Beyond Artificial Intelligence: Investing in Deep Learning

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.

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5 min read
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Key Takeaways

  • Consider both small startups and large tech firms in deep learning investment opportunities 
  • Tech, health care, retail and marketing are among the many niches where deep learning’s role is growing
  • Be aware that some investments in deep learning may carry more risk 

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.

Where Investors Can Notice Deep Learning’s Uses

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.

Deep learning and artificial intelligence: potential uses

Deep Learning’s Impact On Tech and Other Industries

Here’s a brief look at how three major players are implementing deep learning now:

  • Alphabet’s (GOOG, GOOGL) open source software library, TensorFlow, became a hub for machine learning and deep learning software development. It’s been used to help build efficacy within GOOG’s Voice Search tools; to create a deep neural network model for identifying promising drug candidates (a project involving GOOG and Stanford University); and to contribute to the development of optimal AI-generated email responses for GOOG’s Gmail SmartReply.
  • Amazon (AMZN) created Amazon Web Services (AWS) to provide major corporations with software whose learning models are capable of generating accurate customer insights and predictions. Using complex pattern recognition in pictures, text, sounds, and other data, AWS is an example of a deep learning AI application geared toward marketing, one that may provide more accurate and predictive insights toward products that individual customers might desire. 
  • NVIDIA (NVDA) has developed more intuitive GPUs, (Graphic Processing Units) that have been able to capitalize on the effects of parallel processing and GPU-accelerated AI neural networks. This helps NVDA provide its services to clients like Tesla (TSLA), TensorFlow, and MSFT.

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. 

Acquisitions for Deep Learning Are Heating Up

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:

  • GOOG: CleverSense (2012); DNNresearch (2013); DeepMind, Jetpac, and Emu (2014); Dark Blue Labs, Vision Factory, Granata, and Timeful (2015); Moodstocks (2016); API.ai and Halli Labs (2017); AIMatter and Banter (2018).
  • AAPL: Siri (2010); Novauris Technologies (2014); Perceptio and Vocal Q (2015); Emotient, tuplejump, and Turi (2016); SensoMotoric, Lattice, and RealFace (2017); Regaind, Init.ai, and Pop Up Archive (2018).
  • FB: Face.com (2012); Mobile Technologies (2013); Wit.ai (2015); Masquerade Technologies (2016); Zurich Eye (2017; Ozio (2018).
  • AMZN: Evi Technologies (2013); Orbeus (2015); Harvest.ai and Angel.ai (2017); Sqrrl (2018).

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.

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Key Takeaways

  • Consider both small startups and large tech firms in deep learning investment opportunities 
  • Tech, health care, retail and marketing are among the many niches where deep learning’s role is growing
  • Be aware that some investments in deep learning may carry more risk 
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