This comment is untethered from reality. Apple Silicon at present beats every single laptop on the market at CPU-bound workloads using a fraction of the power draw. Exceptions exist but usually those cases are break even or close calls.
It trails GPU workflows on the high end but wins on the low end. It still wins on efficiency.
It falls over on storage and RAM prices (well, for about 6 months it was competitive here).
I say this as someone who over the last year has done the majority of my competition on PC hardware running Linux.
You may be looking at this as a status game but it has clouded your vision. It is implausible that mass market products with mass adoption find their success solely on status. If believing that makes you feel superior, well, enjoy the rush.
> Apple Silicon at present beats every single laptop on the market at CPU-bound workloads
[citation needed]
> It is implausible that mass market products with mass adoption find their success solely on status.
People still pay a massive premium for blood diamonds over physically indistinguishable lab diamonds. You underestimate how wildly irrational the market is when it comes to status perception.
If you want a macbook, go for it. I wouldn’t presume to know your needs more than you. I want something that I can easily run OpenBSD on and is amd64. And none of the apple laptop fits the bill.
I don't own or want anything apple. But I want no fan and maximum possible power/battery life. So I am really looking, but they do seem to offer the best hardware.
compare this to the top of the line Intel Panther Lake chips, which have comparable battery life. I cherry picked a 16" Dell XPS machine, which has the best thermal headroom, for its best score: https://browser.geekbench.com/v6/cpu/18390748
Single core: ~2,900
Multicore (16-cores): 16,900
Geekbench is bursty, so we can look at more sustained test, Cinebench 2024:
"Despite the XPS 16's discrete Nvidia RTX 4070 laptop GPU, the MacBook Pro M4 Pro's unified memory architecture outpaced the Dell in 4K video export and machine learning inference benchmarks by 22 percent on average."
For GPU, this is not comprehensive. It depends heavily on whether it needs raw grunt, where Nvidia discrete chips will win. When the processes uses the NPUs on Apple's chips, it will often win. They trade blows.
Efficiency I think is close to a wash on the latest machine, but before Panther Lake, Apple's win handily. My Framework 13 on AMD would last me about 2 hours doing regular work; my Macbook Pro doing the same workload would last over 10 hours. Thank goodness Intel caught up here.
I do scientific computing where Apple has some disadvantages. Matrix math heavy things lose out to discrete GPUs, as do -- I'm told -- things depending on 512-bit extensions (e.g., AVX).
Until last week, prices on Framework/Dell vs. Apple were similar. I think Apple is probably 10-20% expesnive at this point, but adjusting for performance, Apple still comes out ahead.
Apple's displays used to have a huge advantage. Now that you can get OLED displays on performant, efficient Panther Lake machines, this is far less of an Apple advantage.
The upshot is that the new Panther Lake machines caught up considerably to Apple, but they're still about 20-30% slower (sometimes more) in most workloads, and IMO the build quality is still not quite as good. I think many of them actually have better displays. Battery life is comparable on better equipped PCs. IMO once you can work an entire day and a little more unplugged, you're good to go.
It's not hard to find this data and evaluate it objectively.
For me, the fact he tried to compel the WPE CEO to work for him or else he would expose that she was in negotiations with him is the most unhinged thing I’ve ever heard in a hiring process. Quite literally an affront to freedom.
My most charitable guess at what is going on is severe mental illness.
It did all seem to blow up around when he came back from a sabbatical, presumably taken because he really needed a break. Though I guess that he also had a bit of a PR disaster with Tumblr during that sabbatical, so...
I think a lot of this whole saga is easier to understand if you just remember that WordPress is a major open source project and a company, so you get to see a lot of the stuff every company --- almost none of whom run major open source projects --- does in the ordinary course of business.
Anyways, if you thought there was any freedom or purity to the tech job market, bad news for you.
> Anyways, if you thought there was any freedom or purity to the tech job market, bad news for you.
Ahh, "everyone else does it" - no, have never been threatened that if I refuse a job offer, or otherwise decline, that my current employer will be told all about how disloyal I was to them.
Hey, to be clear, I'm not sticking up for it, I'm just saying: commentary about this whole saga sometimes feels like people have lost some perspective, and are holding WordPress to a standard that pure commercial companies aren't held to. Hiring is ruthless! Executive hiring in particular!
Good thing (glass half full) about clicky-baity version, it forces facebook to take action, because it directly associates their brand with the problem.
For what it’s worth, in most cases, an organization that overly focuses on process is superior to one with a naive individualism that throws employees under the bus by default.
If you took the "no it won't" side of every argument about "how in X number of years, AI is sure to Y", you'd be way ahead.
In any event, raw parameter/weight count to me seems like a very primitive way to judge "complexity" in comparison to the human brain. Looked at most ways, our brains are for more efficient at doing the incredible things they do than LLMs. Consider how little language young children are exposed to in comparison to LLMs given their abilities to figure out how to produce language.
If the brain doesn't work like an LLM, you can expand the size and "complexity" of these models to the moon and they won't outperform the brain. Current models can write impressively well, but they can barely do math. It's clear they don't reason as we do.
Training on ai-generated data isn't a problem, and has been routinely done by everyone for 18 mo +.
The issue is training on 'indiscriminate' ai-generated data. This just leads to more and more degenerate results. No one is doing this however, there is always some kind of filtering to select which generated data to use for training.
So the finding of that paper are entirely not surprising, and frankly, intuitive and already well known.
I would disagree. I work in healthcare and we’ve always used SQL Server. While I wouldn’t pick it, it’s been reliable and integrates with auth.
No one “loves” Teams, but honestly it serves its purpose for us at no cost.
No one loves OneDrive but it works.
I think people underestimate how much work it would take to integrate services, train people, and meet compliance requirements when using a handful of the best in class products instead of MS Suite.
People use Teams and OneDrive because it’s “Free” when you use Office. IMO, that’s a bit of an anti-trust problem. Both have good competitors (arguably better competitors) that are getting squeezed because of the monopoly pricing with Office.
But with SQL Server, on the other hand, I think you are right. It is a good piece of software. But it also has high quality competition from multiple vendors. Some of it enterprise (Oracle, DB2), some of it FOSS (Postgres, MySQL). Because of this, it has to be better quality to survive… they couldn’t bundle it to get market share, it actually had to compete.
People use Teams because it's well integrated into Office, 365, Entra and other MS products, they would (and recently do) pay for it. It has functionalities that no other alternative has, e.g. it can act as a full call centre solution through a SIP gateway.
Yeah, sure. But the marginal cost is zero, whereas a Slack subscription for every person in our org will cost about 1 million dollars a year. And it doesn’t integrate as well with every other piece of functional but mediocre software.
The person approving the $1 million dollar budget item doesn’t really care that Teams isn’t “free” in the sense that there is no free lunch, and while they perhaps have moral qualms of antitrust, that’s outside their purview. We’re locked into Office suite and right now there is no extra charge for Teams.
My experience with DataSpell has not been great. Granted, my workflow leans toward R, and it DataSpell has a Python-first approach, but the app was basically completely broken to even load R, and StackOverflow was full of relatively old posts of people with the same problem. If they really cared about that app that would never happen.
I just do a lot of my R editing in PyCharm now and flip between terminals and RStudio. I was hoping DataSpell could unify that, but it's not ready.
