How new technology could topple the tech giants

As for Bill Gates, nowadays he’s more about saving the world than running it – a humanitarian hero not the Bond villain that some people took him for.

The fate of Microsoft shows that there is nothing guaranteed about the current dominance of the Big Four. As new technologies are developed, they create the basis for commercial as well as technological change.

In a richly insightful blogpost, Benedict Evans writes about the technology most likely to bring about the next wave of change – machine learning.

Machine learning is often referred to as Artificial Intelligence – somewhat unhelpfully, says Evans:

“The term ‘artificial intelligence’… tends to end any conversation as soon as it’s begun. As soon as we say ‘AI’, it’s as though the black monolith from the beginning of 2001 has appeared, and we all become apes screaming at it and shaking our fists. You can’t analyze ‘AI’.”

Machine learning isn’t about to produce a general purpose silicon ‘mind’ – let alone a conscious one capable of original thought. And, as for the notion of the Singularity, don’t hold your breath.

However, we don’t need these outlandish scenarios to see that machine learning is likely to change the world.

Evans draws a parallel with an earlier breakthrough in software – the relational database:

“Before relational databases appeared in the late 1970s, if you wanted your database to show you, say, ‘all customers who bought this product and live in this city’, that would generally need a custom engineering project. Databases were not built with structure such that any arbitrary cross-referenced query was an easy, routine thing to do. If you wanted to ask a question, someone would have to build it.”

An example of a relational database is Access – which is bundled in with some versions of Microsoft Office. In all the offices I’ve ever worked in this was ignored in favour of Outlook, Word, Excel and PowerPoint. And yet, in the right hands, relational databases are immensely powerful:

“Relational databases gave us Oracle, but they also gave us SAP, and SAP and its peers gave us global just-in-time supply chains – they gave us Apple and Starbucks. By the 1990s, pretty much all enterprise software was a relational database… this technology became an enabling layer that was part of everything.”

If machine learning also becomes an “enabling layer” what will it enable us to do? The basic answer is to identify patterns in data at a speed, and with an unwavering attention to detail, that humans can’t match. 

These are capabilities that are already being developed, but largely by organisations with the resources and the specialist expertise to create “custom engineered” machine learning systems. At some point, however, machine learning will undergo the equivalent of the relational database revolution – i.e. becoming available as a range of off-the-shelf products that a much greater number of organisations and individuals will be able to use.

If something as relatively simple as a relational database was enough to transform the economy, one can only wonder at what widely-accessible machine learning will achieve. At the very least one should expect some big changes to the IT sector. New markets will be created and old ones rendered obsolete.

After a decade in which the Big Four have consolidated their grip on digital they can expect machine learning to loosen it. Needless to say, they’re making efforts to stay ahead in the new game. But then the same was true of Microsoft when it was unrivalled leader of the pack. No company, no matter how big, can be the best at everything. And that’s especially true when the ‘next big thing’ comes from an unexpected direction – which, with machine learning, you can pretty much count on.

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Peter Franklin is Associate Editor of UnHerd. He was previously a policy advisor and speechwriter on environmental and social issues.

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