Cloud computing and artificial intelligence (AI) are taking human imagination to new heights. Tech giants such as Alphabet (GOOGL), Microsoft (MSFT) and Amazon (AMZN) are rushing to build new infrastructure to train machines to solve complex business challenges and predict future outcomes much faster than humans can.
“Cloud computing is being dominated by AI spending with huge sums spent on GPUs instead of CPUs,” said Michael Sansoterra, CIO of Silvant Capital Management. The latter is much more capable to handle the massive data speeds and analytics required by the growing spate of AI models on the drawing board versus traditional computing. “The expectation is that investment will grow 30% to 40% on a CAGR basis in the next three years.”
Currently the cloud market, which basically refers to businesses outsourcing data management and storage functions to so-called hyperscalers such as Amazon AWS or Google Cloud, is worth around $500 billion. But as generative AI injects efficiencies into cloud computing, both sectors will become increasingly intertwined and become a market north of $1 trillion in the next five years, analysts estimated.
“The market is moving very quickly with leaders such as Nvidia, Microsoft, Meta, Google and Amazon spending hugely. Nvidia, for instance, took last quarter’s semiconductors’ spending to $7 billion from an expected $4 billion,” said Sansoterra. Nvidia (NVDA) reports its latest financial results on Wednesday.
Goldman Sachs agrees the investment cycle will be massive, reaching $200 billion by 2025, as firms spend on physical, digital and human capital to acquire and implement new technologies.
Lifting Productivity
Sansoterra predicts generative AI – the technology behind popular chatbots such as ChatGPT – will add heft to cloud computing.
“Right now, cloud is about storage, data access, management or security but AI will provide a new way to shift data around and make better decisions with it that can help cut costs and increase revenue over time,” he explained.
Generative AI models can be trained to analyze vast amounts of data to come up with creative enterprise solutions executives can act on.
“Right now, customer service chatbots have a very linear and pre-programed way to answer questions so if they go outside that realm, they can’t help,” Sansoterra continued. “Generative AI will learn from all the same questions people have asked in the past and then figure out how to best answer them, populating them from much larger data sets and without a strict rule book, paring speech recognition, video and audio.”
‘Accelerated Discovery’
If you are a call center, drug company or chip maker, you will have a new way to engage customers, manufacture drugs or make semiconductors as data processing and calculations will be done much quicker.
“As machine learning engines get smarter and smarter, their power will become much greater,” noted one analyst. “Chatbots will disrupt call centers in India because they will be able to answer questions in a very compelling, human-like way so you won’t even know it’s a bot.”
At IBM, for example, developers will be able to look at ways to make semiconductors more efficient and automated.
“The generative AI engines can search for hundreds or thousands of chip compounds to determine which is best to use and automate for a specific new chip, instead of having to do this process through trial and error,” Sansoterra mused. “This will massively cut down the time and effort for which things are developed. AI will bring people and business thought processes into an age of accelerated discovery.”
Analysts say these technological breakthroughs could take three to five years to come to fruition, depending how the global economy fares.
Big Bang?
Jane Edmondson, who manages ETF indexing firm EQM, agreed AI will help boost the cloud space where the likes of Microsoft or Google have yet to see a return on investment.
She agreed the potential is enormous with exciting changes also envisaged for language processing, computer vision, autonomous drones and driving, etc.
The healthcare space could also be revolutionized, according to consultancy PwC, who says AI models are already helping predict certain cancers more accurately than existing diagnostics.
“There’s going to be amazing potential with bots to help provide health information and make decisions on future disease treatments for,” Edmondson said. “ChatGPT could tell you when you will get a disease, at what age, etc., depending on your genetic code.”
But will robots predict your life expectancy?
“That could be decades off,” Edmondson added. “It will also take years before we see AI used for completing surgeries and things of that nature.”
Regulation is, of course, a looming challenge. Laws will need to be drafted so that AI develops responsibly.
In that vein, the European Union recently approved the EU AI Act to ensure generative AI training tools meet copyright laws, while U.S. regulators are calling for provisions to govern the sector.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Image and article originally from www.nasdaq.com. Read the original article here.