Tech firms turn to self-replicating AI to make up for talent shortage
SOME of the world’s biggest technology firms are working on self-replicating artificial intelligence programs and machines in order to make up for the lack of talent in the field.
With hundreds of artificial intelligence-powered tools set to roll out over the next few years, the tech industry is hungry for talent. Think of any forthcoming technology that you might be even remotely excited and they will inevitably include some form of artificial intelligence: self-driving cars, facial recognition, autonomous drones, cityscapes that can measure temperature and traffic. Each of this requires a little kick of artificial intelligence.
However, according to industry estimates only about 10,000 people across the world have the education, experience and talent needed to build complex, mathematical algorithms that are key to building AI-based technology. Today, the biggest technology companies in the world, from Baidu to Google to Microsoft, are shelling out millions in order to draw and retain AI experts.
The shortage of these talents is leading to concerns about the ability of smaller incumbents to make any headway into the monopoly created by these big firms, though many are turning to AI itself to overcome the issue.
According to a report from the New York Times, companies are investing heavily in AI technology research and development that can circumvent the difficulty of building AI products that are meant to do smaller tasks. These include image and speech recognition tools, and online chatbots, both of which have proliferated over the years.
There are now tiny boutique firms offering drag-and-drop, customizable versions of these technologies that allow even small enterprises to include AI-powered tools into their business, alongside the offerings from bigger firms, such as Google’s open source artificial intelligence engine, a similar product by Microsoft, and an Amazon machine learning project.
Researchers at these firms are also working on AI systems that reduce its dependence on human labor. Google’s AutoML – ML is a shorthand for “machine learning”, a subsection of artificial intelligence tech – is a long-running project by the company, targeted at producing computer algorithms that are programmed to run certain tasks based off data analyses that don’t require human intervention.
Google’s AutoML will put this complex technology into the hands of businesses without extensive expertise in AI, given that many already have strong data legacies which are crucial to setting up machine learning processes.
“We want to go from thousands of organizations solving machine learning problems to millions,” said Google CEO Sundar Pichai, according to NYT.
“We are following the same path that computer science has followed with every new type of technology,” said Joseph Sirosh, a vice-president at Microsoft, to NYT. “We are eliminating a lot of the heavy lifting.”
Eventually, the Google project will help companies build systems with artificial intelligence even if they don’t have extensive expertise, Dean said. Today, he estimated, no more than a few thousand companies have the right talent for building AI, but many more have the necessary data.
Alongside Google, Microsoft recently launched a development tool that will help coders create “deep neural networks”, that is a kind of algorithm that has driven much of the recent progress in the AI industry.
This new kind of tech has the potential to scare up a lot of money throughout the industry. Enterprises unwilling to startup their own AI labs will likely lean heavily into this new breed of corporate services, especially as more begin pivoting to digital networks and data systems.
“There is real demand for this,” said Matt Scott, a co-founder and the chief technical officer of Malong, to NYT. His startup in China offers similar services to Microsoft. “And the tools are not yet satisfying all the demand.”
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