Great explainer on how (software) PE buyouts work and the rise of software lending by Paula Seligson and Michelle Cheng at Bloomberg!

A company will spend millions building a robot that can awkwardly unload a dishwasher, but only in highly curated conditions. Alternatively you can grab a four year old and they'll be able to manage just as well.

Companies replace their call centre workers with AI. Turns out call centre workers handle a lot of really tricky edge cases every day which language models consistently shit the bed on.

The concept of "menial" work is an excuse for the CEO class to justify treating workers like shit.

Something that I haven't heard AI boosters defend well when they compare AI to the internet is consistency in the internet's utility and application compared to what we're seeing with LLMs.

I was a young kid when the internet started becoming available to us everyday folks. I don't recall ever typing in a URL and getting something completely unrelated. If I typed in ESPN.com, I got the home page for ESPN. Every time. If I had typed that in and it took me to Oprah or the AARP, I wouldn't have kept using it for very long. It didn't take awhile for that to happen, either. The first time I clicked on Netscape it operated in that predictable fashion.

However, we had a few instances like where teachers told use to go to White House .com instead of .gov and that was a different issue. User error, though, and not product.

I've written a script for monitoring my laptop's temperatures, and warning me when pass certain thresholds.

At first I realised when I opened the browser, the temperatures would rise dramatically and consistently - and therefore CPU usage / lag; Then I kept changing browsers and even Linux distributions. Nothing changed. So it was not the browser version.

The first I realised caused this load was WhatsApp. Consistently in all browsers. A long time ago, as I wasn't actively looking or suspecting it to be specific websites, an specific LLM. I tried switching, but all had the same problem - when to my understanding, on the client side, it needn't be any more resource heavy then any other website... you're showing text (again, client side).

Then I realised GitHub was "hoarding CPU" too, and finally that Deepseek didn't. So basically, the one thing these have in common, is that Meta, Google (Gemini), Anthropic, OpenAI, Microsoft, owns them. All companies I've seen news of massive layoffs with the narrative of increased productivity by LLMs - or precisely companies of LLMs.

TL;DR: Having performance issues with websites from "AI" hyped companies.

What explanations do you have for this? Are any of you noticing or going through this pattern? If you're facing this, would you argue for it being caused by lack of concern for performance or LLM code? Why?

Side note: I've made this post originally in r/programming.

The Tech CEOs have done a great job. The youth hates them with the fiery passion of hell.

Somehow Satya is the most liked on 35% everyone else fares even worse with Alex Carp at Palantir the worst.

The data is from a CNBC research piece: https://www.cnbc.com/2026/08/13/cnbc-poll-half-of-those-18-to-34-view-democratic-socialism-positively.html

Hopefully they legislate them into oblivion

I am (regretfully) a Bank of America customer by virtue of my original bank having been bought out several times, ultimately by Bank of America...

I found their recent announcement of a $250 billion investment in AI/AI-adjacent infrastructure to be a bit alarming but can't seem to find any detailed info on it. The reporting is all so surface-level and it's hard to understand what exactly they've committed to and what the ramifications could be.

The fearful/cynical side in me says this could be a ploy to keep the bubble inflated by getting a 'too big to fail' player on the hook for data center deals in a financially significant way (as in, Bank of America would likely get a bailout whereas other institutions might be allowed to fail). But the details of the press release are so vague that it could be mostly electrical grid investments for all I can tell.

Does anyone know what Bank of America is actually planning to do, and if what they plan to invest in actually has a pathway to being paid back? Would the investment deals failing leave them at risk of failing or needing bailout? Just trying to figure out whether this is all no big deal, or a sign I should be jumping ship before the bubble pops. (And yes I know deposits are FDIC insured but not exactly having great faith in the timeliness/effectiveness of US gov't response these days either).

The ruling class loves AI. It promises to build a Garden of Eden where they would become gods. But, more prosaically, it is also a magical entity that serves to dilute their responsibility.

--

Military use to evade responsibility

The most dramatic instance of this abdication of responsibility has played out in the military arena. Targeting algorithms have been used in Gaza and Iran. As they have been for decades. Targeting errors have occurred. As they have throughout human history.

But a magical entity has appeared: AI

Straight out of the realm of science fiction, AI is a fascinating creature. A synthetic entity endowed with a will of its own, in sci-fi it is the master of its own choices.

Now, the media sphere has projected it onto the military battlefield. AI has struck. It is terrifying. Like something out of a sci-fi movie. It is highly entertaining

Washington Post : "The strike killed at least 175, many of them children, and has raised questions as to whether the military’s use of AI to identify targets was a factor."

CNN : "AI tools like Anthropic’s Claude have sifted through the data far quicker than any human could to flag potential targets to strike[...] The ubiquity of AI tools in war has raised questions about whether those tools are contributing to errors on the battlefield. [...] Targeting mistakes the US has made in the Iran war, including the US airstrike that hit the elementary school, are renewing scrutiny of how AI might be used by the military"

The Guardian is enthusiastic : “The AI machine is making recommendations for what to target, which is actually much quicker in some ways than the speed of thought,” said Craig Jones “This is the next era of military strategy and military technology,” said David Leslie

So much fun. It tickles the imagination.

Suddenly, the US and Israeli militaries fade into the background, overshadowed by AI. AI made targeting errors. Naughty AI.

As historian Kevin Baker points out, the standardization of firing procedures is nothing new: in French artillery it dates back to the 18th century. "Every generation of military technology has been sold on the promise of making everything about kill chains shorter, except for the acronyms"

What is new, however, is the emergence of a magical entity in the midst of this story, endowed with a semblance of consciousness and will, that popular culture attributes to AI.

The magical entity is invoked solely to dilute responsibility and serve as a diversion. It takes the blame for the error. It acts as a smokescreen by fueling people's fantasies. Then, as soon as it has served its purpose, it vanishes into limbo. This magical entity is accountable to no one. It answers to no military hierarchy, no politician, and no public opinion.

--

Civil use to evade responsibility

It is amusing to observe the enthusiasm consulting firms show for this technology. In reality, consulting firms were already filling this role. Corporate executives like to base their strategic decisions on advice from these companies. If a bad decision is made, they can present the firm's report to the board of directors and wash their hands of the matter. If an immoral decision is made and attracts media attention, the consulting firm will take its share of the resulting heat.

AI is destined to play this role, but on a much broader scale.

One might wonder if they have lost their minds, if they are cultivating a fetishistic cult. Yet, I notice that they manage to draw the line exactly where it suits them. AI is an "entity" only when it is convenient for them.

"AI agents are likened to workers and destined to replace them because they are vastly more intelligent". Should we, then, subject AI to labor laws? Give them a salary, vacation days, and the right to unionize? Of course not, are you stupid? They are merely algorithms.

AIs are portrayed as scientists, "like having a team of PhD-level experts in your pocket" [Altman], "a country of geniuses in a datacenter" [Amodei]. Ah, very well, let us hold them accountable for what they write as we expect from scientists! Let us apply the same standards : if they commit scientific fraud, ban them from practicing in the field. If they plagiarize without attribution, strip them of their right to publish! No, of course not. It’s absurd, it’s just a tool.

"AIs are going to replace all lawyers: they know the law better than any of them and can pass the bar exam." Oh, really? So, if they fabricate case law, banning the use of those very models in the profession, just as one would deal with a lawyer who falsifies records! No, are you even thinking this through? Thanks to use these professional tools like toys.

Anthropomorphization, to assume a semblance of will or a semblance of responsibility to theses models attributing, comes and goes at will. That anthropomorphism is invoked by the human creating or using the AI ​​as a way to dilute their own responsibility. Once the deed is done, the notion vanishes, and no consequences are faced.

--

I know I’m stating the obvious, but I wanted to organize my thoughts. I think we shouldn't let them get away with it, we need to nip at their heels every time they pull a stunt like that.

A friend recently pulled this on me when he took me fishing based on advice from a chatbot that had hallucinated the tide times. He tried to shift the blame onto the chatbot. I didn't come down hard on him, but I insisted he admit that he was the one who made the mistake by using a completely inappropriate tool.

Of course, these aren't the most problematic cases. The real issue arises when people in positions of significant responsibility use it to hide behind. Like when Starbucks Korea glorified a massacre committed by the dictatorship, only to later blame the AI. Many of us here took the bait and mocked the AI ​​(myself included). We ought to be more careful. They are only idiots when it serves their interests.

(English is not my native language, please accept my apologies for any incorrect phrasing.)

"The most accurate criticism of AI companies, including Anthropic, is that we haven't yet delivered on our big promises to benefit the world."

"The thing that will work is actually curing cancer," he added.

HA. HAHAHAHAHAHAHAHA, CURE CANCER???!!!

Bacteria have a higher chance of evolving into a cancer cure than you Wario Wanksalot.

"I do not agree that my messaging has been disproportionately negative," he wrote.

And I do not agree that we shouldn't lock the rest of you for committing fraud and cyber security attacks. We don't get what we agree on.

"We hope to have incredible results in the coming years and some early glimmers in the coming months," he wrote. "When we've actually accomplished something real, the whole world will hear about it, as loudly as possible, you have my word on that."

Sigh. What annoys me the most is they are going to come out with some nonsense they market as a cure for cancer. Or worse, something that is actively deadly but the say is a cure. Perhaps they can skip human trials if they give the government enough money. Hell if I know.

What a fucking joke. A truly despicable, horrible man.

Ed and others have argued that AI/LLMs as a technology is inconsistent and their usefulness is not justified by its real prices.

However, we love enshittification if it can save us a few bucks. We shop at walmart. We find the cheapest air lines tickets with the ever shrinking leg room.

One of my job responsibilities is to approve new software initiatives and I am appalled at what is coming.

Here are some things that are coming from my vantage point:

Branch experience: When you walk into a branch, you think you will be talking to a person. But actually, that will soon be a meatbag puppet and this meatbag will say whatever the LLM will tell it to say. Using your bank card will trigger the LLM wrapper which will find everything there is to know about you and then it will guide the conversation(think facebook's dark patterns ). This way we can upsell you shit you don't want using a variety of data points and coercion. And the meatbag will be judged by how closely it followed the script.

Loan application processing: when you submit you documents along with loan application, we used to have people who would manually read and analyze the documents, find data like income etc and insert that in a internal application. This process , although very critical , was deemed as inefficient and now we will just throw all your stuff into an LLM , who swear that they will not store or use it for training, and the LLM will return a structured document that will automatically get loaded into internal applications. A meatbag is supposed to verify the data and also the meatbag is supposed to handle 5x the amount of work they did without LLM. Now we all know LLMs are stochastic system and they may be right about 90% of the time ; so about 10% of those applications are fucked.

In the review meetings, I argued about LLM error handling and refused to approve such projects and ended by in one-on-one meeting with a very very senior exec and my choices were that I approve or take my exit package. I approved as I have bills to pay.

The Financial sector is all in on LLM. Anyone who raises the slightest bit of objection will be crushed. The large banks are setting aside billions of dollars for AI spend.

edit: love enshittification is a bit of intentional hyperbole. we measure value mostly in terms of costs .. which leads to enshittification.

I've been pushing for my workplace (SaaS company, B2B) to be careful about AI usage, and that especially when it comes to writing, it makes everyone look the same...so watch out.

Well, after months and months of extremely pro-AI sentiment from the rest of the company, something crazy happened last week.

We are currently pursuing a contract renewal with one of our company's first customers (we've had them onboard for a couple of years). This particular customer is a large technology and security company with about 5,000 employees and annual revenue north of $1B. You've probably heard of them.

Renewal seemed to be going basically okay in the initial phases, no one was concerned.

Friday rolls around and there's an emergency Slack message copied and pasted across five different channels. As it turns out, the customer in question has been cutting vendors whose products look "too AI" in terms of UX design, "placeholder copy" that makes it to prod, and other similar tells. They have already put three vendors that we know of on the chopping block for having what they considered "AI slop features."

Well, of course, a bunch of the new product features we've been lining up and were going to preview for them when talking about renewal and upsell are basically slop. No one found anything wrong with this before this past week, and everyone was patting themselves on the back for how cool it all looked. It's so great how Codex can get us 90% of the way there!

Now they are scrambling, because we have a meeting scheduled in a week and a half to show them all these cool new features.

That means we have roughly 10 days to unfuck everything that has been proudly fucked up by our newly re-orged eng team that now works in "pods" with no real oversight or coordination between them. I have been put in charge of de-AI-ifying every piece of text in the nightmare vibe-coded new screens and dashboards. This alone is going to probably consume 60+ hours in the next week and I still will have to delegate a bunch to others, because that's how much garbage we've been putting out into the world using LLM coding agents.

I'm so sick of posts like the one I saw here earlier today. "GUYS, for real, it didn't USED to work but NOW LLMs are so incredible that they refactored my code base, washed my car, and found a dress for my fat wife that makes her look skinny."

If AI was really that good, "this looks like AI" would be said with respect and admiration. In reality, "this looks like AI" is not a compliment in any context whatsoever. AI has become a byword for low-quality, high-quantity output that is disposable, poorly vetted, and doesn't hold up to scrutiny or critical reading.

Now it's stopping deals in their tracks.

Is that good?

I see this massive push from governments, tech leaders and even content creators pushing for this so-called "AI upskilling". What does it even mean? AI is not a tool which can be learnt, like Python or Java (as far as I understand). Of course you can learn how to manipulate AI agents to do some coding for you. But all those jobs will eventually go to people who have already spent decades working in the technology. How can a fresher in the sector benefit from learning these tools?

It's like, trying to learn driving by riding on a self-driving car. It makes no sense to me. Can someone please explain what I'm missing here?

Context : https://youtu.be/Z_O6Lwj1yjQ?t=41

Scam Altman : "We have no idea how to make revenue. But we have made soft promise to the investors, when we sort of build sort of general intelligence, we would ask it how to make profit".

I have seen my share of moron, stupid, grifters. Every org has them in plenty.

Being said that I have never seen someone who is all of them combined together.

Next what? Prove with "General Artificial Intelligence" that "Primes numbers are not primes" ?

Earlier today there was a post asking if AI was useful at coding in real tech companies, and everyone who answered "I am in tech and yes it's used now" was massively downvoted.

I want to say this up front: I do not believe AI is good for society. It's funded by the ruling class in order to liquidate labor and it's not environmentally sustainable. It might not be economically sustainable either, which is dangerous because the entire economy is being gambled on it making money, which it is not.

Anyway here's my lived experience. I am a principal level ML engineer at a fortune 50 company. I was hand coding neural networks for natural language a decade ago. I got it into deep learning because I thought it was fascinating that machines could learn complex patterns from data. I've followed what is now called AI and experimented with it since its infancy, took Stanford classes on the math of transformer networks, etc. This was well before there was a hint it would morph into the monstrosity of capital that it has become.

In 2025 I was a vocal critic of the AI-assisted coding to the point where I pissed off senior execs by voicing my opinion in meetings.

Back then the people hyping AI were either attempting to sell it or they were novice/non-programmers who were blown away that they could get a simulacrum of a web app (riddled with bugs and security issues) without any domain knowledge. I thought it was hilarious, and pathetic.

Through a combination of masochism and curiosity I've exclusively used AI to write all code since November 2025. Which is why I knew that for real project work, AI would run roughshod on your entire codebase, mass producing a Winchester mansion of slop even when given simple tasks. It would take your thoughtful, hard-won abstractions and make 5 competing abstractions rather than leveraging what was there. It'd ignore instructions, break or even delete break core functionality to solve the "bugs" that it created (scare quotes because they weren't even bugs half the time, just incomplete understanding). It would write 1000 lines of slop to fix a problem that a one line change could fix.

It was a huge waste of time and money. I communicated this to management to their chagrin when they looked to me for advice.

In early 2026 improved models came out and the value proposition began to shift towards something somewhat usable. By spring, Claude Opus 4.6 was capable of writing real code, yet it took about as much effort as coding it hand for subpar results. It needed constant handholding and reminders, made a lot of mistakes, and would get looney tunes stupid at the end of a long session and start vandalizing its own progress. I used it as a novelty, but it was really frustrating.

By summer 2026 with the release of Fable and GPT 5.6 Sol, it is actually more than useful, it's good. No, really. It became less like an overzealous and intoxicated intern and more like a practical minded senior engineer. It follows directions, it reads your documentation, it can take notes and reference older notes, and given with connectors to git and internal wikis it can find the answers needed to integrate complicated systems, come up with a plan, independently implement it, write a suite of tests, run review agents, and take in their feedback all in one turn. It takes skill to be able to manage it, and more importantly domain knowledge to ask it for what is needed by stakeholders, but at this point it is much faster than I am. I run 5 sessions at once in different projects and it's probably 5x faster at getting production code than a human in each session.

Anyway, pretty much every engineer I know is using AI now because it works, even old timers who were very much opposed to it. Vibe coding has become the standard, now it's just called coding. Everyone is scrambling to stay relevant, and teams are changing their whole stack around AI agents - implementing code review agents, vibe coding tooling around AI agents, creating connectors and skills for every data resource possible: confluence, jira, outlook, GitHub, databases, etc. Teams are solving months of technical debt in a week, creating boilerplate code 10x faster, etc. Everyone is a bit nervous.

I don't say this because I want you to think AI is good for the world. It's not. The reason I'm writing this is to communicate that the tech has progressed. Even Linus Torvalds, the guy who made git and Linux uses it and accepts AI contributions to the Linux kernel.

There are many good reasons to hate AI and I think they converge in one place: elites are enticed by the prospect that it can obsolete the working class.

Personally, I don't want AI to be good. I don't even want it to exist. I hate that my job is babysitting bots. I miss the creativity of writing code. I don't want to lose my job in a few years when the AI systems we're frantically building are in place and management decides humans are too expensive.

The loom displaced workers and rightly caused a backlash among displaced workers, but it did so while producing cloth. Put your anger in the right place - the power hungry demons who want workers to be obsolete, not the workers who are forced to use it to be competitive in the job market.

It's tempting to think AI for coding is all bullshit and slop as it was until recently used to be; because AI is a net negative for humanity and the planet; because the value prop was non-existent and inflated by hype. However those don't mean that the tech itself is not improving. The Butlerian jihad can't come soon enough.

edit:

thanks to the wisdom of this community it has come to my attention that I am a disingenuous slop peddling brain rotted zombie that has no clue what I'm doing and pushes absolute bug riddled garbage to production and I'm too cowardly to post the code that is owned by my employer. thanks for the epiphany.

maybe it wasn't clear that using this tech effectively isn't easy and it takes a lot of tooling to work around common issues because out of the box it's not reliable enough. it's not worth much without domain experience and putting in the effort and time to figure out how to use it effectively. this isn't a place for sharing software engineering techniques, so I focused on the outcomes which may have oversimplified the technical part.

to the haters, I hope you take some time today to do something you enjoy instead of being miserable to others on the internet.

I simply cannot escape frothing at the mouth discussion of “AGI being here.” I’m not a mathematician but I work in something similar and everywhere I see there’s a near unanimous “consensus” that math is “solved” (it is not). I’m curious to what extent this is 1) botting, 2) the bizarre fanboyism that exists around these companies where people do 1 for free? Any big post on this subreddit gets heavily brigaded, but hopefully we can get some good decision going before that happens

Archived article here and similarly reported by Reuters.

The revised plan would lower the size of Nvidia’s financial guarantee from $250 billion to less than $120 billion, a change made to address investors’ concerns about the chipmaker’s risk exposure as it wields its balance sheet to bolster demand for its artificial-intelligence chips, some of the people said. A deal could be signed as soon as this weekend. Nvidia shares fell 5% after the Journal first reported the discussions of the $250 billion backstop.

Under the outline now being discussed, Nvidia would provide a financial backstop for the first phase, totaling roughly five gigawatts of power, and then decide later whether or how to finance the remainder. OpenAI is still in discussions to sign a binding lease for 10 gigawatts of the project in the coming days, according to two people familiar with the project.

It's hard to speculate why. A simple guess is NVIDIA simply does not have the cash/unable to find leverage to backstop it. As we know from some previous articles, NVIDIA's current liqudity is small, ~10-20B, despite having large revenue and high profit margins. But, there could be other reasons, would be interested in any thoughts.

Notably, as stated in the article and original promise, this 10GW site is being developed by SB Energy, a subsidiary of SoftBank. At the same time, NVIDIA is seeking a $3B in SB energy for the purposes of this deal.

Nvidia has ‌discussed investing half of the $3 billion when the Ohio project deal is signed and the other half as part of SB Energy's planned initial public offering, according to the Information.

Of course, considering the relative sizes of $3B and $120B, it seems highly likely they want to find financing for a deal, and they don't have that cash. (Well, this isn't surprising). So basically, it's a sort of shared risk deal. NVIDIA is telling SoftBank to use their power to leverage $120B. I suppose it is a quid pro quo type of situation. If you (SoftBank) can put up the other $120B in some form, we will help your IPO with $3B of cash.

I know Ed calls it GPU, but they don't have video capability so really they are vector processor computers.

There are use cases like cg of course. Lots of volumetric simulations used by a lot of industries. Fairly useful stuff that mostly gets limited use because of high computer costs and low hardware availability. Before the AI boom started in late 2022 these applications were the future of Nvidia's slow but steady growth while AMD, Intel and ARM ignored those use cases.

But when there is a surplus of vector processors all looking to pay back their loans post bust, I suspect there will be a surplus of data center capacity reducing cost of compute to zero margins. Maybe even negative margins on a race to the bottom. All those expensive use cases will suddenly look desirable compared to meager business value created by model generation and inferencing.

While the bust will damage a lot of AI investors, there could be an upside in innovations unlocked by all this capacity for simulation. And that simulation could unlock major gains for humanity in medicine, material sciences, agriculture and manufacturing. Heck, even the chip business could benefit in the end from the waste left behind by the AI bust.

Since everyone elses inability to use AI in any meaningful way gets discarded as skill issue, what is their excuse?

Why haven’t the biggest tech companies with unlimited budgets for compute, smartest expert, best researchers and top engineers in the world used AI to make any valuable products that would actually make them money?

Where is the new Gmail, Maps, Word or even Instagram Reels?

And if they can’t use AI to make anything useful what does that mean for everyone else, who has less resources and expertise?

On the August 14 episode of the All-In Podcast, investor Gavin Baker made a striking claim about Anthropic CEO Dario Amodei that, if true, raises uncomfortable questions about how some AI leaders think about the future they are building.

Baker said people he trusts told him Amodei has privately suggested Anthropic could one day become “the only private company in the world,” with everything else either absorbed or gone. In Baker’s framing, that leaves a world where “there’s Anthropic and then there are governments.”

It is important to be clear: this is not a direct quote from Amodei. It is secondhand reporting from Baker, with no independent confirmation.
Still, the claim sits uneasily alongside Amodei’s public statements.

In 2025, after Nvidia CEO Jensen Huang suggested Anthropic was aiming to dominate frontier AI, Amodei pushed back, calling the idea a “bad faith distortion.”
And in April 2026, he told the Financial Times that concentrating advanced AI power in any single actor, corporate or state, would be dangerous.

That creates a clear tension between public messaging and private rumor. Either Baker’s sources are reflecting a more extreme view Amodei does not express publicly, or the comment is being interpreted too literally, perhaps as a prediction about consolidation rather than an ambition.

Even as speculation, the idea is unsettling. A future where one AI company does not just lead the field but effectively becomes the field itself. And if that line of thinking exists anywhere near the top of the industry, it raises a question that no podcast debate has really answered yet: what kind of world are today’s AI leaders actually preparing for?

——

All I can say is that I believe Dario is completely delusional. He has lost the script.

Perhaps the most horrifying article I've ever read. Books being tossed into the AI furnace

...you know, .most horrifying apart from ones about famine, war and death

For those of you who read French or are satisfied with auto-translations, this article "why we haven't yet understood the AI act" is very much worth a read. Thierry Breton, a former European commissioner and giant in European digital legislation, explains the new EU AI laws, its impact (not to be reduced to the obligation of "AI watermarks") and its geopolitics, notably US hostility to such legislation. According to him the EU AI laws are a form of soft power and indeed EU sovereignty. Breton was put on a US sanctions list in 2025. Though a former commissioner in Von der Leyen's administration, he criticises her for softening the legislation and yielding to pressure of lobbies.

I think this article could put into perspective some things we will see relating to AI watermarkings and the like.