The future of photography is computational, not optical. This is a massive shift in paradigm and one that every company that makes or uses cameras is currently grappling with. There will be repercussions in traditional cameras like SLRs (rapidly giving way to mirrorless systems), in phones, in embedded devices and everywhere that light is captured and turned into images.

Sometimes this means that the cameras we hear about will be much the same as last year’s, as far as megapixel counts, ISO ranges, f-numbers and so on. That’s okay. With some exceptions these have gotten as good as we can reasonably expect them to be: Glass isn’t getting any clearer, and our vision isn’t getting any more acute. The way light moves through our devices and eyeballs isn’t likely to change much.

What those devices do with that light, however, is changing at an incredible rate. This will produce features that sound ridiculous, or pseudoscience babble on stage, or drained batteries. That’s okay, too. Just as we have experimented with other parts of the camera for the last century and brought them to varying levels of perfection, we have moved onto a new, non-physical “part” which nonetheless has a very important effect on the quality and even possibility of the images we take.

The present of photography is already computational, it’s always been, since the advent of the digital camera: from the very moment an imaging sensor’s output signal is digitized, billions of operations are performed to turn a stream of electrical levels into a colorless bitmap, then reconstructing colors by means of interpolation, correcting gamma, white balance, lens aberrations, reducing noise, compressing the image by discarding information not visible by the human eye, etc., just to name a few basic operations performed by a typical image processing pipeline. There is no such thing as #nofilter.

What we are seeing now is an unprecedented rate of innovation in image processing enabled by huge advancements in computing power and integration, bound to marginalize the traditional photographic industry.

For the past decade we’ve invested in and celebrated companies through the lens of network effects, Amazon’s power in retail, and measuring the potential of a brand by its scale and path to category dominance. We assumed that antiquated monolithic brands would be attacked by new modern brands that take over consumer consciousness enmasse. But instead, old and big brands are fighting against thousands of tiny brands with low overhead, high on design merchandise, and supremely efficient customer acquisition tactics. Many of us failed to recognize the collective impact of the long-tail of micro brands.

A lot of questions here: how many of these brands will survive the test of time? Isn’t it too risky to build a business on top of a single, closed platform? How can you tell which brand is authentic and which is not? Does it even matter? Only consumers hold the answers.

Can you think of any other demographic, ethnic or social group that anyone would claim is best influenced by targeting someone else? The whole science of marketing is based on finding the most relevant message and delivering it to the most probable buyer. Except when it comes to people over 50. Then all the rules are suspended. Because these people don’t count. They just “skew the data.”

So why are marketers and advertisers ignoring people over 50?

In this post from 2013, Bob Hoffman makes some great points against the universally accepted notion that teenagers are the most valuable demographic to target in advertising.