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I think in Picasa's case, they learned from that and turned it into Google Photos. I don't think there's any shared code, but at least they learned from it from a product perspective. I would say Google Photos turned out great.


There's lots of tools built on top of K8s to accomplish this tho. For example, Argo, Tekton, Flyte etc.


Absolutely, no shortage of things atop. Helm is probably the most well used composition tool.

It seems unideal to me to forever bunt on this topic, leaving it out of core forever. Especially when we are slowly adding im very specialized composition orchestration tools in core.


Requiring the user to write their own operators to manage state using the kubernetes api is very much a feature and not something which is missing.


Agreed that is a feature and not a bug.

But! The one thing that custom orchestrators can’t do is easily get the benefit of kubelet isolation of containers and resource management. Part of slowly moving down this path is to allow those orchestrators to get isolation from the node without having to reimplement that isolation. But it will take some time.


Oh I see orchestrating runtimes is quite different. Good points!


Helm really solves a different use case than this.

This is about describing the desired coordination among running containers. Helm is about how you template or generate your declarative state. You could certainly add this description to your templates with Helm, but you couldn't actually implement this feature with Helm itself.


I bundled both composition & orchestration under the same header.

It so happens that pods have multiple containers, which is another example of Kubernetes having a specialized specific composition or orchestration implementation. One that started as composition, and here iterates towards orchestration.


Does this affect Hacker News?


Have a look at ULIDs


Lots of comments about Avro Arrow here lool. As a Canadian, I'm both proud and saddened by the fact that although we have elite engineering talent, that talent tends to be drained to the US.

Side note, just a couple decades after the Arrow, Canadian researchers once again lead the world, but this time in the field of AI, specifically deep learning. However, what happened after that? Google hired Geoffrey Hinton, and the industrial might of the US took over.

Perhaps this is inevitable given that we are much weaker economically compared to the US.

However, one last thought is that, aerospace vs software is not the same. For aerospace, yea I think you need a giant super power of a nation to keep it alive. However, software can be built by one guy in a garage. I'm not sure why Canada just let its dominance in AI "slip away".

Also side side note about Avro Arrow, is it just a weird naming coincidence that the two Apache projects exists: Avro and Arrow? I think Avro is named after the original British Avro company. However, I don't think Arrow has anything to do with aviation.


> However, software can be built by one guy in a garage. I'm not sure why Canada just let its dominance in AI "slip away".

Could be that Canadian software engineers prefer to move to the US to make much better money.


This was an opportunity for Canadian VCs/Investors/Gov to invest heavily on AI talent. This isn't what happened; the majority of capital continues to flow to real state. Lacking investment, banks acqui-hired promising talent/startups, those remaining went to the US and now the AI industry in Canada is on life support.


Is there proof that we have "elite engineering talent" and that's why it gets drained? Or is it the fact that we have engineering talent on par with the USA but the USA is willing to pay them more because they have a larger need for engineers?


I think the parent comment is suggesting that "engineering talent on par with the USA" == "elite engineering talent". In my anecdotal evidence, I'd estimate that ~1/3 of my Canadian engineering graduating class are now in the US, either working or researching at US institutions, with most of these folks representing the top 1/3 of the class.


>In my anecdotal evidence, I'd estimate that ~1/3 of my Canadian engineering graduating class are now in the US, either working or researching at US institutions, with most of these folks representing the top 1/3 of the class.

Similarly, in a IEEE survey of scientists from 16 countries <http://spectrum.ieee.org/at-work/tech-careers/the-global-bra...>, the US is the top destination from 13 of the 15 others and the #2 choice from the other two. If you are a Canadian scientist, there is a 16% chance <https://np.reddit.com/r/dataisbeautiful/comments/37lgxg/the_...> that you will move to the US. That's not "16% of all Canadian scientists that move out of the country move to the US". Let me repeat: 16% of *all* Canadian scientists move to the US. As you noted, they're also likely to be among the top Canadian scientists, too.

By comparison, 5% of all American scientists move to another country, of which 32% go to Canada, so about 1.6-1.7% total. Since the US has nine times more people, that means that in absolute numbers the 1.7% of American scientists is about equal to the 16% of Canadian scientists, but there is no reason to think that the 1.7% makes up the top tier of American scientists; why would the best move north of the border? In other words, the US is receiving the best of Canadian scientists in exchange for an equal number of its non-best.


Anecdotally, seems there's a lot of Canadians expats here in the Valley and they don't seem too keen on returning. We've been getting a lot of international applicants (but work from home was supposed to mean Canadians could avoid moving to the "dangerous" US but work for American companies?).

Post 2016 the messaging from most commonwealth countries (UK, Canada, Australia) seemed to be that they were going to be the ones benefiting from a brain drain of Americans leaving the country. Canada was supposed to become an "AI Superpower" and its Universities were supposed to be where innovation was going to happen next due to the perceived hostility of the United States to foreign talent.

Canada sure had a lot of "talent" immigrate in the meantime, but from my observations it's mostly people who can't -and likely won't ever be able to- secure a US visa, mostly due to skills (there's a reason they immigrated to Canada, it's way easier and the quotas are close to 10x per capita compared to the US). Some companies leverage this and have floors of international devs they park in Canada for a fraction of their US counterpart through a subsidiary.

It's interesting, in retrospective, to see how wrong these predictions were. Top destination for Canadian nationals in Academia was, and still is... the US.


> Post 2016 the messaging from most commonwealth countries (UK, Canada, Australia) seemed to be that they were going to be the ones benefiting from a brain drain of Americans leaving the country.

I can't find the article now, but the well-publicized crash of Canadian immigration's website on US election day 2016 was actually because of maintenance, not because hordes of Americans hoping to flee north overwhelmed the site.

>Canada was supposed to become an "AI Superpower"

This was repeated so often that it became a punchline in /r/canada.

>Some companies leverage this and have floors of international devs they park in Canada for a fraction of their US counterpart through a subsidiary.

My understanding is that this is the norm for FAANG offices in Canada: Mostly non-North American people who are either waiting for a US visa or (as you said) can't get one, plus the odd Canadian who wants to stay home for family or personal reasons.


Can confirm. Just graduated, and a significant chunk of my cohort is going or is planning to go south.

Mind, I don't get the impression that they want to stay in the states. I include myself in that camp, the plan eventually being to work remote for an American company from Canada.


There's a catch with that strategy - need a Canadian operation or they have a big administrative overhead to keeping you on board. Remote pay question marks too.


IME most places will take you on as a contractor or use a PEO. If they're open to remote they'll find a way. Canadians are so cheap it's still worth the overhead


Yeah but if the point is to get US salary not sure you get the trade off benefits.


Something you have to keep in mind is that there are two parallel markets over there: SV caliber developers and the rest. The former won't have any issue getting a job in the US (takes maybe a week for a talented engineer to get one). Therefore, comp has to be priced appropriately. The later can't -and likely won't ever be able to- secure a US visa, mostly due to skills. A lot of them are immigrants to Canada themselves (there's a reason they immigrated to Canada, it's way easier and the quotas are close to 10x per capita compared to the US). Some companies leverage this and have floors of international devs they park in Canada for a fraction of their US counterpart through a subsidiary.


For software developers your comment is correct. If you’re a Canadian citizen and a professional engineer all you need to get a TN visa is a job offer. There is a path to get both citizenship and a professional engineering title for foreign engineers so eventually the engineers with an engineering degree can make it to the US.


> However, software can be built by one guy in a garage.

Not for these AI models. The deciding factor seems to be the resources you can throw at it in training.


Don't forget about Nortel! They got all their IP stolen by Huawei! Your welcome Huawei!


just use dbdiagram.io


Haha a lot of funny comments here. I think overall it's neither here nor there. You should be proud that the "elites" at Google copied your code ;)


Just read the original paper "Attention Is All You Need". Cohere's founder was the guy who wrote that paper in the first place.


Hold on... aren't there a bunch of incredily successful "open source" / "source available" companies? Databricks, Cockroach Labs, Hashicorp, MongoDB, Elasticsearch etc?


Yes this article is promoting the "open core" model those companies follow, as opposed to the "pure" open source model Red Hat follows.


Which is basically PD and Shareware for post-2000 folks.


And how many of them are now trying to switch to fauxpen source licenses like MongoDB's SSPL?


I switched out of data engineering, and became a software engineer instead. I work on building the data infrastrue tools that I used to use. Maybe this only applies to me, but building the tools that I used to use is somehow incredibly satisfiying. I think it's because as someone who used to use the tools, I know what I want, and then I build it, completing the "cycle of needs".

So my advice to some of the data scientist/engineers out there is to go a little deeper into the tooling and try to understand how they were built.


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