2013.12.27

Cognition-as-a-Service will be big in 2014

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Dudu Noy is the CMO at Ginger Software. Ginger’s Grammar Checker and Sentence Rephraser are available as desktop software, browser add-ons and Android mobile keyboard. Readers of our Japanese site may recall that we featured the company’s Japan launch back in April.

Ginger CMO Dudu Noy

I predict that 2014 will be remembered as the year that CaaS, or “Cognition-as-a-Service” platforms came of age. Cognition is historically a complex biological trait including skills such as decision making, problem solving, learning, reasoning, working memory and not least language, skills that today the computer sciences are chipping away at from various angles.

With each major evolutionary step in computing we have seen over the last 30 years, from mainframes to PCs, the internet, cloud and SaaS, and now ubiquitous smart mobile, the new realm has not so much replaced but augmented what was there before.

In the same way the promise of CaaS is to allow apps and services to function more intelligently and intuitively, allowing you to converse with them, ask questions, give commands and complete tasks more efficiently and conveniently.

Apple’s Siri is one of the most famous cognition-based services in general use today. And now Google’s recent innovations to its search product for mobile, incorporating more contextual conversation for queries, pits it against Siri in the cognition-augmented search arena. In both cases, the technology itself is in the cloud, even though the device is in the user’s hand. Their main functions only work when there is an internet connection [1].

The reason is that the two necessary tricks to make sense of a user’s speech input – speech recognition and natural language processing (NLP) – require cloud-based servers performing intensive processing of proprietary algorithms that is beyond the capabilities of handheld technology.

When it comes to NLP it is the sheer diversity of languages that makes it such a challenge. Old school NLP solutions were based on rigid rules that map inputs to a big list of known inputs. But the list can never be long enough, and the hard rules can never cover all the edge cases. So the experience of talking to a supposedly “smart assistant” always left the user frustrated.

You need more powerful, agile technologies that can figure out that in a sentence such as: “Yuko wants to eat an apple.

Yuko is something that can have wants, and can eat things, and that apples are things that can be eaten. The technology needs to be able to do this for the vast majority of sentences the app is likely to encounter. This is incredibly hard, but here at Ginger and a few other places, we are doing it.

It is not just Apple and Google who are eyeing this space. IBM is now also a player with Watson, recently announcing that the same supercomputer-strength software that conquered the quiz show “Jeopardy!”, will be available to app developers through an API and software toolkit. This will allow cognitive apps that leverage cognition to be hosted in the cloud on Watson. This would obviously be a great thing for IBM’s cloud hosting service as well.

This “platform model” in tech business is nothing new of course. In recent years IBM did this with its Websphere application server technology, which went from an internal project to a software community of thousands of developers. Salesforce.com did this with its Force cloud-app development platform, as did Amazon with Amazon Web Services.

But what is different with CaaS platforms is that cognitive powers will be baked in to the operating system, and all the apps that are developed on that platform. That will bring intelligence to a mass public in a wide variety of as yet unimagined contexts.

At Ginger we have not opened up our technology as a platform via an API yet, but we are providing the benefits of its cognitive powers to a mass user base globally. Our technology uses statistical algorithms in conjunction with natural language processing, referencing a vast database of trillions of English sentences that have been scoured from the web. This allows us to work out what the users of our applications are trying to communicate, be it in Microsoft Office apps, Gmail, Facebook or wherever, and correct their mistakes and suggest improvements to their expressions.

One thing is for sure – this is a really interesting space to work, and it will be fun to see where computer based cognition will go in 2014.


  1. As an exception, Siri can be used to control some local apps.  ↩

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