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CONTRIBUTORS

Jonathan Curtis

Chief Investment Officer,
Portfolio Manager
Franklin Equity Group
United States

Key takeaways:

  • We are in the beginning stages of generative artificial intelligence (GenAI): In the coming years, the application of constantly evolving GenAI models will bring revolutionary change to enable innovation, accelerate growth and boost the efficiency of the global economy.
  • Investors underestimate the transformative nature of this technology and the opportunity it represents: Most investors do not yet fully understand GenAI and are significantly underestimating the value we believe it will deliver over the next decade. 
  • Growth of GenAI will drive demand across inputs to scale: Large language models (LLMs) will drive demand for compute (raw processing power), electrical power, data and algorithmic enhancements.

Introduction

Despite some volatility in recent weeks, technology stocks have delivered strong returns year to date through July 31, 2024, outperforming all other sectors—often by a large margin.1 In our view, this outperformance represents a continuation of the trend that followed the launch of ChatGPT 3.5,2 the first widely adopted transformer-based artificial intelligence (AI) model, in November 2022. Despite witnessing the phenomenal growth of AI infrastructure businesses during this period, we are convinced that many investors do not fully comprehend the improvements in AI models that are yet to come. They also do not foresee how these improvements, once employed, will enable innovation, accelerate growth and boost the efficiency of the global economy in the years ahead.

As we explain in this paper, we believe we are at the beginning of a profound, revolutionary change. Recent capability improvements in transformer-based models are impressive;3 the world’s most advanced AI models are now able to complete complex coding tasks, ace the bar exam, outperform most humans on standardized tests, create videos and develop complex reasoning flows. And as more compute (raw processing power), data and algorithmic enhancements are applied to planned transformer models over the next few years, they will certainly continue to improve.

Endnotes

  1. Source: MSCI All Country World Index (in US$ terms). The Index is a free float-adjusted, market capitalization weighted index designed to measure the equity market performance of global developed and emerging markets. Indexes are unmanaged and one cannot directly invest in them. They do not include fees, expenses or sales charges. Past performance is not an indicator or a guarantee of future results.
  2. Any companies and/or case studies referenced herein are used solely for illustrative purposes; any investment may or may not be currently held by any portfolio advised by Franklin Templeton. The information provided is not a recommendation or individual investment advice for any particular security, strategy, or investment product and is not an indication of the trading intent of any Franklin Templeton managed portfolio. Past performance does not guarantee future results.
  3. There are different types of neural networks, including recurrent and convolutional. The GPT models are transformer neural networks. A transformer-based large language model (LLM) is a type of AI model designed to understand and generate human language.
     

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Any companies and/or case studies referenced herein are used solely for illustrative purposes; any investment may or may not be currently held by any portfolio advised by Franklin Templeton. The information provided is not a recommendation or individual investment advice for any particular security, strategy, or investment product and is not an indication of the trading intent of any Franklin Templeton managed portfolio.

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