The peer reviewed publication is linked to from the press release. The press release's headline does somewhat overhype up the actual finding though. The actual finding is that different parts of the brain arise from different neural ectoderm progenitors, which explains why it’s so hard to get a forebrain neuron to behave like a hindbrain neuron and vice versa in the lab. The paper then postulates that this difference in progenitors resembles being two different organs evolutionarily, but this is not really the most important part of the paper.
BTW I suspect that this finding comes as completely unsurprising to biologists and the medical field generally. I'm not in either field, but even in high school biology we learned that the brain stem is behaviorally and structurally radically different from the rest of the brain, to the point where it seems almost obvious in hindsight that it's a different cell line and potentially has a different evolutionary history from the rest of the brain.
I have two Powerwalls mounted on my house and while I think they're fantastic and pretty compact for what they are, I would not describe them as anywhere near the size of a pizza box (unless you mean one of these things [1]).
Why are macOS and OS X listed separately? Is it to delineate pre-2016 Macs from post-2016 Macs, when the rename to macOS happened? But in that case, I have a hard time believing that there are way more pre-2016 Macs floating around out there than post-2016 ones, as the chart shows. I have a hard time believing that anyone is running pre-2016 OS X versions at all, outside of a very small group of hobbyists; I thought Apple’s data showed that generally Mac users were pretty aggressive about being on relatively current macOS versions.
Also why separate out OS X and macOS at all when it appears that all Windows versions are lumped together and all Linux versions and distros are lumped together?
Anecdata: Every time over the years that my parents (now in their 70s) have purchased a new mac, software updates only ever happen if I run them.
I don't visit all the time. They run outdated versions of everything until I hear "we need to buy a new mac because we can't use this website for some administrative thing", which is caused by not updating the os and the browser becoming unsupported over time.
Also account for i.e musicians (I hear there's a few of them in Apple-land) who seem to keep getting bitten by Apple somehow breaking compatibility with a bunch of audio software/equipment even with developer release, time and time again.
StatCounter uses browser tracking as its data source, and it seems like Firefox, Chrome, and Safari all froze the OS version they report in their user agent at Mac OS X 10.15 in order to avoid breaking sites that have poorly written parsing code by bumping the major OS version. I imagine that browsers that expose enough information to identify the actual OS version get shown as "macOS" and browsers that don't get shown as "OS X". See https://bugs.webkit.org/show_bug.cgi?id=216593 and https://bugzilla.mozilla.org/show_bug.cgi?id=1680516
Is anyone else amused that the car shown on the landing page looks a lot like a Tesla Model Y, which famously does _not_ use any Nvidia chips (Tesla onboard computers have been AMD based for some time now)?
AWS Bedrock is other companies’ models running on separate dedicated AWS hardware, metered through AWS billing. AWS owns and operates all of the infrastructure and the client interface; the model provider basically hands over the model and weights to AWS and AWS Bedrock take it from there.
So, as an example, if you use Codex through Bedrock, that’s a totally separate instance of Codex from anything you would be interfacing with if you directly used OpenAI’s API; if you use Codex via Bedrock, OpenAI never sees your data or prompts because they stay sandboxed in an ephemeral Bedrock instance. For many large enterprise deployments this hard boundary is a big big deal.
Over the past year, Claude being available via Bedrock and ChatGPT/Codex not being available via Bedrock has been a huge competitive advantage for Anthropic in the enterprise space.
If you've used AI coding models in a large corporate setting, you'll know that a lot of big corporate deployments basically require using AWS Bedrock for two simple reasons:
1. Large companies tend to already have an existing relationship with AWS, which makes things way easier to go through vs. setting up a new vendor relationship
2. Large companies tend to have strong internal requirements about making sure that internal data stays under company control. With AWS Bedrock, you can be a lot more confident that what you're feeding into the models is not going to end up in someone's training set somewhere. For where I work, this requirement is a dealbreaker for going directly through OpenAI's API instead of going through AWS Bedrock.
To go a step further, the reason it's often impossible to add a new vendor if that you've signed a bunch of contracts with your customers saying you're not going to send their data to other vendors in all sorts of various flavors.
3. from my opportunity - For many (not all) LLMs, Bedrock gives you control over which country the data stays in. You have no control over that with the Claude API, for example. We do not work in the US and have strong requirements for the data to stay in our country, which Bedrock gives us control over.
> We do not work in the US and have strong requirements for the data to stay in our country, which Bedrock gives us control over.
It doesn't actually. The US can request data from whatever country US companies store it, and companies must comply.
So if you have strong requirements for data to stay in your country, using a US provider, whatever it is, is out of question no matter what the company's marketing claims (they are not maintaining these claims under oath for what it's worth: https://www.senat.fr/compte-rendu-commissions/20250609/ce_co... )
Ah yes, there is a gap between what our regulator wants and what the reality is. I have no qualms that they'll hover out the data if they want to, we know that since Snowden. But I have to comply with the regulator, not with reality.
4. AWS billing is already cross-charged to different departments per account. Copilot/Claude/Codex would need that setting up all over again, and is (probably) all coming out of a central bucket right now. Switching to Bedrock APIs is really easy, and solves a problem for people high enough up in the organisation that they can insist on it.
Curious to understand how AI will continue to grow if this is the trend. Assuming most valuable data is behind such firewalls. And whatever is public has been harvested, trained on top of whatever has been acquired illegally (this is a grey area).
Will it become a closed ecosystem without outside input?!
The pace of data creation is only increasing, and our capabilities of sharing and storing it is growing as well. Lots of this is out in the open, ready for anyone to crawl and scrape.
There probably is a point of “peak data” where the amount of new data will start decreasing, but that’s likely a 22nd or 24rd century problem.
Pace of data creation ignores the fact that the majority of the big gains in LLM “intelligence” has come from scraping and feeding in the huge amount of public data that already exists.
Unless we’re producing data on the order of an entire new internet every couple of years, then it’s hard to see how LLMs can achieve further huge leaps in capability compared to training on effectively 0% of the internet vs 100% of the internet.
That is without going into fact that many already use AI to type out and write stuff. I have a customer in Far East that routinely uses it even for simple emails, he is not so familiar with English.
The majority of the gains come from the size of the supercomputers used to train them on. That's still growing. The algorithms used, and how the data is annotated is also some secret sauce.
If anything, trend will go towards sharing data less. It will become more important to keep the knowhow and data to yourself so the companies will do that.
And individuals will loose motivation to share, because it wont be that pro-social activity anymore anyway.
What other people are saying, but also because Amazon does not want to fuck around in this space. They don't want the legal fight or the reputational damage that would come with it.
To take an easy example that has actually had lawsuits I can link to, you must be unfamiliar with the lawsuits against Amazon for misusing sellers' data in order to undercut them with their own products... https://www.reuters.com/sustainability/13-bln-uk-lawsuit-acc...
There's zero reason to "trust" Amazon about anything. (And yes, I know the retail and AWS sides of the company are different, but it's still the same company. The same rot is always there, just shuffled around.)
this is not related to AWS, but merely to amazon's retail business and their sellers know and sign up for the deal when they sell via amazon.
every single retail company does this, they allow suppliers to sell the product using retails's infrastructure, and then retailer turns around and create private label products using sales data (Costco's Kirkland Signature, Walmart's Great Value, are just some examples)
Yes, but Kirkland's signature comes from the same factory. If I'm the factory owner and Costco vis going to guarantee me sales albeit at a slightly lower margin, so long as I slap a different sticker on it, that's different than from Amazon finding out which of my products sells best and then gets someone else to rip it off so I don't get paid anything.
First of all, we don't know which factory kirkland's products are coming from. Even if they are coming from the same factory, who guarantees the same ingredients and quality control was used???
everything from amazon is coming from China, I dont understand why does a random person who resells stuff from Chinese factories via Amazon FBA feels entitled for exclusivity arrangement with Amazon?
Was such exclusivity encoded in some form of legally enforceable agreement ?
That’s not the case at all. Kirkland just ditched Huggies making their diapers. They just introduced a breaded chicken tender nug to compete with one on the shelf.
They absolutely go out and find who can make the product and the quality and price they want. It’s not always an identical product to the brand name on the same shelf. Sometimes it displaces the brand name.
Wow there must be an echo in here because I swear I said just that... And then pointed out that it's the same crap being recycled back and forth across the company. There is no real separation.
In contrast to Microsoft, OpenAI, and Anthropic, AWS has never done anything close to sneaking in unwanted training opt-outs after the fact.
They are the only ones I trust not to do that so far. And their terms are extremely clear on that, no fuzzy language. Exactly what we want to see. So we use Bedrock.
Laws and rules don’t hold anyone accountable. Anyone can say anything and then break that trust the next second.
Instead you trust your best friend because you have known them for 15 years and seen them in enough situations. It’s long term observation and predictability they ultimately gives trust.
AWS has been around 20 years and has never once shown a sign that that they would sell customer data. Could they still try? Sure, in the same way they my friend who hates seafood his entire life could suddenly flip 180 and love it. Yeah I guess it’s possible.
Actually yes, when it’s other huge corporations holding them accountable. It’s only when politicians who are much more cheaply bought get involved that creates problems. When the other side has a significant war chest to combat you with, suddenly behavior improves
You really don't understand what AWS offers if you think this is what is getting them workloads (including competitors and highly sensitive govt workloads).
Contractual obligation, external third party audits, and above all, AWS’s reputation.
AWS isn’t going to risk their reputation, and thus huge chunks of their business, just so a few AI labs can get some extra training data. That’s an insane risk with zero upside for AWS. AWS knows full well they will make insane quantities of cash without breaking legal contracts with companies who pay them billions each year for infra.
Having worked with lots of companies, I can say that trust is there. But true test is competitors of Amazon. Does Walmart use them? Ebay? Although not in exact same business.
they’re crap on a lot dimensions of how they treat customers but data privacy/security is one thats taken pretty seriously at AWS, perhaps owing to the massive reputational damage that would result if they played loose with it.
A medium-spicy take of mine is that a bytecode VM in a GPU kernel is not as bad of an idea as one might think, and in some cases it can actually be the most reasonable solution. Some fun examples:
1. As mentioned in the post above, the Dolphin emulator famously implements the entire Gamecube/Wii GPU pipeline in a single gigantic ubershader, and this is useful because it avoids shader compilation stalls [1].
2. Blender's Cycles renderer implements its shading graph eval system as a bytecode VM in a GPU kernel [2]. IIRC early versions of Vray GPU did something similar. There are better ways of course, but a VM gets you surprisingly far as a general approach.
3. Finally, a lot of ML frameworks (Tensorflow, PyTorch, etc) by default use the GPU relatively suboptimally (especially without kernel fusion and such). Tensor frameworks can extract a lot more perf out of GPUs using a VM-in-a-giant-kernel approach [3].
If you think abstractly about how a GPU SM actually works (using CUDA terminology here), all threads in a warp must execute in lockstep and the cost of execution divergence across threads in a warp is that you effectively run serially, losing the parallel advantage of the SM. This penalty gets magnified enormously if you are doing memory reads after wherever the execution divergence happens, since you now have multiple slow memory stalls in serial instead of one big memory read at once for all threads. If you're clever about implementing a bytecode VM, you can load as much state as you need upfront into shared memory, and then if your bytecode VM is just looping through executing a bunch of opcodes in a huge switch statement, then at least as far as the SM is concerned, there's no execution divergence! All threads look like they're doing the same thing at the same time; even if within the VM what is happening a lot is just no-ops, at the SM level you're not dealing with serialized memory stalls and serial scheduling and such.
Is it the _best_ most optimal approach imaginable? Almost certainly not! But can it be a _surprisingly good_ and possibly even reasonable approach for some problem domains and specific constraints? Yeah absolutely!
https://www.nature.com/articles/s41593-026-02433-7
The peer reviewed publication is linked to from the press release. The press release's headline does somewhat overhype up the actual finding though. The actual finding is that different parts of the brain arise from different neural ectoderm progenitors, which explains why it’s so hard to get a forebrain neuron to behave like a hindbrain neuron and vice versa in the lab. The paper then postulates that this difference in progenitors resembles being two different organs evolutionarily, but this is not really the most important part of the paper.
BTW I suspect that this finding comes as completely unsurprising to biologists and the medical field generally. I'm not in either field, but even in high school biology we learned that the brain stem is behaviorally and structurally radically different from the rest of the brain, to the point where it seems almost obvious in hindsight that it's a different cell line and potentially has a different evolutionary history from the rest of the brain.
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