7th Apr 2023
The buzz around OpenAi’s ChatGPT-3, a conversational artificial intelligence (AI) model that produces human-like text, has motivated a number of people to invest in AI. It’s not possible to invest in OpenAI itself, because it’s a private company, but investors excited about ChatGPT can buy shares in related enterprises.
Some savvy investors who look beyond the narrow framing of OpenAI are turning to invest in quantum computing, with many of them investigating a quantum computing stocks ETF like Defiance’s QTUM, which exposes them to the broad potential of the sector. The Defiance Quantum ETF seeks to track the total return performance, before fees and expenses, of the BlueStar Quantum Computing and Machine Learning Index.
What do quantum computing and OpenAI have to do with each other?
Buying shares in quantum computing companies might not be the obvious way to add OpenAI to your portfolio, but when you learn more about the two fields, the synergy between them becomes clear.
OpenAI is a leading research laboratory developing advanced AI models that are used to create cutting-edge applications like ChatGPT, GPT-3, Codex, and DALL•E 1. Like other AI scientists, OpenAI often hits computing barriers, because the datasets involved are enormous and AI algorithms are incredibly complex, requiring massive amounts of compute power which traditional computers can’t always provide 2.
Quantum computing uses the principles of quantum mechanics to perform calculations that are exponentially faster than classical computing. While classical computing relies on binary digits, or bits, quantum computing uses quantum bits, or qubits, which allow for much more powerful calculations. The power of quantum computers grows exponentially (2x2x2x2…) with more qubits, where the classical computing power is linear (2+2+2+2) when more bits, bytes, gigabytes , etc. are added.
What is the OpenAI-quantum computing synergy?
The quantum-OpenAI synergy refers to the potential for quantum computing to enhance the capabilities of OpenAI’s artificial intelligence systems, and for AI to advance quantum computing. In brief, OpenAI and other AI applications need the compute power that quantum computing can deliver, while AI problem-solving can potentially help quantum computing surmount some of the obstacles to success.
Research and Markets suggests that “Quantum computing and AI are highly synergistic with one another as the former speeds up problem solving for the latter, and the latter provides an automated learning structure for the former […] AI may at some point overcome current hardware-centric limitations of quantum computing.”3
OpenAI’s GPT-3 currently operates with 175 billion parameters (or neurons). It takes months to train a model of this size and complexity, even with the largest cloud-based computers, and AI models keep getting larger.4 As futurist and thought leader Bernard Marr points out, “the complexity and size of our data sets are growing faster than our computing resources and therefore place considerable strain on our computing fabric,” adding that AI and its subset, machine learning (ML) “can benefit from advances in quantum computing technology … even before a full quantum computing solution is available.”5
By combining the power of quantum computing with the advanced algorithms developed by OpenAI, it is possible to tackle complex problems in AI that are currently beyond the reach of classical computing.
How quantum computing can improve AI
The greater power enabled by quantum computers can be used to process huge datasets more quickly, helping AI systems identify patterns and features in large datasets and learn new capabilities more quickly and accurately. Quantum computing also increases accuracy for AI algorithms by helping verify the results of predictions, and reduces noise to lower the incidence of errors. Additionally, quantum computers can cope with complicated optimization problems that are impossible for traditional computing, potentially producing new AI algorithms that are not limited by the classical laws of physics.6
One of the use cases that scientists are most excited about is neural language processing, or NLP. Language understanding is a serious challenge for AI models, because there are many variables in even a short sentence. According to Ilyas Khan, founder and CPO of Cambridge Quantum Computing, OpenAI’s GPT-3 is a “very, very sophisticated autocorrect.”7. Bob Coecke, Chief Scientist at Quantinuum, agrees that language is quantum-native. “It may be that meaning-aware computers — machines that deeply understand language — can only be built using quantum computers,” he said8.
Quantum computing and AI are already working together
The last few years have seen a number of partnerships between quantum computing companies and AI research organizations. Microsoft, which invested $10 billion in OpenAI and secured the exclusive lease of GPT-39, is also investing in quantum computing, with the two companies recently extending their partnership across AI supercomputing and research10.
Satya Nadella, Chairman and CEO of Microsoft, informed the world about the corporation’s plans to lead the quantum computing revolution, telling leaders at Davos in January 2023 that “Microsoft will achieve quantum supremacy and […] is opening up access to new AI tools like ChatGPT.”11
At the same time, Google is working on its Quantum AI initiative, with the goal of building a quantum PC by 202912, having launched its quantum AI-hybrid platform TensorFlow Quantum in March 202013. The UK government and IBM are running a five-year collaboration in the fields of AI, quantum processing, superior execution registering (HPC) and information investigation, and cloud advances14. Finally, OpenAI’s founder and CEO Sam Altman has made many investments in quantum computing, participating in Rigetti Computing’s funding round in 2017, PsiQuantum’s funding round in 2019, and the 2020 funding round for Quantinuum, among many others.
The quantum-OpenAI synergy offers an opportunity for investors
Quantum computing is still in its early stages of development, and there are many technical and practical challenges that need to be addressed before the full potential of the quantum-OpenAI synergy can be realized. However, the possibilities that it represents make it an appealing option for investors who want to be part of this disruptive, innovative, and cutting-edge sector.
Instead of searching for the best quantum computing stocks to buy, or hoping that OpenAI will go public, investors can add this synergy to their portfolio by buying shares in QTUM, a quantum computing ETF from Defiance, which tracks promising startups and established corporations that are involved in the development of quantum computing.
As an ETF, QTUM can add exposure to 70 quantum computing and machine learning companies to a portfolio, allowing investors to take advantage of the rise of this exciting market while helping remove some of the guesswork of trying to identify which quantum computing companies and AI organizations that will be the first to achieve their goals.
As of this writing the following stocks mentioned are current holding of Defiance’s ETF, QTUM:
Alphabet, Inc. CL A (GOOGL: NASDAQ), Microsoft Corp. (MSFT: NASDAQ), International Business Machines Corp. (IBM:NYSE), Rigetti Computing, Inc. (RGTI: NASDAQ).
1 “General availability of Azure OpenAI Service expands access to large, advanced AI models with added enterprise benefits” January 16, 2023 https://azure.microsoft.com/en-us/blog/general-availability-of-azure-openai-service-expands-access-to-large-advanced-ai-models-with-added-enterprise-benefits/
2 “What has quantum computing got to do with AI?” July 25 ,2022. https://www.verdict.co.uk/what-has-quantum-computing-got-to-do-with-ai/
3 “Quantum Intelligence: Quantum Computing and Artificial Intelligence 2018 – 2023” December 2018 https://www.researchandmarkets.com/reports/4704016/quantum-intelligence-quantum-computing-and
4 “What has quantum computing got to do with AI?” July 25, 2022 https://www.verdict.co.uk/what-has-quantum-computing-got-to-do-with-ai/
5 “How Quantum Computers Will Revolutionise Artificial Intelligence, Machine Learning And Big Data” https://bernardmarr.com/how-quantum-computers-will-revolutionise-artificial-intelligence-machine-learning-and-big-data/
6 “The Future of AI Is Quantum Computing: 10 of the Most Important Use Cases” July 19, 2022 https://pub.towardsai.net/the-future-of-ai-is-quantum-computing-10-of-the-most-important-use-cases-3a4b50c58f3e
7 “Over chatbots already? Quantum computing could change that” December 14, 2020 https://techhq.com/2020/12/over-chatbots-already-quantum-computing-could-change-that/
8 “How Could Quantum Computing Improve Large Language Models?” February 13, 2023 https://thequantuminsider.com/2023/02/13/how-could-quantum-computing-improve-large-language-models/
9 “Can I Invest In OpenAI? Putting Artificial Intelligence In Your Portfolio” February 10, 2023 https://www.forbes.com/sites/qai/2023/02/10/can-i-invest-in-openai-putting-artificial-intelligence-in-your-portfolio/?sh=8ec14157e127
10 “Microsoft ups its investment in OpenAI’s supercomputer plans” January 24, 2023 https://aimagazine.com/articles/microsoft-ups-its-investment-in-openais-supercomputer-plans
11 “Microsoft makes plans for quantum supremacy in new age of AI” January 23, 2023 https://aimagazine.com/articles/microsoft-makes-plans-for-quantum-supremacy-in-new-age-of-ai
12 “QUANTUM COMPUTING: THE ADVANCE AND FUTURE TECHNOLOGY” May 2, 2022 https://techstory.in/quantum-computing-the-advance-and-future-technology/
13 “Why Quantum Computing Is Even More Dangerous Than Artificial Intelligence” August 21, 2022 https://foreignpolicy.com/2022/08/21/quantum-computing-artificial-intelligence-ai-technology-regulation/
14 “QUANTUM COMPUTING: THE ADVANCE AND FUTURE TECHNOLOGY” May 2, 2022 https://techstory.in/quantum-computing-the-advance-and-future-technology/
15 “Sam Altman’s (from Open AI) 9 investments in Quantum Computing” February 26, 2023 https://quantumzeitgeist.com/sam-altmans-from-open-ai-9-investments-in-quantum-computing/