Artificial intelligence is the new frontier

In the beginning, there was Big Data. Then, taking centre stage and the spotlight, marched the quantitative analysts (quants) and their algorithms. Then Artificial Intelligence (AI) came along and stole the spotlight.

Artificial_IntelligenceThere is, perhaps, something absurd, maybe even oxymoronic, in writing about something called artificial intelligence. After all, who but us humans can possess wisdom? And, can the very attribute that allows us to sit at the top of the food chain, intelligence, be replicated in other beings, organic or not? And can machines be infused with such an ineffable attribute, wisdom? For now, our answer is ‘No’, Watson withstanding. Yes, a machine can be smart, but can it be intelligent? For the time being, and only for the time being, the answer is also ‘No’. But perhaps only for the time being.

Artificial intelligence (AI) involves programming a computer to perform cognitive functions such as learning and thinking. This is usually referred to as machine learning, which essentially sees a computer learn patterns from data and use those patterns to analyze and make predictions about new data. (Deep learning, another commonly used term in the field, is a specific machine-learning technique.)

AI is just about everywhere today, and shows no sign of becoming a fad. Almost any organization uses it, and many more are thinking of using it. A good number of investors are pouring money into stocks of companies that make artificial intelligence apps or that are run on those apps. A good number are thinking of putting their money into those companies. And why not? If the platform powering many companies’ operations is not artificial intelligence, then it will be before too long.

Surprisingly, perhaps, Canada is a leader in the field. With three established AI centres in Montreal, Toronto and Edmonton—each led by a world recognized superstar—and a $125 million federal government gift to fund a Pan-Canadian AI strategy, this country is among the global top five in the field. If Yoshua Bengio, Jeffrey Hinton and Richard Sutton are not household names, they will be—tomorrow.

From financial services to healthcare to supply chains, to common algorithms, which are fed and analyze data, applications abound. In Fintech, staff is streamlined, as are call centres and back office functions. Reduce the head count by 1,500 because artificial intelligence apps enable banks to do so—and investors roar. In health care, more people are managing their well-being and are going online to diagnose and self-administer. In supply chains everywhere, AI is sensing, detecting and correcting inaccurate or even corrupted data. And in financial services, a robo-advisor selects the best investment for an individual.

The MoneyLetter is not a robo-advisor, but we can help a little to separate the wheat from the chaff. To say that the AI bandwagon is gathering momentum is an understatement. To say that more investors are becoming more interested in AI stocks is also an understatement. To help separate the wheat from the chaff, The MoneyLetter has compiled a list of AI companies that a number of investment experts and web sites prefer. We describe them below. A cautionary note: These are not recommendations, merely companies that have established a beachhead in the field of AI and that appear to be among the leaders.

Kinaxis Inc. (TSX—KXS)

Ottawa-headquartered Kinaxis is in the cloud-based, supply chain management services business, and has already blown through analysts’ price targets. It has identified several business operations that could benefit from AI, such as detecting and correcting master data, and forecast sensing. (See comments on Baidu for the importance of data. “AI is all about the data.”) It’s also improving supply chain management’s predictive capabilities. Analysts expect Kinaxis’ business volume to increase dramatically, with high growth rates in the coming years. Activity appears to be highly profitable thanks to the company’s ability to outperform net margins and analysts remain confident with respect to the group’s activities. More often than not, they have revised their earnings per share estimates upwards.

VersaBank (TSX—VB)

With its tiny market cap of  $145 million, Canadian chartered bank VersaBank is much smaller than the big banks, but also much cheaper. The bank operates as an online banking alternative with no branches to maintain. The business model is similar to other online banks such as Equitable Group Inc., where the lack of branches frees up capital to offer higher interest rates to depositors. It is also investing in block chain-based savings accounts in hopes of staying ahead of other traditional banks in technological innovation. Over the last year, VersaBank managed to increase net income by 102 per cent and earnings per share increased by 157 per cent. These numbers are quite astounding, even more so since this company is not priced for growth at its modest valuation. VersaBank also offers investors a dividend, albeit a small one. At the current stock price, the dividend is around 0.43 per cent, not at all as large as the 3-4 per cent yields currently offered by the larger banks.

Nvidia Corporation (NASDAQ—NVDA)

Established leader Nvidia is leveraging demand for AI-induced offerings by supplying companies looking to take advantage of growth opportunities. Its Metropolis platform enables governments to use AI-powered software to analyze video feeds for monitoring activities. It’s also leveraging an AI-enabled, new technology to enhance slo-mo video without the pain of collecting the massive amounts of data while shooting slo-mo video on smartphones. The new technology converts 30 frames-per second video into 240 or 480 frames. Nvidia’s computing platform, combined with its proprietary interconnect and AI software that handles inferencing, makes it uniquely positioned to capitalize on the next wave of intelligent computing.

Microsoft Corporation (NASDAQ—MSFT)

‘Big Kahuna’ Microsoft just bought AI startup Bonsai to enhance its research by leveraging its Azure cloud platform. Bonsai specializes in reinforcement learning, which can train autonomous systems to complete specific tasks. This is the third Microsoft AI-related acquisition in last 2 years, after Maluuba and SwiftKey. The giant also launched Bing, which leverages AI to perform quick object recognition on photos.

Zendesk Inc. (NYSE—ZEN)

Zendesk, a software development company, is anchored by its flagship product Zendesk Support, an AI-powered system for tracking, prioritizing, and solving customer support tickets across various channels. The company also offers Zendesk Chat, a live chat software to connect with customers on Websites, in applications, and on mobile devices; Zendesk Talk, a cloud-based call center software; Zendesk Guide, a knowledge base that for customer self-service and support agent productivity; Zendesk Message, a customer messaging software; and Zendesk Explore, that makes customer data accessible across an organization. In addition, it operates a developer platform that allows organizations to extend the functionality of its family of products, integrate them into internal and third-party systems, and customize the experience for their employees and customers. Analysts believe the company is already a stalwart in the AI field.

Baidu Inc. (NASDAQ—BIDU)

AI is all about data, and China has reserved its regional data for local players. Google talks a lot about breaking through the literal Chinese wall to establish its own search engine there but the country is likely to continue to forbid external, i.e., not Chinese, service providers from operating in the country for some time yet. Remember too that Baidu is the country’s biggest search and mapping company, which puts it in a favorable position for self-driving and digital marketing AI development.

When people talk about artificial intelligence today, what they usually mean is machine learning. Researchers come up with a new model (algorithm), feed it data to help it learn, and then test it in the real world. According to industry pioneer Andrew Ng, the data here is more important than the algorithm itself. That’s because vast computational power is mostly a commodity now and a handful of clever engineers can come up with a relatively robust algorithm. However, the ultimate prize in the AI research world is a giant pool of high-quality data. Following the data will lead to the winners in this space.

This is an edited version of an article that was originally published for subscribers in the October 2018/First Report of The MoneyLetter. You can profit from the award-winning advice subscribers receive regularly in The MoneyLetter.

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