AI Research
Why Some Investors Are Betting Big on Quantum Computing as a Moonshot Artificial Intelligence (AI) Play

Quantum technology has become an emerging opportunity for artificial intelligence (AI) investors over the last several months.
While there are several major players fueling the artificial intelligence (AI) movement, perhaps none is more important than Nvidia. The company’s industry-leading chipsets and sophisticated CUDA software application provide an end-to-end, tightly integrated ecosystem for many of the world’s largest AI developers. The company’s visionary CEO, Jensen Huang, has metaphorically referenced the rise of AI to that of an industrial revolution — paving the way for a vast, ongoing runway of upside.
Within the AI realm, a new pocket known as quantum computing is beginning to receive quite a bit of attention. While it’s not commercially scaled today, quantum computing is believed by many technologists to contain transformative potential — from accelerating drug discovery to enhancing machine learning capabilities.
One company that has benefited greatly from the bullish rhetoric surrounding quantum applications is a company fittingly called Quantum Computing (QUBT -1.59%). With shares up nearly 3,000% over the last year, could Quantum Computing be the next big moonshot to pay off during the AI-themed industrial revolution?
Quantum computing could completely revolutionize the AI storyline, but…
Global management consulting firm McKinsey & Company categorizes quantum technology across three major applications: quantum computing, quantum communication, and quantum sensing. According to its forecasts, the quantum computing market could be worth up to $72 billion by 2035, while the total quantum technology market could reach closer to $200 billion by 2040.
With the potential to disrupt end markets across robotics, climate tech, cybersecurity, healthcare, and cryptography, it’s not entirely surprising that AI’s leading developers, such as Nvidia, Microsoft, Amazon, Alphabet, and IBM, are all exploring quantum computing in various ways — from developing next-generation chips to supercomputers.
Image source: Getty Images.
… investors should be very careful as to which companies deserve attention
Anytime a stock rises as sharply as Quantum Computing’s has — and seemingly out of nowhere to boot — it’s usually a good idea to investigate why.
Earlier this year, I wrote a deep dive on Quantum Computing’s corporate history. To summarize, the company was once doing business as Innovative Beverage Group Holdings (IBGH). At the risk of stating the obvious, this has nothing to do with quantum computing. After an unsuccessful venture in the beverage market, which was later followed by lawsuits from investors, IBGH rebranded as Quantum Computing.
While such a transformation may appear odd, it’s actually not as uncommon as you might think.
Back in 2017, a relatively unknown beverage company known as Long Island Iced Tea Corp. rebranded as Long Blockchain. The rebrand was marketed as a strategic shift in the company’s business — transitioning from a beverage company to one focused on Bitcoin mining. These efforts never panned out, and Long Blockchain was delisted from the Nasdaq exchange.
Along similar lines, companies struggling with growth such as GameStop and Strategy (formerly known as MicroStrategy) have managed to stay relevant and win investor enthusiasm by adding Bitcoin to their balance sheet.
QUBT Revenue (TTM) data by YCharts
Over the last year, Quantum Computing has generated less than half a million dollars in sales. And yet the company managed to burn through $45 million. This is an upside-down financial profile, regardless of its industry.
I have serious doubts over Quantum Computing’s technological foundation and its ability to compete in such a sophisticated, capital-intensive industry against the likes of big tech.
Is Quantum Computing stock a buy?
The reason I highlighted these examples is that changes in corporate narratives can be more performative than strategic to the underlying business. In other words, companies such as GameStop, Strategy, and Quantum Computing are using hot trends to capitalize on hype narratives as opposed to actually developing a concrete plan rooted in long-term value creation.
Quantum technology could be seen as a venture capital-style investment opportunity — one that carries asymmetric upside relative to its risk profile.
Given how little traction Quantum Computing (the business) has generated so far in combination with its seemingly directionless roadmap, I do not see the stock as a moonshot opportunity. Instead, I view Quantum Computing stock as a highly speculative opportunity masquerading as an innovative play on one of AI’s next megatrends. For these reasons, I would pass on investing in Quantum Computing stock.
Adam Spatacco has positions in Alphabet, Amazon, Microsoft, and Nvidia. The Motley Fool has positions in and recommends Alphabet, Amazon, Bitcoin, International Business Machines, Microsoft, and Nvidia. The Motley Fool recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.
AI Research
Databricks at a crossroads: Can its AI strategy prevail without Naveen Rao?

“Databricks is in a tricky spot with Naveen Rao stepping back. He was not just a figurehead, but deeply involved in shaping their AI vision, particularly after MosaicML,” said Robert Kramer, principal analyst at Moor Insights & Strategy.
“Rao’s absence may slow the pace of new innovation slightly, at least until leadership stabilizes. Internal teams can keep projects on track, but vision-driven leaps, like identifying the ‘next MosaicML’, may be harder without someone like Rao at the helm,” Kramer added.
Rao became a part of Databricks in 2023 after the data lakehouse provider acquired MosaicML, a company Rao co-founded, for $1.3 billion. During his tenure, Rao was instrumental in leading research for many Databricks products, including Dolly, DBRX, and Agent Bricks.
AI Research
NFL player props, odds: Week 2, 2025 NFL picks, SportsLine Machine Learning Model AI predictions, SGP

The Under went 12-4 in Week 1, indicating that not only were there fewer points scored than expected, but there were also fewer yards gained. Backing the Under with NFL prop bets was likely profitable for the opening slate of games, but will that maintain with Week 2 NFL props? Interestingly though, four of the five highest-scoring games last week were the primetime games, so if that holds, then the Overs for this week’s night games could be attractive with Week 2 NFL player props.
There’s a Monday Night Football doubleheader featuring star pass catchers like Nico Collins, Mike Evans and Brock Bowers. The games also feature promising rookies such as Ashton Jeanty, Omarion Hampton and Emeka Egbuka. Prop lines are usually all over the place early in the season as sportsbooks attempt to establish a player’s potential, and you could take advantage of this with the right NFL picks. If you are looking for NFL prop bets or NFL parlays for Week 2, SportsLine has you covered with the top Week 2 player props from its Machine Learning Model AI.
Built using cutting-edge artificial intelligence and machine learning techniques by SportsLine’s Data Science team, AI Predictions and AI Ratings are generated for each player prop.
Now, with the Week 2 NFL schedule quickly approaching, SportsLine’s Machine Learning Model AI has identified the top NFL props from the biggest Week 2 games.
Week 2 NFL props for Sunday’s main slate
After analyzing the NFL props from Sunday’s main slate and examining the dozens of NFL player prop markets, the SportsLine’s Machine Learning Model AI says Lions receiver Amon-Ra St. Brown goes Over 63.5 receiving yards (-114) versus the Bears at 1 p.m. ET. Detroit will host this contest, which is notable as St. Brown has averaged 114 receiving yards over his last six home games. He had at least 70 receiving yards in both matchups versus the Bears a year ago.
Chicago allowed 12 receivers to go Over 63.5 receiving yards last season as the Bears’ pass defense is adept at keeping opponents out of the endzone but not as good at preventing yardage. Chicago allowed the highest yards per attempt and second-highest yards per completion in 2024. While St. Brown had just 45 yards in the opener, the last time he was held under 50 receiving yards, he then had 193 yards the following week. The SportsLine Machine Learning Model projects 82.5 yards for St. Brown in a 4.5-star pick. See more Week 2 NFL props here.
Week 2 NFL props for Vikings vs. Falcons on Sunday Night Football
After analyzing Falcons vs. Vikings props and examining the dozens of NFL player prop markets, the SportsLine’s Machine Learning Model AI says Falcons running back Bijan Robinson goes Over 65.5 rushing yards (-114). Robinson ran for 92 yards and a touchdown in Week 14 of last season versus Minnesota, despite the Vikings having the league’s No. 2 run defense a year ago. The SportsLine Machine Learning Model projects Robinson to have 81.8 yards on average in a 4.5-star prop pick. See more NFL props for Vikings vs. Falcons here.
You can make NFL prop bets on Robinson, Justin Jefferson and others with the Underdog Fantasy promo code CBSSPORTS2. Pick at Underdog Fantasy and get $50 in bonus funds after making a $5 wager:
Week 2 NFL props for Buccaneers vs. Texans on Monday Night Football
After analyzing Texans vs. Buccaneers props and examining the dozens of NFL player prop markets, the SportsLine’s Machine Learning Model AI says Bucs quarterback Baker Mayfield goes Under 235.5 passing yards (-114). While Houston has questions regarding its offense, there’s little worry about the team’s pass defense. In 2024, Houston had the second-most interceptions, the fourth-most sacks and allowed the fourth-worst passer rating. Since the start of last year, and including the playoffs, the Texans have held opposing QBs under 235.5 yards in 13 of 20 games. The SportsLine Machine Learning Model forecasts Mayfield to finish with just 200.1 passing yards, making the Under a 4-star NFL prop. See more NFL props for Buccaneers vs. Texans here.
You can also use the latest FanDuel promo code to get $300 in bonus bets instantly:
Week 2 NFL props for Chargers vs. Raiders on Monday Night Football
After analyzing Raiders vs. Chargers props and examining the dozens of NFL player prop markets, the SportsLine’s Machine Learning Model AI says Chargers quarterback Justin Herbert goes Under 254.5 passing yards (-114). The Raiders’ defense was underrated in preventing big passing plays a year ago as it ranked third in the NFL in average depth of target allowed. It forced QBs to dink and dunk their way down the field, which doesn’t lead to big passing yardages, and L.A. generally prefers to not throw the ball anyway. Just four teams attempted fewer passes last season than the Chargers, and with L.A. running for 156.5 yards versus Vegas last season, Herbert shouldn’t be overly active on Monday night. He’s forecasted to have 221.1 passing yards in a 4.5-star NFL prop bet. See more NFL props for Chargers vs. Raiders here.
How to make Week 2 NFL prop picks
SportsLine’s Machine Learning Model has identified another star who sails past his total and has dozens of NFL props rated 4 stars or better. You need to see the Machine Learning Model analysis before making any Week 2 NFL prop bets.
Which NFL prop picks should you target for Week 2, and which quarterback has multiple 5-star rated picks? Visit SportsLine to see the latest NFL player props from SportsLine’s Machine Learning Model that uses cutting-edge artificial intelligence to make its projections.
AI Research
In the News: Thomas Feeney on AI in Higher Education – Newsroom

“I had an interesting experience over the summer teaching an AI ethics class. You know plagiarism would be an interesting question in an AI ethics class … They had permission to use AI for the first written assignment. And it was clear that many of them had just fed in the prompt, gotten back the paper and uploaded that. But rather than initiate a sort of disciplinary oppositional setting, I tried to show them, look, what you what you’ve produced is kind of generic … and this gave the students a chance to recognize that they weren’t there in their own work. This opened the floodgates,” Feeney said.
“I think the focus should be less on learning how to work with the interfaces we have right now and more on just graduate with a story about how you did something with AI that you couldn’t have done without it. And then, crucially, how you shared it with someone else,” he continued.
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