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Having lived through both ... the job market was INSANE during dot-com. Getting a job was like falling off a tree. If this is 17 times bigger, where are the job

Having lived through both ... the job market was INSANE during dot-com. Getting a job was like falling off a tree. If this is 17 times bigger, where are the jobs (serious question)?

badpun 1y ago
The money goes to hardware this time, not to labor.
- jmaestrooper 1y ago
  Hardware doesn't just pop out of the thin air. Data centers need to be built, GPUs need to be produced, and storage, and other compute, and networking, etc etc. All this needs people. Shouldn't there be boom in construction? Hardware manufacturing?
  - orwin 1y ago
    I've read that the US have almost a million skilled worker shortage in construction (especially commercial and industrial that demand more specific skills), and that since a quarter of the demand is for federal/state/county projects that cannot decide as fast as a company to accept rising prices, it also mean the already decaying public infrastructure risk to never be repaired in time (constructing new stuff is more expensive than repairing expensive stuff. More GDP growth i guess, but :/) And you have a boom in hardware manufacturing, in Asia mostly, but even in europe you see new companies popping up (before Covid we had like 2 comapnies that could print custom pcbs, both german, now i found like 5 in France (2 of them are the german who expended but still))
  - badpun 1y ago
    All the electronics (inlcuding the insanely expensive GPUs from Nvidia) are imported from Asia.
mongol 1y ago
Good point. The dot-com co-incided with the Y2K bug timeframe. I don't think getting a job in IT was ever easier.
kypro 1y ago
To build a dot-com you needed an army of geeks who knew how to use computers. To build an AI company you need a small team of PHDs and a huge GPU budget.
- marstall 1y ago
  i've hung on for 35 years in this profession by reskilling every 5 years or so. but going through the gauntlet of learning the AI theory/tech sufficiently to be able to contribute meaningfully, and then compete for one of these tiny number of jobs seems unwise particularly at my age. Fortunately I'm employed but I have limited ideas on how to gain an edge for the next jobsearch, whenever that is.
  - alephnerd 1y ago
    If you are actually serious, I'd recommend 1. Living in a tech hub like the Bay Area or Seattle. There may be tech hubs in RTP, Austin, Boston, etc but these tend to be inshoring offices and are oftentimes the first on the chopping block when offshoring is considered, because they never built the internal gravity needed to own P/L and roadmap, and those offices that did are few and far between. 2. Concentrate on doing a reputable online or part-time MSCS (eg. GATech, UIUC, UT Austin) and concentrating on fundamental courses. Coding is commodified, but programming isn't. Just understanding how to glue together Python, C/C++, or whatever language and associated libraries is not enough. Technical complexity is rising, and skills like understanding OS internals, understanding the fundamentals of SGD, or truly understanding how to derive a path tracing algorithm matters. 3. Hyper-specialize in a specific industry. "AI" is broad, just like "Mobile" was broad. What matters is how these platforms are applied to a specific industry subdomain. If I'm a cybersecurity company working on building an AI SOC, I'd rather hire Engineers who understand both core fundamentals of AI and Cybersecurity. If you are an engineer who can understand how to communicate both the business incentives as well as the engineering incentives you are worth your weight in gold. The thing is, this isn't 2000 anymore. Eastern Europe, China, India, ASEAN, LATAM, and other regions of the world have fairly large and robust dev and tech scenes, and async+remote work has been proven out during COVID, thus removing one of the biggest barriers to offshoring. Additionally, there has been a reverse brain drain since the mid-2010s from the US to those countries that is making it easier to find talent to open an office following American norms. I think as a mid-career engineer, you have the tools to survive this kind of a change. Any American SWE who graduated in the last 10 years is in a worse position because their universities failed them by watering down curricula to compete with bootcamps, reducing the business justification for building a domestic new grad pipeline aside from a couple top target programs.
cheema33 1y ago
In the dotcom era, money was mostly being spent on people would could help create websites. In the AI era, money is mostly going to NVIDIA.
- kulahan 1y ago
  Surely we can all see the difference between a whole bunch of websites being paid for (lots of ethereal bits) and lots of actual computing hardware? Even if AI dies off, I imagine there are tons of uses for those same farms. Computing power might get cheap for a while, but I'd be pretty shocked if this resulted in another pets.com Definitely interested to see where my thinking is off here, if anyone can help. This just doesn't seem much like a bubble to me.
  - grues-dinner 1y ago
    > Even if AI dies off, I imagine there are tons of uses for those same farms Are there tons of uses for 2023 crypto farm hardware? A trillion dollars of GPUs in various stages of obsolescence and/or shagged-outness in data centres might be useful to the right people but it's a depreciating asset.
    - kulahan 1y ago
      Everything in tech is a depreciating asset. If you're talking about GPUs used for mining crypto, yeah - most people run them well below max load, keep temps stable, and pay close attention to their crypto farm. Buying a used crypto farm GPU is great. If you're talking about purpose-built ASICs, probably still yes? It's not like it's performing some incredibly unique action when farming for crypto. The secondhand electronics market is fairly strong.
      - bloudermilk 1y ago
        Any good guides for buying on this secondhand market? I'd love to pick up some older decommissioned hardware but it's hard to find and harder to trust
pjmlp 1y ago
Same here, kids that barely knew HTML getting hired no questions asked, no letcode, no mission statement about changing the world, no repos on source sourceforge required,....
doublerabbit 1y ago
Start-Ups and Internal positions. Not old enough for the dotCom (36) but my educated guess is that because the internet was new and exciting, companies were prepared to train and take risks. Training for AI now requires specialist skills which can be syphoned from within an existing organisation or from those with existing skill sets. Unlike the latter where anyone can pick up a programming language. Not everyone can do quantum algebra mechanics or whatever AI/ML uses. Plus the cost of running AI is expensive. SME's don't have the resources to hire those for new jobs; AI kit and training. So it's easier to hire from within then outside. AI is a rich boys toy.
- kevindamm 1y ago
  it's Tensor Calculus, mostly... but it's also a fair amount of systems engineering. The proportion of each depends a lot on whether the task is research or application.
  - samat 1y ago
    Still harder than PHP…
  - doublerabbit 1y ago
    No knowledge on such a thing. Wikied it up then got introduced to Christoffel symbols. Sounds editable. But from what I understood is that they're correction coordinates to something thats not sitting straight on a curve; I'll pass. I never got given maths at school.
lawn 1y ago
This bubble develops tools that supposedly replace developers.
theli0nheart 1y ago
The big difference is that the dot-com bubble coincided with low interest rates, whereas interest rates increased sharply after COVID ended, which was right when AI was taking off. If we were still in ZIRP things would be insane.
MadDemon 1y ago
During the dot-com era, a much larger share of the money could be spent on engineers. Today, a lot of the money goes into data centers and not salaries.
xcskier56 1y ago
My friend owns a metal stamping company. One of the things they make are the heat dissipation fins for radiators. That portion of their business has grown 20x in the last few years.
jmaestrooper 1y ago
My guess would be infrastructure. Like brick and mortar, buildings, laying down fiber, installing and setting up servers, and then maintenance. Construction is booming... Or should be. Any day now :)

Having lived through both ... the job market was INSANE during dot-com. Getting a job was like falling off a tree. If this is 17 times bigger, where are the jobs (serious question)?

badpun 1y ago

The money goes to hardware this time, not to labor.

jmaestrooper 1y ago
Hardware doesn't just pop out of the thin air. Data centers need to be built, GPUs need to be produced, and storage, and other compute, and networking, etc etc. All this needs people. Shouldn't there be boom in construction? Hardware manufacturing?
- orwin 1y ago
  I've read that the US have almost a million skilled worker shortage in construction (especially commercial and industrial that demand more specific skills), and that since a quarter of the demand is for federal/state/county projects that cannot decide as fast as a company to accept rising prices, it also mean the already decaying public infrastructure risk to never be repaired in time (constructing new stuff is more expensive than repairing expensive stuff. More GDP growth i guess, but :/) And you have a boom in hardware manufacturing, in Asia mostly, but even in europe you see new companies popping up (before Covid we had like 2 comapnies that could print custom pcbs, both german, now i found like 5 in France (2 of them are the german who expended but still))
- badpun 1y ago
  All the electronics (inlcuding the insanely expensive GPUs from Nvidia) are imported from Asia.

mongol 1y ago

Good point. The dot-com co-incided with the Y2K bug timeframe. I don't think getting a job in IT was ever easier.

kypro 1y ago

To build a dot-com you needed an army of geeks who knew how to use computers. To build an AI company you need a small team of PHDs and a huge GPU budget.

marstall 1y ago
i've hung on for 35 years in this profession by reskilling every 5 years or so. but going through the gauntlet of learning the AI theory/tech sufficiently to be able to contribute meaningfully, and then compete for one of these tiny number of jobs seems unwise particularly at my age. Fortunately I'm employed but I have limited ideas on how to gain an edge for the next jobsearch, whenever that is.
- alephnerd 1y ago
  If you are actually serious, I'd recommend 1. Living in a tech hub like the Bay Area or Seattle. There may be tech hubs in RTP, Austin, Boston, etc but these tend to be inshoring offices and are oftentimes the first on the chopping block when offshoring is considered, because they never built the internal gravity needed to own P/L and roadmap, and those offices that did are few and far between. 2. Concentrate on doing a reputable online or part-time MSCS (eg. GATech, UIUC, UT Austin) and concentrating on fundamental courses. Coding is commodified, but programming isn't. Just understanding how to glue together Python, C/C++, or whatever language and associated libraries is not enough. Technical complexity is rising, and skills like understanding OS internals, understanding the fundamentals of SGD, or truly understanding how to derive a path tracing algorithm matters. 3. Hyper-specialize in a specific industry. "AI" is broad, just like "Mobile" was broad. What matters is how these platforms are applied to a specific industry subdomain. If I'm a cybersecurity company working on building an AI SOC, I'd rather hire Engineers who understand both core fundamentals of AI and Cybersecurity. If you are an engineer who can understand how to communicate both the business incentives as well as the engineering incentives you are worth your weight in gold. The thing is, this isn't 2000 anymore. Eastern Europe, China, India, ASEAN, LATAM, and other regions of the world have fairly large and robust dev and tech scenes, and async+remote work has been proven out during COVID, thus removing one of the biggest barriers to offshoring. Additionally, there has been a reverse brain drain since the mid-2010s from the US to those countries that is making it easier to find talent to open an office following American norms. I think as a mid-career engineer, you have the tools to survive this kind of a change. Any American SWE who graduated in the last 10 years is in a worse position because their universities failed them by watering down curricula to compete with bootcamps, reducing the business justification for building a domestic new grad pipeline aside from a couple top target programs.

cheema33 1y ago

In the dotcom era, money was mostly being spent on people would could help create websites. In the AI era, money is mostly going to NVIDIA.

kulahan 1y ago
Surely we can all see the difference between a whole bunch of websites being paid for (lots of ethereal bits) and lots of actual computing hardware? Even if AI dies off, I imagine there are tons of uses for those same farms. Computing power might get cheap for a while, but I'd be pretty shocked if this resulted in another pets.com Definitely interested to see where my thinking is off here, if anyone can help. This just doesn't seem much like a bubble to me.
- grues-dinner 1y ago
  > Even if AI dies off, I imagine there are tons of uses for those same farms Are there tons of uses for 2023 crypto farm hardware? A trillion dollars of GPUs in various stages of obsolescence and/or shagged-outness in data centres might be useful to the right people but it's a depreciating asset.
  - kulahan 1y ago
    Everything in tech is a depreciating asset. If you're talking about GPUs used for mining crypto, yeah - most people run them well below max load, keep temps stable, and pay close attention to their crypto farm. Buying a used crypto farm GPU is great. If you're talking about purpose-built ASICs, probably still yes? It's not like it's performing some incredibly unique action when farming for crypto. The secondhand electronics market is fairly strong.
    - bloudermilk 1y ago
      Any good guides for buying on this secondhand market? I'd love to pick up some older decommissioned hardware but it's hard to find and harder to trust

pjmlp 1y ago

Same here, kids that barely knew HTML getting hired no questions asked, no letcode, no mission statement about changing the world, no repos on source sourceforge required,....

doublerabbit 1y ago

Start-Ups and Internal positions. Not old enough for the dotCom (36) but my educated guess is that because the internet was new and exciting, companies were prepared to train and take risks. Training for AI now requires specialist skills which can be syphoned from within an existing organisation or from those with existing skill sets. Unlike the latter where anyone can pick up a programming language. Not everyone can do quantum algebra mechanics or whatever AI/ML uses. Plus the cost of running AI is expensive. SME's don't have the resources to hire those for new jobs; AI kit and training. So it's easier to hire from within then outside. AI is a rich boys toy.

kevindamm 1y ago
it's Tensor Calculus, mostly... but it's also a fair amount of systems engineering. The proportion of each depends a lot on whether the task is research or application.
- samat 1y ago
  Still harder than PHP…
- doublerabbit 1y ago
  No knowledge on such a thing. Wikied it up then got introduced to Christoffel symbols. Sounds editable. But from what I understood is that they're correction coordinates to something thats not sitting straight on a curve; I'll pass. I never got given maths at school.

lawn 1y ago

This bubble develops tools that supposedly replace developers.

theli0nheart 1y ago

The big difference is that the dot-com bubble coincided with low interest rates, whereas interest rates increased sharply after COVID ended, which was right when AI was taking off. If we were still in ZIRP things would be insane.

MadDemon 1y ago

During the dot-com era, a much larger share of the money could be spent on engineers. Today, a lot of the money goes into data centers and not salaries.

xcskier56 1y ago

My friend owns a metal stamping company. One of the things they make are the heat dissipation fins for radiators. That portion of their business has grown 20x in the last few years.

jmaestrooper 1y ago

My guess would be infrastructure. Like brick and mortar, buildings, laying down fiber, installing and setting up servers, and then maintenance. Construction is booming... Or should be. Any day now :)