Artificial Intelligence

Report: Why the big challenges in AI aren't close to being solved

A recent Edison Investment Research report said that artificial intelligence is poised to improve digital life, but it has yet to solve the problems facing it.

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Image: iStockphoto/ktsimage

As tech companies continue to dump mountains of cash into artificial intelligence (AI) development, the technology promises to greatly improve our digital lives. However, the AI ecosystem still has major problems to solve before it can advance, a new report said.

The report, released Friday from Edison Investment Research, said that AI has the potential to be a major differentiator but it is still in the early stages of its development. Most of what is referred to as AI, currently, is "simply advanced statistics," the report claims.

SEE: Understanding the differences between AI, machine learning, and deep learning

According to the Edison Investment Research report, there are three goals that must be solved for AI to move out of its infancy.

  1. AI system must be able to be trained using less data than they are currently trained on.
  2. AI systems must be created that "can take what it has learned from one task and apply it to another."
  3. AI systems need to be able to build their own machine learning models, rather than relying solely on humans to build the models.

The company that performs the best in solving these problems is likely to move ahead of its competitors, the report noted.

For most companies, the initial investment in AI comes in the form of a digital assistant or chat bot. These tools are often being offered free of charge, or folded into other core products, in order to generate and collect the data needed to strengthen the AI behind them. Digital assistant are "a good first yardstick of each ecosystem's competence in AI," the report said.

AI is built on data, as is another product many people use everyday: Search engines. As such, it makes sense that companies like Google, Baidu, and Russia's Yandex are growing leaders in the AI space due to their focus on data-powered search. Under these leader, companies like Microsoft, Apple, and Amazon are also investing heavily in their own AI efforts as well.

"Both Microsoft and Amazon have scope to earn a return on AI in their businesses that are not part of the ecosystem," the report said. "Apple appears to have voluntarily hobbled its AI development with differential privacy."

Facebook, however, was ranked much lower in the report. Edison researchers even called it a "laggard with one of the weakest positions in AI globally." The core issues that Facebook is facing have to do with its inability to properly leverage automation, and its late start in the market. Additionally, Facebook's disastrous attempt to automate the removal of fake news further demonstrated how weak its AI was.

"The net result is that without a human element, almost all of Facebook's services that depend on AI tend to fall over pretty quickly," the report said.

At this point, many of the tech playter investigating AI solution are struggling to make sense of their own data, the report noted. However, with investment ramping up in the space and competition increasing, the AI market is ripe for development.

"The big ecosystems are all very well-funded and so both their in-house R&D and their M&A activity is likely to increase in 2017," the report said. "AI is also likely to be the buzzword in many of the trade shows in the coming 12 months and for once, it will be more than just hype."

The 3 big takeaways for TechRepublic readers

  1. Tech sector investment in AI solutions is increasing, but there are many problems that need to be solved before the technology can deliver on its promises.
  2. Search engine companies have a head start in AI, as they've been working with data for a long time.
  3. Many companies are struggling to understand their data, but development is ramping up and AI will grow strongly over the next few years.

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About Conner Forrest

Conner Forrest is a Senior Editor for TechRepublic. He covers enterprise technology and is interested in the convergence of tech and culture.

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