As soon as I read this, Ed’s “if you ignore the costs, they’re profitable” line came to mind. The person who said this was serious, but this is actually a slightly more egregious way to put it than Ed’s sarcasm, imo.
I most likely suffer from confirmation bias, but I'm starting to see signs everywhere.
The point is, I feel a shift; I could be wrong as I want this whole circus to stop.
Do you relate to this?
I can't wait for this to be over, it has done so much damage to the world.
I'm not expert, but this has to be kinda good.
Manufacturing problems = delays in scaling = delayed purchases = infrastructure spending slows = the circle jerk slows = ...selloffs start?
Maybe I'm being too optimistic. Thoughts??
Was super surprised to hear 'The Big Dawg' not only drop Ed's name ("Zitron, Citron?"), but also;
I know Ed's not a big fan of Galloway (as many in the community aren't), but his voice does lend even more credibility to Zitron's thesis, and will likely cause some within his sphere of influence to start paying attention to what Ed's been shouting for the last couple of years...
Source: Prof G Markets
Did you guys see this?
Democratic Project 2029 calls for child social media ban, strict kids safety rules on tech
It's another Patriot Act. Another Citizens United. "Kids over Clicks".
I'm so serious - yall wanna make a vote/poll/something for issues that must be addressed? I'm sure there are think tanks for this sort of thing, but that article pissed me off
Liberalism driving us further and further into fascism, avoiding socialism at any cost to protect corporations
We know Trump's approach to bad news is to cover it up.
Remember when he claimed the key to reducing Covid infections was to stop testing for Covid?
If the AI bubble blows up while he is still President, the mental gymnastics he projects will be out of control, especially if it pulls the stock market down significantly.
Somehow Communists will be to blame.
Also, when they belch out propaganda like
>“The official position of the Secretary and the U.S. Treasury is that Artificial intelligence will be a key driver of America’s new Golden Age,” the spokesperson said.
Do they really expect to be taken seriously?
One dude just did, here is the code: https://github.com/ammaarreshi/Generals-Mac-iOS-iPad
And it is an embarrassment. The AI-bro wrote the following on Twitter
> I used Fable 5 to port Command & Conquer: Generals Zero Hour to the iPhone and iPad! This is the actual 2003 engine compiled for ARM64 natively, no emulator. Campaign, skirmish, Generals Challenge all work with touch controls built for an RTS.
What actually happened is:
Then the AI bro came in. The "AI" contribution was to cross-compile the MacOS application for iOS - which was trivial. Apple makes that easy on purpose. But since C&C is an RTS game it relied heavily on mouse input, but there was none on the iPhone. So the "AI" added mouse emulation the usual way - long tap for right click and so on.
This is incredibly dumb for an RTS game. A casual RTS gamer makes 100 actions per minute - all kinds of clicks and commands. A "long tap" is not something that could ever exist in the world of RTS. It is just too slow of an action!
The "AI" claimed whole lot of things it did that were not true. For example, writing about bug fixes it said
> Every one chased to root cause on a real device, fixed, and offered upstream.
That is wrong on all counts. It was a human who debugged the problems on an iPhone and there was nothing contributed upstream. There are no Pull Requests to either MacOS port nor the original open code.
There are 2000+ commits in the repository and most of them are by humans. The modern port heavily relies on pretty big opensource projects like ffmpeg (video library) and DXVK (DirectX translation layer for systems without DirectX).
The dude with AI did ~20 commits on top of that and claimed that it was something of value. The commits were mostly Markdown files anyway. The end result is not really good or usable, because the kind of controls they created are not suitable for an RTS game at all.
That is why they usually stay behind vague unverifiable claims of "great things AI does". Because every time they showcases anything - it is a huge facepalm moment like this one.
One of the main problems with AI - and specifically LLMs - is that to understand what’s going on, you need to have an understanding of a large number of fields: human cognition, stochastic modeling, machine learning, stock market bubble behavior, circular lending, hardware lifetimes, etc.
Almost every expert has deep knowledge in one of those fields - some even have two. But those of us wandering tinkerers, who have a small practical knowledge of a number of them, know enough to call bullshit when an expert rambles outside their domain (ultracrepidarianism) and says something demonstrably false, but not enough to be confident of the whole picture.
Hell, so much of the way industry leaders talk about AI wanders into territory that is either deliberately fabulist and self-serving, clearly and inescapably technically wrong, or disturbingly sociopathic that they’re useless. Especially since most of their “good outcomes” are actually dystopian. And that’s not just execs, but tech leaders and watch dogs.
There’s just so much I don’t know. I don’t know what ‘inference” really means, other than clustering similarities, I don’t know how any of the “breakthroughs” on cost are actually being tested by the Chinese. I don’t know what the socioeconomics of ‘winning’ on the AI front by our government subsidizing it and then ‘losing’ on energy infrastructure and storage means. I don’t know whether the patterns of thinking from ‘Thinking Fast and Slow’ applies to AI and if so, whether that requires an ontological backbone and integration into pattern analysis… and on and on.
But like Rilke said, I try to love the questions themselves, like locked rooms or books written in a foreign tongue.
So in that spirit - what are all the burning questions you wish you had answers to?
And just to make this perfectly clear in advance, this is not a f*cking AI post.
Somewhat old news, but new to me, probably to some to you guys as well. Another small thing to pile on the infinite list of AI suckiness.
https://futurism.com/future-society/anthropic-destroying-books
Edit: Something tells me that the now deleted, somewhat less friendly reply to the post is the same person/shill/bot as Ok-Eye4820:
I am one of the few peoples in software engineering who already were aware of the tech industry enshittification before AI trend even began. I worked my first job at a startup and the signs it beings a crazy market was visible from the start, people care for code velocity more than quality. I left my job and did not apply to any other workplace because I was burned out. Then the whole AI news froze the hiring everywhere. This pushed me towards working on my own low budget software consultancy rather than relying on market to be sane again. But me and my co-founders did not find it worth while after 6 months and had to pivot because of widespread AI psychosis hurting our margins and there is no money for innovation unless it can be turned into a SaaS product.
We pivoted into financial investment algorithms and research as means of making money for short term and have grown into a team of 5 people now. Each of us from a different background in science ( I do most of the code and they being from academic side of finance, mathematics and physics ) do theory and analysis of financial instruments.
We are subscribed to Ed since last year I think and regularly follow what he has to say. But our AI usage is not zero and here where our problem began. We are paying for our AI usage through OpenRouter which charges on a per million token basis, this is simply because we want zero data retention ( which is opt in smh ). Hence all frontier models are simply not feasible for us to pay for every month. Mostly sticking to open-weight models like deepseek v4 flash/pro and kimi k2.6 which are well under $3-4 / M.
We were using AI to fix obvious code paths, debugging functions in our main strategy and creating analysis on market data that we were gathering. Writing long python notebooks by hand is very time consuming and AIs were giving us quite a productivity boost. Their reasoning seemed quite fine for the tasks we have.
This is where I think it clouded my judgment. Because we were up against a deadline we never set up any pipeline or rule-book for checking bias. So whenever we hit a strange result, we came up with all sorts of explanations except the obvious one - that something was wrong in the code or in our assumptions about market data.
Six months into development, while I was manually refactoring parts of it, I fixed a tiny bit of code. It was in a simple data loader utility that pulled bars data from our database into the model. Before it included one extra minute of data (a <= where it should have been <), it introduces a look-ahead bias and we weren't aware of it for the past 5 months and considered it as a positive result and ran with it. This was catastrophic because all of our assumptions and work were invalidated in an instant. This loader was generated by an AI, which we copied into our program on day one. Although the code was reviewed when it was added, it's the conjunction of this code with rest of our system was not explored by anyone.
Although this may look like that the same mistake can be made by a human. It wouldn't have happened if it was being worked on without AI help. Our main codebase is really small. AI's have contextualized this part numerous times, every time I have asked it to generate a new analysis notebook or something, it goes and reads the same data loader code. It has reasoned about our code base directly when I asked it to find any obvious bugs. It loves dissecting the complicated paths but never picked up this simple error. Any human would have caught this way way sooner if they had some time debugging and reading the code thoroughly, and took time to debug and check the output.
Now that we are snapped out of this AI psychosis it is really clear it's not just about this one error. AI changes the way you think. The worse part is that the output it gives now works 90/100 times. But just because it "works" does not mean it's the right thing to use. It's worse than gambling, it's like winning every time you are betting but there is a guy puncturing holes in your back and draining your blood out to offer it to the devil.
I think the core value proposition of "AI" is not necessarily its correctness or "thought" but rather its ability to ingest vast amounts of data without human intermediaries and produce speciously authoritative outputs based on the inputs. "AI" is obviously already very good at this so even if the more sci-fi claims don't pan out it will still remain an integral and harmful part of our society.
Why are these attributes useful apart from their claims to correctly analyze reality? Here's a non-exhaustive list
Disciplining, demoralizing, and disaggregating workers by isolating them in front of a chatbot, overwhelming them with LLM-generated outputs and bypassing recalcitrant middle managers and senior technicians to get information and make decisions. All this serves to reinforce power in the hands of the C-suite and investors.
surveillance and flagging - stuff like Flock cameras are obvious use-cases, but there's lots of old-school tech like credit checks, resume screening, background checks, air-strike targeting etc. that can get a face-lift with LLMs. False positives and biases are either acceptable costs or even broadly beneficial to the elites for reinforcing existing hierarchies
propaganda - Generated video, text and images is valuable for both governments and right-wing corporate propaganda. The chatbots themselves can also be directly influenced, see for example how Grok was conceived as an alternative to "woke AI".
The assumption is that if "AI" hurts business efficiency that it will automatically be dropped but I think history and even the present-day shows that maintaining control and hierarchies overrides efficiency. For example the present hysteria-driven immigration crackdown is not "efficient" for business yet it has proven durable and even gets support from some of the richest businessmen in the world. Another example in the past might be how slavery and Jim Crow racism stifled the modernization of the American South's economy while being overwhelmingly supported by the white South's business interests. So I think businesses and government will accept a great deal of inefficiency in order to reap the benefit of these tools.
Short video, but showed a chart of the recent deals Anthropic signed for computer, including the last one with SpaceX. Briefly mentioned the new one with TeraWulf, light on details however. They made a comment that existing crypto mining campuses somehow gives Terawulf a leg up, though it is never actually explained how.
Most on this sub know the demand story and how its dominated by two unprofitable companies.
I don't understand the logic behind Anthropic doing this? Are they too playing the buy a bunch of things and see which ones deliver first and cancel the rest game? I don't know what the details of these deals are though.
What are Britain’s AI growth zones and are the plans feasible or ‘complete bunk’?
Guardian analysis shows that proposals for AI data centers in the UK are massively over inflating job creation and renewable energy provision. In a related article, they uncovered that the Lanarkshire site is supposed to be powered by 1GW of renewable energy, for which they'd need 40-100sqkm of land. They've only submitted planning applications for 2sqkm. Private correspondence shows they plan to connect the data center to the national grid...
"Outrage started bubbling up last year when residents of an affluent subdivision named Annelise Park in Fayetteville, Georgia, noticed their water pressure was unusually low.
When the county utility investigated, officials discovered two industrial-scale water hookups feeding a data center campus located 20 miles south of downtown Atlanta. One water connection had been installed without the utility’s knowledge, and the other was not linked to the company’s account and therefore wasn’t being billed.
All told, the developer, Quality Technology Services, owed nearly $150,000 for using more than 29 million gallons of unaccounted-for water. That is equivalent to 44 Olympic-size swimming pools and far exceeds the peak limit agreed to during the data center planning process...
While the utility charged the data center a higher construction rate for the unapproved water consumption, Tigert confirmed the utility did not penalize or fine the data center."
I live in the South and the drought we're all going through is awful. That a data center would intentionally attempt to steal water from the people of its state--and get away with it without so much as a fine for illegally siphoning water from residents--is fucking infuriating.
We need a moratorium on data centers, immediately, everywhere. Call your congresspeople as often as you can, or this is what we all can expect.
The setback stems from difficulties manufacturing a key circuit board at the heart of the system, SemiAnalysis said in a post on Monday.
“Kyber NVL144 rack architecture has been delayed to 2028 as the PCB midplane remains challenging from a manufacturability standpoint,” the firm said, referring to a specialized, multi-layer printed circuit board that connects electronic modules within a system.
The reported delay adds to mounting strains across Nvidia’s product lines, underscoring concerns that Nvidia’s breakneck annual release cadence is colliding with manufacturing limits.
A backup plan — bolting two of Nvidia’s current-generation racks together for similar power — has also been scrapped after cloud customers rejected the design as awkward and costly to operate. “It has since been cancelled due to heavy pushback from CSPs [cloud service providers] and hyperscalers over its odd design and heavy operational burden,” SemiAnalysis said.
That leaves Nvidia with “no proven solution to expand the scale-up world size for Rubin Ultra,” SemiAnalysis said, predicting that could give rivals Advanced Micro Devices and Google, whose in-house chips are already winning business from top AI labs, a rare technical opening at the high end of the market.
Poor Jensen, can't these AI bros catch a break?
I wanted to share a story that I think underlines why the state of AI / The tech industry feels so shitty right now, and am curious to hear if anyone else has experienced this recently. I’ve also been enjoying Cory Doctorow’s new book “A Reverse Centaurs Guide to Life after AI” and I think there are some interesting parallels here.
Here’s the context: I’m a PM (Product Manager) at a large financial firm, so think legacy tech stack and tons of complex systems. I would say I’m quasi-technical, enough to understand technical details, but I’m never in the code-base nor do I have a desire to be. My team was building some features for a huge release that involved 10+ other teams, and that had to go out that day. However, a pretty large bug was discovered maybe 3 hours before Go-Live that sent everyone into a fire-drill.
People were spamming this Teams chat left and right hypothesizing root cause issues, devs were going back and forth finger pointing that it was other teams that caused the issue, people kept adding new people to the chat, it was a mess. This group chat is about 50+ people at this point, and I’m periodically checking to see if my team ends up being mentioned. Then out of nowhere as I’m reading it, I see this massive wall of text get sent. I read a few sentences and immediately turned to my coworker and said to him “this is AI right?”. It was basically a Co-Pilot diagnosis of the root cause, but it was so obvious. It had all the tell tale signs of antithesis statements, emojis, and emdashes. And I was pretty shocked because I knew the person who had sent it was a relatively senior (1 level higher than me) non-technical person. Think program/project management type. And even I could immediately tell that the Co-Pilot diagnosis was inaccurate and the solution it was recommending didn’t make any sense.
I don’t even think there was a “hey this is what AI told me”, it was literally just a copy/paste wall of text of the Co-Pilot response! And the funniest thing about it was that no one acknowledged it all. I mean no one! I was showing my friend the chat thread later, and it’s hilarious. One minute there’s a bunch of devs going back and forth discussing root cause and sending Splunk screenshots. Then there’s this MASSIVE wall of AI slop diagnosis from this non-technical person, and then a few minutes later the devs pick up right where they left off without even acknowledging it. It’s honestly kind of dystopian when I look back at the thread. In a funny way it reminded me of an ad when you’re scrolling down a news article or a feed. Your brain just automatically tunes it out because you know it’s slop and completely irrelevant.
I wanted to share this story because #1 it’s funny, but #2 I also had a great conversation with my friend about how non-technical people are being forced into using AI. There’s this desire for senior people in non-technical roles to visibly demonstrate they are using AI, but they want to do it in this weird “spray and pray” kind of way.
Here’s what I mean by this: My friend and I were cracking up because we thought it was hilarious for a senior person’s thought process to be this (obviously exaggerated):
My friend and I laughed about this for a bit, but he also brought up an interesting comparison where similar things happen on JIRA tickets and bugs. A non-technical person will take the ticket, feed it into Claude, and then copy/paste the response as a comment in JIRA. It’s weird because it feels like they are trying to pass it off as their own investigation, and anyone who isn’t familiar with how LLMs talk might actually believe it. It looks like the response of someone’s well thought out investigation, but as you read it you don’t actually garner any real info. And if someone asks for further clarification, the response often ends up being “That’s a good question, I’m not sure, this is just what Claude / Co-Pilot told me”.
It’s a weird contradiction with accountability in the sense they want to take credit if it leads to a solution, but they also want to avoid accountability if any follow up q’s are asked or if it leads someone else astray. If it turns out to be wrong, they can always just blame the LLM. It has this really weird undertone of “Hey not sure if this is right, but I plugged it into Claude and this is what it told me… Again not sure if it’s right, but hopefully it helps!” All the while they can proudly inform their leadership they are using LLMs to solve real world production defects. And I have to imagine leadership eats this up!
The final thing I wanted to highlight and tie in a bit to Cory Doctorow’s new book is I worry this leads to further enshittification of both products as well as the working environment. In Doctorow’s new book, he discusses the concept of a “reverse centaur”. Think of a person using LLMs to aid them in meaningful ways as a “centaur” with the human on top and horse on the bottom. They are in full control and have actual expertise, thus they now can run like a horse while retaining the human head. Contrast that with a “reverse centaur”, someone who blindly plugs stuff into Co-Pilot and copy/pastes the response. They have the horse head on top, and the human legs on the bottom. And they just end up looking like an ass 😀!
I love this analogy. I worry all the doom-trolling and scare tactics to force people into using AI has made the vast majority of non-technical people reverse centaurs. I worry that more and more of these reverse centaurs will spawn and as I mentioned with the analogy to ads with AI slop, when you are actually trying to solve an issue, you’re going to have to wade through a sea of AI slop thrown at you from reverse centaurs. It’s crazy to think it’s possible batting away AI slop from non-technical people is going to become part of the debugging experience.
These worsening of conditions leads to the next knock-on effect, which is further enshittification of our products. The software we use everyday will continue to be riddled with bugs and the rate at which they will be solved will only decrease. Ironically, the response from leadership may be to invest even more into AI after these degradations occur, resulting in a horrible enshittification loop.
I’ll be honest, I don’t really have a concluding message or anything to say about how to solve this problem. I just wanted to post this here, see if anyone else has had similar experiences, and maybe feel less alone about things. This sub has been nice for that, as well as Ed’s podcast. I highly recommend reading Cory’s new book as well! If you made it this far, I sincerely want to thank you for your time and I hope to hear from you in the comments.
-Classic_Tap
P.S. - If you’re curious about if we got the release out the door, we did. They just ended up just rolling every single app/system one by one until we found the one that introduced the bug 😞 . The funniest (sad) part was the team who initially reported the bug was whose app rollback fixed the issue.
I'm personally routing for Brookfield to wise up because they're all in on an LLM DC within a few miles of me. That last sentence gives me hope too.
Does this qualify as one of the horsemen??
"The largest data center project ever proposed in the U.S. is officially dead.
Blackstone-owned QTS Realty Trust withdrew its appeal to the Virginia Supreme Court on July 2, closing out a three-year legal fight over the Prince William Digital Gateway, a planned 2,100-acre campus in Prince William County, Virginia that would have packed 37 buildings and 22 million square feet of data centers next to Manassas National Battlefield Park. At full build-out, the project carried an estimated $100 billion price tag and would have been the largest data center complex in the world.
QTS was the last developer standing. Co-developer Compass Datacenters, backed by Brookfield, dropped its own appeal in April, and the Prince William Board of County Supervisors withdrew from the litigation the same month after spending nearly $2 million in taxpayer funds defending the original rezoning. That approval, granted in 2023, was voided by the Virginia Court of Appeals in March, which found the county's public notice for the rezoning hearing fell short of the state's six-day spacing requirement between newspaper notices.
In its withdrawal filing, QTS said the project had "advanced through years of planning, analysis, and public review" and would have delivered tens of billions of dollars in capital investment and thousands of jobs to the county. The company added that Virginia remains central to its business, pointing to $5 billion in ongoing investment in the Richmond region on top of its existing Northern Virginia footprint.
The retreat comes days after Blackstone agreed to hand Digital Realty full ownership of three built-and-leased Northern Virginia data centers valued at $7.8 billion, in a $3.5 billion cash-and-stock deal. That transaction extends an existing joint venture rather than an exit, but the timing puts fresh attention on how Blackstone is managing its data center bets in the state that hosts more capacity than anywhere else in the world.
Northern Virginia remains the industry's biggest hub, and the region's buildout keeps running into local resistance over land, water and grid strain. Several states have floated moratoriums or tighter permitting rules as utilities warn that data centers are driving an outsized share of new electricity demand, and grid operators in some regions have started asking developers to bring their own power generation rather than compete for scarce capacity. A Gallup survey released in May found 71% of Americans oppose data center construction in their area, with 48% strongly opposed, running higher than opposition to a local nuclear plant.
For Blackstone, the Digital Gateway collapse doesn't change the broader trajectory. The firm still manages a data center portfolio worth more than $150 billion globally, and in May it raised $1.75 billion taking its acquisition vehicle, Blackstone Digital Infrastructure Trust, public on the NYSE, to keep buying already-built, leased facilities tied to AI demand. What the Prince William outcome shows is that even the biggest players in the space can lose a fight over land use once local opposition organizes and the legal process runs its course."
1000 evaluators given identical resumes & told candidate used AI. Only difference on resumes was candidate’s name: Emily vs James. Study found women using AI are evaluated as less competent than men who use AI...To evaluators, women’s AI use signaled inability, while men’s AI use signaled initiative
>“Our position is that informed consent requires consumers to understand the benefits and limitations of the technology to which they are consenting.” (The Australian federal health department)
And I'm guessing that'd go a little something like:
"Before we continue, do you consent to my use of AI scribe software? It will listen to and transcribe our consultation for our records. It will make mistakes regularly, and those mistakes may be what I base your treatment upon. So, do you consent to my use of AI scribe software?"
🙃
My strategy now is as follows:
Edit to add that item 1. might be a bit harsh. But it may be good to ask about their proof-reading/review process.
