> As a result, Evernote will be shutting down its previous storage architecture that was based around a private cloud infrastructure, along with some of its own tech.
Good riddance! Deploying Openstack Swift was a nightmare in my personal experience. A few outages and I decided I'll never work a job supporting it again.
If a recruiter mentions "Openstack" to me what I hear is a shamble mess of a services with components you'll be on-call for which will break in unique ways. Oh and of course you're expected to maintain the entire infrastructure while you do your normal job.
The deployment part of OpenStack is why some companies have ceased having multiple solution offerings for their customers. Instead they now offer a single uniform OpenStack distribution that they know can be supported more so than 2+ other distribution and deployment variants of it.
There are a lot of on-premise workloads which cannot be moved to someone else's remote cloud (for varying reasons). This is where OpenStack fills in the gap and provides something better than an ad-hoc brew-it-yourself cloud platform. That being said it still requires a good understanding of the requirements as well as a well chosen distribution to match the foreseen use-cases.
CPUs, networking, and storage are not Evernote's money makers. And I'm fairly sure Google's machine learning is a lot better than what Evenote can do.
Anyway, infrastructure in cases like these is really like a public utility. No one says companies are putting their money maker in other's hands because they use public grid electricity (or sewage, or water supply, etc.).
> You are always partially in someone else's hands unless you happen to own a private, dedicated connection to your client.
A listenable connection to your client is entirely different than handing your entire infrastructure and data to a third-party. I fail to see the merit of putting your whole business in the hands of a potential competitor.
Yeah I tried Openstack swift and while there are some great parts to it, dear god that thing was riddled with piles of python and bash scripts holding everything together hahaha, look maybe I'm wrong I certainly didn't spend long looking through it but I did find it a little 'scary' to say the least.
Openstack swift isn't great, but if you move the proxy/account/container services away from the actual object store, as the read/write requirements are different, and if you opt to run your object store on proper hardware, it will scale well pretty well.
I'm curious as to what really made you hate it. From my vantage point of running openstack in production from Essex to Juno, Openstack Swift after Folsom release was the most reliable part of openstack outside of keystone and glance.
(Nevermind that it was also the easiest to upgrade as well).
Or you can use the ceph stuff, which is also pretty nice.
Good to know. For a year or two now, I've felt guilty that I haven't taken the time to learn OpenStack, and felt I was missing out on a career-enriching experience.
I worked for a company that did openstack; was pulled into their security team. That company dumped so much money just to have a terrible openstack client offering.
There was no CVE mailing list like other projects. We had to scrape their launchpad bug tracker. On top of that none of the package repos we checked (Canonical's, Debian's .. couple of others) would even have package updates for up to three weeks on some of the CVEs. We started building out own CI so we could build and patch ourselves. Then I got pulled from the open stack team onto something that was not a bottomless pit of haemorrhaging money.
So out of curiosity, what did you see about OpenStack that made you go this route?
I myself am a PTL (project technical lead) in one of the OpenStack projects and although I do understand where you are coming from I wonder what the gist of the experience you had was...
Care to share what experiences you have that made you think 'total dumpster fire'?
I know the software isn't perfect, but then what software is? Also I've seen that the OpenStack 'having a bad time experience' is as much of a cultural change as it is a software change; ie, OSS in general isn't a take and not contribute kind of thing, that's not how it really works/gets better.
What exactly does a company like Evernote have to do with machine learning ? Do they have a targeted advertising platform? I can see how it might be good for things like image recognition but what else are they doing with it?
I am Genuinely curious, I've not used Evernote for several years, it just got out of hand and bloated I found.
Machine learning is really starting to feel just like another trigger phrase.
And I've been very, very impressed with the handwriting recognition. I discovered it by accident before it was a paid feature when I was searching for something and it brought up an image of some scribbled notes I had taken with the search highlighted. And my handwriting is bad, really bad.
Awhile ago someone asked how a product like ABBYY Finereader, which does great when OCRing typed text, does on handwriting. Not well at all I'm afraid:
Evernote doesn't just OCR handwriting to a single text; it indexes a bunch of possibilities for every handwritten word. This way the search functionality can search through all these variations, not just the most likely one.
I haven't used its handwriting OCR feature so genuinely curious. Does it not show a single piece of text? If not, what value does the OCR handwriting provide? Is it solely for the search feature?
Yep it seems to be, it indexes every possibility that the handwriting might be so that if you search for it then it comes up. You can see this if you dig through the XML it exports.
OCR with Evernote works very well because it's allowed to be fuzzy. One hand written word is allowed to have multiple predicted texts. This is because the predictions are only used for search - you can't copy/paste OCR'd text because Evernote can't guarantee it's correct. But it's good enough for fuzzy search. In fact it's pretty much exactly what you want for search: allowances for misspellings and typos. Very smart.
Possible applications that come to mind are image recognition, note classification (e.g. recipe, web tutorial, news), text search, and text recognition in things like PDFs
They have some context searching features -- so when you open or type a note it displays (off to the side) other notes, wsj articles and the like that are supposed to be contextually related.
I suppressed this because I found it a distraction, but if their searching and matching gets better I might un-disable it and give it another try.
Evernote’s new CTO Anirban Kundu told me the first two areas that will be replaced by Google’s machine learning APIs are its voice recognition for speech-to-text translations; and natural language processing, used to help search for contextual content.
I think there is a good opportunity in helping users with notes categorization using ML.
> Evernote’s new CTO Anirban Kundu told me the first two areas that will be replaced by Google’s machine learning APIs are its voice recognition for speech-to-text translations; and natural language processing, used to help search for contextual content.
Thanks. On mobile these single line quotes are really frustrating. Is this just considered to be fine in the design of HN? Sort of a meta post sorry if it's not appropriate here.
Evernote's main feature when first announced was very good handwriting recognition. You could just snap a picture of a board or note pad and have searchable text in the cloud.
There's some kind of cluster of OCR expertise in the Russian computer science community given ABBYY Finereader as best-in-class printed OCR and Evernote as best handwriting OCR.
>Machine learning is really starting to feel just like another trigger phrase.
Yes, and its close cousin "data science" fits the same description, to me. They're quickly becoming what "the cloud" is: marketing jargon that doesn't provide useful information.
Both of those terms are indeed "marketing jargon", but I don't think they're intended to market products—rather, they market people.
The point of treating data science as a field is to distinguish the people doing it from "regular programmers." This creates a distinction of caste: the "regular programmers" are relegated to maintenance work, never trusted to touch any of the mathematical and CS-degree-requiring parts of their own discipline. The "data scientists" are then hired from outside, to do precisely the parts of programming that every programmer at the company would have already been proved competent at, through degree-qualification and technical interviews that seek out exactly these talents. And the "data scientists" are paid better for it, and given better working conditions, and less micromanagement.
Same with machine learning: it's just programming—certainly, a kind of programming that is heavy on CS, but certainly one you can pick up quickly enough to get some good practical results. But you hire ML people separately from "programmers", and you never hand your "programmers" ML tasks.
From yesterday's subthread on the wind-down of Starfighter, I gather that a large part of its goal was to reveal that the emperor has no clothes here: that nearly any programmer is capable of doing "data science" or "machine learning" (and, as well, "reverse-engineering", "low-level programming", and a host of other things) if actually given a chance to solve the problems.
The logic here seems flawed; it's generally cheaper and faster to hire from within than without (you don't have to spin up people on corporate process or software that someone else wrote). So why wouldn't companies do that?
And the flaw in the logic is revealed here, I think:
> nearly any programmer is capable of doing "data science" or "machine learning"
Nearly any programmer might very well be capable of learning these disciplines, but they're different disciplines from business logic or database theory or networking; they're non-discrete and statistics-interpretation heavy, and it's entirely plausible that you can have an entire company full of programmers who are neither excited about nor prepared to take on these categories of challenge. Some programmers will (lots of people are polymaths), but it's not nonsense to consider them different categories of discipline.
I think smart companies provide an internal channel to get into these sub-disciplines, but it's not necessarily a problem space you can throw at any developer and say "Here you go; good luck tuning those training and test sets!"
I think you make some good points, but I think I need to agree with the previous poster, it seems mostly like marketing jargon. I come to this conclusion because these people, who market themselves as "data-scientists", really seem just like statisticians, or am I wrong? Don't all scientists, to some degree work with data?
I recently worked at a company who employed "data scientists", they rarely worked in isolation as far as I could tell, and usually required heavy assistance form system/database/storage administrators to be successful and aided by (but not always) with software engineers.
In the case of ML, I still see it as just software engineering / computer science. Sure there are pioneers in the field of deep learning, but aren't most of us just leveraging APIs or existing algorithms?
Honestly, I'm pretty confused myself lately and I work with some of this tech. Open to enlightenment on this topic by the way.
That wasn't quite my point. I do agree that "data science" is just marketing jargon for "statistics" (and definitely disagree that it's the same as labeling "programmer" as "software engineer", the way another person commented in response to you), but I don't think any and every programmer can "do data science".
What you describe with respect to data scientists needing help is what I'd call "data engineering." A data science person who is supposed to be doing production-facing engineering should be a competent enough data engineer that he or she can extract information from the data stores without having to have outside help most of the time, but strictly speaking, in my view, these are two different kinds of development.
The "data science" vs "data engineering" distinction helps a lot. Let me try to re-make my original point in light of it.
There are a few Bigcorps with real, novel Big Data datasets that need original statistical work slung at them. These companies need data scientists, for real: people with Ph.Ds in statistics. These people are indeed not interchangeable with programmers. They're partially interchangeable with academic computer scientists, and mathematicians, and physicists; but not with any trades-workers, including your average programmer. Their job is Science, capital-S: to do sound, replicable, high-powered experiments to learn things about the data. That is a skill in-and-of-itself, and one you need a lot of practice with—under the scrutiny of people like Journal editors—to get right (because it's hard to tell from your own observation if you've got it wrong.)
Everyone else, though—that is, all the companies but the SV Big Five and maybe some mobile-game and advertising firms—when they say they're looking for "data scientists", all they're really looking for is data engineers. The actual "data science" they're trying to do is a solved problem: you can find out the same thing a data scientist would tell you from five minutes of Googling the problem, because dozens of companies have solved the same problem for their own data-sets already and written case-studies on how they did it. You only need to implement said solution. Which, like I said, any competent programmer could do, after a few hours spent reading the API reference of a statistics package.
The majority of "data science" (read: data engineering) jobs aren't looking for people to Do Science; they're looking for regular programmers clever enough to have self-selected into the higher caste by doing nothing more than having learned some statistics-package APIs and then marketing that skill. (Much like the "officer class" of the American military in the 1800s allowed people to self-select into it just by being voracious readers.) It's basically an implicit open question at the beginning of the hiring process, "what do you want to be doing all day?", that is answered by choosing a different (pretend) job title.
You're 100% right that "data scientist" is a fancy made-up term for people who mostly do statistics. In the same way, "software engineer" is a fancy made-up term for people who mostly do programming.
The fact that data science is basically statistics supports the argument of the guy who is saying data science and software engineering are different jobs.
If you are a software engineer and want to be a data scientist, you are free to switch careers. Or maybe work as an engineer for a startup that could use someone to do statistics on the side. But that might be a bad move with no experts around. With data science, your work product is often conclusions and advice. Those are highly susceptible to bullshit. You don't get a compiler or unit tests that tell you that you are coming to the wrong conclusion and giving bad advice. It takes experience and judgement to get that right, not just hacking on an IPython notebook and accepting what the model spits out.
>This creates a distinction of caste: the "regular programmers" are relegated to maintenance work, never trusted to touch any of the mathematical and CS-degree-requiring parts of their own discipline.
Perhaps it's because people with formal training and degrees often have better skills than some random kid who taught himself javascript and thinks that that makes him a software engineer?
Mind you, I'm talking about how companies like Google and Facebook treat the people in their "Software Engineer" role, here. They already have a minimum hiring bar that ensures "formal training and degrees", and in fact ensures the skills themselves. They do ridiculous technical interviews that ensure the "average programmer" at these companies could probably code every part of the distributed system underlying a NASA Mars rover mission by themselves.
And then, having found all this great talent, they let it rot, under-employed in maintenance work. Because they were hired to "do programming", not to "do data science" or "do machine-learning" or any of the other 'specialized disciplines' that they could totally pick up given about two hours, given how freakishly intelligent they already have been proven to be.
(If you're wondering, this isn't bitterness; I've never worked for these companies myself. I'm just summarizing a number of rants I've heard from others.)
Yeah, Evernote being bloated was also the reason for me to stop using it. I wanted to take a few notes here and there, not document my entire life in all available forms of media. I can't believe that they are still adding even more things onto it.
I used to use Evernote all the time, although I wouldn't consider myself a power user. I don't think I utilized all of the features very well. I came to it through Tim Ferriss, I believe, and it was really amazing for me at the time.
I hardly ever use it anymore, using mostly notebooks for actual note taking now. I used to use the web clipper to save articles, but I found that when I would put something in Evernote, I hardly ever went back to access it later. It was like putting things in a vault. That probably all speaks more to me than the product. I am curious what new features they can provide with access to all of Google's machine learning APIs.
I'm there with you. I used to use it all the time and even paid for Evernote business for the office (I think only 7 or 8 other in the office use it), however I've been using it less and less lately and will probably drop it at renewal time. It seems like I'm always stepping over useless features (Work Chat? uh, no) while hoping they actually implement features their users are asking for (e.g. dark mode - https://discussion.evernote.com/topic/94974-dark-mode-for-ma...). I probably just need to bite the bullet and figure out how to export everything I have in it to OneNote or something.
OneNote is vastly better, IMHO. (With the major caveat that it's not available for Linux, which will be a dealbreaker for many. Works on OSX/iOS/Android, though.)
I really don't understand what happened to Evernote. It was very good and getting better all the time; then a few years back they decided to pivot to...something else, I'm still not sure what...and essentially abandoned all the features I used to start pushing lots of features I never would.
It looks like it is free now. Given Evernote's horrendous move to limit the number of devices a user can access their notes with (literally the dumbest gating mechanism I've ever heard of in this day and age where device-agnosticism is table stakes), I'm looking for a free alternative.
Are there any downsides moving from a free Evernote account to a free OneNote account in your opinion?
A couple of things I noticed when moving to OneNote:
- OneNote doesn't have tags
- search function is pretty primitive compared to Evernote
- The Webclipper is frustrating: Websites are often clipped as an image. Very frustrating if you actually need to work with the content afterwards.
- ON seems to generate much more traffic on my phone.
- publishing notes with Evernote is much better: You get a public link, etc. Everything looks more polished. Also, when publishing clipped websites you automatically get the link to the source. In ON it just looks bad. (I use Evernote for press articles.)
- Spellchecking is a mess in ON. For some bizarre reason they've decided to set the notes language to your keyboard locale. It is ugly as hell. But there's a macro for OneTastic to reset the locale.
- no Context.
Good things in ON:
- free form canvas
- no more messing your notes up when you work on them cross platform.
- Excel-tables natively supported
- as somebody noted, Evernote is practically a vault where you never touch stuff again. you basically hide everything behind tags. Then you use the search to get only relevant stuff. That's partly due to the UI. In OneNote you organise your notes more "optically" and actually reread stuff.
I introduced ON at work and we now couldn't do without it. I've been using Evernote in privat for several years. Now I'm using both - EN for press and my literature library, ON for everything else.
Visual hierarchical organization as opposed to tag search is what I prefer, so that's a plus for Onenote. Evernote actually used to be better at doing that, but they obfuscated it for no reason, like so many things.
Also, Onenote seems to handle sync conflicts better than Evernote. I once emptied my trash in Evernote and it decided to delete the live versions of all the old sync-conflict duplicates I'd trashed. I lost about a third of my notes. That's when I realized I needed to change.
One other downside is that the OS X version of Onenote is not quite full-featured. It's not missing anything essential, but e.g. you can only have one window at a time, for some reason.
Basically, my use case is personal notes and data, mainly formatted text rather than images or websites, for my own use, organized hierarchically for easy browsing. Onenote is ideal for that. If you're big on group sharing, or clipping web pages, or tag search, or whatever the hell else Evernote thinks they're optimizing for, then I can't tell you much.
I'm in the same boat, I would try to save articles into it, especially recipes but there are two reasons why I stopped.
The awful search with the web clipper plugin. It seems to match any single word in a saved article. It just ends up being faster to ignore the evernote typically unrelated results and look through Google results.
Inability to embed YouTube videos. Once again with recipes I'm better off using a browser since I'll have to open one up to view the video anyway. Most of the good cooking sites include a video embedded with the recipe, making for a more pleasant experience in the browser.
For recipes I can highly recommend Paprika. It does a great job of importing recipes and it is cross-platform/device (except linux but you might be able to run it in wine). Only downside is you have to buy it on desktop/tablet/phone separately but it was well worth it for me at a total of $30 ($20 Mac, $5 iPad, $5 iPhone) and it all syncs together. I stumbled across it randomly and now it's all I use. I used to just use my iPad for cooking with the website pulled up or AllRecipies but now I can't imagine going back.
There's no mention in TFA of the data belonging in any way to the users. And maybe that's accurate.
Yes, we have web/cloud apps now. But that is—or should be—orthogonal to where data is stored and hosted. Of course app vendors have every incentive to create lock-in. And most users are just happy to hear that "you do not need to take any action" and your data will just be magically faster and more secure. But at least around here, wouldn't people rather own their storage? Does remoteStorage have any legs?[0]
This kind of happened with authentication, right? It's common now to use OAuth to provide login using a third party. Of course, they're mostly silos, too, but at least in principle an app could let you choose a provider.
Your points are covered in the official announcement [1], and cross-linked on their FAQ about the announcement [2]. That was also posted to HN but didn't get much traction [3].
After many years in this industry I've personally come to the conclusion that nobody actually cares about security, privacy, or data ownership. People say they do but they are lying, as evidenced by the fact that they do not change their behavior. People gripe about security and privacy but continue to use "free" surveillanceware/spyware and continue to migrate everything to cloud hosts they don't control.
The only thing people care about in reality is convenience and user experience, and they're obviously willing to give up an almost unlimited amount of personal privacy and control to get those things.
One point is that you often don't really hear about the people who care enough to avoid much "social media" and cloud services... because they're avoiding many of the tools by which they might talk about it. They're also relatively uncommon, and if your friend group pretty much requires use of social media tools to stick together, you're not going to find them.
At the moment, I use GMail, IRC, a Matrix server I set up for my hackspace, a couple of niche forums, and a niche social network. I'm in the process of organising some hackspace servers to provide email hosting, so hopefully I'll be able to switch off of GMail at some point. The next step after that would be some form of cloud file hosting.
I'm not overly privacy-conscious though - I've used Tor once to see what the fuss is about, and I don't have AdBlock or NoScript installed. But at least I avoid explicitly putting my data in the hands of companies I have no control over as much as possible.
I have a similar situations. In a hackerspace I manage, we're still using GMail and Google Docs for collaboration. We're slowly moving to self-hosted services, like OwnCloud, but we can only do that because we're an established group of people. Back when the space was forming, there was no one willing to shoulder the sysadmin responsibilities for managing all the tools we needed to start and grow the organization.
--
What we need is separation of virtual machines from the code they run. Exchangable backends, if you like. We should be able to use cloud tools like e.g. Google Docs while also being able to choose our own backend - whether this or that cloud, or even our own servers. Right now, instead of running someone else's code on our data (as it is with files and local work), we're giving third parties our data for them to run the code for us.
We don't need all people to care, only those who can make a difference. We have the technology to build privacy-enforcing versions of popular services. We can make them better, faster, and stronger. We could create new, fun, and interesting things as well! What is lacking is the coordination and funding to compete properly.
I wish too, but this is a moot point - everyone has a shit ton of things to care about in their adult lives. By the time we're done putting out fires at work, dealing with mortgage, bills, grocery shopping, sick parents, broken sinks, searching for a good school for our kids, etc. there's precious little care left to be given. Greedy and socially destructive cloud/SaaS business practices are a distant position on a long list of things to care about, so you can't say that "if people don't care about something then it means they're ok with that". It only means the issue isn't immediately pressing/dangerous enough to warrant prioritizing it.
It sounds like that might be a reaction to the lack of obvious repercussions of giving up privacy and security. What tangible harm does the average person come to by giving up privacy, security, and data ownership?
Will I be hurt today if I put my data on someone else's cloud? probably not. Will I 10 years from now? possibly, but by then, my brain will have disassociated those two.
You don't necessarily sacrifice those when choosing a third party. We all apparently work in related industries...do you and your colleagues sit around and dream up ways to exploit customers? I don't, nor do those I work with.
I don't think anyone does. Its rarely a thought-out malice. It's more of unexpected things that happen because no one thought or cared to safeguard against that, or because such safeguards would've broken some legit feature or business model.
Like that E2E vs spam filtering issue explaination from GMail engineers.
Somebody does, apparently, otherwise business models would be much more straightforward. I worked in a social media marketing, "let's take an EU grant and spin off random shitty SaaS to bolster our marketing platform" company. I could see people in charge inventing new and great ideas for "bringing in value" without noticing (in any apparent way) that those ideas were mostly literally shitting on the users to make a quick buck. Reality distortion field? Sociopathic tendencies? Call it what you want, but it does happen, and that's where most of the "brilliant" business models come from.
Because not caring for the issue has adverse effects in society.
It's not about individual happiness.
To give an extreme example, there are people who don't care about police violence. While they are might fine, and probably wont ever have to suffer it, the resulting society is worse than if they cared.
But at least around here, wouldn't people rather own their storage
I know I'd rather not own any storage at home. I have a 9TB storage array (well, I'm only using about half) that I use for pictures, music and movies, and if I had a faster and more reliable internet connection, I'd happily move that all to the cloud.
I'd want my own encryption key though, so the provider can't see any of the data.
All of that data already lives at a cloud provider as backup -- took a couple months to upload it all.
I've thought about doing this a lot. I have a solid and stable 20 Mb connection at home, only have had ~2 hours of downtime this year.
The thing is... I don't want to basically trap myself into AWS or Dropbox. I run a 6Tb array like you, and kinda set up my own cloud, drag and drop, etc.
I don't think I'd ever give it up because:
1) It's cheaper to run myself (long term) - I'd have to consistently pay someone else ever increasing amounts to store data (which seems dumb since storage gets cheaper every year, their service doesn't).
2) Security - I don't want anyone to have access to those files but me. I'm 100% sure Amazon or Google would be able to access those files if ordered too by a government. Hell, they might do it without being ordered, who knows what's happened since Snowden.
3) Ease of use - my setup is based on a local network (as well as an ssh component). Basically, my setup works like Dropbox. The only drawback is no mobile component. If I want to change that I have access to all the parts and can do what I want. With AWS (which I use all day for work) I cant swap out a drive or stream a movie to my TV, phone, or desktop with a click.
On security, I'd like to point out that GCS now supports Customer Supplied Encryption Keys [0]. If you lose your key, we can't help you. Nobody can just unwrap your encrypted data.
On cost, I'm using Nearline myself ($.01/GB/month so about $10/TB/month) as an offsite backup of my home NAS setup. Paying for actual bytes stored instead of bytes of capacity gets you at least 20% (raid overhead) but honestly closer to 50% or more depending on how full you are. The poster above had about 3 TiB apparently which works out to $30/month. That's pretty good for an unthrottled replicated storage system offsite.
(And like you, I'm considering making my media directly read-only available via App Engine or something, because once you're talking about 1+ TiB of photos all photo hosting sites fall over).
Hosting yourself is still way cheaper. But services like S3 do get cheaper. When S3 was released in 2006, it cost $0.150/gb*month. That price underwent a half-dozen or so cuts every couple years to reach its current price of $0.03.
Its actually been that price for about 2.5 years now. With competition from Google, Microsoft, and Backblaze, its possible we could see a push toward even cheaper prices before too long.
As for security, S3 does support SSE at rest with a user-provided encryption key. So you're good to go there.
Agreed. I keep a server at home, not because I want to but because I have to. The cost of cloud storage and compute, relative to what you can field in your closet, is inordinate. You do pay the premium for not managing it yourself.
Its my hunch that the statement you quote is just simply wrong. If you're keeping a computer at home that is doing something valuable enough to keep it around, it should valuable enough to you that there has to be _some_ price cheap enough, and _some_ capabilities good enough, that the cloud makes sense. The exception to this is, of course, the hobbyists and the tinfoil hatters.
Why would you think that? I didn't read them carefully, but the TOS seem reasonable, granting Evernote a limited license to the data for the purpose of providing the service.
Because a rational person will assume a TOS attempts to acquire as many rights as possible. I certainly don't read them because IANAL.
This is just a round about way of saying "I sure am surprised people think they 'own' their data if it's stored and managed by a commercial entity as a business and not spelled out as a primary feature of the service".
The primary business purpose of Evernote is, indeed, selling data storage and access. The price tiers are based, in part, on max upload and max amount of notes.
I'm not quite sure what you're saying. Are you agreeing with me, or are you arguing that protecting the legal ownership and rights to data is a primary selling point of the product? I just don't see it.
That's not a rational person, it's a simplifying-until-wrong person.
That person is neglecting the fact that it's not in the business' interest to "acquire all rights". The main reason being that _some_ layer would read it and _everyone_ would read it the next in the New York Times.
A secondary reason is that it'd be illegal and/or unenforceable in many jurisdictions.
There is a very strong chance that this PR was "strongly encouraged" by Google in exchange for huge credits on the actual service. They've been hunting for larger customers they can use to advertise like they did with Spotify.
While I've heard this narrative discussed before, I'd like to offer some thoughts:
- Companies do not (or should not) make cloud purchasing decisions be based entirely on some kind of preferential pricing. Cloud is far from a commodity, especially in ML/Big Data space. In both Evernote and Spotify cases, they highlight strategic technological advantages of Google Cloud. In fact, customers tend to be fairly specific in outlining their findings[0], cost rarely being the main factor.
- I urge you to share evidence that Spotify received "huge credits" in exchange for PR.
- It's not unusual for companies to make such announcements. It's very much standard practice for AWS customers. It's good PR for both parties, imho.
- There are many other "big" names disclosed in 2016. And it's no secret that what Snapchat has achieved on Google's PaaS is nothing short of extraordinary.
Well, I didn't say that Spotify made the move in exchange for credits. However, since you brought it up:
> Some critics, surprised by such a high-profile company going with what is seen as the distant Number 3 in the hyper-scale public cloud market, have suggested that Google extended a sweetheart deal as part of the move. Details of the agreement haven't been disclosed, but Nicholas Harteau, Spotify's vice president of engineering and infrastructure, told The Wall Street Journal that the company "negotiated hard on price."[1]
> Of course, for such a high profile customer and for the priviledge of a case study, we can assume Spotify has some heavy discounts. [2]
Not "proof," but it's pretty well-mentioned across the industry that Google benefited from this deal probably more than Spotify did.
I understand your points - it's narrative that's floating on the internet, and it's one that's very easy to believe.
Unfortunately [2] is 100% opinion.
As far as [1], every single "large" deal is negotiated. That is standard practice for deals of this size, including your employer and AWS. It's also very different from "Google is the one benefitted" and "Spotify chose Google because of sweetheart pricing" and "Spotify got paid to do PR for Google". As I've said before, these narratives diminish both parties. It's Trump's "many people say that..."
I don't doubt you, but how would the average HNer have any evidence of what goes on between companies behind closed doors? :)
I am surprised to see Evernote moving to GCP to be honest. The cost increase in using GCP vs self-hosted hardly ever make sense for storage providers (which is kind of what Evernote boils down to). And it's not like Evernote is doing well financially.
I agree, of course. However, insinuating that such an announcement, and choice of cloud partnership, is dictated heavily by preferential pricing diminishes both customer's decision making and provider's intrinsic abilities. It's the not so subtle cloud "ad hominem" these days.
On your second point, per [0], Evernote is interested in Google's ML capabilities.
If shut down is in the plan, the move to the Google cloud doesn't completely makes sense, unless they think the big names customers will attract more adopters?
They would acquire users and data from one of Keep's largest and most established competitors short of MS OneNote while simultaneously removing them as a competitor in the market. Seems like a pretty solid incentive if Google is serious about staying in that space.
Not sure how long they will be around but I am not sure if this is a high yield project at this time. Instead they should be focusing on fixing defects and bringing important features to users.
I've migrated completely to DEVONthink (Mac/iOS only, though). Sync databases are encrypted and they live on my own WebDAV server, so I can keep as many notes as I can squeeze into a dozen TB or so of available storage.
I don't begrudge Evernote their business model, but I'm much more comfortable with upfront software licensing than subscriptions. That's especially true when it means I no longer have to trust anyone else's terms of service when it comes to keeping my private stuff private.
The China service is a completely separate service from the main one. Different servers entirely (same-ish code though), housed within servers inside the great firewall. AFAIK that stuff is staying in the data center in China.
Level 1:
'Buzzword' has the connotation that it sounds impressive to outsiders but is not much else than hot air. Sometimes there is even a connotation that it is an imprecise, non-technical term.
Level 2:
Machine Learning, however, has been well-defined in the past (starting in the 50s), is now widely used, contains a whole set of (old but also) new innovative techniques and actually contributes massive value to many domains.
Level 3:
VR is far from dead.
EDIT: a word
EDIT_2: I would have agreed if you had said 'trend'. Yes, it is a trend.
I'm not sure why this would be the case. They're just using google cloud services (computing, storage, and apparently tensor flow). You use tons of other services right now which are built on the same back end. It would be no different for you and me (end users I mean) if they had chosen Amazon.
> Will Google be able to index my notes or use it for targeted advertising?
> No. As a cloud provider, Google is subject to strict security and legal obligations which limit Google’s access to Evernote data. The data you put into Evernote belongs to you. Google will not process data for any purpose other than to fulfill our contractual obligations.
That likely won't happen but then as mentioned in other comments. 1st collaboration with google, 2nd move to google cloud, 3rd acquisition by google...?
AFAIK Google Cloud uses encryption throughout including for storing data with customer-provided keys. Not sure how your privacy would suffer in this case.
Thanks. I have tried them all (except notebook) and didn't find one more convincing than evernote yet - at least for my purposes, mostly note taking, documentation. Guess I'm stuck.
If data is just stored and encrypted at transport and at rest I would say not necessarily.
But if I read about that deep-learning magic they plan to do, I'm seriously concerned. Especially since I find the already existing note context feature quite invasive. Companies should only be allowed to do with my data what I give consent to.
I'm all for privacy and tinfoiling, but I have to say they already can do only what we allow. And oh boy do we allow. It's very simple, if you do not want to allow, then don't use service X. To expect some kind of personalised privacy policy deal from these companies is not reasonable. It would be great, but it ain't gonna happen, even if they were willing. It's practically and economically impossible.
I tried a lot to find a good alternative and the best one I could fine was Microsoft OneNote. However, I didn't like the apps and went back to Evernote.
I also think evernote is top from a usability point of view.
On the other hand I'm more and more disappointed from their pricing politics and general company values.
Good riddance! Deploying Openstack Swift was a nightmare in my personal experience. A few outages and I decided I'll never work a job supporting it again.
If a recruiter mentions "Openstack" to me what I hear is a shamble mess of a services with components you'll be on-call for which will break in unique ways. Oh and of course you're expected to maintain the entire infrastructure while you do your normal job.
Just move to the cloud already.