Zero data retention was an enterprise agreement that Anthropic and Amazon agreed with customers and delivered on.
There’s no way AWS would trade in their reputation with enterprises just to soak up some slop.
Also broadly available to us plebs via openrouter and similar. Claude is available on there under ZDR terms via the Google Vertex and Amazon Bedrock providers.
This is why I prefer open source software. I can modify it
One person can use librsync to create a Dropbox company. Another person can use librsync for noncommercial purposes, e.g., to transfer and sync their own files
I mean... I, for my own needs, which are rather simple, can replace Dropbox with rsync. That's one thing. But yes, it's an entirely different thing to consider you don't need, or worse, could own, such business, on the simple premise you don't need it at your own level. That would be madness to mistake one for the other.
The data science is where the real value comes in. 10x flags changed this release - which one caused the improved CTR? Booleans as a service need to address this, and there are benefits to having your boolean service live next to your other services
At least Anthropic claims that they are profitable on a per model basis. But since both revenue and training costs are growing exponentially, and they need to pay for model N training today, and only get revenue for model N-1 today, the offset makes it look worse than it is.
Obviously that doesn’t help them turn a profit, until they can stop growing training costs exponentially.
So it’s really a race to see whether growth in revenue or training costs decelerates first.
I also think fsync before acking writes is a better default.
That aside, if you were to choose async for batching writes, their default value surprises me.
2 minutes seems like an eternity. Would you not get very good batching for throughout even at something like 2 seconds too?
Still not safe, but safer.
I don't use AI though. Are they going to put automatic AI responses on the SERP? That's less green than simply not having AI on the SERP. Giving me something I do not want is wasteful by definition.
I disagree. Without AI I might take 15 min to search for something in google that would have taken me a single prompt in ChatGPT. The energy used by my screen in those 15 minutes would be higher than the energy taken by that prompt.
It’s interesting that the author chose to use SHA256 hashing for the CPU intensive workload.
Given they run on hardware acceleration using AES NI, I wonder how generally applicable it is.
Still interesting either way though, especially since there were reports of earlier Graviton (pre v3) instances having mediocre AES NI performance.
Hardware-accelerated SHA support has a patchy history. I wrote an article some years ago about the prevalence of SHA instructions in x86 in x86_64 CPUs [0], like the current mess we see now with AVX-512, Intel invented something useful then declined to continue supporting it, while competitors that were late to the party became the real champions.
AES-NI is x86-specific terminology. It was proposed in 2008. SHA acceleration came later, announced in 2013. The original version covers only SHA-1 and SHA-256 acceleration, but a later extension adds SHA-512 acceleration. At least for x86, AES-NI does not imply SHA support. For example, Westmere, Sandy Bridge, and Ivy Bridge chips from Intel have AES-NI but not SHA.
The equivalent in Arm land is called "Cryptographic Extensions" and was a non-mandatory part of ARMv8 announced in 2011. Both AES and SHA acceleration were announced at the same time. While part of the same extensions, there are separate feature flags for each of AES, SHA-1, and SHA-256.
So if you want to invest in the top companies, you either need to think they won’t change anymore, or you need to find when to buy and sell.
Index funds solve this problem for you, albeit with slightly lower returns in the short term.
> At successful tech companies, engineering work is valued in proportion to how much money it makes the company
If you look at what it actually takes to get promoted at most tech companies I’d say this isn’t generally true at many big tech companies.
Being on a very lucrative part of the product may not get you as much “impact” on your promotion packet as if you are working on a platform/infra touching the whole org. Even if that platform isn’t generating the company much money even indirectly.
Generational GC optimizes for both. They assume that most objects die young, so choose to relocate live objects and just mark the entire region that was evacuated as empty. So this is a very efficient way to delete data.
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