Feminized seeds promise no wasted space or time sexing out males. Autoflowering promises predictable growth, with no need to fuss with light schedules.
#Phototime review free
Sign up for a free trial.Autoflower, feminized, and photoperiod (regular) are all options you may be confronted with when it comes time to buy cannabis seeds.
Related research and analysis from Gigaom Research: I’m still waiting for some photo application to perfect the curated photo album, something Disney Research is working on using another machine learning approach.Īnd while accuracy continues to improve for recognizing objects and faces, researchers are already hard at work applying deep learning to everything from r ecognizing the positions of our bodies to the sentiment implied by our photos. Xia told me that while PhotoTime’s application servers run largely on Amazon Web Services, the company’s deep learning system resides on a homemade, liquid-cooled GPU cluster in the company’s headquarters.Īs I’ve written before, though, tagging photos is only part of the ideal photo-app experience, and there’s still work to do there no matter how nice the product functions. The company does have a fair amount of experience in the deep learning field, with several members, including research scientist Wei Xia, winning a couple categories at last year’s ImageNet object-recognition competition as part of a team from the National University of Singapore. Images are sent to the cloud, ran through Orbeus’s deep learning models, and then the metadata is sent back to your phone so you can search existing photos even without a network connection. More impressive than the tagging features, though - and the thing that could really set it apart from other deep-learning-powered photo-tagging applications, including well-heeled ones such as Google+, Facebook and Flickr - is that PhotoTime actually indexes the album locally on users’ phones.
#Phototime review for android
I can’t vouch for its accuracy personally because the PhotoTime app for Android isn’t yet available, but I’ll give it the benefit of the doubt. You might search your smartphone, for example, for pictures of flowers you snapped in San Diego, or for pictures of John Smith at a wedding in Las Vegas in October 2013. L to R: Yuxin Wu, Yi Li, Wei Xia and Meng Wang. (If you want to get a crash course in what deep learning is and why web companies are investing billion of dollars into it, come to Structure Data in March and watch my interview with Rob Fergus of Facebook Artificial Intelligence Research, as well as several other sessions.) The field has made big strides in recent years, largely with regard to machine-perception workloads such as computer vision, speech recognition and language understanding. The more data that deep learning systems have to train on, the better they perform. But it looks really promising and, more importantly, it isn’t focused on business uses like so many other recent deep-learning-based services, nor has it been acquired and dissolved into Dropbox or Twitter or Pinterest or Yahoo.ĭeep learning, to anyone unfamiliar with the term, is essentially a term for a class of artificial intelligence algorithms that excel at learning the latent features of the data they analyze. It’s called PhotoTime and, yes, it’s yet another photo-tagging app. A Sunnyvale, California, startup called Orbeus has developed what could be the best application yet for letting everyday consumers benefit from advances in deep learning.
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