Facebook open-sources Detectron
research.fb.com
research.fb.com
I only linked to the xception paper because it mentions JFT. It's not state of the art for large scale recognition.
For example, humans can identify a monkey riding a Segway on the airport runway, but there probably is no such thing in the training set, even if it is quite large. The neural net might not know if that constitutes a "riding" action because it has never seen such a combination. Maybe the monkey is jumping over the thing and the picture shows it in proximity to it, not riding it - a human would know that a slight gap means there is no riding taking place.
Then, the even harder problem is to predict the consequences of actions on objects and just to physically simulate the scene. Such knowledge is useful in robot action planning. Beyond computer vision, there is also a need to create a "mental simulator" that has theory of mind and can simulate other agents (what humans intend), and we need simulators, both physical and mental to create the next level of AI.
Further, nearly every time a computer recently has been trained to do some very nuanced classification, such as in radiology, they exceed human expert performance.
(Outside of classification, computers are rapidly making progress - for instance they are getting surprisingly good at predicting the next few frames of a video, which requires a lot of "world knowledge" to do correctly.)
This page isn't available. The link you followed may be broken, or the page may have been removed.
If you are, Google will spam you to death with captchas; it kinda makes sense because captchas are getting easier to solve for machines, so apparently the new test of humanity is whether Google can track your activity on other sites.
It's annoying to the point that it's pushed me to use DuckDuckGo more often and I tend to avoid platforms that require me to continually take their captchas. I used Discord for a little while, but once it started asking me to verify my humanity again periodically per session, I booked it.
My question is: are they doing this to simply get more training data for image classification, reduce server load by minimizing automated traffic, or to sanitize their queries for human input for NLP models?
As someone that works in an industry where CAPTCHAs have historically played a large role, and some players flat our use technology to bypass them, and do so using proxy and/or VPN services to get good IP addresses to do so, I imagine those automated systems both corrupt the CAPTCHA system somewhat, since it looks like a large corpus of humans behave in a certain manner and it's not humans at all. It likely also causes those IPs to be considered by the CAPTCHA system as highly suspect whenever encountered.
For your next questions, the industry is event ticket resale, and no, we don't do that (there are aboveboard ways to function in this market that rely less on brute force and more on data mining and analysis for specific targeted investment, and sometimes long after it's been on sale).
An answer like "This is definitely a sign" from Google Images would be funny.
http://www.jaruzel.com/files/streetsign.jpg
:)
There isn't a valid cert for that domain and for some reason for server is offering a different one. Presumably you need to unbind 443 from that host header name (this is based on memories of configuring IIS a decade ago).
Really?
The only response is a 404, which is exactly what should be displayed (to the best of my knowledge) for a domain that isn't configured for that IP/port when there are other sites utilizing that IP/port.
I have an IP... that IP points to a router, that router port-forwards ports 80 and 443 blindly to a web server, on that web server is a bunch of websites. IIS knows which ones to serve to clients based on a) the host-header, and b) the port.
jaruzel.com:443 is not valid, but because I run an older version of IIS[1], that does not support SNI, the cert is bound to the port, not the host-header. As such any domain name that points to the IP will dump you at that cert if you try to connect on port 443.
Hope this clears up any confusion. :)
---
[1] for um... reasons.
So far I've had a less than stellar experience with letsencrypt, so I'm not quite ready to go all free-certs just quite yet. It also requires a rebuild of my web-server[1] which I've been putting off for a very long time already.
---
[1] See my other post in this thread.
This creates a twisted Turing test situation where, to prove you are a human, you have to pretend to be a machine's idea of what a human is.
But interestingly, it also depends on my mood, when I feel lazy, I click fewer boxes.
Nowadays it's much easier, you can click anything that looks vaguely the same (e.g. boxy things for cars, ads for traffic signs, traffic signs for store fronts etc.). The fact that it's so easy to poison the training set makes me very wary about the autonomous car future...
And if you think that it's somehow good because it's mutually beneficial to train AI to better the future of humanity, don't. That is what their marketing department wants you to think.
So the forum is providing you value, you are providing Google value, and Google is providing the forum value.
If it was free then you wouldn't be doing them!
Exactly. I think Recaptcha was better when it was looking for consistency with other human answers. Using "AI" has the same problem you mentioned, plus its more vulnerable because it has the assumption that your "AI" is unapproachably far ahead of competitors.
That's also covered eventually in fast.ai, but not until the second course if memory serves.
Meanwhile, I wonder about the human costs if systems like these are adopted for purposes where they may be ill suited for, especially cases where their confidence scores are ignored (or mistakenly assumed to be 100% even when they're lower). Anyone have reading material on this?
Even low FPS (3-5) would be acceptable.
https://github.com/tensorflow/models/tree/master/research/ob...
google also recently put up their mobilenet v2 paper which handles segmentation https://arxiv.org/abs/1801.04381
Unless I misunderstood figure 2, YOLO seems to be more than twice as fast than the second runner and yes I agree and already was aware that YOLO's accuracy is not as good as other classifiers.
Any idea what they mean by "community integrity"?
That type of check should become standard in a short amount of time for all communities that accept photos (that isn't meant to be general purpose, eg Imgur).
I checked out Facebook Marketplace a few times since the launch and and everytime I'm just overwhelmed by the sheer amount of better or worse counterfeits.
On top of that I start getting notifications more counterfeits, for a short while I reported them but after a while it felt pointless and now I just ignore the marketplace tab.
For instance, in my country you cannot use or publish children images without parents consent.
The fine for doing that is way higher than your benefits even discounting bad press.
(serious request... I got a cluster, and something like a million pictures; but no GPUs or time for another side project...)
Follow me on Twitter, and I’ll post it there when it’s finished. Same username as here.
* edit: I've put a pull request in that builds the Dockerfile for the GPU for now: https://github.com/facebookresearch/Detectron/pull/15
Of course, if you run IRC bots that scrape Google with a headless browser to implement a .search functionality, and which offer link titling in IRC, and you use a separate bucket of cookies and IP for every IRC bot, your bots now also have a human search and browsing history, and also will pass all ReCaptchas...
If I'm trying to automate a system to fool their captcha, I'm probably getting a lot of bad results. Or I could just be intentionally feeding them bad data, the fact that not being allowed through captcha keeps letting me make more and more inputs would enable someone to do that as long as they would like to.
I don't know, maybe I'm missing something.
The thing you're missing is volume. Even if you assume the vast majority of people will attempt to mess up your data, when you have enough people doing it, you can look at them on aggregate and based on patterns disregard bad data. It might be "expensive", but still worth it.
Also, for drugs that do make it to market, efficacy and side effect information is published as a condition of drug approval, at least for new drugs.
Whether basic science research papers should be behind a paywall is a wholly separate issue, but the life science community largely shares its finished products. Indeed, there’s even a push to share early stage data, too.
Companies rarely do basic research, and that's why it's very important to keep up public funding for it.
There is a company creating a 3d-printed chemical reactor. By downloading a schematic and buying some raw substances, you can create your own lab. It can be used to synthesise drugs in remote areas, such as on Mars, or to make generics for cheap. The exciting part is that the reactor schematic can be downloaded and shared easily. It can also make illegal drugs just as easily as 3d-printers can print guns.
http://www.sciencemag.org/news/2018/01/you-could-soon-be-man...
Humans are objectively terrible for the environment. Now you might start to argue other metrics instead, or that on an nth removed degree it/we might result in a net positive, but then you've abandoned your initial premise anyways.