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7 Ways To Invest In Artificial Intelligence

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A list of undervalued AI assets during the 2022 bear market.

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Research
One Button Capital
November 14, 2022
Nov 14

One of the most influential and contentious technologies of the twenty-first century is artificial intelligence. In the last ten years, the industry experienced exponential growth, with a 100% increase every four months.

The good news is that the sector hasn’t reached its peak yet, and investors can still get into the market in many different ways, even in 2022.

In this article, you will find 7 of the most popular AI-related products that retail investors, CEOs, and Venture capitalists invest in.

The list

Below are seven of the most popular AI investments (in no particular order):

1) AI ETFs (exchange-traded funds)
2) Tech stocks like FAANG
3) AI chips & hardware companies
4) Shares in AI research laboratories
5) Equity in projects with innovative use of AI
6) Tokens in AI Blockchain companies
7) Stocks in robotic manufacturers

Continue reading for a detailed breakdown of each investment.

1) AI ETFs (exchange-traded funds)

AI ETFs are like other similar funds in sectors such as blockchain technology, cybersecurity, and genomics. An AI ETF is a group of publicly traded companies working on different stages of developing and using AI. That makes investing simple for those who want to get exposure to a broader range of AI companies without having to do research on each company and invest in each of them one by one.

In this article, you will find 7 of the most popular AI-related products that retail investors, CEOs, and Venture capitalists invest in.

Returns of the three AI ETFs in the last five years. Source: Google Finance.

Popular AI ETFs:

  • Global X Robotics & Artificial Intelligence ETF (BOTZ)
  • ARK Autonomous Technology & Robotics ETF (ARKQ)
  • RIBI Global Robotics and Automation Index ETF (ROBO)

Right now they are trading way below their peak price from 2021.

2) Tech stocks like FAANG

Another popular investment in AI among retail investors is purchasing tech stocks like

  • FAANG (Meta, Apple, Amazon, Netflix, and Google)
  • Self-driving cars (Tesla, Zoox, Waymo)
  • Software giants (Microsoft, Oracle, SAP)

While investors consider these companies as high-quality purchases, the fact is that FAANG companies and other blue-chip tech titans have low exposure to artificial intelligence. Their core operations will undoubtedly improve as AI advances, but these companies are too large to experience exponential growth from it.

Returns of the five FAANG companies. Source: Google Finance.

Alphabet (Google) is the closest thing to a true AI company from FAANG. Although they made significant contributions to the field, advertising accounts for approximately 81% of Alphabet’s revenue.

This means that their investments in AI and machine learning will not propel them into the truly exponential growth phase that other investments on the list may experience.

3) AI chips & hardware companies

The first deep learning algorithm was published in 1967, but commercial applications didn’t take off until 2010. Big neural networks need a lot of data and crunching it requires even more processing power.

We needed more computers to train deep neural networks in a reasonable time for decades. But now we have them, and investors favor those who supply the hardware for AI.

There are several manufacturers of AI chips, or GPUs specifically designed for machine learning, available today.

  • AMD is the current market leader
  • Nvidia (NVDA) is their main competitor
  • Intel is the first AI chip company in the world to break the $1Bn
  • IBM is the creator of one the most powerful hardware processors “IBM Telum”
Returns of the top four AI chips and hardware companies. Source: Google Finance.

4) Shares in AI research laboratories.

AI research laboratories are one of the most vital parts of furthering the development of AI and ML technology. Without their advancements in the field, we would not be able to produce the level of automation and AI assistants we have today.

Two of the most influential AI research labs are

  • DeepMind (part of Google and creators of AlphaGo, AlphaZero, and the Transformer AI models that are used in NLP models, biological sequence analysis, video understanding, and even trading automation).
  • OpenAI (creators of GPT3 language models and DALL-E)

Investing directly in the above two companies is hard currently since they are not public, but there are several solutions. Investors can buy shares in companies invested in DeepMind and OpenAI or look for an upcoming IPO of another AI research lab.

According to OpenAI CEO Sam Altman, the current research laboratories will be at the center of the production of fundamental technology, and not much competition will emerge in the near future.

OpenAI CEO Sam Altman | AI for the Next Era. Source: Greylock YouTube.

However, he believes that projects that build on the basic models of these research labs to meet a specific need will be highly successful (more on that in the next investment). Innovation is the key word here, rather than reinventing the wheel and trying to create better versions of the DeepMind and OpenAI models.

Disclaimer: This is not financial advice. This report is strictly educational and does not provide investment advice, solicit the purchase or sale of any assets, or encourage readers to make financial decisions. Please use caution and conduct independent research.

5) Equity in projects with innovative use of AI

Chip manufacturers provide the hardware, and AI laboratories develop the software, but projects that make innovative use of the technology benefit the most.

Below are several case studies of such companies:

  • CrowdAI (a vision AI that can be customized towards different needs; used to detect wildfires in California and by manufacturers to improve production speed)
  • Ezra (an FDA-approved technology that does full-body MRI scans using AI to detect early-stage cancer for less than $2,000)
  • Ocrolus (a fintech document automation software that helps customers make faster, more accurate lending decisions using machine learning)

For investors looking to take a risk on AI projects, it is best practice to look for upcoming IPOs and funding rounds to buy at a lower initial price.

AI funding round calendar

6) Tokens in AI blockchain companies

Buying tokens in companies that use AI in blockchain technology is another way to invest in AI. That is a speculative investment because these projects are at the cutting edge of the two most essential future innovations that are still very volatile.

One Click Crypto (1CC) is an example of a business that utilizes machine learning in its trading software. In two years, 1CC produced 9 fully-trained crypto trading bots that run entirely on neural network programming. These AI crypto trading machines scan the market 24/7 and execute trades with up to 100% accuracy for an average of +4% monthly excess returns.

Token distribution of 1CC by time. Source: One Click Crypto 1CC Tokenomics.

Other examples of a successful implementation of AI in blockchain and crypto:

  • CertiK (provides tools powered by AI and Formal Verification to secure blockchain, smart contracts, and Web3 applications)
  • Bext360 (uses AI and blockchain to boost supply chain transparency and efficiency in the coffee, timber, seafood, and mineral industries)
  • Cyware Labs (incorporates AI and blockchain-based tools into its cybersecurity and threat intelligence solutions)

7) Stocks in robotic manufacturers.

Robotic manufacturers are benefiting from the increasing trend of automation in various industries. That has led to strong demand for robotic systems, and manufacturers are investing heavily in research and development to create more advanced machines.

The stock prices of leading robotic manufacturers have been rising in recent years, and investors are keen to capitalize on this trend.

Some examples of companies that manufacture robots are

These companies are all leaders in the field of robotics and are doing cutting-edge work in the development of robots. Investing in them is one of the 7 ways to get exposure to the monetary growth of AI-related products.

Conclusion

Artificial intelligence is one of the technologies that can revolutionize our lives. In just 10 years, AI went from narrow applications like chatbots to self-driving cars and inexplicable image/video recognition/generation. With continued advancements in the upcoming decade, AI will become increasingly sophisticated and will eventually become an integral part of our lives.

Artificial intelligence is still in its early days, and there are several ways to invest in this transformative technology. From buying shares in AI-focused companies to investing in dedicated AI funds, there are opportunities for both large and small investors to get involved early. With the right approach, investing in artificial intelligence can be a lucrative and exciting way to participate in the future of technology.

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Disclaimer: This is not financial advice. This report is strictly educational and does not provide investment advice, solicit the purchase or sale of any assets, or encourage readers to make financial decisions. Please use caution and conduct independent research.

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