Ovum's new AI Reality (AIR) chart, "AIR check", monitors AI developments in the news on a monthly basis to help readers navigate the hype and find the substance. As a short-term view, the monthly AIR check (see Figure 1) may show items reappearing in a revised position based on new information. The idea is to help gauge what AI related feature has prospects and what is impractical based on current knowledge, to identify cool AI products and services of today or the future, and state our opinion if we believe it to be just hot air. This article also has a long-term view on AI, to see where we are today and how far we have yet to go to achieve the creation of machines that can match or exceed human intelligence.
In the July 2017 AIR check (see Figure 1), the vertical axis represents hot (bad) to cool (good) air. Hot air labels are "hype" and "noise", and cool air labels are "signal" (appearing above the noise) and "substance". The horizontal axis represents how grounded the technology is, from impractical on the left to practical on the right, as understood at the time of publication.
In this month's AIR check, we look at AI-powered autonomous driving, which is represented in the chart by the levels defined by Society of Automotive Engineers (SAE) International standard J3016:
0: No automation
1: Driver assistance (human driving)
2: Partial automation (driver fully alert when not in control)
3: Conditional automation (driver required when requested)
4: High automation (very rare driver intervention)
5: Full automation (no human driver needed)
In the AIR check, AI-powered autonomous levels 4 and 5 are shown as dipping into hype and impractical territory. With further development, however, these levels are expected to be achieved and to move into the cool air and feasible region. For this technology to work effectively, it may well require more changes in the road infrastructures to support AI-powered autonomous levels 4 and 5 (smart cities), or it may be that AI-powered passenger carrying drones will get there first.
In the news this month are also reports of how China is racing to catch up with the US on a number of fronts in AI. The US currently leads in the number of papers published on deep learning, which is one of the most successful AI technologies, as well as in the number of active AI companies, including start-ups, and in the number of AI patents applied. These measures indicate how active this space is and how it is rapidly becoming a new economic war front. Of course, only a fraction of the research papers, patents, and AI start-ups will emerge into a further, useful life. There is hype and substance within it all, reflected by the positioning of AI patents and AI start-ups in the AIR check. We will also delve more deeply into AI start-up applications to identify the more promising ventures.
Finally, the chart carries a quote from the media that “AI is a zero sum game”, meaning that the winner will reap all. We don’t believe this is true. First of all, AI is a very widely applicable technology, so there can be many winners. It is an evolving field, so today’s winners may easily be superseded by newer AI technology start-ups, and AI can be a win-win for society, users, and owners of the technology. To play devil’s advocate we can assume the writer meant that some one party may create the most advanced AI machine and reap the rewards of the world running to their doorstep to buy this technology. I think this is most unlikely, AI research at a basic level is incredibly open, not just within academia but even commercial research laboratories such as Amazon, Facebook, Google DeepMind, and Microsoft openly publish research findings and share open source code. Applications of AI are also highly specialized so a commercial venture will typically dominate at best just one narrow domain. There is also a divide amongst vendors on the software and hardware sides of AI. Nvidia’s very dominance in GPUs, for example, has given rise to massive venture capital investment in competitive products. Where things stand today, AI is an open game, which I believe is more win-win overall. Hence, this comment is placed in the hot air - impractical region in the AIR check.
The long-term view of AI is shown in Figure 2. Currently we are in the machine intelligence or assisted intelligence stage of AI evolution. Deep learning, the most successful of current AI technologies, has further potential, but today it is still a technology that is very limited when compared to human intelligence. Singularity or transcendence is the point where AI machines are cleverer than humans and can be better in designing the next generation of AI machines and so forth.
Michael Azoff, Principal Analyst, IT Infrastructure Solutions
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