* Easy to Maintain (for a small team) -> 1. Astro, 2. Remix, 3. NextJS
* Self Hostable -> 1. Astro, 2. Remix, 3. NextJS
* Some interactivity and smooth transitions -> 1. Remix and NextJS, 3. Astro
From your description, it seems you are most familiar with NextJS. My question: How about the other maintainers? If everyone is familiar with NextJS, that is a big bonus point.
In conclusion, it comes down to how high you prioritize "Some interactivity and smooth transitions" and "Familiarity with the chosen framework." Astro, being a multi-page framework first and foremost, will not deliver the smooth transitions that the other two will. However, it shines on pretty much all your other requirements.
If you can live with Astro being a Multi-Page Framework that, by default, does a full-page reload for every route, and your team is comfortable using Astro, I would go with Astro. Otherwise, pick NextJS or Remix, whichever your team is more familiar with.
thank you, really appreciate it that helps me a lot! Currently I would be the only one starting this project and maintaining it. Everyone else is working on php and not transitioning to the forntend. I would be the one in charge to get new frontend devs on board so yeah. I worked with Nextjs a lot and also use Astro a lot for smaller projects
No, it’s because people approximate the costs badly. Pretty much everyone I know is biased towards inaction even if the action provides immediate as well as long term benefit. Especially when it comes to technology. Even the technology oriented people.
I am not sure how you can be so certain that it would be an immediate benefit to those users… how are you measuring the cost of having to learn something new and the benefit of knowing how everything works?
If we're talking purely about the average user it's perfect for them. They use a browser primarily, which work great.
The trouble is the slightly above average user who is not technical. They think they know computers because they can click around in some random Windows GUI and get something to work. But they don't actually know much in a general "how stuff works" way.
And then there's the highly technical like SWE who thrive under Linux.
So really it's just the weird middle ground that struggles. You know, your MBAs who can use Excel but get scared at plaintext files.
I didn’t say it’s stupid. Everyone’s assessment is inaccurate every once in a while. Or pretty much always, when it comes to certain biases.
You say “average user” and then point to a comment where someone’s disappointed that they can’t get their professional software to work. The average user these days needs a web browser, and doesn’t care which one.
You're claiming that the main reason most people don't switch to Linux is some sort of deficiency of judgment rather than anything practical, and that's not true and it's never been true.
You dismissed the costs of getting used to a new OS right off the bat, and that's a real thing. In my link that you dismissed, the first sentence ("while Windows is very hostile ... to its users, it's rarely broken or buggy") is relevant to most users. Professionals may have trouble getting their apps to work, gaming has gotten better but still has the same problem. If user literally only cares about running a web browser, then yeah, Linux would be fine; but Windows is already fine, so why bother switching?
I like Linux. I've used it at home and professionally. I'm a huge fan of FOSS principles, and I think it would be better for everyone if more people used open systems. But Windows works well enough to satisfy most people, and they're not going to change purely for ideological reasons. Maybe it'd be a better world if they did! But it's not reasonable to expect them to, or to cast that as a failure of judgment.
Devils Advocate: If there is no disruption in Taiwan, and TSMC continues to execute as it has, and Intel continues to execute as is has (not), then Intel might go to $0 or survive only because of government subsidies and military contracts.
NVIDIA, AMD, Apple and other companies seeking cutting edge performance will choose the most advanced node to stay competitive. Being the second best foundry has historically not been good business.
TSMC today has more than 60% of the foundry market share, and an estimated 80%+ market share for the leading edge.
If you exclude Intel themselves (although they also use TSMC now) and Samsung, TSMC is pretty much the sole supplier to the leading edge.
So, yes, TSMC has the capacity.
Your Boeing / Airbus analogy hinges on multiple factors. First, Airbus and Boeing have comparable capacity. Second, they have comparable products. Both are not true when you compare Intel and TSMC.
NVIDIA is heavily supply constrained. Why haven’t they sourced Intel or Samsung as second source?
Historically, there are also many other issues with Intel operating as foundry. Do you think NVIDIA and AMD will be happy to send their CPU and GPU designs to Intel for manufacturing? Independence was one of the main drivers why TSMC was founded. To have an independent supplier who does not compete with its customers.
It was a genuine question, I don’t follow the sector closely.
That said to poke at your answer a bit:
If nvidia is heavily supply constrained, wildly profitable, and strictly limited to TSMC doesn’t that dynamic lead to other customers being pushed aside? If so, doesn’t that open an opportunity for Intel if they can execute?
My take: Today, using AI for search-related problems is still not cost-effective for most use cases. That being said, the landscape is evolving quickly. First, in some areas, an individual search creates more value than in others. An individual consumer doing a Google Search is totally different from a lawyer searching for reference material. Areas where the individual search creates more value can already benefit from AI today. Second, LLMs become exponentially cheaper, driven by more cost-effective computing but also more cost-effective models. Look at the pricing of GPT4o-mini vs GPT4 (the original). The models are comparable in performance for many search-related problems, but the price has decreased by 200x in 1.5 years ($0.15 vs $30 per 1M token). If that price trend continues, more and more search use cases will benefit from AI.
I am not sure. While Intel still has a dominant market share in personal compute, it’s data center market share has been shrinking for years and Intel doesn’t have a convincing story why that would change.
The main issue I see for Intel is that they are trying to catch up in multiple areas at the same time against more specialized companies with more resources, and fend of new architectures like ARM.
Look at the segments:
- Foundry: TSMC is way ahead, has the right culture and is better capitalized. Even Samsung is ahead.
- CPU Architecture: Compete with AMD on the x86 side and with Apple, Google and the likes with ARM architectures.
- GPU: Compete against NVIDIA and AMD.
- AI/NPU: Compete with NVIDIA, AMD, Qualcomm,…
All those companies were smaller than Intel in the past, and Intel couldn’t keep their advantage. Now, those companies are ahead and in a better overall position.
Nothing is impossible but I can certainly see why investors are skeptical, especially given Intel‘s track record in the past few years.
Fundamentally, the pre-trained model would need to learn a "world model" to predict well in distinct domains. This should be possible not regarding compute requirements and the exact architecture.
After all, the physical world (down to the subatomic level) is governed by physical laws. Ilya Sutskever from OpenAI stated that next-token prediction might be enough to learn a world model (see [1]). That would imply that a model learns a "world model" indirectly, which is even more unrealistic than learning the world model directly through pre-training on time-series data.
But the data generating process could be literally anything. We are not constrained by physics in any real sense if we predicting financial markets or occurrences of a certain build error or termite behavior.
Sure, there are limits. Not everything is predictable, not even physics. But that is also not the point of such a model. The goal is to forecast across a broad range of use cases that do have underlying laws. Similar to LLM, they could also be fine-tuned.
1) Talent. The more engineers are familiar with Llama, PyTorch, and the likes, the easier it is to find ML talent for Meta.
2) Free research and innovation that Meta can readily copy for their needs.
3) They don’t really give up any power. They can always keep future models proprietary.
In my opinion, it is a bit like Microsoft’s “Embrace, Extend, Extinguish.” Make SW publicly available, extend it to your own business needs, and if a competitor emerges, the power is still with Meta to restrict its use or copy the use case (“extinguish”).
I think the time is not necessarily the issue. The issue is that everything is very manual and “analog” in Germany. You have to find a notary, register the “Gewerbe” at the Gewerbeamt, get a tax ID, and so forth. All are different processes with different institutions.
In theory, you can do the notarization online, but when I attempted to do it, the first notary did not even reply, and the second one told me: “The system is currently down. I would need to come to the office.”
In the US, you can just use Stripe Atlas or similar services, and get everything done for $500 in a nice digital interface within 2 or 3 days. But even if it took 2 weeks, it wouldn’t matter much because one doesn’t have to put time and energy into it whereas in Germany you have to contact people, coordinate, etc…
These kind of frictions are typically not an exception. When I read this blog post about the steps to just start a business, I immediately assume that there'll be similar frictions during other steps. And indeed, the comments here talk about the difficulty to own a home when the money was already paid in October, how it can take up to 2 years to close down a company, or how there's a 30% exit tax even if you leave the country only for a few years.
The friction that you seem to like has almost certainly cost Germany a good deal of jobs from people who decides that the hassle just wasn't worth it.
It is and it isn't. The IHK registration is a sham, since they're a government protected cartel that don't even act in the interests of those they're supposed to guard (like Azubis).
Hence, buy $GOOG.