 to $1.55 or higher depending on how well run this program is. Not to mention the costs of all the other government departments that have to have a hand in receiving the tax money, audiiting, accounting, etc...

Again, I'm not knocking the arts. I just don't think this sounds as groundbreaking as the article makes it sound.

If your AI can act on instructions given in slack, update code in source control, and then compile/deploy that code you just opened a whole can of worms. If I were a threat actor I would 100% be aiming to try and compromise their slack. Just tell the AI to introduce these few lines of code into the build... Or add this feature... It sounds like a security nightmare to me.

I had another broadband provider at my old house and Comcast bought them out. Suddenly the cable modem which came free with my service for five years had a monthly charge and they jacked my price. Bought my own modem and they kept trying to charge me the rental fee. Move to another house and they tried to charge me rental on my own hardware again and jacked the price more. My wife wound up trying to get them to fix a bill that they screwed up. They brought down the red headed fury and she cancelled everything. Had fiber service up within a few days and havenâ(TM)t looked back. Their prices are a joke and their customer service is trash.

Obviously you weren't paying attention to the first few months of Biden's presidency in which he signed EO's rolling back as many of Trump's EO's as possible. Executive Orders have been a thing for quite a while. When Obama couldn't get congress to do what he wanted he was quoted as saying something like "I have a pen and a phone" and then making a number of executive orders. That set the stage before Trump became president the first time to start passing EO's. Both sides do it, and it should be done far less.

When I last dealt with these contracting firms, and when the model was at its worst for us, we would have a few full time employees scoping and drafting up the project. There would be an onshore contracting lead, an offshore contracting lead, and then the offshore team.

Those multiple layers allowed them to jack up the charges, insist they needed more contractors on each project, and hide the quality of the contractors we were given. I was extremely confident we were getting very low quality engineers with barely any experience and the majority of the actual work was being done by that offshore lead. Unfortunately we were being driven to push more and more work to contractors at that time until it all blew up and they reversed course bringing everything back in house.

We do have an offshore captive presence today but they are all full time employees now, not contractors. We also have better alignment where my quality of life isn't suffering because of having to do early AM and late PM calls with offshore.

Jacking up the price of H1B's will impact that onshore/offshore contracting lead model which will make the costs less desirable to companies and potentially removing their ability to field the onshore leads who mask what is really happening offshore.

I think for any company that truly is using H1B's to bring in talented workers who they want to employ it will encourage them to sponsor green card applications with a higher frequency rather than using the H1B model to keep workers as indentured servants. I'm good with that because someone coming in on a green card has the option to compete in the market and receive market rates. It may even cause companies to consider going back to hiring local talent and *gasp* actually doing career development.

It's not "boomer shit" it's reality. When companies hunker down, which is what has been happening for the past few years, hiring becomes limited. And, the honest truth is that large companies are already hyper selective of who gets in the door direct from college. I don't agree with it, but it is the reality. Many of the best engineers I've worked with were not the ones with the top grades who got their foot in the door right out of college. In fact in my experience many of those top grade kids are some of the first out of the door because they are chasing job title jumps.

And, FYI I'm not old. But, I have been in the market long enough to see a few hiring cycles. Over the last few years companies laid off most of their recruiters and attrition has stalled out. This problem has been growing for at least 3-4 years. I'm hoping we're at the peak and it will trend back down afterwards.

Anyone who finds themselves outside the market right now needs to do anything and everything they can to stay relevant. Take a lower paying tech job if you can find it. Contribute to open source, or create your own project. Volunteer your technical skills with a charitable organization. Go talk to a military recruiter and see if you could use your degree in the military. If you sign up with a college degree you will probably go to OCS and become an officer. Re-enter the workforce later on as an honorably discharged officer with a bachelor's degree and a tech background and you will be very marketable vs someone who did nothing with their degree and instead served coffee or burritos.

Is she only looking at large companies? If so she needs to broaden her perspectives. You're not going to get a job at Google, Meta, Amazon, Apple, or any other Fortune 500 company unless you're near the top of your class coming directly out of college. I know for a fact my company has a limited pipeline for college grad engineers and they have to be darn good to get their foot in the door. In fact you won't get your foot in as a college grad here unless you also interned here. Anyone else has to go work somewhere else for a while and then apply once they have experience. The vast majority of engineers I work with, including myself, went that latter route.

My main guess is that the primary use is for trend analysis. If you throw a relatively large amount of data at the right LLM and ask it questions it can find patterns in the data which a human may miss. You can't empower more people to ask more questions about the data in a natural language model and potentially come up with more insights.

Once you have various signals identified from your data you can train a model to take actions on those signals and it can tell you now is the right time to raise prices on route A. Or maybe it suggests discounting Route B. Or perhaps you normally would raise the price on Route C but the signals aren't strong enough so the model tells you to only do 50% of your normal increase.

You can of course achieve all that with normal processes too. But, the LLM makes it easier in some ways to achieve the same goal. So long as you double check your results.

I don't think it's just "less educated" people who get stuck in their bubbles. I know plenty of well educated people who while very smart in some subjects are dumb as rocks in others. I know doctors, nurses, and engineers who all have been stuck in their own bubbles of idiocy.

I had one of those people as my manager's manager around that time. I did not realize how much the immediate layer of management was shielding us from him until three managers burned out in rapid succession and I wound up reporting directly to him for a period of time. One of the first hints I had about his behavior after that was when I was called over to his desk to explain what he just heard about us needing to buy several more waves of servers for the project we were on and he had never heard this yada yada yada. I politely asked if he had the spreadsheet that showed the expansion phases of the project and the hardware needed for each phase. He opened it up on his computer and showed it to me. I asked him to scroll down. His jaw dropped. The idiot had never scrolled down. Worse yet in his eagerness to get ahead he had given back the budget for all the hardware. I'm sure he tried to throw me under the bus when begging for the money back.

Later on he made the very big mistake of blaming an admin for various things, claiming she never sent him things or she must've lost his response. He finally learned not to lie about an admin to the vp she supports because he was fired. A good admin is far closer and tighter with the vp they support than any subordinate to that vp.

That single bad manager caused at least seven good people I knew to quit the company and never look back. Taking all their knowledge and experience with them. The project ultimately succeeded. And, I did not get run over by the bus. Partly because that same admin was a friend of mine and I'm sure she relayed to the vp the whole incident about the spreadsheet.

I lived through a few years where my employer was quietly cutting the "bottom 10%". It was ugly. Everyone knew it was happening and it definitely created a hostile work environment and people would step on each other just to make themselves look better to avoid being cut.

The way it played out was that every area had to find a bottom 10% even if everyone on their team were rockstar contributors. So if team A was all rockstars and team B were all less-good engineers guess what? Instead of cutting only from team B and transferring a rockstar over they would cut a rockstar and a less-good engineer at the same time. Everyone saw it.

Eventually the rockstar employees stopped helping the new guys because they didn't want to enable someone leveling up and them getting cut. A lot of people left to get away from it. And, at the end of the day most of management was populated by even worse jerks because they were the ones who had gleefully stepped on anyone in their way in order to not be considered bottom 10% material.

It took almost a decade after that policy ended for the culture to really turn around. And, that involved cutting th ranks of middle management populated with those jerks who had survived/thrived from the bottom 10% policy.

I clicked into the article and did not see any quantitative numbers only percentages. That doesn't tell me much. Especially since it seems to report increased over the previous rate. So if 10 researchers applied for positions in Canada the year before and now it's 13 this year, that's a 30% increase which sounds really dramatic but, would only be 3 people.

The only quantifiable numbers I saw in the article were the total number of open positions hosted on their board. Which sound dramatic but it doesn't seem to give me a solid understanding of how those number relate to historical trends.

So the article could be a giant nothing burger, or it could indicate a huge problem. Just can' tell when I'm only given percentages.

Well, if we follow your reasoning here are some common terms which we would have had to come up with other words for:

Tablet - A slab of stone or clay used for writing, now a portable touchscreen computer
Mouse - A small rodent, now used to describe a computer input device
Spam - A canned meat product, now means unsolicited email or messages
Stream - A small river, now to watch or listen to media online in real time
Swipe - A quick movement (often to steal), now to move your finger across a touchscreen
Cool - A slightly cold temperature, now stylish or trendy

Here's a few more: startup, unicorn, pivot, disrupt, gig, agile, ecosystem, bandwidth, deliverable, scale, remote, hack, influencer, viral, content, hybrid, sandbox, ping, onboarding, etc...

And, let's not forget the word engineer. I know this will get a few people's goats. It used to be someone who worked with bridges, engines, infrastructure, manufacturing, construction, and in many fields required a certification and formal education. Now we have software engineers...

That was just from a quick query to ChatGPT. The list goes on and on and on. There are many business buzzwords I left out because I too find them annoying. I've seen quite a few come into fashion and then fizzle out of usage. But, the fact remains that we repurpose words all the time. Sometimes the changes stick, sometimes they don't. Picking a fight over the single word "spend" as a noun when it has been commonplace for around fifty years is a bit silly.