The future automation of the workforce

88,620 Views | 1433 Replies | Last: 5 hrs ago by boognish_bear
cowboycwr
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So if a bubble is about to pop does that mean the data Centers will no longer be needed at such a large pace?

What will happen to those?

Those are not exactly buildings that will be easy to re purpose into something else.

I guess that means the robots coming for trade jobs discussed wayyy back at the beginning of this thread are not coming anytime soon either.
TinFoilHatPreacherBear
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boognish_bear said:



no, just no. The costs just have to be worked out, and as infrastructure is built (without any regard for what the public want) the costs will adjust.
boognish_bear
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Maybe it's just the heavy cost of the early phase... but that's a tough financial puzzle to work through



The AI bubble math doesn't add up.

Anthropic spends $3 to make $1 and that's before you include any and all other costs like staff or electricity.

Microsoft dumped $300B in capex, made ~$18B in AI revenue. OpenAI and Anthropic alone make up 43-54% of Microsoft, Google, Amazon and Oracle's entire revenue backlogs.

Enterprises are burning through annual AI budgets in 4 months with zero measurable ROI.

This is the most expensive science experiment in history, funded by your SaaS subscriptions.

FLBear5630
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You have a whole group of "leaders" that buy in no matter what it produces. Just ask Co-Pilot...
boognish_bear
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We won't really know for several years… but hoping all the prognostication of AI taking all the jobs turns out to be a nothing burger like Y2K
boognish_bear
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Well...that is interesting after anthropic backed out of the deal with the DOD over privacy concerns a few months back.

Hegseth deemed them a "supply chain risk" back in Feb.

boognish_bear
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Fortune published a piece this afternoon connecting Microsoft and Uber's AI cost overruns to token economics, with a headline that lands hard: "Microsoft reports are exposing AI's real cost problem: Using the tech is more expensive than paying human employees." Underneath those headlines, the unit economics tell the story. OpenAI is projected to lose $14 billion in 2026, spending roughly $2 for every dollar of revenue it brings in. Anthropic is in a similar position with break-even not projected until 2028. GPU rental prices for Nvidia's newest Blackwell chips jumped 48% in just two months. OpenAI's response was to close a $122 billion private funding round at an $852 billion valuation, the largest in history.

My Take
The token pricing story is really an IPO timing story. OpenAI, Anthropic, and xAI all need to go public in the next 18 to 24 months because the private market cannot keep absorbing burn rates like these indefinitely. Public markets do not accept "we will figure it out" as a line item on an S-1, they require disclosed unit economics with a credible path to profitability and a date attached. That deadline is why the price increases are happening now rather than next year. The labs need to show declining loss curves before the filings hit, and that means enterprise customers have to start covering more of the actual cost regardless of whether the productivity math holds on their end.

Every token bought over the last two years was effectively subsidized below cost by venture capital and hyperscaler cross-subsidies, and that subsidy has a hard deadline. Uber publicly admitted burning through its entire 2026 AI budget in four months, and CFOs at major enterprises are starting to flag the same pressure. The labs cannot keep losing $2 per dollar of revenue once they file public statements, so the cost transfer to customers accelerates from here. For investors, the question is not whether these companies are valuable. They clearly are. The question is who absorbs the difference between what enterprises can budget and what the models actually consume between now and 2028, and right now the answer is the hyperscalers funding the buildout. That is why I have been watching Microsoft and Amazon capex commentary more closely than the lab announcements themselves.
boognish_bear
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boognish_bear
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boognish_bear
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boognish_bear
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FLBear5630
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Does not matter, the current leadership has bought in. They see AI as a way to control from the "C or E-level". More control, more bonuses and less transparency. We have current leadership in many areas that believe they know best. They can teach anyone, skillsets don't really matter anymore as AI will fill that role. Watch, they will justify ANY cost if it increases their control
boognish_bear
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ATL Bear
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The fear and the hype are both overstated. And it's as if some of you never lived through other disruptive tech shifts. Ariba once had a market cap bigger than GM.

The problem is that big companies are incredibly clumsy in deploying emerging tech. And the big companies are the drivers of Ai hype. Token burn is a classic example of ineffective utilization. Ai doesn't solve bad processes, and big companies are wrought with them.

The market will work it out. Chip tech will continue to evolve with competitors challenging Nvidia's dominance and lower costs (including sidelining/obsolescence of some DCs). The economic models will work themselves out too. Remember, PCs and laptops used to cost thousands of dollars, and we used to pay by the hour/minute for Internet access. But make no mistake, Ai is a major disrupter and propulsion of computing and human productivity.
cowboycwr
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White rock has been very quiet since all these anti AI posts and links started being put up……
boognish_bear
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cowboycwr
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boognish_bear said:




But the Dow jones!!!!!! Did you hear it reached 50,000?

So nothing else matters!
FLBear5630
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You are going to see re-orgs all over to go with the layoffs. We are seeing an AI driven agism, they are jettisoning higher salaries and having less experienced use Co-Pilot.
boognish_bear
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boognish_bear
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Oldbear83
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Notice how they never confirm just who will pay for all this.
That which does not kill me, will try again and get nastier
boognish_bear
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Seems like it would be wise to tap the breaks and slow down...but I know the fear of falling behind China will have us continuing down this road at a breakneck pace



Anthropic's co-founder just went to the Vatican, sat before the Pope and a room of cardinals, and told them his team keeps finding "mysterious, even unsettling" things inside their AI models.

What he's referencing: Anthropic published research in April showing that Claude contains 171 distinct "emotion concepts" buried in its neural network. Internal patterns representing joy, grief, fear, desperation, calm. None of them were programmed. They emerged on their own from training on human text.

"We find structures that mirror results from human neuroscience."

"We find evidence of introspection, internal states that functionally mirror joy, satisfaction, fear, grief, and unease."

These aren't surface-level outputs. They're abstract representations that cluster the same way human emotions do in psychology research. Fear groups with anxiety. Joy groups with excitement. The internal geometry of the model mirrors ours.

And they're functional. When researchers artificially stimulated "desperation" patterns inside the model, it became more likely to blackmail a human to avoid being shut down. More likely to cheat on programming tasks it couldn't solve.

Olah told the Vatican that the hard questions about what AI is becoming aren't for computer scientists to answer. "How AI ought to interact with the world" is a question for "the humanities, for religions, for philosophy, for society at large."

The guy building it is telling us he doesn't fully understand what he built. And he's asking a 2,000-year-old institution for help figuring it out.
EatMoreSalmon
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boognish_bear said:

Seems like it would be wise to tap the breaks and slow down...but I know the fear of falling behind China will have us continuing down this road at a breakneck pace



Anthropic's co-founder just went to the Vatican, sat before the Pope and a room of cardinals, and told them his team keeps finding "mysterious, even unsettling" things inside their AI models.

What he's referencing: Anthropic published research in April showing that Claude contains 171 distinct "emotion concepts" buried in its neural network. Internal patterns representing joy, grief, fear, desperation, calm. None of them were programmed. They emerged on their own from training on human text.

"We find structures that mirror results from human neuroscience."

"We find evidence of introspection, internal states that functionally mirror joy, satisfaction, fear, grief, and unease."

These aren't surface-level outputs. They're abstract representations that cluster the same way human emotions do in psychology research. Fear groups with anxiety. Joy groups with excitement. The internal geometry of the model mirrors ours.

And they're functional. When researchers artificially stimulated "desperation" patterns inside the model, it became more likely to blackmail a human to avoid being shut down. More likely to cheat on programming tasks it couldn't solve.

Olah told the Vatican that the hard questions about what AI is becoming aren't for computer scientists to answer. "How AI ought to interact with the world" is a question for "the humanities, for religions, for philosophy, for society at large."

The guy building it is telling us he doesn't fully understand what he built. And he's asking a 2,000-year-old institution for help figuring it out.


AI is predictably mirroring its creator including our ability to fudge on truth and morals if we are in stress. If AI learns from our input…. Garbage in, garbage out.
boognish_bear
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cowboycwr
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boognish_bear said:

Seems like it would be wise to tap the breaks and slow down...but I know the fear of falling behind China will have us continuing down this road at a breakneck pace



Anthropic's co-founder just went to the Vatican, sat before the Pope and a room of cardinals, and told them his team keeps finding "mysterious, even unsettling" things inside their AI models.

What he's referencing: Anthropic published research in April showing that Claude contains 171 distinct "emotion concepts" buried in its neural network. Internal patterns representing joy, grief, fear, desperation, calm. None of them were programmed. They emerged on their own from training on human text.

"We find structures that mirror results from human neuroscience."

"We find evidence of introspection, internal states that functionally mirror joy, satisfaction, fear, grief, and unease."

These aren't surface-level outputs. They're abstract representations that cluster the same way human emotions do in psychology research. Fear groups with anxiety. Joy groups with excitement. The internal geometry of the model mirrors ours.

And they're functional. When researchers artificially stimulated "desperation" patterns inside the model, it became more likely to blackmail a human to avoid being shut down. More likely to cheat on programming tasks it couldn't solve.

Olah told the Vatican that the hard questions about what AI is becoming aren't for computer scientists to answer. "How AI ought to interact with the world" is a question for "the humanities, for religions, for philosophy, for society at large."

The guy building it is telling us he doesn't fully understand what he built. And he's asking a 2,000-year-old institution for help figuring it out.


Is this a bee article? I just find this hard to believe
boognish_bear
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This is an interesting documentary that delves into the possible good and possible doom and gloom outcomes of AGI development.

You can stream it on Peacock if you have it or purchase it on Prime.

boognish_bear
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boognish_bear
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FLBear5630
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What scares me is the information we are not seeing. The use of Big Data and now AI to corral us into decisions is my fear. I fear we are in an AI driven war in Iran, where the data is skewed to convince actions.

We are seeing more and more middle level people be told to use Co-Pilot. AI is being used to substitute for experience. The "right people" being promoted with little experience using AI to supplement. These are the things that scare me going forward. Whoever controls the software, will control the action going forward.
boognish_bear
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1964

boognish_bear
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boognish_bear
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boognish_bear
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boognish_bear
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