https://www.imec-int.com/en

The game gets a bad rap for the last-gen console performance, but even 2020's iGPUs could handle it: https://youtu.be/oUm5GmJcBPA

- Lots of options competing on quality, price, user experience, user needs

- Every marketplace innovation that we talk about on this platform

So somebody might offer exactly that and if it's a good option, people will use it. If it's not, they'll use an alternative.

Government regulation will lead to:

- Giant entrenched companies that are difficult to disrupt thanks to insider connections

- Lack of competition, price increases, terrible customer service and pretty much everything that "anti-capitalists" today complain about in regards to capitalism.

Maybe we'll see a return to the late 1990's, when companies would give you a free computer as long as you allowed it to constantly display an ad banner on the top of the screen.

Would love to know where this comes from. I am not sure about that. Could you point to data/anecdata?

no one remembers the last time things got better rather than worse. shitcoin-driven scarcity seamlessly transitioned into COVID-driven scarcity and now into hyperscaler-driven scarcity. the chipmakers' cabal decided to meet increased demand with four digit margins rather than expanding production.

TSMC, plus flash and memory manufacturers with their own facilities, have dramatically cut production of almost anything that isn't in demand for AI, plus Macs were just about the only way to get more than 16GB of 'VRAM' without spending multiple thousands of dollars, so Mac Minis and Studios with more than about 24GB of ram have been under months-long backorders, which is unprecedented. Tim Apple made is name in supply chain logistics. Even he can't logistic his way out of this. Making things worse, the RAM that Macs use is really fast stuff, nearly the speed of high end desktop GPUs.

Supply for anything that isn't exactly what NVIDIA, Meta, OpenAI, Anthropic, and MS want has pretty much evaporated. And even that stuff has skyrocketed in cost because, essentially, the race has turned into who can hoard the most of TSMC's and NVIDIA's production capacity in a particular year.

The pathetic thing is that it isn't even actual purchases in some cases. In some cases, it's OpenAI or Anthropic merely "promising" they will buy X% of a memory manufacturer's capacity.

I can't wait for all of this to come crashing down.For all this hardware that is useless for anything else because of its density and power consumption - to absolutely crater in price and become e-waste.

Even when the cost of the cheapest computers bottomed out, it likely had more to do with lower prices not making sense. At a certain point, the cost of things that encapsulate the computer and I/O (like the enclosure and screen) end up overwhelming the cost of the actual compute.

This is capitalism, as demand increases, so does price, regardless of the cogs.

And then the opposite can happen like an unknown drone with 100 kg warhead striking memory production facility.

To be honest though, my usage does not benefit from the speed. The only benefit is to the reptile part of my brain that says “speed. Must have the fastest possible, and since I’m paying for it, even though maybe I should downgrade it, I want my speed.”

Wait for the product to be publicly available if you want in depth testing.

I feel like a big part of macos slowing down is installing too much crap over the years that sits in the background.

I'm usually running about ~4 instances of it locally in separate Git worktrees, which (in our setup) means I'm also running 4 copies of the whole stack: web, frontend, Redis, Postgres, etc. These are rebuilt and torn down multiple times per day. Lot of frontend assets to compile.

Additionally, like many people in corporate environments, we do of course also pay a performance tax thanks to the security software we need to run.

So perf does matter for us.

We could, of course, alternatively... just run cheap shitboxes locally and have all our dev environments in the cloud. Certainly appealing in many ways from a cost perspective and you don't even need to give up DX really.

However, in the next ~5 years, as "actually useful" local LLM inference starts to become genuinely useful (for software engineering, this seems to roughly mean "the ability to run 28B+ models at usable speeds") then having local compute horsepower might start to look more attractive again. Even if it's not an absolute winner on cost/utility alone, the data privacy and cost certainty have value to many.

It definitely matters, if you're intending to run a Claude Code/OpenCode style agent workflow. Most of those harnesses start with 8-12k token contexts, which is a lot of prefill for a Mac but cheap for a CUDA GPU. The GPGPU compute on the fastest Macs is still trailing behind Nvidia's laptop GPUs; the highest-bandwidth Apple Silicon chip (now the M5 Ultra) has ~7x lower memory bandwidth than a single B100 card.

There's a good reason why Apple Silicon isn't to be found anywhere in the datacenter buildout. It's nonviable for training, and wastes electricity running real-world inference workloads.

It is big. No dashboard. square steering wheel without turn signals or gear stalk. The rear-view mirror doesn't see out unless you lower the cover in the back. The side mirrors are strangely shaped and small. The front corners are a mysterious mostly unpredictable distance out the front window.

But then... It has cameras in all directions including the front bumper. There is a top-down sort of heat-map display when you park. All 4 wheels can be turned for a tighter turning circle. and it can self-park.

So... I would feel embarrassed to be seen in it, but it was definitely an interesting experience.