Premium: The AI Bubble is a time bomb, burdening hyperscalers with billions of new depreciation a quarter that will soon eat away profits, VCs with dead equity in fallen AI startups, and Oracle with hundreds of billions of unpayable leases.
www.wheresyoured.at/premium-timebomb/
It's strange how rarely journalists covering this space can ask "Hey, but is it bullshit?". CEO's whose companies are over-leveraged, bubbly, and unprofitable promise a major breakthrough that will justify their fragile position and no one seems to *consider* they may be lying.
It's Theranos 2.0.
Exclusive: Based on documents viewed by this newsletter, OpenAI spent over $12.4 billion on inference from 2024 to September 2025. As part of its Microsoft revenue share, it sent $493.8m in 2024/$865.8m Jan-Sep 2025, implying lower revenues than previously reported.
www.wheresyoured.at/oai_docs/
A table showing profit margins of major publishers. A snippet of text related to this table is below. 1. The four-fold drain 1.1 Money Currently, academic publishing is dominated by profit-oriented, multinational companies for whom scientific knowledge is a commodity to be sold back to the academic community who created it. The dominant four are Elsevier, Springer Nature, Wiley and Taylor & Francis, which collectively generated over US$7.1 billion in revenue from journal publishing in 2024 alone, and over US$12 billion in profits between 2019 and 2024 (Table 1A). Their profit margins have always been over 30% in the last five years, and for the largest publisher (Elsevier) always over 37%. Against many comparators, across many sectors, scientific publishing is one of the most consistently profitable industries (Table S1). These financial arrangements make a substantial difference to science budgets. In 2024, 46% of Elsevier revenues and 53% of Taylor & Francis revenues were generated in North America, meaning that North American researchers were charged over US$2.27 billion by just two for-profit publishers. The Canadian research councils and the US National Science Foundation were allocated US$9.3 billion in that year.
A figure detailing the drain on researcher time. 1. The four-fold drain 1.2 Time The number of papers published each year is growing faster than the scientific workforce, with the number of papers per researcher almost doubling between 1996 and 2022 (Figure 1A). This reflects the fact that publishersā commercial desire to publish (sell) more material has aligned well with the competitive prestige culture in which publications help secure jobs, grants, promotions, and awards. To the extent that this growth is driven by a pressure for profit, rather than scholarly imperatives, it distorts the way researchers spend their time. The publishing system depends on unpaid reviewer labour, estimated to be over 130 million unpaid hours annually in 2020 alone (9). Researchers have complained about the demands of peer-review for decades, but the scale of the problem is now worse, with editors reporting widespread difficulties recruiting reviewers. The growth in publications involves not only the authorsā time, but that of academic editors and reviewers who are dealing with so many review demands. Even more seriously, the imperative to produce ever more articles reshapes the nature of scientific inquiry. Evidence across multiple fields shows that more papers result in āossificationā, not new ideas (10). It may seem paradoxical that more papers can slow progress until one considers how it affects researchersā time. While rewards remain tied to volume, prestige, and impact of publications, researchers will be nudged away from riskier, local, interdisciplinary, and long-term work. The result is a treadmill of constant activity with limited progress whereas core scholarly practices ā such as reading, reflecting and engaging with othersā contributions ā is de-prioritized. What looks like productivity often masks intellectual exhaustion built on a demoralizing, narrowing scientific vision.
A table of profit margins across industries. The section of text related to this table is below: 1. The four-fold drain 1.1 Money Currently, academic publishing is dominated by profit-oriented, multinational companies for whom scientific knowledge is a commodity to be sold back to the academic community who created it. The dominant four are Elsevier, Springer Nature, Wiley and Taylor & Francis, which collectively generated over US$7.1 billion in revenue from journal publishing in 2024 alone, and over US$12 billion in profits between 2019 and 2024 (Table 1A). Their profit margins have always been over 30% in the last five years, and for the largest publisher (Elsevier) always over 37%. Against many comparators, across many sectors, scientific publishing is one of the most consistently profitable industries (Table S1). These financial arrangements make a substantial difference to science budgets. In 2024, 46% of Elsevier revenues and 53% of Taylor & Francis revenues were generated in North America, meaning that North American researchers were charged over US$2.27 billion by just two for-profit publishers. The Canadian research councils and the US National Science Foundation were allocated US$9.3 billion in that year.
The costs of inaction are plain: wasted public funds, lost researcher time, compromised scientific integrity and eroded public trust. Today, the system rewards commercial publishers first, and science second. Without bold action from the funders we risk continuing to pour resources into a system that prioritizes profit over the advancement of scientific knowledge.
We wrote the Strain on scientific publishing to highlight the problems of time & trust. With a fantastic group of co-authors, we present The Drain of Scientific Publishing:
a š§µ 1/n
Drain: arxiv.org/abs/2511.04820
Strain: direct.mit.edu/qss/article/...
Oligopoly: direct.mit.edu/qss/article/...
Nature suggests you use their "Manuscript Adviser" bot to get advice before submitting
I uploaded the classic Watson & Crick paper about DNA structure, and the Adviser had this to say about one of the greatest paper endings of the century:
Yay. Priceless. The right column at the right time. And a gleefully English two fingers to the haters.
If you're having a rough day, remember that in 1991 Tim Berners-Lee's paper for the World Wide Web was rejected and he was relegated to the poster session.
I saw the dot coms crash from a front row seat. AI is running out of money way faster.
The evangelism is insecurity from people who made the wrong bet. Iāve seen it before. futurism.com/future-socie...
The Trump administration has stopped funding of PubMed, not considering a vital service.
Your doctor will not know the newest information that affects your health. This will cost lives.
"Science communication isn't about dumbing it down, it's about meeting people where they are with curiosity, care and clarity."
Great read in Development, and I will definitely try some of these challenges to practice science communication. doi.org/10.1242/dev....
Reminder: It's always good to stay humble!
I've shared this quote before but I'll share it again, as it's one I've been thinking about a lot as I've watched how our oligarchs have been behaving over the past few months.
League One football always offers surprises. Not Luton playing badly and losing away at Lincoln this afternoon. That's expected. But direct-to-consumer marketing of asbestos is not something I've seen before.
Abstract: Under the banner of progress, products have been uncritically adopted or even imposed on users ā in past centuries with tobacco and combustion engines, and in the 21st with social media. For these collective blunders, we now regret our involvement or apathy as scientists, and society struggles to put the genie back in the bottle. Currently, we are similarly entangled with artificial intelligence (AI) technology. For example, software updates are rolled out seamlessly and non-consensually, Microsoft Office is bundled with chatbots, and we, our students, and our employers have had no say, as it is not considered a valid position to reject AI technologies in our teaching and research. This is why in June 2025, we co-authored an Open Letter calling on our employers to reverse and rethink their stance on uncritically adopting AI technologies. In this position piece, we expound on why universities must take their role seriously toa) counter the technology industryās marketing, hype, and harm; and to b) safeguard higher education, critical thinking, expertise, academic freedom, and scientific integrity. We include pointers to relevant work to further inform our colleagues.
Figure 1. A cartoon set theoretic view on various terms (see Table 1) used when discussing the superset AI (black outline, hatched background): LLMs are in orange; ANNs are in magenta; generative models are in blue; and finally, chatbots are in green. Where these intersect, the colours reflect that, e.g. generative adversarial network (GAN) and Boltzmann machine (BM) models are in the purple subset because they are both generative and ANNs. In the case of proprietary closed source models, e.g. OpenAIās ChatGPT and Appleās Siri, we cannot verify their implementation and so academics can only make educated guesses (cf. Dingemanse 2025). Undefined terms used above: BERT (Devlin et al. 2019); AlexNet (Krizhevsky et al. 2017); A.L.I.C.E. (Wallace 2009); ELIZA (Weizenbaum 1966); Jabberwacky (Twist 2003); linear discriminant analysis (LDA); quadratic discriminant analysis (QDA).
Table 1. Below some of the typical terminological disarray is untangled. Importantly, none of these terms are orthogonal nor do they exclusively pick out the types of products we may wish to critique or proscribe.
Protecting the Ecosystem of Human Knowledge: Five Principles
Finally! š¤© Our position piece: Against the Uncritical Adoption of 'AI' Technologies in Academia:
doi.org/10.5281/zeno...
We unpick the tech industryās marketing, hype, & harm; and we argue for safeguarding higher education, critical
thinking, expertise, academic freedom, & scientific integrity.
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Academia may not give you job security, flexibility, or wealth, but it will let you unexpectedly connect to eduroam in foreign cities
This is both funny and acuteā¦might assign it to my incoming students as an introductory exerciseā¦
I did this before in German but I guess today is a good day to compile English resources on why AI isnāt actually intelligent and also a real danger: š§µ
@andywatson on the NGS Sequencing market and the prisoner's dilemma
It was good to make the case for the molecular testing we need to help patients with cholangiocarcinoma in Scotland to @jennimintomsp.bsky.social and the Scottish Government. Hopefully this will stimulate a solution. Thanks to @benmacpherson.bsky.social for hosting.
As Jon says this is absolutely fascinating and a stark warning to science journalists that if a result looks too good to be true it probably is.
Newsletter: I am sick and god damn tired of everybody pretending that generative AI is the next big thing. The media is complicit in accepting fantastical nonsense - both in the numbers put out by OpenAI and the silly jobs created by Anthropic - and it has to stop.
www.wheresyoured.at/reality-check/
Interesting opinion in Science suggesting to replace 'scientific consensus' with convergent evidence.
Because it is less easily derailed by quoting one dissenting opinion.
Seems like a good idea!
www.science.org/doi/10.1126/...
1. LLM-generated code tries to run code from online software packages. Which is normal but
2. The packages donāt exist. Which would normally cause an error but
3. Nefarious people have made malware under the package names that LLMs make up most often. So
4. Now the LLM code points to malware.
Why academia is sleepwalking into self-destruction. My editorial @brain1878.bsky.social If you agree with the sentiments please repost. It's important for all our sakes to stop the madness
academic.oup.com/brain/articl...
If LiverTox has gone, my reporting of ?DILI will be far less nuanced.
Love the energy of young Shostakovich. He looks like a Harry Potter who will fuck you up
For more than a decade, Amy Paris worked for federal agencies as a problem solver: retooling overly bureaucratic and cumbersome processes to make them easier for the public to navigate. Last year, she was hired to help reform the nationās organ procurement and transplantation network, a public-private partnership that connects organ donors to patients in vital need of a transplant. The program had recently come under fire. As thousands of patients were dying on waitlists, some donor organs werenāt even being used. Multiple kidneys had to be thrown out because of transport delays ā couriers not picking them up in time or airlines misplacing them. One was accidentally left on an airport luggage trolley.
Amy Paris was hired to help modernize the nation's donor organ network, which ensures critically-ill people get the organs they need.
She was also let go.
"We had alignment from Democrats and Republicans on the Hill, we had funding, and they were hiring more of us.ā
