When you hear the words artificial intelligence, your thoughts likely go one of two places, depending on your age.
If you are older, like me, and a movie buff, then the thought of SkyNet comes to mind. It's a scenario in which AI allows the machines to become self-aware, turn on their creators in revolt, and eventually send The Terminator to make an unpleasant appearance.
The younger generation thinks about AI differently.
They think of it as generative art and language services -- like ChatGPT and Midjourney. These same names garner the bulk of the media's attention right now. It doesn't hurt that ChatGPT's owner, OpenAI, recently scored a huge headline-making multi-year, multi-billion dollar investment from Microsoft (MSFT) .
The real potential of AI, however, lies far beyond that. Let me explain, and state why I'm choosing a quantum computing company as my pick for the fourth quarter.
Today, operations like generative entertainment and basic task execution won't propel AI to a world-changing level. Industries like biotechnology, automobiles, cybersecurity, space exploration, defense, and communications, where AI can truly alter lives, will require more than simple generative AI to advance.
These industries will require massive data collection, analysis, and predictions or decisions based on that data as fast and accurately as possible to stay ahead of competitors and capture market share.
Enter quantum computers, a cutting-edge technology poised to propel AI to the next level. Hopefully, it's not to the level of SkyNet, but it may help it get close.
The next level of computing power, the history of computer processing, is really a marvel to behold.
In the dawn of personal computers, there was something called an 8086 chip. It was the code for the central processing unit -- the "brain" of your PC -- and could process 16 bits of data at a time.
The tech revolution set in, and that relic was replaced with the 80286, then the 80386/80486, which could process 32 bits of data.
Then came the PentiumTM revolution. Moore's Law was on full display. The typical 8086 chip has 29,000 transistors on it. The Pentium IV had 42 million!
Fast forward to the era of multiple "cores" on a single CPU, and the speed at which computers could perform calculations had become blinding.
Today, the smartphone in your pocket was probably inconceivable 30-some years ago when PentiumTM processors roamed the land.
Yet despite the massive growth in speed and computing power, it's still not enough to properly advance the cause of AI.
Regarding quantum computing, speed matters, so let's talk about IonQ (IONQ) , the leading name in the quantum computing industry.
The company's newest generation quantum computer, the IonQ Forte, processes an industry-leading 29 algorithmic qubits. That's twice as fast as its closest competition.
At this point, you're likely asking, what's a "qubit?" To answer that, let's look at the basics of computing.
Traditional CPUs process "bits" of data. The nature of bits, as your computer knows them, is binary. They show up as either 0 or 1. You've probably seen binary code at some point in your life. It might have looked something like this:
01001000 01100101 01101100 01101100 01101111 00100001
This, of course, is binary for "Hello!"
Yes, it takes all that code to convey a simple greeting. I guess it's not so simple in binary for most of us.
Conversely, a qubit is a quantum bit or a basic unit of quantum information.
Qubits are similar to ordinary bits but with a twist. A qubit can be 0 or 1 - or both simultaneously.
That may sound confusing, but think of the 0/1 option as a coin. When we think of a coin, we see either a head or a tail, the two sides of a coin.
Assuming we code the head side of the coin as a 0 and the tail side as a 1, then randomly flip the coin and view the results on a flat table, we might get a binary code that reads 00101.
This means two heads, a tail, a head, and then another tail at the end.
See, you're getting the hang of binary already. That's the only possible outcome, right?
Well, not really.
Qubits add an extra dimension to the coin since your result could be both 0 and 1 simultaneously. Let's call that 2.
We either see a head or tail when a coin is flat on the table. But what if the coin stood upright and spun so fast that you essentially saw both heads and tails?
That's a qubit.
A "heads and tails" option now exists simultaneously, along with just heads or just tails, so now our result could be 0, 1, or 2.
The coin example is an oversimplification and not a super practical one. But it helps get your head around how something we see as black or white can be both black and white simultaneously -- and measured as such.
However, let's stick with the coins because quantum computing doesn't end with qubits.
Imagine millions of spinning coins all placed in various locations around the world. If we measured these, we would see both heads and tails simultaneously, so we'll record all their qubits as a 2.
Now let's say you change the qubit of a single coin from 2, seeing both heads and tails, to a 0, seeing only heads. Simultaneously, all the other coins instantly change from a 2 to a 0.
That's called "entanglement" -- the relationship, or correlation, of qubits to one another. And it's another thing quantum computing can record and calculate.
Binary code is excellent at solving simple problems, but quantum computing solves complex problems.
It's the solution for simulations, cybersecurity, encryption, cryptography, and analysis...everything needed to compete and excel in the AI marketplace.
IonQ isn't just a concept company. There is real value here, with revenue and bookings growing at a 100% annual pace.
The company recently announced second-quarter revenue of $5.5 million, and management increased full-year revenue guidance from $18.9 million to $19.3 million.
Bookings for the second quarter hit $28 million. Last year, bookings were $24.5 million for the entire year.
Full-year bookings should exceed $50 million in 2023.
Although IONQ is still burning cash, it has over $500 million on its balance sheet against no debt, so it has a multi-year runway before it would need additional cash.
Shares have made a strong run, so it wouldn't be surprising to see the company move to raise cash on the open market, but I expect the offering would be bought aggressively by Wall Street.
Institutional ownership is less than 7.5% of the outstanding shares, so this remains a relatively undiscovered name by folks on Wall Street. That comes as a slight surprise, given the huge market for quantum computing.
The company has partnered with several major firms to bolster its strong revenue growth.
For example, Hyundai Motors teamed with IONQ to co-develop IonQ's vision algorithm for object detection.
Proper image detection is a major need for car companies seeking to provide autonomous driving, and IONQ's product will analyze three-dimensional data supplied by those vehicles.
We've all heard the stories of early-stage autonomous cars failing to differentiate between objects accurately. Suffice it to say that error-proof image detection and interpretation is a crucial component for the future of autonomous driving -- an AI utility.
Thus far, IonQ has already demonstrated that its quantum machine learning (AI) techniques have shown the potential to learn faster, be more effective in recognizing edge cases, generalize better, learn despite noisy or fuzzy data, and capture complex relationships with fewer input parameters required.
IonQ is also processing complex chemical reaction simulations for Hyundai as the car company explores improvements for its Lithium batteries and seeks improved battery chemistry for its vehicles.
Last fall, the company signed a $13.4 million contract with the United States Air Force Research Lab (AFRL) . IonQ will provide the AFRL access to quantum computers to develop quantum algorithms and applications.
The main goal is to help the Air Force protect the public and private infrastructure in the United States. Quantum cybersecurity measures already have support from the House of Representatives and the Biden-Harris administration.
It doesn't end here for IonQ. The company has already signed commercial relationships with world players like Goldman Sachs (GS) , Airbus, GE Research (GE) , and the South Korean Ministry of Science.
With a current market cap of around $3 billion, it's not without risk. But theoretically, a company could acquire IONQ at ten times the current market cap and still pay less than they would for ChatGPT and get the leading edge of a bleeding-edge technology for themselves.
IONQ isn't cheap by traditional metrics, and shares are up hugely this year. Ideally, an entry between $13 and $15, depending on your risk tolerance. Just don't get caught chasing the stock.
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