In the twenty-first century, AI techniques have experienced a massive surge in interest following concurrent advances in computer power, large amounts of data, and theoretical understanding. Companies are focused on it, Google has rebuilt their software around it, and Mark Zuckerberg personally hires and pays AI engineers seven figure salaries right out of graduate school. AI is simply the hottest area in technology.
But, what exactly is AI, and how can it impact your investments? These are the questions we will try to explore in this week’s newsletter.
The following excerpt is from an article titled The Great AI Awakening and appeared in The New Yorker Magazine in December 2016.
Late one Friday night in early November, Jun Rekimoto, a distinguished professor of human-computer interaction at the University of Tokyo, was online preparing for a lecture when he began to notice some peculiar posts rolling in on social media. Apparently Google Translate, the company’s popular machine-translation service, had suddenly and almost immeasurably improved. Rekimoto visited Translate himself and began to experiment with it. He was astonished. He had to go to sleep, but Translate refused to relax its grip on his imagination.
Rekimoto wrote up his initial findings in a blog post. First, he compared a few sentences from two published versions of “The Great Gatsby,” Takashi Nozaki’s 1957 translation and Haruki Murakami’s more recent iteration, with what this new Google Translate was able to produce. Murakami’s translation is written “in very polished Japanese,” Rekimoto explained to me later via email, but the prose is distinctively “Murakami-style.” By contrast, Google’s translation — despite some “small unnaturalness” — reads to him as “more transparent.”
The second half of Rekimoto’s post examined the service in the other direction, from Japanese to English. He dashed off his own Japanese interpretation of the opening to Hemingway’s “The Snows of Kilimanjaro,” then ran that passage back through Google into English. He published this version alongside Hemingway’s original, and proceeded to invite his readers to guess which was the work of a machine.
Kilimanjaro is a snow-covered mountain 19,710 feet high, and is said to be the highest mountain in Africa. Its western summit is called the Masai “Ngaje Ngai,” the House of God. Close to the western summit there is the dried and frozen carcass of a leopard. No one has explained what the leopard was seeking at that altitude.
Kilimanjaro is a mountain of 19,710 feet covered with snow and is said to be the highest mountain in Africa. The summit of the west is called “Ngaje Ngai” in Masai, the house of God. Near the top of the west there is a dry and frozen dead body of leopard. No one has ever explained what leopard wanted at that altitude.
Even to a native English speaker, the missing article on the leopard is the only real giveaway that No. 2 was the output of an automaton. Their closeness was a source of wonder to Rekimoto, who was well acquainted with the capabilities of the previous service. Only 24 hours earlier, Google would have translated the same Japanese passage as follows:
Kilimanjaro is 19,710 feet of the mountain covered with snow, and it is said that the highest mountain in Africa. Top of the west, “Ngaje Ngai” in the Maasai language, has been referred to as the house of God. The top close to the west, there is a dry, frozen carcass of a leopard. Whether the leopard had what the demand at that altitude, there is no that nobody explained.
Rekimoto promoted his discovery to his hundred thousand or so followers on Twitter, and over the next few hours thousands of people broadcast their own experiments with the machine-translation service. Some were successful, others meant mostly for comic effect. As dawn broke over Tokyo, Google Translate was the No. 1 trend on Japanese Twitter, just above some cult anime series and the long-awaited new single from a girl-idol supergroup. Everybody wondered: How had Google Translate become so uncannily artful?
The answer was simple…the technology behind the translation was learning and improving itself. It was exhibiting Artificial Intelligence (i.e. machine learning) and, as a result, making dramatic improvements all on its own.
In a nutshell, AI is the ability of a computer to take an ever expanding data set (the bigger the better) and learn from it. If Google Maps sees traffic going slowly on one road, it reroutes you on another. That is artificial intelligence. If Facebook sees the Zac Brown Band trending on users with similar qualities as you, an ad for their next concert might appear. That is artificial intelligence.
AI is on its way to becoming ubiquitous in our lives. According to an article, How to Invest in Artificial Intelligence, by The Motley Fool, it will be a $46 billion industry within three years. NVIDIA (NVDA) is a name cited in the article as its graphic processors are used heavily by AI computing machines. Here’s a breakdown of what NVIDIA sees at its primary artificial intelligence markets, along with its total addressable market in each:
Besides Nvidia, Amazon (AMZN), Facebook (FB) and Google (GOOG) are three obvious ways to invest in Artificial Intelligence. They have their tentacles in at least one if not all of the above categories. However, they are also behemoths with incredibly high market caps, large businesses outside of AI, and valuations that assume a lot of success in the future. It’s likely they will achieve this success to a large degree, but will investors benefit from here? Maybe not in an outsized way any more…
At Tailwinds, we are focused on finding small companies with disruptive technologies. These companies, to enter our portfolio, have to have the chance to return many multiples on investment.
Disruptive technologies come in many forms. For some companies, like ChromaDex, they are simply a new product that will likely gain massive market share. However, for other companies, their disruption is not in a new technology or product at all…it is taking technology that already exists and using AI to make that technology smarter and more useful.
Like Google Maps taking Garmin to the next level, we have four companies in our portfolio who are using currently available technologies and, with the help of machine learning and big data analytics, are making disruptive changes to existing industries. While they are not developing AI, they are using it to develop their products. The result being that disruptions to large, existing industries are coming and these companies are pure-plays not on the development of AI, but real world applications thereof.
The Four Tailwinds’ AI Plays:
1. Remark Holdings (MARK). True, MARK touts itself as an AI play, but they are more than that. They have developed the tools to take large amounts of data and are now developing real world products around it. The best example of this is in China, where consumer lending is a large and growing business, but there are no credit scores or equivalents for lenders to gauge the creditworthiness of borrowers. Enter Remark who, through a partnership with Alibaba, has data on 1.3 billion consumers. They have the ability to determine “social” creditworthiness, which actually works well. Lenders use them to qualify borrowers, which they do by looking at their social media and online shopping interactions. Using Artificial Intelligence, they can very accurately determine if a borrower is likely to repay or not. This is just one example of a product they can offer that is disrupting a traditional business; small consumer loans in China. For their KanKan AI subsidiary, Remark is guiding to at least $30M in sales in 2018 from $6M in 2017. Boom!
2. Catasys (CATS). Investors look at CATS as a company that is performing outpatient treatment on patients with mental health disorders, i.e. anxiety, depression and addiction. However, understanding why the largest healthcare insurers in the US allow CATS to access their database of enrollees helps you realize the disruptive AI part of their solution. It’s not the patient engagement that is different; there are many rehab facilities in existence, obviously, and many doctors focused on this. No, what makes CATS unique is their ability to use AI to determine individuals suffering from these diseases; a determination based on patterns recognized by AI and undetected by the insurers on their own. They then, also, use AI in evaluating their patient engagements. By using AI and natural language processing, CATS is finding and helping individuals that were, previously, a major cost for insurers due to their undetected mental health diseases. AI is helping CATS disrupt a multi-billion dollar industry. This is why seven of the eight largest insurers in the US are current, or in the very near future, clients of Catasys and why their billings will more than double in 2018…and, likely spike much higher in 2019. Pow!
3. ITUS (ITUS). This Company has two business lines, but AI is the secret sauce of their unique cancer diagnostics that they are developing. ITUS is taking blood samples and running them through an existing piece of lab equipment (a flow cytometer) and looking at the levels of MDSCs (Myeloid derived suppressor cells) to determine the presence of cancer. Nothing they are doing, in terms of the lab work, is unique. You could have ordered a blood test to look at MDSC levels years ago. What is unique is their use of AI to determine trends of MDSC levels as they relate to healthy or cancer-stricken individuals. As their dataset grows, ITUS believes they will be able to determine the type and stage of any kind of cancer through this AI diagnostic methodology. So far, clinical tests are showing that it works. Thus, by taking an existing test and overlaying Artificial Intelligence diagnostics on top of it, ITUS is on the verge of disrupting the whole cancer diagnosis industry and, potentially, saving millions of lives and billions of healthcare dollars. Kaboom!
4. Patriot One (PTOTF). Very similar to ITUS, Patriot One is taking existing technologies and making them smarter, which then allows them to work in unique ways. PTOTF is building radar scanners that will screen individuals (unobtrusively and safely) as they walk by, looking for concealed weapons. In and of itself, this could have been done decades ago. The issue is that the results of the screening would have been undecipherable. However, by overlaying an AI analysis on the data from the scanners, Patriot One can detect the unique signatures given off by weapons passing by the detectors. The key to this is developing a data set that accurately recognizes each type of weapon, be they a gun, knife, etc., while also recognizing, and disregarding, non-lethal items such as cellphones and coffee mugs. Patriot Ones systems are just now starting to get installed in several locations. During this initial phase, they will be gathering data in real world applications…data that will go into their database and make them smarter and smarter. Through machine learning, their ability to recognize and detect weapons will improve daily. Forever. And, in doing so, Patriot One will soon be offering an ever-improving method of screening for hidden weapons that rivals metal detectors in effectiveness, yet is unobtrusive and doesn’t affect the consumers’ interaction with a venue. Security is a multibillion industry and, through the use of AI, Patriot One is on the verge of disrupting it in a big way. Kapow!
These four companies are all on the leading edge of using Artificial Intelligence in real world applications. In each case, sales of their products are small to non-existent currently. However, the opportunity for astronomical growth exists for each company and, with the exception of ITUS who requires FDA approval, is starting to happen right now.
AI will be a disruptive force for the planet. The companies that take advantage of the strengths of AI will be the winners of the next generation. Several large companies are known beneficiaries of AI. Yet, there are numerous, lesser-known, companies on the verge of disrupting their respective industries using AI that are off the radar screen. These are the opportunities that Tailwinds seeks to find. We have given you four and are looking for more.
Disclaimers & Disclosures: For a full list of disclaimers and disclosures, please visit: www.tailwindsresearch.com/disclaimer/