Posts from machine learning

Feature Friday: Photo Search

I’ve been uploading my smartphone photos to Google Photo for my last two phones. Earlier this week, I was in a meeting with some architects and I said that I really liked the way they do the showers at the Soho House in Berlin. They asked if I had a photo of them. I opened up Google Photos, typed “Soho House Berlin”, and got this result.

soho house berlin

Sure enough, I had taken some photos of the shower. I showed them to the architects and we were able to talk about the features I liked in the shower. That was kind of magical because other than taking the photos, I had done nothing to tag or categorize them.

This works for all sorts of searches. I remember seeing a painting I really liked at The Hammer Museum in LA. A search on “Hammer Museum” produces the image I was looking for.

hammer museum

If you are looking for photos you took on a trip, you can do the same thing. Here are some photos I took of Grand Bazaar in Instanbul:

grand bazaar istanbul

Google Photos isn’t perfect. Some searches that I would expect to work don’t. But it is pretty good.

Our portfolio company Clarifai has a similar service in an iOS app called Forevery. If you don’t want to upload your photos to Google Photo and want to search them locally on your iPhone, Forevery is a great way to get a similar experience. Forevery will also search your photos in Dropbox.

Since I’m on an Android right now, I am using Google Photos but I use both apps on my iPhone.

Photo search is amazing. You no longer need to create albums and tag and categorize your photos to be able to find them. You just search for them. Kind of like how email changed when Gmail arrived.

A NSFW Content Recognition Model

Last week our portfolio company Clarifai released a NSFW adult content recognition model.

If you run a web or mobile service that allows users to upload images and videos and are struggling with how to police for NSFW content, you should check it out.

Ryan Compton, the data scientist at Clarifai who built this NSFW model, blogged about the problem of nudity detection to illustrate how training modern convolutional neural networks (convnets) differs from research done in the past.

We are excited about the possibilities that modern neural networks open up for entrepreneurs, developers, and scientists. Our investment in Clarifai is based on our belief that AI/machine learning/neural networks/etc have reached the point of mainstream adoption and usability. And we are seeing more and more use cases for this technology every day.

Solving the problems of content moderators and trust and safety teams at scale, as we discussed here at AVC this past weekend, seems like a particularly good use of this technology.

Artificial Art

Last week we opened up a new thread on USV.com to think about and discuss the intersection of creativity (art) and artificial intelligence.

We have seen a lot of interesting companies in this area but have not yet made an investment.

Of course, the entire notion that machines will help us make art or even make it without human intervention gets to the essence of what art and creativity are.

Last summer I posted an art project by Ian Cheng that my daughter was involved in. The cool thing about that art project is that it evolves over time based on rules provided to a machine. The art is initially made by humans but it evolves and changes over time using a machine. That is one of many interesting ideas that artists are exploring at the intersection of creativity and computing.

An existential question that society is grappling with right now is how humans and machines will co-exist in the future. And one of the roles of art, maybe it’s most important role, is to force us to confront issues like this.

So while the idea of using a machine to make a song or an image or a novel or a sculpture without human intervention is at some level disturbing, it is also revealing. We expect that artists will push the envelope of what is possible with technology and we also expect that technologists and entrepreneurs will be willing collaborators in this effort.

Whether this will lead to interesting investment opportunities is anyone’s guess, but we think it might. And so we are going to spend some of our time and energy thinking about it and we’ve created a public space to do that. If you are interested in this area you can follow the thread and contribute to it here.

What Happened In 2015

Last year in my What Just Happened post, I said:

the social media phase of the Internet ended

I think we can go further than that now and say that sometime in the past year or two the consumer internet/social/mobile gold rush ended.

Look  at the top 25 apps in the US:

top 25 apps

The top 6 mobile apps and 8 of the top 9 are owned by Facebook and Google. 10 of the top 12 mobile apps are owned by Apple, Facebook, and Google.

There isn’t a single “startup” on that list and the youngest company on that list is Snapchat which is now over four years old.

We are now well into a consolidation phase where the strong are getting stronger and it is harder than ever to build a large consumer user base. It is reminiscent of the late 80s/early 90s after Windows emerged as the dominant desktop environment and Microsoft started to use that dominant market position to move up the stack and take share in all of the important application categories. Apple and Google are doing that now in mobile, along with Facebook which figured out how to be as critical on your phone as your operating system.

I am certain that something will come along, like the Internet did in the mid 90s, to bust up this oligopoly (which is way better than a monopoly). But it is not yet clear what that thing is.

2015 saw some of the candidates for the next big thing underwhelm. VR is having a hard time getting out of the gates. Wearables and IoT have yet to go mainstream. Bitcoin and the Blockchain have yet to give us a killer app. AI/machine learning has great potential but also gives incumbents with large data sets (Facebook and Google) scale advantages over newcomers.

The most exciting things that have happened in tech in 2015 are happening in verticals like transportation, hospitality, education, healthcare, and maybe more than anything else, finance, where the lessons and playbooks of the consumer gold rush are being used with great effectiveness to disrupt incumbents and shake up industries.

The same is true of the enterprise which also had a great year in 2015. Slack, and Dropbox before it, shows how powerful a consumerish approach to the enterprise can be. But there aren’t many broad horizontal plays in the enterprise and verticals seems to be where most of the action was in 2015.

I’m hopeful that 2015 will also go down as the year we buried the Unicorn. The whole notion that getting a billion dollar price tag on your company was something necessary to matter, to be able to recruit, to be able to get press, etc, etc, is worshiping a false god. And we all know what happens to those who do that.

As I look back over 2014 and 2015, I feel like these two years were an inflection point, where the underlying fundamentals of opportunity in tech slowed down but the capital rushing to get invested in tech did not. That resulted in the Unicorn phase, which if it indeed is over, will be followed by an unwinding phase where the capital flows will need to line up more tightly to the opportunity curve.

I’m now moving into “What Will Happen” which is for tomorrow, so I will end this post now by saying goodbye to 2015 and hopefully to much of the nonsense that came with it.

I did not touch on the many important things that happened outside of tech in 2015, like the rise of terrorism in the western world, and the reaction of the body politic to it, particularly here in the US with the 2016 Presidential campaign getting into full swing. That certainly touches the world of tech and will touch it even more in the future. Again, something to talk about tomorrow.

I wish everyone a happy and healthy new year and we will talk about the future, not the past, tomorrow.

Forevery – An iOS App For Searching Your Photo Library

Our portfolio company Clarifai, which offers a visual recognition API to developers so they can understand the images and videos on their service, has released an iOS app called Forevery which allows you to search your iPhone photo library.

If you’ve ever found yourself swiping down and down and down on your iPhone trying to find a photo to show to your friend, then Forevery is for you. It is one of those things when you first see it in action you think its magic.

Here’s the screen you get when you open the app:

2015-12-09 06.37.32

When you type the into the search field, you get this:

2015-12-09 06.38.02

I typed sushi and got these results:

2015-12-09 06.41.54

I was looking for a sunset photo of the Flatiron building from my office so I typed “sunset building” and got these results. The photo I was searching for is the third one.

2015-12-09 06.43.16

But maybe the most amazing thing about Forevery is you can train it to recognize people and things. I’ve trained it to recognize these people in my photos:

2015-12-09 06.44.09

So that’s a quick run through of Forevery. If you want to get it on your iPhone, you can download it here.