Within artificial intelligence, deep learning innovations are finding their way into the real world, from self-driving cars to voice-activated devices. And investors are taking notice.
You’ve probably heard of artificial intelligence (AI) and the innovative products it’s spawning, from self-driving cars to voice-activated devices. Artificial intelligence is an area of computer science focusing on how machines can learn from experience. The next wave of technological transformation in artificial intelligence might be “deep learning,” which is essentially the complex process of how machines can learn by example and develop solutions from big data with limited human supervision.
Many investors are watching how some major tech companies incorporate this evolutionary concept, which will likely be found in nearly every sector. And that’s a reason why many firms, from technology to health care and financial, are competitively seeking ways to harness its capabilities, incorporating it into their products and systems, and pushing it toward the share-driven community of open-source development.
Keep in mind that like any investment in a burgeoning industry, investments in deep learning do carry risks. First, consider that the technology sector is generally riskier than other sectors because it is changing rapidly with new developments. This sector is generally more volatile than, say, health care or utilities. Also, remember that start-ups that are successful can offer high rewards, but start-ups can also have a high failure rate. One way to invest in deep learning that may carry lower risk than direct investment in startups is to buy shares of a bigger, established public company that has deep learning initiatives.
If you’re looking for investment opportunities in this market, you should have a good understanding of how deep learning has been playing a role in a number of major companies and industries.
Deep learning solutions are already solving real-world problems. In health care, its potential includes tailoring treatments according to a patient’s genomes. In retail and service industries, companies are using it to improve customer service such as for self-service technologies. In media, it can be used to intuitively add color into black and white images or video.
Here’s a brief look at how three major players are implementing deep learning now:
Ultimately, what might be at stake in deep learning is its potential to empower a large body of existing technologies, which in turn may affect new and emerging industries.
Investors are likely to find that the market for deep learning includes opportunities to benefit from the potential for an acquisition, which often significantly increases the market value of a company. The deep learning market may generate up to $261 billion by 2027, according to a Persistence Market Research report. As this is a budding market, investors can tap into this market in a variety of ways. There are generally two categories of “players”: small startups and large tech companies, many of which have increased their acquisitions of the smaller startups.
Acquisitions of AI-based startups jumped by 44% in 2017; a total acquisition of 115 companies compared with only 22 companies acquired in 2013, according to tech research firm CB Insights, whose own platform is powered by machine-learning AI.
Here’s a shortlist of AI and deep learning startup acquisitions by large tech firms:
The tech giants and others have a growing number of startups in deep learning that could serve as potential future acquisition targets. And these companies are increasingly well funded, with more of CB Insight's top 100 startups in deep learning advancing past seed funding to advanced funding stages.
The list is extensive, but it includes companies focusing on agriculture, automobiles, government initiatives, software development, retail, real estate and health care, just to name a few. The most well-funded start ups on the list include SenseTime, a software company using deep learning for visual things like facial recognition, with $1.63 billion in equity funding, according to CB Insights. Face++, another company with facial recognition technology, has secured $608 million in funding, and Zymergen, which develops new ways of making products by using machine learning, has secured $574 million.
Startups like Butterfly Network, Paige and IDx are among the numerous new companies in health care that use artificial intelligence. In retail, startups attracting investments include TwentyBN and Abeja. And in cybersecurity, firms like Vectra Networks, Agari Data Inc. and Area 1 Security have also been attracting attention lately with their deep learning innovations.
Other companies investors can watch for investment opportunities or for acquisition targets by larger firms expanding in deep learning include Boston-based Voysis, which is aiming to fine-tune voice AI for the business and consumer sectors, and Austin-based Boxx, with technology to improve workflow. Then there’s TwoSense.AI, which is working on using behavioral biometrics for better authentication that can prevent fraud.
Research is an important component of any sound investing strategy. One way to begin looking into particular companies is to use TD Ameritrade’s screener tools, which can search specific companies or industries you may be interested in. With these screeners, you can find stocks, options, mutual funds and ETFS that suit your specific needs.
Once you’ve found a company you may want to invest in, you can access research and set up alerts to monitor stock price changes, earnings and other information.
for thinkMoney ®
Financial Communications Society 2016
for Ticker Tape
Content Marketing Awards 2016
Content intended for educational/informational purposes only. Not investment advice, or a recommendation of any security, strategy, or account type.
Be sure to understand all risks involved with each strategy, including commission costs, before attempting to place any trade. Clients must consider all relevant risk factors, including their own personal financial situations, before trading.
Inclusion of specific security names in this commentary does not constitute a recommendation from TD Ameritrade to buy, sell, or hold.
TD Ameritrade and all third parties mentioned are separate and unaffiliated companies, and are not responsible for each other’s policies or services.
Market volatility, volume, and system availability may delay account access and trade executions.
Past performance of a security or strategy does not guarantee future results or success.
Options are not suitable for all investors as the special risks inherent to options trading may expose investors to potentially rapid and substantial losses. Options trading subject to TD Ameritrade review and approval. Please read Characteristics and Risks of Standardized Options before investing in options.
Supporting documentation for any claims, comparisons, statistics, or other technical data will be supplied upon request.
This is not an offer or solicitation in any jurisdiction where we are not authorized to do business or where such offer or solicitation would be contrary to the local laws and regulations of that jurisdiction, including, but not limited to persons residing in Australia, Canada, Hong Kong, Japan, Saudi Arabia, Singapore, UK, and the countries of the European Union.
TD Ameritrade, Inc., member FINRA/SIPC, a subsidiary of The Charles Schwab Corporation. TD Ameritrade is a trademark jointly owned by TD Ameritrade IP Company, Inc. and The Toronto-Dominion Bank. © 2022 Charles Schwab & Co. Inc. All rights reserved.