I and not necessarily many, but at least some people I know donate (and, somewhat irregularly, will continue to do so) small-ish amounts to the foundation. [1]
You’d imagine that ought to be sufficient to cover running costs. However, it might actually not be enough with hardware prices these days? Not sure.
They’ve also recently (edit: “recently-ish”, it’s actually been a year!) introduced paid storage for backups, which I’d imagine comes with some amount of profit margin, too. [2]
Also, just imagine being the group at Apple responsible for designing this section of the chip, starting probably almost a decade back – under the constant uncertainty of not knowing what direction ML workloads would develop in…
> ML research was a rather known quantity, or the separate "Neural Engine" CPU explicitly aimed at existing ML pipelines wouldn't exist.
No, not really. Transformers were just one of the possible directions. Silicon design does not have the same time scale than software. Now, everyone is using transformers so it becomes harder to do anything else, and it’s been the case long enough that hardware had some time to align (but is still lagging). But who’s to say that a different architecture published last year won’t take the world by storm 2 years from now?
It’s easy to say it in hindsight, but transformers took a bit of effort to get where they are now.
> Silicon design does not have the same time scale than software.
"Neural Engine" has been a part of iPhones since 2017. So, in development since at least 2013, possibly earlier. And it targeted the rather well established, known, and widely used ML practices.
GPT-like models didn't become even remotely useful until at least 5 years later.
I'm all for compassion, but engineers knew the NE was empty when it sat idle for 10 years on our computers.
- when you're given no usecase for your engineering piece, apart from "detour characters in pictures". It's an exageration but AI's contributions in iOS aren't visible; Meanwhile Google has features that people actually notice like removing tourists from your holidays photos — worse: it's mostly a simple collage feature working on the main CPU, and it has the same social effect as green bubbles in iMessage ("ah. Tourists on your photos. iPhone user?")
- and you tout it as "16 Neural Engine cores" during the sales, with no associated software, no listed material feature, just hand-waving,
- Siri maxxes out at "There is no contact named 'What's the weather today' in your agenda",
Then can't really claim that Apple engineers' problem was really the bad luck that ML wasn't the determining part of the future. It's more like misreading the room for 5 to 10 years straight.
Apple engineering's excellence on vertical integration and supply chain control gave them absolute power over our world (with merit), it just failed at that particular project. Which occupies 40% of our CPUs.
> an exageration but AI's contributions in iOS aren't visible
If you want to ignore them, that’s right. In the real world, they’ve been talking about ML and how it’s making pictures or such-and-such aspect of the OS better for about a decade now. It might not be flashy, but it is used throughout the OS.
> Meanwhile Google has features that people actually notice like removing tourists from your holidays photos — worse: it's mostly a simple collage feature working on the main CPU, and it has the same social effect as green bubbles in iMessage ("ah. Tourists on your photos. iPhone user?")
The feature to do this has been in the Photos application for years, what are you talking about?
This is the correct response, but it also feels as though ≈nobody is sandboxing their agents/harnesses in practice. Or at least, a good majority isn’t.
I think there is a cycle, like with most things of this nature.
You start really locked down, and you read and approve every request for access. You do this for a while, but never see a result you deny, so you stop reading as closely. You keep hitting that approve button. You start paying even less attention to it. You start feeling silly, like you are simply slowing the process down. You get frustrated, because you keep coming back to your session and realizing your agent has been stuck waiting for approval for a long time, and the task that would have been done by now hasn’t even started.
Now you are running even more simultaneous sessions, which means more and more of your agents are stuck waiting for your approval. You feel even sillier, because you are taking even less time now to review and approve requests, but your review step is causing more and more slowdowns because you have more sessions going so you take longer between approvals. You feel like you are spending most of your time cycling through sessions hitting approve. You still have not come across a request that was dangerous or would have caused an issue, so you feel more and more like you are wasting your time.
So you slowly start to give your agents more access with fewer review steps.
Maybe this results in a catastrophic failure at some point, or maybe it doesn’t.
> You start really locked down, and you read and approve every request for access.
Or you start out with almost every permission granted always, but the entire thing runs in a sandbox with the minimum amount of credentials needed to do its work… Sounds preferable to me to catastrophic failures :-)
AFAIK, I know plenty of frontend engineers that without blinking run "npm install" on random 3rd party projects they find on GitHub, and they do their banking and everything else on the same machine. But then again, I also know people (one person to be fair) who have unprotected sex with prostitutes, so maybe something makes me slightly biased here.
I mean yeah, there are a ton of people who are stupid enough to disregard all kind of safety precautions. That doesn't mean the safety precautions are invalid though.
Same. Models that are fast (and thus by extension, in some direction, efficient) but not local/self-hosted IMO fill a niche for quick and cheap (and acceptable quality, of course) inference in business contexts.
Agreed, but do you think either of the two federal/state governments would even have enough support material available, whether in the form of capital or otherwise (i.e. contracts), to give to Isar Aerospace that would enable them to compete with (at current valuation) a giant like SpaceX?
Bavaria is one of the most richest (if not the most) state in Germany. By GDP alone it's the 7th largest economy in Europe (https://www.vbw.com/int/About-us/Facts-about-Bavaria/index.j...). Of course they have money to support Isar and they should do it to diversify their economy and break the heavy dependency on auto manufacturers.
(As a Bavarian,) I’m acutely aware of the state’s economy – but my point is that SpaceX has an even bigger economy behind it, if the two were to actually be compared or compete.
Good point re/ depending on auto makers, though. That also applies to all of Germany…
Bigger economy, yes by about 10x. But despite the spectacle, SpaceX's actual expenses have been around 0.3-0.4% of German GDP in recent years.
It's priorities rather than absolute costs that matter here. Germany could absolutely do all of SpaceX as almost a rounding error, but probably has better things for that money to get spent on.
I'm guessing it's because making specialised robots was so much cheaper and easier than usable humanoid robots.
See also the humble domestic dishwasher. It's a robot that washes dishes and works in an environment that's otherwise sized for humans and hasn't really been redesigned to accommodate robots. Similar also for washing machine and dryer etc.
> we can't block models from scraping the public repos
FYI, there is the nuke option, which is generating endless nonsense pages as a form of “bot sink” [1] that ends the scraping relatively quickly, but IIRC that also tanks your search rankings, since it likely affects benign crawlers too – not something you’d necessarily want to happen to a new domain, unless you really need to protect server resources against aggressive hostile crawlers like SourceHut and so many others had to combat.
You’d imagine that ought to be sufficient to cover running costs. However, it might actually not be enough with hardware prices these days? Not sure.
They’ve also recently (edit: “recently-ish”, it’s actually been a year!) introduced paid storage for backups, which I’d imagine comes with some amount of profit margin, too. [2]
[1] https://signal.org/donate/
[2] https://signal.org/blog/introducing-secure-backups/
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