Profits from The Rise of the Machines!

January 1, 2022

Today, we’re taking a closer look at a recent IPO that stands to win big from the increasing prevalence of artificial intelligence, or AI.

For years, writers and dreamers alike have hailed artificial intelligence as the technology that will dramatically change the world that we live in.

It has long been a staple of dystopian science fiction. And I can’t think of a piece of technology that is more revered and feared at the same time.

In 2017, Russian Vladimir Putin said that whoever wins the war on AI will dominate the world. And the race is still on, but more are more pieces of the technology are coming together quicker than ever.

Many consumers have already adopted Amazon’s Alexa, Google Home, or another virtual assistant to enhance daily life. And although, convenience is important, artificial intelligence is expected to help solve some of humanity’s biggest scientific problems.

Unfortunately, despite being around for many years we’re still in the early days of unleashing the full potential of artificial intelligence. But we have come a long way.

The journey into AI begins in the 1940’s, when research papers were published exploring both the mathematical and the behavioral traits of neural networks.

The first wave of artificial intelligence had explicit rules based on logic and reasoning. Think of this more as a complex series of if this then that statements, rather than true intelligence. From there the technology moved into the neural networks, which attempted to replicate human thinking and problem solving.

Two things happened in the 50s that really started the development of AI.

First, Alan Turing laid out the method now called the Turing Test. This test measures if a machine does in fact meet the criteria of being intelligent. Second, Dartmouth hosted the Summer Research Project on Artificial Intelligence. This was the first mass use of the phrase “artificial intelligence”.

Even though it seems like this technology has been in development for over 50 years…that’s not the whole story. By the 70s both the British government and DARPA had concluded there were too many disappointments in the field. Essentially no progress was made from 1974-1980.

Researchers and scientists tried again in 1980…but there was not enough progress to justify the money spent. And we headed into a second AI winter from 1987 to 1993.

I don’t have to tell you about how much technology has exploded since 1993. We’ve lived it. Most of us carry around an AI virtual assistant in our pocket every day.

You might even remember in 1997 when IBM’s “Deep Blue” beat a world chess champion. Or in 2012 when Andrew NG fed a neural network 10 million YouTube videos and it learned to recognize a cat without being told what a cat was. Or in 2014, when Google made the first self-driving car to pass a state driving test.

But artificial intelligence is more than just these newsworthy stories. To really understand the trends and advancements, we must take a second to break down exactly what we mean by artificial intelligence.

The Different Aspects of Artificial Intelligence

According to the encyclopedia Britannica, artificial intelligence is the ability of a digital computer or computer-controlled robot to perform tasks commonly associate with intelligent beings.

It’s important to realize just how big of a moat that phrase tends to cover. We might immediately jump to a human like robot, but there are many more applications than that.

Broadly AI can be categorized as strong or weak/narrow. Weak or narrow AI is designed to complete a specific task. This would include industrial robots and personal assistants such as Siri or Alexa. Strong AI describes programming that can mimic the cognitive abilities of the human brain.

In 2016, Arend Hintze, a professor at Michigan State University, explained artificial intelligence by expanding it into four types. These are reactive machines, limited memory, theory of mind and self-awareness.

Reactive machines have no memory and are task specific. It can take in data and react, but cannot use past experiences to inform future one. This is very much an expansion of an if/then statement. If this happens, the machine reacts in a predetermined way.

Limited memory expands on the reactions. In addition to having the if/then parameters, these AI systems have memory. This means that past experiences can be used to inform future decisions. This is where the term machine learning comes in.

Machine learning is the subset of AI which allows a machine to automatically learn from past data without explicit programming.

The data is fed to that computer and uses statistical techniques to help it “learn” how to get progressively better at a task. This eliminates the need for millions of lines of written code.

The third type, theory of the mind is based off the psychology term. This means that the artificial intelligence would also have social intelligence. The goal is for the AI to be able to infer human emotions and use that information in its reaction as well.

The final type is self-awareness. This type of AI has yet to exist, but it is surely the future. When AI systems finally have a sense of self, they will then have consciousness. This is where we are inevitably heading…towards the days when artificial intelligence walks beside us in society.

Even though that may be the end goal, artificial intelligence is weaving its way into many seemingly mundane aspects of society.

Google, Facebook, Amazon, Apple and Microsoft all have established dedicated AI labs over the last decade. And you can bet they are using artificial intelligence to improve algorithms…and then maybe to create robots.

Where we are really going to see the immediate adoption of is in the enterprise technology space. Companies now have little choice, they must either adopt this new technology or die.

The hype surrounding artificial intelligence is continuing to grow, but many companies don’t have the funds or the manpower to start these massive projects from scratch. This is the main driver for the company that I have for you today.

This company is accelerating like crazy as companies everywhere are put under the pressure of digital transformation.

How to Profit RIGHT NOW From AI

The company that I have for you today has a unique vantage point. This company is behind the platform that powers approximately 1.1 billion predictions per day. That’s coming out of 4.8 million AI models. (NYSE: AI) is a leading AI software provider for accelerating digital transformation.

Its software platform allows for developing, deploying and operating large-scale AI applications. The company has a US patent for the fundamental concept of applying a model-driven software architecture for enterprise AI applications.

The real key is that these applications are a no-code solution. There is a finite supply of both money and talented coders. Not all companies have the resources or the desire to hire a team just for AI, but all companies want to use AI to boost productivity and profits.’s predictive analytics systems are used by the US Air Force, Bank of American, AstraZeneca and many other large organizations. And the applications range from anti-money laundering to energy management to predictive maintenance.

For example, Shell uses it to monitor more than 5,200 pieces of equipment. And Con Edison uses software as part of a conservation voltage reduction program. By operating its system at ideal voltage levels, it can reduce the power that its customers use.

The company has a massive footprint in oil & manufacturing, financial services, aerospace, utilities & other energy and has an average deal size of $9 million.

At the helm is this company is Tom Siebel, the founder of leading 90s application software company Siebel Systems. Now he’s looking to build another high-quality tech company.

In the most recent earnings release for the third quarter, total revenue was up 19% compared to the same quarter last year. Subscription revenue was up 23% which is a large chunk of the business.

The company just went public in December for $42 through a traditional IPO. And it took less than two weeks for share prices to triple.

That kind of movement can usually be expected after a hot new IPO. But now we’re sitting here 3 months later. Those share prices are leveling out and creating the perfect buying opportunity.

In fact, the company used this fresh infusion of IPO cash to hire more employees since the demand for AI is rapidly expanding.

The company is a clear buy as it continues to establish a leadership position in the market.

Action to take: Buy shares of (NYSE: AI).

Joshua M. Belanger
Joshua Belanger is founder of CounterVest and the editor of Hot Money Trader. He has been providing ordinary investors blockbuster returns since 2008. In 2018, the average return of Hot Money Trader beat the markets by over 15%