Super interesting, when Quantum computing would enable really large models, or much larger contexts. But QRAM is even more behind than pure fault-tolerant gates.
I also don't like this focus on practical applications. It is true for me as an engineer, that in the end I want to build something. But when I force myself to focus only on the practical part, just as you said, the whole context is missing. There is this meme of a guy still living with his parents, and trying to acquire all knowledge. This is actually a dangerous mind virus. Learning is an idle activity, often confused with being a do no good. But for me at least this is the only way to really grok something. In university at the summer break, I could only really go through the math and enjoy it, without the stress of exams and cramming. And now it is the same, I learn things idly, and trust in the universe that the application will come, which it always does somehow.
With how apple seemed to be caught by surprise when it came to Macbook Neo demand, I'm not sure they have the quantities of SoC's around to handle the demand a Mini Neo could drive. Especially if they could do it for $299.
I will go out on a limb and say that's not going to be an Apple product, period. It doesn't fit anywhere in the value envelope.
The relevant questions here are: will the person using this machine also conceivably be wearing a pair of $549 AirPod Max? Or a $399 base Apple Watch? Does that person expect to pay more or less for their largest-screen computing device than their headphones?
Framing that way points toward a $350 price point being a laptop for young children (younger than Apple Watch age, so lower elementary). That's a whole different software experience beyond just the hardware.
A Pi running macOS more or less. Not dissing it though. Killer machine for those who don’t need a lot of power locally. Also a great kiosk for some things.
> Is it a lack of knowledge from the users or do they really value iMessage integration that much?
My understanding is that the barrier to entry to using iMessage makes iMessage a LOT more secure from spam. If you want to do mass iMessages you have to register as a business with Apple, go through all sorts of checks and attestations, etc.
At any rate, iMessages are a lot more trustworthy than SMS. So being able to spam people via iMessage is very desirable. I recall a few months ago a guy posting his little spam-iMessage-as-a-Service product here on HN. You could build your little iMessage spam army using a bunch of Mac Minis...
It's anecdotal but the kind of people I know that bought Mac Minis for this purpose are what I'd call "light techies." They definitely know how to use an iPhone or a Mac but would struggle on the CLI of a Linux box.
Anyone who wanted the OpenClaw use case that is comfortable with Linux probably already has several Linux machines (including a few Raspberry Pis) on-hand.
It is a bit like in "Profession" by Isaac Asimov. We will still have the need for some people who will write code manually, fix the craft. We will need the "Feeble Minded" asylum that is actually a secret sanctuary for society's true creators. Because everyone else relies on generated code, they can only repeat what is already known. Only the people who learn the hard way through actual studying possess the creativity and intelligence required to invent new knowledge and create new educational tapes.
The reason LLMs seem powerful is that they can churn out the Nth variation of a CRUD app in minutes. But it’s hard to imagine they’ll ever independently develop a compiler for a truly novel programming language, for instance. They don’t have creativity. They are pattern generators.
> it’s hard to imagine they’ll ever independently develop a compiler for a truly novel programming language
I did exactly that using an LLM. It may not count as independent depending on how strict you are about that, but then LLMs don't do anything independently.
I wrote a small sample program and expected output, then told the LLM to write a compiler for it in C using LLVM. I subsequently told it to extend the language until it could be used for its own compiler, and rewrite the compiler in the new language. It did.
I don't think that contradicts your point about creativity. A compiler is probably a more mechanical task than a CRUD app is. There's a non-negotiable definition of done and correct.
Designing a language is a creative task of course, and I wouldn't expect an LLM to come up with a novel or ergonomic design on its own. In fact subsequent experiments have shown me that LLMs will consistently ignore terrible ergonomics in a language, never seeking opportunities to add abstraction or beauty.
Being serious. "Think about what this might mean..." Finding unexpected links between various ideas and background knowledge. What we call a "novel idea" is virtually always the repurposing of an idea/concept in a new context. A system that maps arbitrary inputs into abstraction spaces in which similarities are discoverable, such as say a deep learning system, is perfect for this.
At the time the LLM generated the compiler, just syntax. The semantics it generated were the subset of C that the C version of the compiler already used.
You could set the goalposts such that it wasn't novel enough to count, but for a short time I had code running in a language that nobody had ever known. Getting it from that point to a language that's ergonomic to use, teaches something about computing, or both is a longer journey, and certainly not one an LLM could take on its own.
An LLM won't come up with an interesting CRUD app on its own either. Parts of that process are pretty mechanical, but we had skeletons and templates before we had LLMs.
I'd say that even if the task is "a compiler for an existing language" the empirical results are far from stellar, and indeed, border the terrain of comedy.
Claude has made my Ruby compiler pass 8k more rubyspecs tests over the last two weeks, and that includes solving crashing bugs in hours that I'd failed to fix for weeks in the past.
Compilers for existing languages is if anything one of the lower bars for LLMs, given existing implementations or test suites provides an oracle to test against.
It's not lack of ability that is stopping this, but that it's a space where very few people are experimenting and willing to burn enough tokens.
Isn't "creativity" the result of a combination of patterns (usually from different contexts) that casually works? I bet LLMs/agents can do that (we can't know how far that can goes).
For me that creativity is very well expressed by the principle of abduction. With induction, generalise towards rules, or deduction, use rules on data, we have this combination of patterns via different contexts. I think abduction might not be possible via LLMs.
that's why I still love the quest3, just for the potential. but xreal makes more sense, and then a more open platform. but I think post-covid we approach neuromancer more than ever.
You could look at only two niche blockchains, QRL and ABEL, and they are both affected. Algorand is the most established L1 with a quite developed migration plan (https://algorand.co/technology/post-quantum) but also not really thriving. I think for Bitcoin in the longterm it is a massive risk psychologically, because what to do with all of the locked in value, that cannot be migrated. My guess is that the market panics and security breaks down, because it is not worth it anymore to run that many nodes. Best time to buy would be then and hope it recovers. It is actually a big chance to move just to another L1 which migrates. Those risks are all priced in.
I feel like Qiskit is the standard nowadays, and maybe because of the early mover advantage it will prevail after NISQ (Noisy Intermediate-Scale Quantum). It's actually just a Python framework.
there's actually a really good book that bridged it well for me when I was doing my bachelors, A Little Java, A Few Patterns. this is from the famous lisp books for groking FP.
