Artificial intelligence has already made a major impact across sectors, including automotive, gaming, finance, healthcare and internet / entertainment, with even Facebook and Google joining the fray.
Touching nearly every aspect of consumer and enterprise technology, and making headway in a variety of other industries, the burgeoning artificial intelligence market provides a wide-ranging investment opportunity. The driving factors behind this technology, top industry applications and the key companies leading the pack will all be explored herein.
Entering the AI Spring
While artificial intelligence as a concept has been around for decades, the evolution of machine learning has brought about a recent “spring of AI,” resulting in more aggressive developments, applications and investment in such technology. First, let’s examine what exactly comprises AI as we currently know it.
According to Mizuho semiconductor analyst Vijay Rakesh, “the term AI is used as a catch-all and includes machine learning (narrow AI) and deep learning (strong AI) as its subsets. Specifically, strong AI would be a system that could do anything a human can, such as planning, recognizing objects/sounds, speaking, translation, creative work and social or business transactions other than physical activity.”
On the other hand, “narrow AI technologies perform specific tasks better than humans can, including, for example, image classification on Pinterest or face recognition on Facebook.”
Industry Applications Create AI Tailwinds
Among the catalysts for the current AI boom are technological and market necessities that incentivize advancement. A broader underlying shift toward applications in the healthcare, insurance, automotive and financial sectors converged with fortified computing powers, availability of historical and real-time data and enhanced cloud / Wi-Fi connectivity to drive AI innovation.
Says Rakesh, “machine learning and deep learning can drive 30-50% further automation across multiple industry groups, redefining tomorrow’s workforce and driving significant productivity.”
For Mizuho’s semiconductor analyst, one of the biggest industries for AI implementation is automotive ADAS – aka: the technology behind self-driving cars. In this market, AI deep learning is set to reduce the 35-40,000 traffic fatalities and millions of traffic injuries that occur every year globally.
As technology (and consumer sentiment) advances, self-driving cars inch closer to the mainstream through AI systems, advanced processors and sensors. “Essentially what the automotive ADAS DL network needs is training. It needs to see hundreds of thousands, even millions of images, until the weightings of the neuron inputs are tuned so precisely that it gets the answer right every time, under all weather conditions: sun, fog or rain,” Rakesh said.
A broader look illuminates the wide variety of industry applications for AI, including:
- Banking – loan approval process automation.
- Trading – identifying patterns, outliers and upcoming market movements through data processing.
- Healthcare – claims approval process efficiency, predicting illness patterns to anticipate medication demand, increased cancer accuracy identification through enhanced analysis of tumors and blood samples.
- Insurance – speeding up the claims approval process in home, flood, and property.
- Customer Service – expedited solutions process by automating customer support call centers
- Security and Surveillance – enhanced identification of legitimate threats through camera recognition.
Equity Investing in the New AI World
For equity-specific AI opportunities, a few companies stand out.
“We see Nvidia as well-positioned for the next decade, and see opportunities for AMD and Intel with field-programmable gate array (FPGA), new AI players and new, massively parallel computing platforms,” Rakesh said.
Continued advances in machine learning will also further increase the need for data center storage – which current estimates place at approximately $18 billion – potentially benefitting a number of players in the market, including AMD.
As Rakesh says, “while we believe Nvidia is currently the top choice for many Deep Learning and AI companies, AMD is well positioned for any increase in high performance GPUs as a key second source, especially as hyperscale and enterprise look to beef up the supply chain.
While the advancement of AI has the potential to impact well known players such as Google, Facebook, Amazon, Huawei and Baidu, it also rewards innovation with smaller players such as Loop AI, Cortical, Numbena and Clarifai asserting themselves as privately-held industry leaders.
When it comes to investing in the future, AI is not only an exciting sector, it’s also a potentially profitable one. With a variety of applications both real and imagined across virtually every industry, it’s safe to say there is nothing artificial about the investment opportunity that AI presents.
Simon Hylson-Smith is a former financial industry editor and currently CEO of Paragon.