Part 2: Easy to Discuss the AI Hype, but What about Substance
With a topic as exciting as artificial intelligence (AI), it’s easy to get wrapped up in the hype. Gartner has even delineated its ‘Hype Cycle’ to more or less codify the emotional journey that frequently accompanies advancements in technology.1 It’s easy to see a new achievement and how exciting it is, but in thinking about an investment thesis, it’s important to step back from the emotion and consider where the rubber really meets the road.
Anthem: What Does ‘Doing AI’ Actually Look Like?2
A Company Using AI
Anthem Inc. is a health insurance company. It was recently reported that Anthem would be working with Google Cloud to generate 1.5 to 2 petabytes of synthetic data.
Pausing for a moment—what is a ‘petabyte’? We are more familiar with gigabytes, in that a two-hour movie might take up 2-4 gigabytes, depending on the video quality used. One terabyte is roughly 1,000 gigabytes and 1 petabyte is 1,000 terabytes. So, a petabyte is it 1 million gigabytes, the unit with which we are more familiar.
Meta Platforms is building a research super cluster focused on training models on an exabyte of data—which is the next step up, and 1,000 petabytes. One exabyte is roughly equal to 36,000 years of high-quality video.3
Secondly, what is ‘synthetic data’? It could be real-world data that has been stripped of personal information and fully anonymized, or it could be completely artificial, generated from deep generative models. An interesting side benefit in using synthetic data, at least possibly, is in how it could mitigate certain biases that have been shown to exist in real world datasets.
So, why does Anthem need to generate 1.5 to 2 petabytes of synthetic data—what problems could that help in solving? The company says that the data will be used to validate and train AI algorithms that identify things like fraudulent claims or abnormalities in a person’s health records. Anthem uses both Amazon Web Services (AWS) and Google Cloud for cloud computing, and the company decided to work more with Google for their capabilities in AI for this specific effort.
Black Knight: Bringing AI to Mortgage Data
On May 4, 2022, Intercontinental Exchange Inc. (ICE) agreed to buy mortgage-data firm Black Knight in a deal valued at $13.1 billion. It is expected to close in the first half of 2023. ICE is known as an operator of exchanges, clearinghouses and other financial market infrastructure, but in recent years it has pivoted into participating in the growing digitization of the housing market. Prior to the Black Knight deal, ICE had purchased mortgage-software firm Ellie Mae for $11 billion. It had also purchased Simplifile, a firm that facilitates the electronic processing of mortgage records.4
Black Knight itself started incorporating AI as a value-added service into their solutions in 2018. It was noticeable seeing AIVA, a mortgage AI digital assistant, being used. This came via the acquisition of HeavyWater in 2018. The company was also very acquisitive in the AI space with Collateral Analytics (automated AI-based real estate data analytics), eMBS (cloud-based analytics platform), Top of Mind (AI-based CRM software) and Optimal Blue (automated loan origination platform). Software solutions represented more than 80% of Black Night’s revenue at the close of 2021.5
Synopsys: Part of the Foundation for ‘Smart Everything’
Synopsys posted a second-quarter profit of $294.8 million, which topped analyst expectations. The market responded particularly well to the firm increasing full-year revenue guidance to a range of $5.0 billion to $5.05 billion, up from a prior target of $4.78 billion to $4.83 billion6.
Synopsys is an electronic design automation company, and it is particularly strong in field effect transistor design, which could provide growth opportunities. Customers of Synopsys include most of the major semiconductor companies. In thinking of the market opportunity for Synopsys, one must consider the increasing demand for ‘smart everything.’ In their investor presentation, Synopsys included a forecast that deep learning chipset revenues could reach $72 billion by 2025, from a level of less than $10 billion in 2018.7
Splunk: Resilience in the Face of Economic Turmoil
Splunk delivered stronger results than the market community was expecting when it reported its results for the quarter ended April 30, 2022. Revenue increased to $674 million, a 34% increase over the prior year. Cloud revenue was $323 million, up 66% year over year for the specific segment. Company leadership indicated that Splunk is not at risk of much impact from current macroeconomic issues because company security budgets do not appear at risk.8
Silicon Motion: Being Acquired by MaxLinear
In early May 2022, it was announced that the Taiwan semiconductor firm Silicon Motion Technology agreed to be acquired by MaxLinear in a deal valued at $3.8 billion.9 Silicon Motion has over 20 years of experience developing specialized processor integrated circuits that deliver market-leading storage solutions that are used in data centres, personal computers, smart phones and in commercial and industrial applications. The portfolio of controller intellectual properties is extremely broad.10
Palo Alto Networks: AI and Machine Learning Could Add Value Across Entire Platform
The Russia/Ukraine conflict has kept a strong focus on cybersecurity so far in 2022, helping Palo Alto’s results. Similar to Splunk, the company does not yet see heightened inflation causing pressure on companies’ cybersecurity budgets. As Palo Alto Networks lays out their view of the market landscape, they clearly indicate that most companies want greater security, but less cybersecurity personnel, opening the door to innovative AI and machine learning solutions. In fact, they note that AI and machine learning should be core to their entire platform.11
Conclusion: Don’t Let the Hype Sour any View of the Action
Hype is dangerous—it can set the bar of expectation too high and lead to inevitable disappointment. Companies in 2022 are taking concrete actions with AI, and while we have listed a few here, this is far from the complete picture. For those interested in an investment vehicle designed to gain exposure to AI, consider the WisdomTree Artificial Intelligence and Innovation Fund (WTAI).
For holdings of WTAI, please click here.
1 Source: https://www.gartner.co.uk/en/methodologies/gartner-hype-cycle
2 Source: Isabelle Bousquette, “Anthem Looks to Fuel AI Efforts with Petabytes of Synthetic Data,” Wall Street Journal, 5/17/22.
3 Source: Suman Bhattacharyya, “Meta Unveils New AI Supercomputer,” Wall Street Journal, 1/24/22.
4 Source: Alexander Osipovich, “Intercontinental Exchange to Buy Mortgage-Data Firm Black Knight for $13.1 Billion,” Wall Street Journal, 5/4/22.
5 Source: Consumer Technology Association.
6 Source: Logan Moore, “Synopsys Stock Is Rising on Strong Review. Analysts See Growth Opportunities,” Barron’s, 5/19/22.
7 Source: https://www.synopsys.com/content/dam/synopsys/company/investor-relations/corporate-overview-investor-q2-2022-final.pdf
8 Source: Eric J. Savitz, “Splunk Stock Rallies as Software Company’s Results Top Estimates” Barron’s, 5/25/22.
9 Source: Lina Saigoal, “Silicon Motion Technology Stock Soars after $3.8 Billion MaxLinear Deal,” Barron’s, 5/55/22.
10 Source: https://siliconmotiontechnologycorporation.gcs-web.com/static-files/7708fce8-a220-49b6-8c11-5dd10b776f5f
11 Source: https://s22.q4cdn.com/606234439/files/doc_presentations/2021/2021-Analyst-Day-Master-Deck_vF.pdf
Important Risks Related to this Article
Christopher Gannatti is an employee of WisdomTree UK Limited, a European subsidiary of WisdomTree Asset Management Inc.’s parent company, WisdomTree Investments, Inc.
There are risks associated with investing, including the possible loss of principal. The Fund invests in companies primarily involved in the investment theme of artificial intelligence (AI) and innovation. Companies engaged in AI typically face intense competition and potentially rapid product obsolescence. These companies are also heavily dependent on intellectual property rights and may be adversely affected by loss or impairment of those rights. Additionally, AI companies typically invest significant amounts of spending on research and development, and there is no guarantee that the products or services produced by these companies will be successful. Companies that are capitalizing on innovation and developing technologies to displace older technologies or create new markets may not be successful. The Fund invests in the securities included in, or representative of, its Index regardless of their investment merit and the Fund does not attempt to outperform its Index or take defensive positions in declining markets. The composition of the Index is governed by an Index Committee and the Index may not perform as intended. Please read the Fund’s prospectus for specific details regarding the Fund’s risk profile.
Christopher Gannatti began at WisdomTree as a Research Analyst in December 2010, working directly with Jeremy Schwartz, CFA®, Director of Research. In January of 2014, he was promoted to Associate Director of Research where he was responsible to lead different groups of analysts and strategists within the broader Research team at WisdomTree. In February of 2018, Christopher was promoted to Head of Research, Europe, where he was based out of WisdomTree’s London office and was responsible for the full WisdomTree research effort within the European market, as well as supporting the UCITs platform globally. In November 2021, Christopher was promoted to Global Head of Research, now responsible for numerous communications on investment strategy globally, particularly in the thematic equity space. Christopher came to WisdomTree from Lord Abbett, where he worked for four and a half years as a Regional Consultant. He received his MBA in Quantitative Finance, Accounting, and Economics from NYU’s Stern School of Business in 2010, and he received his bachelor’s degree from Colgate University in Economics in 2006. Christopher is a holder of the Chartered Financial Analyst Designation.