Apple’s talk about services got specific with a bunch of news subscription services. Most of them are sensible and worthy iteration, but the company still hasn’t explained exactly what it plans with its push into commissioning billions of dollars of premium TV (Spielberg! Oprah!). Maybe all of this is about trust: the old Apple promise was that you don't have to worry if the tech works, and the new promise is you don't have to worry if the tech is scamming you.
Read MoreSmart home today looks a lot like the world of kitchen gadgets a few generations ago - and so does machine learning. We have a bunch of cheap commodity components (DC motors! Cameras! Wifi chips! Voice recognition!) and we’re trying to work out how to bolt them together into things that makes sense. There are lots of experiments - some things will be the toasters or benders of the future, and some will be the electric can-opener.
Read MoreFacebook’s struggle with abusive behaviour today looks a lot like Microsoft’s struggles with malware 20 years ago: you think open is always better, until people take advantage, and then you have to pivot from default open to default closed.
Read MoreMachine learning means smartphones will (nearly) always take perfect pictures. But it also means they might understand what’s in the picture and why you took it. So what do they do with that? What does the discoverability and communication of AI look like, if you can answer lots of questions but might still be wrong?
Read MoreAmazon’s Alexa has been a huge, impressive and unexpected achievement. Amazon created a category from scratch and left both the AI leader Google and the device leader Apple scrambling in its wake. It’s now sold 100m units. So far, though, this success is pretty contingent - we do still have to ask what Amazon actually gains from this. What do consumers do with these devices that helps Amazon? What fundamental strategic benefit does it get? Amazon has put an end-point into tens of millions of homes - what does it do with it?
Read MoreWhat is 5G? Why do we care? How much faster does the pipe get? What can we do with a fatter pipe? How does this relate to VR? Cars? Broadband? What’s the killer app?
Really, unless you work in a few very narrow niches, you shouldn’t spend much time thinking about it.
Read MoreMachine learning is probably the most important fundamental trend in technology today. Since the foundation of machine learning is data - lots and lots of data - it’s quite common to hear that the concern that companies that already have lots of data will get even stronger. There is some truth to this, but in fairly narrow ways, and meanwhile ML is also seeing much diffusion of capability - there may be as much decentralization as centralization.
Read MoreClose to three quarters of all the adults on earth now have a smartphone, and most of the rest will get one in the next few years. However, the use of this connectivity is still only just beginning. Ecommerce is still only a small fraction of retail spending, and many other areas that will be transformed by software and the internet in the next decade or two have barely been touched. Global retail is perhaps $25 trillion dollars, after all.
Read MoreCar people often look at Tesla the way Nokia looked at the iPhone. “Nice ideas, but we can easily do all of that, and they don’t understand our industry.” Nokia was wrong - but will the car industry look the same? Maybe not.
Read MoreEveryone has heard of machine learning now, and every big company is working on projects around ‘AI’. We know this is a Next Big Thing. But we don’t yet have a settled sense of quite what machine learning means - what it will mean for tech companies or for companies in the broader economy, how to think structurally about what new things it could enable, and what important problems it might actually be able to solve.
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