- The market has overlooked the importance of Data, the real gold mine itself in the age of AI.
- Interview with Xiadong BAO, Co-Portfolio Manager International Equities.
The year of Generative AI
While Open AI recently celebrated the 1-year anniversary of ChatGPT’s public launch last month, capital markets have fully embraced the arrival of generative AI in 2023: Nvidia, recovered from the crypto meltdown in 2022, where it lost more than 50%. The company saw its market capitalization increase fivefold since the start of 2023, reaching close to $2 trillion. Other Magnificient 7 companies highly involved in the GenAI development have also had a stellar performance during that period: a combined $4.5 trillion market capitalization gain for Microsoft, Meta, Apple, Alphabet, Amazon and Tesla.
Data is king
It is the new gold rush, they say, buy companies that make picks and shovels. Granted, there are three ingredients to make AI: computing power, code and data. While market is overly enthusiastic about the first two, we think data is King.
Jensen Huang, CEO of Nvidia said earlier this year that this is the iPhone moment for AI. We fully agree. Generative AI can be a game changer for a lot of industries. We are just at the early stage of exploring the full potential of these LLMs. But we think the market has overlooked the importance of Data, the real gold mine itself in the age of AI. The behavior of these large language models is not necessarily determined by its architecture, parameters or optimizations. It is determined by the datasets that have been used to train the model.
ChatGPT front run the competition thanks to its earlier-than-peers training based on the whole open internet. Bard, powered by Gemini, leveraged Google’s data to catch up quickly. Grok, by X.ai, Elon Musk’s latest AI venture, also showed its capability on the real-time social interactions thanks to the now privately-owned twitter platform data.
With the hefty investment into the computing power and the quick optimization of the code, we think proprietary data will shine very soon via verticalized LLMs or even small and nimble models close to final users1.
We do not speculate on the future, we build it
Our approach to participate in this early stage of the AI age is to invest in big data. Our investment style on our Big Data strategy is largely unconstrained in terms of sectors, regions and market capitalizations. We invest in companies which are either a thematic pure player with significant portions of their revenues derived from Data Analytics or Data Infrastructure, or Data Users who use Data and in today’s context, potentially AI, to accelerate the digital transformation, rescale and upscale their business.
Since its inception in 2015, the fund has achieved its objective of outperforming its benchmark. We put a high emphasis on managing concentration risks and avoiding over-dependency to a single sector. We have also paid attention to valuation metrics as we did not want to overpay for growth. This is largely the result of our investment culture where wealth preservation is a core investment principle.
1 EdgeAI: AI at the edge, is the implementation of AI that allows computation to be done close to where data is actually collected.
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February 2024. This document is issued by the Edmond de Rothschild Group. It is not legally binding and is intended solely for information purposes.
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