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In a year marked by a paradigm shift for artificial intelligence (AI), OPTO Sessions spoke to a range of thought-leaders in the space. As AI extends its influence across the economy, from healthcare data processing to revolutionary genomic analysis, OPTO provides exclusive insights and expert perspectives for investors navigating this dynamic landscape.
OPTO’s weekly podcast, OPTO Sessions, gathers exclusive insight from a network of founders, CEOs and pioneers, highlighting the investment potential of the world’s most disruptive and innovative businesses.
AI is a critical area of focus. Its transformative potential spans industries: the integration of AI can address complex challenges, unlock new possibilities and foster advancements that have profound implications for economic, social and scientific domains.
Here, we collate some of the most radical and far-reaching insights to have been shared on OPTO Sessions this year.
2023 was a paradigm shift for AI. It has moved from a niche interest to a global concern in the blink of an eye, principally thanks to the rapid adoption of generative AI technology.
Pedro Palandrani, Vice President and Director of Research at Global X ETFs, told OPTO Sessions that he believes the fast-evolving technology is positioned to transform every company in the world. “I would say that by the end of the decade, there are going to be two types of companies: companies that are using AI — embedding AI into services and operations — and companies that don’t exist anymore.”
Within the AI value chain, chipmakers are already reaping rewards. “Short-term, you’re clearly seeing companies like Nvidia [NVDA] truly benefitting,” says Palandrani. “I think this is part of a long-term, structural trend that will take 10–15 years to fully play out.”
Looking at previous technological paradigm shifts, says Palandrani, you can identify three phases: the initial compute phase (“that base hardware layer for machine interaction”), the infrastructure and data-management phase, and the interface phase.
“Short-term, you’re clearly seeing companies like Nvidia [NVDA] truly benefitting.”
In the compute phase, Nvidia is the “first company that gets recognised by the market… and it’s just scratching the surface of the opportunity”. In the infrastructure phase, “you have hyperscalers, where companies like Amazon’s [AMZN] Amazon Web Services and Microsoft’s [MSFT] Azure are really winning”.
However, the interface stage is wide open, Palandrani tells OPTO. “I think that interface layer is still to be identified by investors.”
In the past, “Google [GOOGL] and Amazon won as the interfaces of the internet revolution. Then Apple [AAPL] really positioned itself as the winner of the smartphone era.”
This time, it’s different. “Unlike prior paradigm shifts, interface companies are going to be the ones that already have the technology-oriented relationships, and they’re going to be able to drive top-line revenue growth rates from these.”
Bubble to Burst?
This has fuelled investor excitement, but also given rise to fears that AI’s growth may prove to be unsustainable. “Yeah, we probably are in an AI bubble,” Anthony Scaramucci, Founder and Managing Partner of SkyBridge Capital, tells OPTO. “But that should not dissuade people from getting a toehold in that group of stocks or thinking about the future in that way, because it is going to transform us.”
The potential bubble should not scare investors off, as some market players are well-positioned to weather headwinds. “Nvidia is a clear winner,” Scaramucci says. “So it may be up, it may be down, it could get cut by 50% once the ‘bubble’ bursts. But I am willing to bet you if you hold that stock for 15 years if you are brave enough, you will be well served.”
“Nvidia is a clear winner.”
Scaramucci likens the hype — and corresponding scepticism — around AI and technologies like ChatGPT to the chatter that surrounded the dot-com boom in the 1990s. In 1999, he watched Jeff Bezos give a talk at a conference about his online bookstore and his plans to apply his logistics know-how across the economy. It was exciting, but the next speaker, Warren Buffett, urged caution when investing in unproven, unprofitable tech firms. “So I never bought the stock. But let me just say this: if you put $10,000 in the stock the day I heard that presentation, and you stayed with it until 2023, you’d have $14m in your account,” he ruminates.
“Just think about where the internet was in 1998, with 4% saturation in the global market,” Scaramucci says. “Then think about where it is 25 short years later. If you were brave enough to invest in things like Microsoft, Google and eventually Facebook [META] and others, you did very well.”
Impact Across the Economy
“Healthcare is the largest data-generating industry in the world,” according to Arelis Agosto, Senior Healthcare Analyst at Global X ETFs. But at present, the sector lacks the technological infrastructure to process the reams of data that it produces. This leads to huge inefficiencies that manifest as elevated costs and long waits for new treatments to come to market.
The data processing and AI capabilities of Nvidia could be a powerful force to address these challenges in the healthcare industry.
Nvidia is making inroads into the space and has the potential to support digitisation of the healthcare industry and develop genomic technology, says Agosto.
“We can offer genomic profiling to the entire world, but we can't really garner the full potential of the technology if we don't have a way to actually analyse and collect all this data. Currently, unfortunately, it’s either not prevalent enough, or we don’t have the computing power to actually process all the benefits of genomic sequencing.”
Nvidia’s technology is the key to unlocking this value. “This is where Nvidia really sees potential,” she says.
Genomic analysis could unlock an abundance of data with many potential uses. Agosto thinks the data’s deployment in drug discovery will be especially influential.
“This is where Nvidia really sees potential.”
There is an advantage in “essentially having information from electronic medical records, genomic profiling, clinical trial data and prescription data, to feed into models to predict better efficacy for drugs, a better safety profile for drugs, and drugs that can serve multiple purposes,” she says.
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