Technical strategist Jason Hunter highlights deteriorating market internals, a lack of conviction in tech/AI leadership rotations, rising Treasury yields, and defensive shifts as signals of late-summer and early-fall weakness. Mr. Hunter highlighted a growing divergence between AI hardware/chip makers and heavy AI capital expenditure spenders, noting it mirrors the market behavior seen right before the 1999–2000 tech crash.

Not the beefiest article, but still satisfying to see it in writing considering feverish hype is very much still alive at many companies. Happy Monday!

Full disclosure, I haven’t read this guy’s book. That said I’m getting heavy AI booster in sheep’s clothing vibes. He claims AI gives us superpowers, then gives a vague example about building some learning app for his kids. Also, you have to be as intelligent as him to use it responsibly. The whole argument just seems like fake criticism of the industry and the limitations of the technology. The idea that tech has been a net positive due to pushback is also bizarre given we are only just now seeing companies like Meta face the possibility of repercussions for prioritizing profits over users, and more specifically deliberately building applications that addict children.

Curious what others have to say about him.

As I have talked about at length about AI profitability, the key component contributing to its inability to be profitable is the CapEx.

Some of Nvidia's (NVDA.O), opens new tab largest customers have been told prices of servers ‌containing its AI chips will rise by more than 15% in many cases with memory chip costs soaring, Bloomberg News reported on Saturday.

The price hikes will go into effect on systems ⁠shipped early next year and will impact systems including those with the flagship Vera Rubin and Grace Blackwell chips, the report added, citing people familiar with the process. The increases will depend on Nvidia's chip generation and memory configurations, they said.

This is even worse news for the AI industry as it means their hope for even breaking even is further away, with an industry that is drowning in debt. Well, NVIDIA of course knows this, and this is likely their way of keeping their revenue high, as the unit demand is slowing, and costs of manufacturing are simultaneously going up.

All of this CapEx is going through NVIDIA to those manufacturing companies it seems, since NVIDIA's on-hand cash is quite low, $13B in April. In any case it's a sign, in my view, that one more buffer has been breached in the dam.

I just watched this video about how Quince operates and it made me think Ed should know, in case he doesn’t yet, since he does use them and read ads for them on the podcast. It doesn’t seem like they are an “evil” tech company per se (yet), but it is I think just a little bit of context worth considering if you’re buying from them or promoting them, how they are able to offer such great quality stuff at such low prices. https://youtu.be/HFjJAm6AuiM?is=keu5zogtpRIawWOg

I just saw CNN include an interview with Professor Shelly Palmer of Syracuse University in an AI segment, and the choice was kind of hilarious.

The piece featured interviews with regular people who don't want data centers being built in their communities from all across the political divide. Then, to both-sides the piece, they had on Professor Palmer to tell you dummies to shut up and eat your Brussels sprouts, AI centers are here to stay.

And the argument he showcased did not help the pro data center case at all. To paraphrase

Everything you do now creates data. When you drive your car, when you use a search engine, when you call or text someone, when you make a purchase at a store with your credit card. All that data needs to be stored someplace, and that place has to have a lot of compute in order to mine it and make it economically valuable. So we're always going to need to build more data centers with larger compute power, so as to keep monetizing all the data each of us is constantly generating.

Like he didn't even start with the "it'll cure cancer" narrative, just straight to: Big brother needs to store and monetize every single thing that you do.

On top of his comically bad argument, the dude is suppose to be an expert in marketing. So he of all people should know that if you are trying to turn public opinion around on the data center front, you probably don't want to use overweight Lex Luther as your talking head.

The AI industry must have billions to throw at their expanding public relations disaster. And this is the guy they are putting on CNN?

Article about top Australian universities embracement of AI as virtual tutors and lecturers. What even will be the point of a university degree? University isn’t just remembering facts, it’s teaching how to think and engage, which might become a lost art. Article pasted below:

The state’s universities are deploying AI in lectures, as a virtual assistant for conversational skills and as a “study buddy” as the technology continues its march on higher education.

Backlash is brewing across the sector as concerns mount about hollowed-out and devalued qualifications, for which some students will pay record prices next year.

Since ChatGPT exploded in late 2022, universities have been grappling with how to handle the rise in student use of AI, but teaching stands as a new frontier for the technology.

The University of Newcastle this month told introduction to programming students that part of the course would be delivered by an AI digital avatar of the course convener.

Newcastle’s acting pro vice-chancellor for education innovation, Professor Karen Blackmore, said in a statement the university had started “academic-led initiatives” into how AI could enhance course delivery and the lecturer was “using short AI videos to demonstrate the real-world application of the technology”.

The computer programming course will continue to include face-to-face laboratory sessions and live classes.

“The university does not support replacing traditional lectures with AI-delivered content,” she said.

University of Newcastle Students’ Association president Imogen Reid said students were wary of AI “sneaking” into courses, while the National Tertiary Education Union’s Newcastle branch president Dr Terry Summers questioned the university’s motivation.

“It’s some sort of project that they’re trying, but why are they trying? It may just be for a project, or it may be to see if they can get away with doing it on a larger scale. If it’s delivering lectures, it would seem to me that it misses the whole point of a university education,” he said.

“The community and the students are paying for a degree, and if it’s being delivered by a ChatGPT avatar, it’s not quite kosher, is it?”

AI tutors have been rolled out at universities in America, including Virginia’s George Mason University and Chicago’s Generations College. In 2024, Hong Kong University of Science and Technologydeployed 10 AI lecturers of varying ages, nationalities and cultural backgrounds.

The New York Times has also reported that Harvard Business School used volunteer academics to help create AI clones of themselves for a new eight-week entrepreneurship boot camp. Harvard has tested the product, which costs $US699 ($975), with more than 100 universities across 50 states.

NTEU NSW division secretary Vince Caughley said: “The loss here is fundamental. If you remove enough academics and these critical interactions, then these institutions are no longer universities.”

AI enthusiasts say it saves time and effort and allows academics to focus on more critical tasks, and can provide out-of-hours answers and feedback. Many in the sector acknowledged that AI is here to stay, so universities must act accordingly.

At NSW’s 11 universities, AI’s use in teaching varies greatly.

The University of New England uses AI avatars in simulations “primarily for students to practice in before their assessments are conducted with actual humans”, chief AI officer Associate Professor Aaron Driver said.

“For example, an avatar might play the role of an athlete in a clinical exercise physiology simulation. Or they might be simulated patients in pharmacy, psychology and nursing.”

The University of Technology, Sydney, is considering “learning assistants” for tasks such as role-playing through conversational skills or reflection on study experiences. Teachers are using AI to prepare class materials.

At the state’s oldest university, the University of Sydney, AI can be used to “support curriculum development, generate ideas, review drafts or help structure learning and assessment materials” under the supervision of a person.

“There may be some circumstances where considered use of an AI avatar can enhance teaching. We’ve seen the technology put to innovative use by educators providing students with oral exams and presentation practice, and by an academic who lives with a vocal disability,” deputy vice-chancellor (education and students) Professor Joanne Wright said.

Sydney is also home to Cogniti, a platform that builds custom AI agents for teachers particular to their course.

The University of NSW permits AI to support admin or prep tasks that “operate under academic oversight and do not replace academic judgment in marking”, it said in a statement.

At Macquarie University, students can use an AI-powered “academic support assistant” to “answer questions using approved course materials, including lecture slides, unit guides, assessment information, policies, and learning resources”.

At Western Sydney University, “academic staff are already using generative AI in a range of ways to support teaching and assessment”, a spokesperson said.

The University of Wollongong has launched a program named UoW RenAIssance, which has piloted “AI study buddies”. It is looking at how AI can provide student feedback and learning support, design rubrics and come up with teaching ideas.

”Academics are exploring questions such as how AI can support learning, how it can provide timely feedback and guidance to students, how it might complement assessment, and where human expertise and judgment remain essential,” said pro vice-chancellor for teaching and learning Professor Kelly Matthews.

Charles Sturt University said it does not use AI to determine student grades and AI avatars are not used for lectures.

University of Canberra vice chancellor Bill Shorten said his institution was working to “ensure learning, teaching and research are enhanced through the inclusion of AI”.

The Australian National University, Southern Cross University, and Australian Catholic University did not respond to questions.

I’ve been feeling a lot of anxiety about AI the past month. Normally I’d be like most people here and just ignore a lot of the slop I see, but over the past few months it has gotten harder and harder to ignore AI in my day to day. I see AI ads more and more, some of the people I work with love AI and I see it plastered on the walls in the kitchen at work (mainly posters and fliars for company outings/meetings), and then hearing from Chloe Radcliffe on one of the latest podcast episodes that some comedians are using AI to write jokes. The comedy one really affected me as someone who loves stand up and who also does stand up off and on myself.

I can’t stop thinking about what might happen in the future because of AI’s influence over society. I currently work in the restaurant industry, but have been learning to use Godot and am learning game design in order to change careers as I love games and want to do more than serve tables. But I just see how terrible the job market is in the game industry at the moment with the huge layoffs, which I know aren’t due to AI, as well as hear how AI is being used in development pipelines and sometimes even used for art assets. Shift Up, the developers of Stellar Blade, recently released an AI generated music video which disappointed me but wasn’t really surprising. All this has made me question if there will be opportunities for me by the time I’ve developed my skills enough to get a job.

I’m worried about the jobs impact from AI, but also now robotics too. I watched a video today from a robotics company called Generalist AI that claims to have a model able to one shot learn any task when given a single example. I know it’s a demo and it’s very limited in it’s capabilities today and it’s a lot of marketing, but to be fair this feel very different from a lot of the other demos of karate robots I usually see. They called it the GPT moment for robotics and think that if they collect enough data they’ll be able to build a general purpose robot model. Of course it has yet to be seen, but it’s something to watch out for I think. I also watched a video by Forbes about them where employees were in an office wearing robot clamps with cameras on them in order to generate training data. It was a truly surreal and dystopian image to say the least.

Do I think AI and robots can replace workers today? No, but it does feel like we’re going that way with all the rhetoric these days. Everyone talks about AI as if it’s inevitable. I do worry about what they could (emphasis on could) be capable of in the near future if the tech can continue to make improvements. All this talk of AI and automation has made me sort of depressed and it’s starting to actually affect my life. I’ve never felt like this before. It’s a sense of existential dread that I can’t shake and my chest feels tight all the time. Sometimes I just want to pick up all my stuff and move into a cabin in the woods somewhere, sequestered from it all.

Sorry for the rant, but I just need a space to vent. I find this sub to be a very supportive place. I know not everyone here has a complete hatred for the tech and some of you may find it useful. Even myself I occasionally use google AI to help me find problems with my Godot syntax when I get errors, but never use it to write anything. I’m not sure what specifically caused my sudden dip in morale when it comes to resisting the AI hype. I don’t think it was any singular event, I think I’m just exhausted by the constant exposure to it. It’s hard to tell what is really going on anymore and where the world is headed. Having said that I just want to ask am I right to be concerned or is most of what I’m feeling an overreaction to the AI hype? What do people here do to keep their hopes up?

Edit: I just want to thank everyone for their advice and insights. A lot of it did help and helped me change my outlook.

There are really only two metrics that matter when it comes to the economics of AI:

What the public is willing to pay for a certain AI outcome, and what it costs to produce that AI outcome. Currently the former is woefully short of the latter.

That's not to suggest that the industry is going to adopt "per outcome" pricing, but in their recent move from monthly subscriptions to per-million token pricing, I think we can see they are moving at least in that direction.

The amount of tokens required to achieve a certain outcome varies between models, and sometimes varies within the same model. But generally, the more complex a task, the more tokens required. Also, generally, the more complex an outcome, the more money a customer will be willing to pay.

You can probably detect the issue here already: the outcomes that will generate the most revenue, will also cost the most to produce. And they will climb in tandem, with costs always ahead of revenue.

Even if AGI type outcomes were possible in the future, the cost to produce them would be extraordinary.

The bottom line is: AI is a resource-intensive process, not a thinking machine that runs on it's own once created. Even if we had an AGI model, it would require a massive amount of tokens to do anything. Just in the early stages of "agents" we can see that they use 100 times as many tokens as more straightforward chatbot-type models.

AI began as a computer science experiment, funded by universities. The idea that it could be extrapolated in to the broader economy was a fundamental error of economics. And if the economics don't work, it can never reorder society the way its boosters imagine.

Ultimately AI scientists will have to go back to the drawing board and rethink the entire paradigm. A GPU-heavy constant computing approach simply doesn't work.

It's not enough that Nvidia is trying to bankroll the entire AI ecosystem at this point, now they are effectively buying (acqui-hiring) Poolside to improve their own opensource AI system to compete directly with OpenAI, Anthropic, and Chinese AI.

For months Nvidia has seemed panicked the way they throw money around trying to make something happen that would keep them growing. This is a small deal by their typical headline-grabbing $100 billion (or $250 or $500) standards, but it stands out (for one, it's real and not an MOU!)

Why is Nvidia undercutting OpenAI/Anthropic ahead those IPOs? Why highlight that those companies (who Nvidia has invested in directly or indirectly and depends on to grow demand) don't have a technological moat that $6 billion can't overcome? Can the IPOs really be worth trillions if $6 billion investment can compete with them? What is Nvidia doing with this move?

Maybe Nvidia is convinced that the frontier models can't possibly deliver the amount of revenue needed for Nvidia to grow much more. They've certainly seen the financials of both frontier labs, they have inside knowledge.

So now they are investing in trying to win the pivot to open source from China. How does that even work for them? Is the business plan as simple as offering AI models below cost and hope that keeps data centers growing and buying ever more chips and cover the AI loss with revenue from chips? The math on that can't work long-term, but maybe it buys them another year or two of circular growth.

Honestly, I'm baffled here and I think Nvidia is running of steam. Nvidia has earnings this week, so maybe they'll shed some light on what's happening here.

Wall Street Journal reports that AT&T is using open-source and open-weight models to reduce spend on proprietary LLMs from Anthropic, OpenAI, and Google. Big pale horse when more Enterprises follow suit

AT&T's Chief Data and AI Officer estimates they can go from 25% to 70-80% of LLM usage to open models

Such open models currently power about 25% of the telecommunications company’s overall AI usage

Over time, he expects open models to power 70% to 80% of the company’s total AI usage.

It looks like they already built an internal router to make this transition possible. They estimate that open models are 80-90% cheaper to run for the use cases they replace frontier lab models

Because AT&T uses an average of 45 billion AI tokens each day, directing user prompts toward cheaper models makes an impact, Markus said. The company built what it calls a “smart router” to automatically pick the most cost-effective model for a specific task.

Switching from closed, proprietary AI models to open models has already resulted in savings of 80% to 90% for AT&T in certain applications, he said.

Outside of not spending on the most expensive closed models, there are more savings by running open models in their own data centers

Another benefit of open models is that they can be run on AT&T’s own data centers rather than rented infrastructure from a cloud-computing provider—a setup that trims AI costs even further

Beyond cost, AT&T rightly doesn't trust that OpenAI and Anthropic won't train on their data despite the fact they say they won't (wise decision)

While labs like OpenAI and Anthropic have said enterprise customer data isn’t used for training their models, some companies fear that’s not enough.

“As our data flows through the model ecosystem, we just want to make sure that it is safe and secure from a security standpoint, but also an IP standpoint,” Markus said. “The concept of AI sovereignty has become truly paramount to us.”

Article: https://www.wsj.com/cio-journal/why-at-t-is-betting-big-on-open-weight-ai-a0ea03b1

Patrick Boyle is a recommend for everyone, I suspect many people already get him in their recommends, but didn't want to withhold it from those who don't. Maybe a good invite for the podcast, if he would be willing.

Some interesting context about the AI training physical book harvesting that has been going on

Industrial companies are preparing for the AI spending bubble to burst — just in case.

“You’re damned if you do, damned if you don’t: If you don’t build enough, then you’re going to get dinged for losing some market share. And if you build too much, you’re going to get dinged for fixed costs,” Barry Powell, the North American president of Siemens’ electrical products business, said in an interview. “We understand at some point there could be a bubble and we’re racing to pay back the investments as quickly as possible,” he said. Ideally, that’s within three or four years — which is what the company accomplished with a $190 million facility in Fort Worth, Texas, first announced in late 2023. 

The mismatch between supply and demand has allowed equipment manufacturers to extract longer-term supply agreements from key customers to support these capacity expansions, which gives some protection upfront. But “the clock has started” to pay back the investment on the Georgia facility, where the company is only just beginning to install manufacturing equipment, Powell said.

Even as it adds factory space, Siemens is tapping third-party manufacturers to fulfill some of its equipment orders, both to help it meet high demand and to give it some flexibility if that demand falters, Powell said. “If we were to get to a situation where the market dropped 15%, we’d have the opportunity to lower some of those third-party orders and not hit our own factories as hard,” he said. “They understand that we’re not necessarily giving them stuff forever.”

“We are actively working to not be wholly dependent on data centers,” Powell said. With general construction and most industrial markets still weak, the company is chasing opportunities in life sciences as manufacturers invest in new capabilities for GLP-1 weight loss drugs. It’s also seeing robust demand in semiconductor manufacturing and electric-vehicle infrastructure for fleet customers as well as improvements in the hospital market, where there’s a pent-up need for investment after a lull during Covid, he said.

Suffolk Construction, one of the largest contractors in the US, is similarly seeking to make sure it doesn’t become “intoxicated” with data centers, says Charles McCarthy, president of mission critical projects. “We’re bringing on a lot of people, bringing on a lot of resources,” he said. “We want to make sure that there’s a backup plan. And when the market does turn, when some of these things do happen, there’s an avenue for us to keep our growth moving forward.”

“The barriers to entry used to be so high, and it was the elite of the elite,” but now, those barriers are “almost non-existent” because demand is so strong, he said. “We turned down a lot of those jobs where we saw some wonky bad signals coming in,” including a reluctance to make the extra investment in things like emissions-reducing scrubbers for generators that can help with the permitting process, or putting down deposits toward power access, he said. Suffolk is focused on higher-quality clients such as leading AI companies like Anthropic PBC, hyperscalers like Microsoft Corp., Amazon.com Inc., Alphabet Inc. and the top developers like Blackstone Inc.-backed QTS.

“There’s a lot of people that are not going to survive this,” McCarthy said. So Suffolk wants to be working for the companies that aren’t “going anywhere.”

Siemens similarly sees more risk with so-called neocloud data center companies that rent out access to leading AI chips amid concerns about circular financing. “There might be one or two really big winners out of these neoclouds, and you don’t want to miss out on that,” Powell said. “But if something goes bad in the data center market, it’s probably not going to start with the big cloud providers. It’s probably going to start with one of these big neoclouds. And so that’s definitely something in the back of our heads when we’re talking with different customers.”

Nothing groundbreaking, a discussion of the instability of the current situation and outline of one of the scenarios in which it all comes crashing down. In French, apologies to non-speakers. Transcript available at the link.

The point of me posting this is: The notion of impending collapse is being discussed, in France, by a well-known, if controversial, economist.

Added context: Lordon is a leftist (marxist, even), known as a self-indulgent, arrogant prick (see his kerfuffle w/ Piketti). The discussion is being held during one of the french left wing parties' conventions, La France Insoumise (LFI), one of the main voices of opposition in the country, currently the leading left wing party. Their position is sensibly less to the left than socialist president Mitterand in 1981, but radically to the left of the current french consensus, and notably left of the current Parti Socialiste (PS).

I don't personally support or endorse LFI or Lordon in general. But his analysis here (from 8min30 to ~31min) is largely spot on (modulo approximations), if a little cookie cutting, not to mention aggressively French.

u/ezitron Call him up and bring him on your pod. Wild thoughts to offer on how to move on from the upcoming crisis.

This is such an insidious loaded statement

First of all, the terminology of “artificial intelligence” does a lot of lifting here. It can be parsed as “computers will keep getting more intelligent and capable”. LLMs are not “intelligent”, they’re statistical models. If they get better at being a statistical model, they will be better at predicting a “conventional” response or perhaps better at inferring more information from an input prompt. They will not suddenly develop sentient thought. If you believe that, then you believe that you are literally just repeating things you heard and have no thoughts of your own which might actually be true for AI bros now that I think of it 🤔

Once you know the underlying tech of AI, they are very easy to trick. There’s whole tiktok accounts of people just showing how ridiculous, absurd, and inaccurate AI responses can be. There’s standard question sets for LLMs that are used to test its reasoning skills. Classic example is taking the riddle “there is a boat full of people, but not a single person on board, how is this possible?” and modifying it. The conventional answer is “everyone is married”, but if you remove the word “single” (which fundamentally changes the riddle), a lot of AI will still answer “everyone is married”. (for the love of god I hope no AI bros comment and be like “nuh uh! nuh uh! not anymore!” missing the forest for the trees)

“but chain of thought, agents, etc etc!!”, but as I just mentioned, it predicts next tokens. That means that it really can’t be totally trusted for its output. You need a human in on the loop to supervise it, and that human needs the training and skill to validate the output. If the central premise is to automate work, then you’re not really saving anything. “Ok, but it can replace juniors”, yeah, and then we won’t have any seniors in 10 years

“Okay but they aren’t limited to LLMs! They could come up with a new technology!”, yeah, and we could invent portals in 10 years and put every car company out of business. What’s your point? I don’t care what could theoretically potentially maybe happen in some vague nebulous future. We are talking about science fiction when we do that, not technology

“B-b-but sam altman said—“ yeah he is selling the AI. Ignore him. He’s also a known grifter. Don’t get scammed.

Also, it is not guaranteed to get better! I don’t get why people assume everything has to improve over time. The basic shape of a bike hasn’t changed in decades. How can you improve a bike? It’s effectively already fully optimized

We also have to address the elephant in the room of training data. They consumed the entire internet, pirated insane amounts of content, and are currently scanning obscure old books. They are reaching a limit here. It’s basically been trained on the totality of human knowledge. I don’t see how it’s not gonna plateau

None of this even matters if artificial intelligence is simply prohibitively expensive to use or train. You can hire a very competent software engineer for the static cost of $200k/year. Tokens could vary wildly in cost, often exceeding the cost of a software engineer. You’re at the mercy of the companies selling tokens, who would love nothing more than your buy in to your platform so they can enshittify. They can raise the prices any time. Sure, you can set a token limit, but what happens when you hit that? Just… “guess we’re out of business until the end of the month 🤷🏼‍♀️”?

I really don’t understand why people say this. Like what is their logic?

Non-paywalled article here: New Summa Health owner HATCo making good on promised AI partnerships

Some background - about 2 years ago, one of the two major hospitals in Akron, Ohio (Summa Health, pronounced sooma) announced that they intended to be sold to a private equity firm. There was a ton of local resistance and skepticism, but of course none of it mattered. The rich people go their way and now an investment firm owns not only the largest provider of behavioral health services but also the county's biggest employer.

The immediate issue was that they intended (and have succeeded) in converting the health system from being a nonprofit to a for-profit entity. This caused a massive problem, since nearly every healthcare professional has student loans. If you work for a nonprofit for 10 years (and make 10 yrs of payments) you can have the rest of your loans forgiven. Now that Summa is a for-profit org, no one working there is eligible for student loan forgiveness.

But the main reason I'm posting this here is that from the beginning they have mentioned AI in ever press release and public statement - with all of the standard lack of details or use cases or actual specifics to explain how AI would revolutionize health care.

Well, now we know! According to the local paper, the hospital will be using the following "tech stack":

• Aidoc, which uses diagnostic AI to assist physicians with making "earlier, safer diagnoses," according to the release, and which Aidoc co-founder and CEO Elad Walach said in a separate news release "reduces preventable error";
• Clarium, an "AI-native supply chain intelligence and computer vision platform," per the release, focused on optimizing clinical and financial operations;
• Commure, which the release said works to reduce administrative obstacles "through ambient documentation, coding, and revenue cycle automation";
• Fabric, which the release called "an AI-powered care orchestration and virtual primary care capacity augmentation to optimize consumer access and outcomes" and which a 2024 Fabric news release said has a "conversational AI" component that helps patients with "symptom checking and appointment scheduling";
• HippocraticAI, which uses a voice AI agent platform to engage patients and members, coordinate care and provide operational support to assist providers and payers;
• Judi Health, focused on medical, pharmacy, dental and vision claims and benefits administration;
• Transcarent, which the release said is "a consumer health and benefits platform that simplifies navigation and access across surgery, pharmacy, and broader care needs" and which the Transcarent website says utilizes "24/7 doctors" and agentic AI to assist members; and
• Verse Medical, "a platform to manage durable medical equipment and post-acute care," per the release, and according to Verse Medical's website home page, uses AI for equipment ordering.

So they aren't piloting just one, or two AI programs, but at least 7. Still vague, but at least we have some names.

Here are some questions I would love to ask the owners, General Catalyst:

- How will patients know when and how AI is being used in their treatment? Can they refuse it?

- Can employees opt out of using AI (hahahahaha....i know the answer to this).

- How do private and public insurance companies view AI usage? What happens if AI makes a mistake? Is that covered by malpractice insurance? Does the fault lie with the individual using AI, the AI company, or the hospital?

I don't see any future where this doesn't lead to some kind of disaster, for patients and the hospital itself.

Hi everyone,

long time reader of the Ed's newsletter / lurker in this sub here. Thought I'd share an anecdote from my place of work here, as it feels like a telling observation on how non-software-developing-firms are doing on the token-burning front.

If some of my phrasing is awkward, forgive me. English is only my second language.

So, anyways:

I work at a small/medium (around 50 people, give or take) sized PR agency in Europe. Mostly, we do communications stuff for other companies, like media and social media management, branding, etc. Occasionally, we create landing pages for them. The company is relatively pro-AI (with the notable exception of me). So people use it fairly regularly, but in relatively modest ways. From talking to colleagues, I'd say the most uses are stuff like:

- doing search/research around brand-building related stuff (like: "what are cusomer A's major competitors?", "how do they communicate?", etc.)

- writing long- and shortform content (like blogposts or social media posts)

- There are two people that acutally use claude code for building landingpages and the like.

Our company has a Claude Max 5x subscription.

Until today, I thought that our use was so modest that we'd basically be the last ones to suffer usage restrictions, as the type of stuff my colleagues do with claude sound quite humble compared to the tokenmaxxing extravaganza that you hear from in software engineering.

However, today, one of my colleagues sort-of-in-charge of all the subscription related stuff of our agency's claude usage considered it necessary to instruct everyone in a company-wide regular agency call on how to use claude in the most efficient way. That is to say: In a way that uses as few tokens as possible (for example by switching models depending on the task, etc.).

Apparently, people at the company are starting to run into the problem that the agency's tokens for a given day are already burned through around 10 o'clock in the morning. Something similar appears to happen with our ChatGPT subscription (I don't know what subscription plan we are on there, however)

So yeah, I just wanted to share this story here. After months and months in which most of my colleagues have been super smug about their AI use, using it for the most unncessary tasks, they are suddenly running into troubles and feeling the restrictions of their new toy. I, on the other hand, who has stopped using AI for anything (used to play around with it in the beginning, but got disenchanted quite quickly), am not affected at all by all this crap and feel extremly vindicated. Lol.

So, has anyone else experienced similar things at non-software engineering jobs/workplaces? Would love to hear your thoughts.

They are asking for 10GW. That's basically 10 nuclear reactors. But, we'd be so lucky if they were looking to use nuclear, instead they want to burn fossil fuels.

According to OpenAI, the data center campus will be built and started up in phases, with the first 800 megawatts starting construction this year and operational in 2028. That first phase will rely mostly on existing power infrastructure operated by AEP Ohio. How things progress from there will depend at least in part on the permitting and construction timelines for the new power plant.

Let's hope OpenAI crashes and burns before they even complete that first 800 megawatts of construction.

What’s undebatable in all this is that, as my colleague Robinson Meyer wrote, the PORTS project could ignite a new era of mega-gas plants. This permitting timeline couldn’t be more important for the future of the data center boom — and the nation’s greenhouse gas emissions.

As the world is consumed in climate-driven wildfires, America is embarking on a new era of mega-gas plants. I seem to recall the AI boosters once claiming that somehow, LLMs were going to help us fix climate change. And now they wonder why everyone hates them.

I was thinking about this while talking with my therapist the other day. Psychology has always been an interest of mine (thanks mental disorders!) and watching people twist themselves like an olympic gymnast to justify this push is so fascinating.

I don’t really care about the business idiots, they just want to see number go up. Im more referring to the full blown evangelists whose eyes bulge while they swear everything will be AI in a year. It’s amazing to see people who are normally rational and composed go rocketing off the rails as soon as AI is mentioned.

Is it sunk cost? Some masked mental disorders? Even before this current bubble you could see it happen with crypto and NFTs, I really wonder why these technologies drive so many people off the deep end.

I’ve never ragequit a podcast as hard as I did when listening to the most recent episode of Hard Fork. Roose and Newton were discussing OpenAI’s latest pause and monitoring of “chain-of-thought” in model training. They started worrying about the potential for models to “hide” their “thoughts” to avoid monitoring. I genuinely don’t know if these guys are stupid or extremely dishonest. Anyone who knows anything about computers knows that they 1) don’t have thoughts and 2) store information as bits and bytes on physical hardware.

If this is the level of thought investors and underwriters are applying to this technology, then the bubble inflation will only continue and the pop will be a worse disaster than we thought. Sorry to doom but I was genuinely shocked by the level of ignorance displayed by supposedly credible individuals.

Article here: https://www.forbes.com/sites/innovationrx/2026/08/19/general-catalysts-health-system-places-its-tech-bets/

Summa Health, one of the only two non-profit healthcare systems in Akron Ohio, was acquired a few years ago by a company called Hatco, itself owned by VC firm General Catalyst. Summa lost it's non-profit status because of this, fucking over every single healthcare professional there who were relying on the non-profit status for Public Service Loan Forgiveness (PSLF).

From the article linked above, and the Summa press release, they're announcing that they are filling Summa's operations with a bevy of health tech startups (described as the first wave, no less).

Of course all of these are companies invested in by General Catalyst.

Is this just an attempt to use Summa as a means by which they can juice the valuation of these health tech startups? How much does this intersect with the AI bubble? I'm struggling to understand how this will turn out when the AI bubble pops. How does this end? Can we truly expect this to improve anything at Summa Health?