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In 1968, Stanley Kubrick’s 2001: A Space Odyssey introduced the world to HAL and what the future of artificial intelligence (AI) might look like: An ever present voice ready to help out wherever its human needed help.
By 1997, IBM had publicly showed off it’s work in AI by having their supercomputer “Deep Blue” crush the then world master chess champion, Gary Kasparov.
In 2011 IBM’s Watson project took on two champions of the game show “Jeopardy!” and soundly took the million dollar prize in a series of three rounds. 
Jump ahead to today and we are literally surrounded by AI technologies shaping our daily experience: driverless vehicles, predictive internet searches, voice activated assistants in our smart homes and on our smart phones, automated stock market trading, bank fraud alerts, purchasing suggestions from Amazon, movie suggestions from Netflix and YouTube, music suggestions from your favorite music streaming service… I could go on and on.
Artificial intelligence is the new technological megatrend and companies are racing for the lead. AI has become a disruptive technology, changing the rules of how we interact with our world and the future.
And the sector is heavily investing in the technology.
Gartner estimates that spending will grow at an average compound annual rate of 18% to $383.5 billion by 2020.
According to a recent report from McKinsey, Alphabet (Google) invested roughly $30 billion in developing AI technologies. Baidu, which is the Chinese equivalent of Alphabet, invested $20 billion in AI in 2017.
We’re a data-rich society and we have been for years… What AI does is allow us to take data and turn it into knowledge. To have a billion pieces of information is useless unless you can distill it into something meaningful.
—Jonathan Schaeffer, computing scientist and dean
of the University of Alberta’s Faculty of Science
Businesses are drowning in data and they are looking for ways to interpret that data into something actionable. AI and machine learning are the answer to this data overload dilemma.
That data analysis is already being used for things such as fraud detection in banking and optimal route mapping in transportation logistics. Insurance companies deploy predictive risk modeling to gain a competitive edge, while doctors turn to machine learning to help improve patient diagnoses.
AI is the most powerful technology force of our time. Its first phase will enable new levels of software automation that boost productivity in many industries.
— Jensen Huang, Nvidia CEO
Like any disruptive technology, there are winners and there are losers. The task of the investor is to look into the crystal ball and try to predict where the winners will be and place your investments wisely in those areas.
Stay with me here as I show you the developing trends in artificial intelligence as I see them, and later some investment ideas to add to your research list.
Most applications of AI are still young and in development, but trends are starting to form. I see the following trends as areas to look into for investment opportunities in the maturing Artificial Intelligence space.
1. Logistics are becoming increasingly efficient
We are entering a world in which it will be possible to run a 20,000-square-foot distribution center with a skeleton crew. Companies like Kiva Systems — now Amazon Robotics — use a combination of artificial intelligence and advanced robotics to provide big box retailers with unprecedented logistics solutions
Research ideas: While Kiva Systems has already been acquired, look for other robotic or automated warehouse innovators for possible opportunities.
2. Auto manufacturers are rolling out self-driving cars
Tesla was one of the first auto makers to launch a self-driving vehicle. In their effort to keep pace with Tesla, traditional automakers like Audi are poised to release their own self-driving cars.
The Audi A8 will feature self-driving technology capable of safely shuttling humans without driver input. Cadillac and Volvo are also developing advanced self-driving technology, which will become available to the consumer shortly.
Research ideas: sensors, cameras, image recognition software.
3. Machine learning will aid workers in their tasks
AI technology is helping workers make educated decisions about how to better perform their tasks, and in some cases actually perform the task for them.
For example, tools like Gong, Chorus and Jog are able to record calls made by sales and customer service representatives. “This technology can coach customer-facing service workers to speak more effectively, thanks to machine learning algorithms. Expect AI to increasingly support white-collar workers,” explains Carrie Christensen, Operations VP of Mint Solar.
Research ideas: business intelligence software, sales software, Splunk.
4. Video and written content is being created using AI
Brands like USA Today, CBS and Hearst are already using AI technology to generate content. For example, Wibbitz offers a software-as-a-service (SaaS) platform that allows publishers to turn written content into video content through AI video production.
Publishers used to spend hours, if not days, creating content for their websites or for social media. Tools like Wibbitz are now helping publishers create compelling videos in minutes.
Similar to Wibbitz, the Associated Press is using a tool called Wordsmith, created by Automated Insights, to apply natural-language generation in order to create news stories based on earnings data.
Research ideas: automated writing software, automated video software, automated image slide show software.
5. Consumers are becoming accustomed to talking with technology
It’s estimated that over 20 million Amazon smart speakers were sold last year. If you add sales of other smart devices like Google Home and Apple Airpod, you realize that tens of millions of Americans are getting used to interacting with technology through voice commands.
Research ideas: voice recognition software
6. AI is helping doctors make better diagnosis
“We are entering a time where a peer-to-peer network of computers could have the capability of solving some of the world’s most challenging health problems by collecting and analyzing human molecular data,” explains Ben Hortman, CEO of Bet Capital LLC.
Now, what if those computers were powered by chips smaller than the head of a pin with secure, built-in AI and cryptocurrency technology? What sounds like something out of a science fiction novel, is now a reality thanks to Nano Vision.
Machine learning technology is being used to identify and analyze illnesses, and to enable new drugs, treatments and cures at a fraction of the time and cost. And more importantly, with a higher degree of accuracy.
Research ideas: medical nano devices, medical AI device manufacturers
There are a handful of mega corporations that are leading the charge into AI development and deployment.
AI development takes big bucks and a team of specialized computer scientists to pull off. The majority of AI investment opportunities are with the larger companies because they have the deep pockets to fund the research.
While those companies offer some investment security, the gains will be less than those smaller innovative companies that are being acquired by the likes of Alphabet and IBM.
Below I offer some investment ideas that you can further research.
Google CEO Sundar Pichai recently spoke at Google’s developer conference, and showed off some of their latest advances in AI tech. The Google Lens (a camera that can recognize what it sees) and AutoML (a suite of machine learning products that enables developers with limited machine learning expertise to train high-quality models specific to their business needs) both use neural networks to build better neural networks, essentially creating an AI that can create itself.
Alphabet employs AI to find the most relevant search results for its users. They also use it in their text-to-speech applications for its language translation app, and has even designed its own AI chips for its Google Cloud servers.
But the most notable way Alphabet is betting on AI is through its self-driving car company, Waymo. The company uses artificial intelligence that allows its autonomous vehicles to recognize and analyze images in real time and determine whether there are road signs to be followed, pedestrians to be avoided, or fellow vehicles in their path.
The company will launch a commercial self-driving service, and some analysts forecast Waymo will be worth $70 billion by 2030 — or potentially even $140 billion, by less conservative estimates.
These days, the so-called Watson platform sits at the very heart of IBM’s business plans.
The transformation from an IT business to an AI-centric business has been long and painful. But IBM’s “strategic imperatives” have been collecting more than half of Big Blue’s quarterly sales all year long. The strategy shift appears to be in its final stages and it looks like an opportune time to take a closer look at this stock.
I always like the newcomers as the upside potential can be multiples higher. There are many business that are working in AI development. While they are smaller, that doesn’t mean they are any less valuable. As I mentioned above, the big boys in AI are actively searching for innovators in the AI space and adding them to their business.
These require more work on your part to be the detective and do the research, but the payoffs can be huge.
Here are a few companies that I discovered that may be worth checking out further.
While traditional data analysis tools are slow and may require multiple steps of data prep from the IT department, Alteryx solutions feature intuitive visual workflows and a drop-and-drag interface, which eliminates the need to write any code.
FPGAs can be, as the name suggests, programmed and reprogrammed on the fly by a coder that needs a device to do something not previously foreseen. That’s in contrast with ASIC chips, or Application-Specific Integrated Circuits, which can only be programmed once at the time as they’re being manufactured.
It seems like a minor benefit, but the flexibility of FPGAs has proven indispensable in many machine learning environments, and edge computing in particular.
It’s not the high-end artificial applications like self-driving vehicles. Rather, much of Xilinx’s wares are the low-brow stuff, like managing sensors that make Internet of Things (IoT) networks work as they should. That’s where the tangible, practical opportunity is though.
Within the AI and deep-learning space, CEVA is focusing on fast-growing markets like automotive, augmented reality, and smart homes, among others. This stock has a nice recent chart and on the upswing!
The company also licenses its deep neural network frameworks to chipmakers for enabling AI applications in their devices. Apple, for instance, is reportedly using CEVA technology to power the much-hyped Neural Engine inside the new iPhone’s A11 Bionic processor.
There might not be a single technological advancement that exists today that has as much potential to transform businesses and the world like artificial intelligence. It has already found its way into many aspects of our daily lives, and this is sure to grow in the coming years.
That’s why it is important for investors to get engaged now and do their research in order to stay on top of the movers in the space.
This could prove to be a very good entry point, as many of the companies discussed are on an upward trend, while valuations are seemingly reasonable.
The use of artificial intelligence is only going to increase, providing strong growth opportunities for companies exposed and focused on the trend. Don’t get left behind.
MF Williams, Contributor
for Investors News Service
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