When we talk about the future of artificial intelligence (AI), the discussion often focuses on the advancements and capabilities of the technology, or even the risks and opportunities inherent in the potential cultural implications. What we frequently overlook, however, is the future of AI as a business.
[company]IBM[/company] Watson’s recent acquisition and deployment of [company]Cognea[/company] signals an important shift in the AI and intelligent virtual assistant (IVA) market, and offers an indication of both of the potentials of AI as a business and the areas where the market still needs development.
The AI business is about to be transformed by consolidation. Consolidation carries real risks, but it is generally a sign of technological maturation. And it’s about time, as AI is no longer simply a side project, or an R&D euphemism. AI is finally center stage.
IBM, for all its investment in the Watson platform, was still missing, among other elements, the “personality” — a critical piece of the virtual assistant puzzle. IBM is betting big on Watson overall, to the tune of $1 billion, and is therefore addressing Watson’s weaknesses aggressively. Assembling the complete puzzle is a non-trivial technological challenge and I’m not at all surprised IBM snapped up Cognea.
One of the companies I advise, [company]Next IT[/company], has gone to great lengths to create IVA’s with fully-developed personas — ranging from SGT STAR for the [company]U.S. Army[/company] to [company]Aetna[/company]’s Ann. These IVAs have a tone, a personality, a sense of humor and a vernacular custom-suited to their use cases. But even those personalities required proficiency in other facets of the technology, such as an expertly developed domain model. If you chat with the above examples, you’ll see how the two pieces interact very differently.
Because intelligent virtual assistants are focused within a domain model, they benefit from a clearly defined knowledge base and are able to go much deeper and stay within those bounds, whereas general purpose assistants like [company]Apple[/company]’s Siri are often asked to deal with users’ wide-ranging and often disorganized goals.
This is yet another argument for consolidation — building and implementing a cross-domain view of the world is a challenge, very likely bigger than any single company or customer. We likely won’t have “one assistant to rule them all,” but rather a team of assistants, each aware of its strengths and weaknesses, always collaborating in the background, delegating and stratifying based on the task at hand.
Personality is just one example of a shortcoming being addressed. So-called “best of breed” capabilities are scattered all over, and right now the AI market has a lot of niches. Natural language processing is important; machine learning — both statistical and symbolic — is important; domain models and ontologies are important; reasoning is important. The list goes on.
These disparate focuses inherently mean most IVAs are incomplete — they’ve either gone to college and have weak people skills, or they skipped college altogether and have some street smarts but little else. They either partied too much or spent too much time in the lab. To echo my point above, they’re not well-rounded.
So consolidation has become the necessary next step in the market. Or, to mark this drive to consolidation with a phrase most technology executives know all too well in accordance with Gartner’s Magic Quadrant, we are now beginning to realize “Completeness of Vision” for AI.
Personalization may be the biggest impediment to achieving that completeness of vision right now. Siri, as an example, is fairly capable as long as you know when to use her. But your Siri is identical to my Siri, despite various claims to the contrary. Because of that, our relationships with her are shallow. Siri’s personality is one-size-fits-all, a quality that prevents greater intimacy.
Early reviews suggest [company]Microsoft[/company]’s Cortana might have a fighting chance, at least in terms of the raw number of tasks she can carry out on your behalf. Cortana is a great multi-tasker, but still misses any notion of adapting to the individual.
[company]Nuance[/company]’s Nina, on the other hand, is strong on natural language recognition (as is Cognition), but weak on real intelligence (learning and reasoning). Other players have a lot of brains under the hood but lack real use cases. And it will be interesting to watch new entrant Viv develop and see what areas it focuses on and what it lacks.
Cognition as a service: The next OS battlefield
Some companies are still only using generic natural language processing and some clever front-end work to create the illusion of intelligence, but have managed to gain an impressive number of users by focusing on user experience. Other new startups have focused on applying these smarts to everyday objects — AI is a natural friend of the IOT (internet of things), and will be key to its development. Even [company]Yahoo[/company] is trying to get off the sidelines and into the game.
There’s a lot of fresh capital flying around in the AI world generally. Industry analysts are already predicting massive growth in the virtual assistant market — as much as 39 percent CAGR between now and 2018. Although the market is vibrant, no one has yet managed to string together the holistic experience that will be necessary for the future of AI as a business.
Consolidation will finally bring about the realization of an end-to-end “cognition as a service,” and as I’ve argued before, CaaS is the next OS battlefield. This is platform wars 3.0. The big internet companies are already spending a lot of money in this area, and they’re only going to spend more.
A real end-to-end platform would make it possible to completely reinvent how we interact with machines in health care, customer service, travel, finance, commerce and more. But the market needs consolidation to achieve that potential, because the technologies at play are unusually complex, and regrettably siloed.
Whether that consolidation comes through M&A or meaningfully executed strategic partnerships, or through standards development and the open sourcing of key technologies, we’ve reached a point of adequacy with AI. More collaboration, cross-pollination, and integration is necessary in order to take the next step.
Nova Spivack is co-founder and CEO of real-time trend dectection company Bottlenose and an advisor to Next IT. His background in AI includes time at Individual Inc. working on AI-based news filtering, and at Ray Kurzweil’s neural network company, Xerox/Kurzweil, and Danny Hillis’ supercomputing venture, Thinking Machines, as well as research at SRI as part of the CALO project (which became Siri), and the founding of Twine, a pioneering B2C semantic web startup. He previously wrote about consolidation of the quantified self market for Gigaom.