August 2, 2024
Earn Real Profits from Synthetic Data
Dear Subscriber,
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| By Michael A. Robinson |
Ever heard of MIT? Of course, it’s one of the most prestigious universities in the world.
How about DataCebo? Ever heard of that? Most investors haven’t — but that’s OK. That means you get to be among the first.
DataCebo is an emerging technology startup that was born at MIT. It has a unique mission: to harness the power of AI and conquer a fast-growing field known as synthetic data.
Today, I’ll explain what this disruptive field is all about — and reveal how we can profit from this piece of a roughly $350 billion sector.
Generative AI — technology that creates things like text, images and videos — gets a lot of the spotlight when it comes to the glitz and glamour of AI.
But make no mistake …
Synthetic data is just as critical. In fact, without it, AI systems wouldn’t be smart enough to be useful at all.
Essentially, synthetic data is information that is artificially (or synthetically) generated, rather than produced by real-world events.
Typically created using algorithms, this data can be used to validate mathematical models or train machine-learning ones.
It may seem confusing, but here’s how several of today’s top companies are using synthetic data …
How It Actually Works
- Amazon.com (AMZN), for example, uses synthetic data to train Alexa’s language system.
- Alphabet’s (GOOGL) Waymo division uses it to train its self-driving cars.
- And American Express (AXP) and JPMorgan Chase (JPM) use synthetic financial data to improve fraud detection.
Then there’s DataCebo … the technology startup I mentioned earlier.
For the last three years, this company has offered an innovative software system called the Synthetic Data Vault, or SDV. This system helps organizations create synthetic data to do things like test software applications.
In short, synthetic data is a key component of almost every technology company’s success …
Which explains why this is a market we definitely want to target.
The Market for Big Data
In fact, synthetic data is part of a broader industry known as “big data.” It’s a field that includes the overwhelming amounts of information we create every day on our computers, our phones and with technology in general.
According to Fortune Business Insights, the market for big data is already valued at $349 billion. And by 2032, it’ll be worth nearly $1.2 trillion.
While a part of this industry, synthetic data is still flying under the radar. But that hasn’t stopped a few tech leaders from focusing on its potential.
Look no further than Nvidia (NVDA). Just a few weeks ago, this tech giant released a new open platform that developers can use to generate synthetic data for AI models.
Of course, DataCebo beat Nvidia to the punch. But that’s not totally surprising.
In 2020, DataCebo was founded to build more SDV features for larger organizations.
A new flight simulator, for instance, enabled airlines to plan for rare weather events in a way that would’ve been impossible using only historical data.
Elsewhere, SDV users synthesized medical records to predict health outcomes for patients with cystic fibrosis.
Synthetic data’s application in healthcare is particularly notable. That’s because one company is using it to change the way healthcare and AI can work together.
Introducing Elevance
The company is called Elevance Health (ELV).
Formerly known as Anthem, this is one of America’s biggest health insurance providers. Its provider network includes 97% of all U.S. hospitals, 350,000 primary care physicians, 486,000 behavioral health providers and 700,000 specialists.
So, what’s this company’s role when it comes to synthetic data? Let’s take a look …
As you might imagine, synthetic data could be put to great use in healthcare, where there are hundreds of millions of patient records to sift through.
But to make sure information about real patients doesn’t get accessed, computer networks need to simulate health records instead.
That’s why Elevance is working with Alphabetto feed its massive AI system to spot fraud, improve patient outcomes and improve profits.
Despite its size, though, this insurer doesn’t have enough different patient histories, billing records or insurance claims to properly train its AI.
That’s both bad for the company — which could be losing money on fraudulent claims and billing errors — and patients who could be walking around with symptoms of rare disorders that no one spots.
That’s exactly why Elevance is partnering with Google. The search giant will be creating 2 petabytes of synthetic data.
To put that in perspective, a petabyte is the equivalent of 20 million filing cabinets or roughly 1 trillion pages of text. That’s a staggering amount of synthetic data, including simulated insurance claims and patient histories.
Beating The Market
Simply put, Elevance is using the power of synthetic data to disrupt healthcare. And that should be a boost to its bottom line — and for potential investors like us.
The company’s stock has been on the rise lately. Since July 2023, it’s been on fire. And its use of synthetic data could continue its profitable ways.
True enough, earnings growth dipped slightly in the most recent quarter. But I don’t base my recommendations on a single quarter.
After all, we’re in it for the long haul. And over the last three years, per-share profits have grown an average of 16%, enough to have them double within the next five years.
Even better, profits are growing much faster than sales. In those same three years, sales grew an average of 10%. In other words, profits are growing 60% faster than sales.
And that’s a good thing because it means the company can maintain its dividend, which currently has a 1.2% yield. It may even be able to raise it over the long haul.
In other words, the data the firm uses may be synthetic. But the profits are sure enough real.
Best,
Michael A. Robinson
P.S. As noted, synthetic data is crucial to AI development. Nvidia knows this, which is why it just released its platform for it a few weeks ago.
Nvidia remains the leader in AI. But just like Google is with Elevance, Nvidia knows it needs partners. Click here to see who those are.
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