While I understand both of your perspectives, please think about how frustrating it can be to have poured years into building a product genuinely solving a problem and building a relationship with clients only for a dozens AI copy cats to come in. Even if your product is clearly better, the SEO slop alone will raise your marketing cost, price cutting will affect you as not all clients are able to tell quality before purchase or will know of your project, etc.
And in the end, everyone is worse of. We get less for the products we build. Customers in many cases get a worse solution. And the AI copy cats multiply until none of them can make a living from it.
That's roughly 11.66$ per hour per GPU, which is above the price that Google Cloud is reselling them at if you commit for 36 months: https://getdeploying.com/gpus/nvidia-b200
There are definitely more shades of grey. On my iPhone I can select a close contact to be able to overturn my protection but this contact needs to have security features turned on, too. So Apple staff cannot do it, only a non publicly known person that has 2FA and encryption themselves. Add time delays, notifications, identity checks and more to it and you can make this process reasonably secure while still ensuring recovery.
As explained in another comment, I think this is more about Google orienting Flash towards more complex use cases. If we got minor improvements vs 3 Flash with 1.5x the price so they can optimize their margin (which on such small models for conversational tasks is a completely different stories than the 3-25x subsidies that these agentic coding plans offer) I would have been happy. Or even no change at all. But knowing Google, I now must fear that they will deprecate 3 Flash without offering any realistic option for that user facing chatbot segment that does not require multi-tool use across 500k context.
When using Hetzner, DigitalOcean or any other VPS service together with Cloudflare, I can handle millions of page views for 5-50$ a month at pricing that has stayed nominally the same for a long time and due to inflation and performance gains of the underlying chips has basically become cheaper.
I am aware that it was likely subsidized or at least did not have appropriate margins. But over time, that same capability should become profitable if parameter efficiency and chips improve. For many customer facing use cases outside of coding assistants, optimizing for speed, basic logic/maths and conversational texts matters much more than being able to use 40 tools simultaneously. I would have hoped that Google would recognize this and keep a dual line up, where Pro and Flash are clearly intended for different market segments. But it seems, it's all in on coding assistants and screw the other use cases..
Now, we might need to change to DeepSeek 4 Flash if Google deprecates 3 Flash.
It's discouraging to see Google price Gemini 3.5 Flash at 3x the cost of Gemini 3 Flash. I would think that most people that deployed this model in production would have used it for low latency tasks, classification/categorization, customer support or basic RAG-/RAG-style chatbots. Performance on coding benchmarks is nice and all, but where is the "intelligence too cheap to measure"? This new cost point is quite prohibitive and will eat up a lot of margins if developers adopt it.
I mean, the 100$ plan is less than the hourly rate of any consultant / senior dev in developed countries. So if it can save even one hour a month, it's cost efficient for the customer (at the current, subsidized rates, of course).
I came here to say something similar. As someone who works in a field that applies machine learning but is not purely focused on it, I interact with people who think that arXiv is the only relevant platform and that they don't need to submit their work to any journal, as well as people who still think that preprints don't count at all and that data isn't published until it's printed in an academic journal. It can feel like a clash of worlds.
I think both sides could learn from the other. In the case of ML, I understand the desire to move fast and that average time to publication of 250-300 days in some of the top-tier journals can feel like an unnecessary burden. But having been on both sides of peer review, there is value to the system and it has made for better work.
Not doing any of it follows the same spirit as not benchmarking your approach against more than maybe one alternative and that already as an after-thought. Or benchmaxxing but not exploring the actual real-world consequences, time and cost trade offs, etc.
Now, is academic publishing perfect? Of course not, very very far from it. It desperately needs to be reformed to keep it economically accessible, time efficient for both authors, editors and peer reviewers and to prevent the "hot topic of the day" from dominating journals and making sure that peer review aligns with the needs of the community and actually improves the quality of the work, rather than having "malicious peer review" to get some citations or pet peeves in.
Given the power that the ML field holds and the interesting experiments with open review, I would wish for the field to engage more with the scientific system at large and perhaps try to drive reforms and improve it, rather than completely abandoning it and treating a PDF hosting service as a journal (ofc, preprints would still be desirable and are important, but they can not carry the entire field alone).
There are ways to independently fund open source projects, though. I have previously contributed to the Python Software Foundation and to individual open source maintainers through GitHub donations (which are not dependent on GitHub, as there are many alternatives). Projects like the Linux Foundation exist, too. And government funding, especially for scientific endeavors or where software is used to fulfill critical state tasks, is an option, too. I refuse to subject to the hypercommercialization of software and still believe in the principles behind open source.
This might be true for uv and ruff, and hopefully that will happen. But pyx is a platform with associated hosting and if successful would lock people into the Astral ecosystem, even if the code itself was open source.
They could have joined projects like the Linux Foundation which try to not depend on any single donor, even though complete independence from big tech is not possible. I don't know the motivation behind Astral's approach, but this acquisition does leave a weird taste behind about how serious they were about truly open source software. Time will tell, I guess. (Edit: typo)
This is a serious risk for the open source ecosystem and particularly the scientific ecosystem that over the last years has adopted many of these technologies. Having their future depend on a cap-ex heavy company that is currently (based on reporting) spending approx. 2.5 dollars to make a dollar of revenue and must have hypergrowth in the next years or perish is less than ideal. This should discourage anybody doing serious work to adopt more of the upcoming Astral technologies like ty and pyx. Hopefully, ruff and uv are large enough to be forked should (when) the time comes.
This did happen in summer of 2022, but only in public buildings, private households were not affected, so the OP's point seems a bit overly dramatic. Given that AC usage is highest when solar production is also highest, this seems highly unlikely given the solar build-out of the last 4 years.
A 2 person startup cannot provide a dedicated developer for your account, a personal contact for each of their thousand customers, is at high risk of being acquired/changing their business model/founders abandoning it, etc.
For enterprise, long-term stability and personal contact matters more than price. A typical SaaS contract is 0.x% of yearly revenue of big corps and nobody wants to be the one person risking the business for such miniscule savings. Another often overlooked part: Employees are the biggest cost center, much larger than any contract. So retraining a single team of 10 employees can often be more expensive and more disruptive to the business than just sticking with a legacy provider and established processes.
I agree. The notary process is a bit annoying, but it only costs 500-1,000 euros. Yes, that's not ideal, but if you're building a proper business, that shouldn't be an issue. You can typically get an appointment within a week, no matter where you are or where your company is registered. However, once the notary sends your documents off, it can take days or weeks for the registry courts to handle them. You have to register with ten other places yourselves, and there's no guidance. There are different forms and requirements, and the yearly costs just for a basic tax declaration are in the thousands. They can be 5-10% of early startup expenses for no good reason.
There are also some shady setups, such as a private company handling the company registry for the state. You have to pay this company each year to publish your books. Accessing that data still costs money, except for the largest companies. It doesn't help with transparency, but it is a public-private rent-seeking nightmare that (possibly) arose due to conflicts of interest among certain politicians (the company's CEO has a higher-level position in political party) and lobbying.
As someone working in bioinformatics, to me it makes sense. Arguably their lead is not in “development” but agentic tool use more broadly. Opus does not have the most up-to-date knowledge despite its training cut-off in my testing, but excels at complex multi-tool calling. The life sciences have a ton of structured data, knowledgebases and some of the most complex use cases for running specialized software, fetching data from dozens of sourcing and contrasting and remixing it. So it fits agentic applications very naturally. Notably, Anthropic is not going into consumer health like OpenAI but rather pitching itself to all the big pharma companies (already partnering with some of them, including Novo).
Definitely not written by AI. Perhaps it just seems strange to you because English is not my native language so my use of it might not fully correspond to what you are used to.
Sending an automated thank you note also shows disdain for the recipient's time due to the asymmetry of the interaction. The sender clearly sees the thank you note sending as a task not worthy of their time and thus hands it off to a machine, but expects the recipient to read it themselves. This inherently ranks the importance of their respective time and effort.
S&P 500 P/E is 30 and historically used to be much lower. Some of it can be surely attributed to increasing inequality and increased wealth of the hyperwealthy who have no other option than to store their money in stocks absent a hypergrowth market, even at lower expected profit. But "growth" can only so long serve as an argument to justify a 40-50 P/E vs. a 25-30 as in other parts of the stock market. If that growth stalls, there is a lot of room to fall, even if the companies will still be profitable and won't go under. Ed at no point claims that Nvidia, Microsoft or Google would cease to exist as companies, as they can of course be very profitable in smaller markets than those that are currently being priced in and without AI contributing to revenue. But companies that purely rely on AI for revenue will have a hard time to ever turn a profit and there is not a single example to proof otherwise. And if that happens, you might also see -20%, -30% or more on some of these larger players that will survive.
I assume you are unfamiliar with how pensions in Denmark work. While there is an unfunded social security part that is paid for through taxes, >90% of Danish workers have "occupational pension plans" that they contribute about 15% of their salary to. By the time they retire, they have saved on average 2 million DKK [https://www.dst.dk/en/Statistik/emner/arbejde-og-indkomst/fo...], so about 300,000 USD. At that time, life expectancy is about 20 years, so that is about 15,000 USD per year from individual capital-backed schemes alone. For the 60% of Danes that are home owners, this alone could probably cover all basic living expenses outside of very HCOL areas.
In that way, Denmark already strikes a good balance between purely tax-based schemes (that you are probably referring to as "Ponzi") and socially detrimental schemes like a pure Austrian backpack approach (which would leave people that cannot work in deep poverty).
While some critical journalism may be simplistic, I would not qualify it as lazy. Much of it is deeply nuanced and detail-oriented. To me, lazy would be publications regurgitating the statements of CEOs and company PR people who have a vested interest in making their product seem appealing. Since most of the hype is based on perceived futures, benchmarks, or the automation of the easier half of code development, I consider the simplistic voices asking "Where is the money?" to be important because most people seem to neglect the fundamental business aspects of this sector.
I am someone who works professionally in ML (though not LLM development itself) and deploys multiple RAG- and MCP-powered LLM apps in side businesses. I code with Copilot, Gemini, and Claude and read and listen to most AI-industry outputs, be they company events, papers, articles, MSM reports, the Dwarkesh podcast, MLST, etc. While I acknowledge some value, having closely followed the field and extensively used LLMs, I find the company's projections and visions deeply unconvincing and cannot identify the trillion-dollar value.
While I never bet for money and don't think everything has to be transactional or competitive, I would bet on defining terms and recognizing if I'm wrong. What do you mean by taking the positive side? Do you think OpenAI's revenue projections are realistic and will be achieved or surpassed by competing in the open market (i.e., excluding purely political capture)?
Betting on the survival of the legal entity would likely not be the right endpoint because OpenAI could likely be profitable with a small team if it restricted itself to serving only GPT 4.1 mini and did not develop anything new. They could also be acquired by companies with deeper pockets that have alternative revenue streams.
But I am highly convinced that OpenAI will not have a revenue of > 100 billion by 2029 while being profitable [1] and willing to take my chances.
If you read any work from Ed Zitron [1], they likely cannot remain sustainable. With OpenAI failing to convert into a for-profit, Microsoft being more interested in being a multi-modal provider and competing openly with OpenAI (e.g., open-sourcing Copilot vs. Windsurf, GitHub Agent with Claude as the standard vs. Codex) and Google having their own SOTA models and not relying on their stake in Anthropic, tarrifs complicating Stargate, explosion in capital expenditure and compute, etc., I would not be surprised to see OpenAI and Anthropic go under in the next years.
I had that same intial reaction but I think it makes sense if you think of it in terms of software development. There are many different MCP clients being developed that are just that - clients. They don't take care of hosting the LLM or any other functionality of the application but are meant to be plugged into existing applications to enable MCP support. So from that perspective, the difference is useful, as it refers to code developed by different people.
Yes, there are ways to buy up existing “empty” companies with a bank account, commercial registration, etc.
If you want to found a new one, there are also services that will prepare all paperwork and set up appointments with notaries, etc. for you for affordable prices
Day to day operations do generally not require much else than bookkeeping and accounting which you can almost fully outsource (though accountant fees are not cheap, however, doing it yourself is also not to hard if you have the right software and do not sell thousands of different products) unless you are in specific industries
There are a few unnecessary fees and it takes longer than it should to get started but for most businesses it does not really matter and is limited in scope when it comes to time and money needed
Maybe because that position is both scientifically and morally unsound and if held strongly will lead to dehumanization and hate, attributes we should prevent any LLM from having.
I truly feel like the focus on PPR, streaming, etc. is forcing most developers to jump through unnecessary hoops and relearn the basics of Next.js every couple of months. Imo, the interceptors idea is just more evidence for that. On the surface, Next.js may try to keep all parts independent and allow PPR, streaming, static and dynamic living right next to each other, etc. but at what cost? Losing the request and the response object makes life unnecessarily harder. Artificially limiting certain pages to run in an "edge environment" is non-sensical when hosting Next.js on Node.js in the same data center as your database. And personally, I do not trust Next.js anymore with new "special" files and features. head.tsx was deprecated before our migration was even complete. Route interception with parallel routes is deeply broken to this day with hundreds of non-obvious caveats of how they can be used. Server actions are an anti-pattern, since they tie all manipulations to Next.js and make it impossible to use your data manipulation endpoints across multiple applications. Meanwhile, using REST-APIs with Next.js is incredibly challenging thanks to the client side cache and is not fully solved by router.refresh, tag invalidation or stale time.
I believe that there are many like me who would just want to use a simple server-side rendering solution with the route-based layout structure of the app directory, which was a great improvement. Please just allow users to render everything at once and synchroneously in Next.js, expose the request and response at every point and allow database access from any point. I would be very happy to trade 2ms of time and lose PPR, etc. if that meant that I could build features for my customers faster. The introduction of the app directory had me exited and I moved the first project on the day it was announced, but recently I find myself fighting the framework rather than it supporting what I need to do.
Another example of Next.js completely breaking existing code seemingly for no reason was suddenly disallowing exporting functions from page.tsx files. It worked before, so there should not be any inherent reason that it could not work anymore. Now, if I want to reuse a getData method in two pages or a page and a layout, I have to create an additional getData.ts file. Is this was the Next.js team wants users to do? Perhaps. Should they force them to do this? Absolutely not, we are all adults and requiring millions of devs to refactor their code because something could not be figured out internally or they suddenly deemed some usage unacceptable is ridiculous and user hostile.
For each individual perhaps not, but there is a right to healthcare and out of this arises the need for physicians. And I for one would like the talent of the candidates to be the deciding factor, not their or in most cases their parents’ bank accounts. I’m a physician myself with an upper middle class background but if I lived in the U.S. I most probably wouldn’t be because of how cost prohibitive med school is over there. And this leads to all kinds of downstream effects like exorbitant physician later salaries on that render healthcare unaffordable for many and are detrimental to society.