Apple was also allegedly "caught off guard" by the Macbook Neo demand.
I don't really see how they couldn't see the Local AI demand or demand for a cheaper Macbooks. This just reads like marketing imo.
I don't really see how they couldn't see the Local AI demand or demand for a cheaper Macbooks. This just reads like marketing imo.
Even though you saw this coming 4 months before the launch, at the launch time itself you're still caught off guard. Demand is still dramatically higher than your capacity to meet it, and that's still going to be true for at least another few months, and there is nothing you can do about that. What you can do, you did 4 months ago to increase parts orders, but you're still caught flat footed right now.
Under Apple's reality distortion you instead must say that they were surprised by the demand.
Projecting much?
The main place they are a bit behind is in the number formats they support natively. Iirc M5 doesn't have native FP8 support, so you will take a speed penalty on quants where other architectures get better acceleration.
Macs don’t have very good prefill, though. So it’s important to use a model serving stack that has excellent prompt caching and use a harness that won’t bust the cache.
I’m cross-shopping DGX Sparks and M5 Studios, and having a hard time deciding because they have exactly opposite characteristics for prefill and decode.
this article's also about enterprise demand specifically. That's a bit surprising to me as well frankly. I'd have thought the primary market for mac studios would be hobbyists/enthusiasts with a bunch of disposable income who are willing to pay 18k for a 512 gb machine to run glm 3.5 flash or 9k to run deepseek v4 flash locally. It's competing with a $200/mo subscription or renting server gpu time for open source models during a memory shortage - and idk if it's going to be powerful enough to train or fine tune so it's really just inference. seems reasonable to be surprised
A big enterprise can drop one (or 4) of these on someone's desk and let them go nuts.
The target audience didn't evaluate that as a limitation - the majority of the market for Apple devices does trust that they will not produce and sell a computer incapable of support their use.
Professionals know there are tasks that a baseline computer cannot handle, and even common tasks that a more powerful computer does better, but those people weren't really the target demo for the laptop.
Well, kinda the point. We know this to be fully true in retrospect (and many people correctly predicted it) but decent arguments existed against it at time of release.
the problem with that argument is that the vision pro exists, where they clearly overestimated demand, and where even among people with interest in VR and disposable income, the compromises on battery life and weight were actually too much to bear. Forecasting is just hard and you always need to be especially skeptical when you yourself are doing the forecasting for something you want to succeed. All those arguments for the neo line up in retrospect hindsight is always 2020
I’d be willing to pay more to own vs subscribe, but the gap is currently far too large where buying a Mac Studio for AI is a straight up terrible investment.
My biggest problem with buying a Mac Studio is that even in the case of the M5 Max models, I can’t think of any non-AI macOS applications in my creative life that have anywhere near that level of hardware requirements, and nor can I forecast that I would within its ordinary supported lifespan as a macOS machine. These machines left high-end stills and most video work behind generations ago, for example.
So while I would like a local machine that I can leave running in a way that I wouldn’t want to do with my old secondhand M1 Max laptop, it’s going to have to be something a little more pragmatic. Probably based around the Radeon R9700, since the AMD/Nvidia gap for LLMs is beginning to close, and even a single R9700 runs the main models I am interested in at speeds that are acceptably faster than what I have here.
At the moment, speccing out a local box more powerful than the machine I am using is largely an intellectual exercise, but it does have some value for understanding what a client might be able to use if they absolutely require on-premises inference, and I do have a couple who fall into that zone. So I am trying to keep up to date in principle, but the built machines don't get beyond the shopping cart.
The M5 Ultra has probably smoothed out the major issues of AI on Apple Silicon (prefill doesn't suck anymore) but the way Apple marketed that chip strongly suggests they are now fully aware of the strengths but also the limitations of their architecture and will get a lot more done.
It's properly put the (fairly equivalently priced) DGX Spark in the shade, though.
Not if you're an enterprise that wants or requires on-prem inference.
i come from a ultrabook with 2 gigs of ram and the neo takes 2 vscode instances, one antigravity and firefox while keeping telegram and whatsapp on the background. that device can be used as a workhorse, pagination is very good.
can even run ios/android emulators but then you have to only have that project open, which is a non-issue for me. and the battery literally keeps working all day. good screen, good keyboard, good touchpad, operative system is close to linux. if youre thinking about getting one for programming and you're scared about the 8 gigs, hope i gave someone some light about it.
Basically you can have your own 24/7 AI Employee. At-least thats the appeal and folks were buying mac minis massively.
Just my gut feel. Everybody moved on from that now. But it was a big deal back then.
Now, I use claude code directly on my machine with the remote control flag.. so its like open claw exactly. I can be outside and give commands to it via mobile app
then Control + Command + Q ftw
(keep system from sleeping if plugged in, keep system from going idle even if not plugged in, for 2 hours, start claude code w/ remote control enabled, lock my mac w/ the keyboard shutcut)
It's quite expensive from a value per token perspective. It's quite cheap from a "send one message from my phone and it does something probably productive" perspective. No major security breaches yet.
AI for developing software that runs predictably seems more useful than AI performing actions like a program would.
I think AI is an incredible competence magnifier. If someone knows what they are doing that competence can get magnified massively. If they do not know what they are doing, that gets magnified just as much. The tricky part is getting people with a low level but real degree of competence, which is all of us when we're starting out, to learn how to reliably magnify that.
It was able to create an application that Claude created, using the same instructions file. Considerably slower but I was surprised it could do it.
You could be right, but I don't see being caught off guard as the kind of praise you seem to think it fosters for Apple. If I were in marketing I would be looking for a message that showed Apple in more of a leading, not following, position.
The way you get people to believe a lie is to put just a bit of truth in it. The way you get people to accept marketing as not-marketing is to put just enough not-marketing in it.
The first time around they almost went broke because people no longer were paying Apple tax, and they did not had any other product to save them.
Nowadays they have the iPhone piggy bank.
We don't know if Apple misjudged the demand or couldn't source enough parts to match the initial demand. Another explanation could be that they decided it wasn't worth it to increase the production capacity to match the higher demand at launch because that capacity would go unused later down the line.