Category: Artificial Intelligence

Has the excitement surrounding artificial intelligence (AI) stocks cooled off? Many top AI stocks are down this year, including Advanced Micro Devices (AMD 1.31%), better known as just AMD, and Nvidia (NVDA 0.28%). They have both declined around 15% thus far in 2025, which is worse than S&P 500‘s more modest drop of 4%.

There’s still massive potential for AI to revolutionize businesses and entire industries, but investors have been starting to scale back their positions in AI. If, however, you’re looking at the long haul, then now can be a great time to add a top AI stock to your portfolio. Which of these two chip stocks is the better option right now: AMD or Nvidia?

Comparing their valuations

Nvidia is one of the most valuable companies in the world, with a market cap of $2.8 trillion. That has come down a bit amid its recent decline (last year it was well above $3 trillion), but it’s still close to 17 times the value of AMD, which has a market cap of around $165 billion. While AMD isn’t a small company by any means, when compared to Nvidia, it looks tiny.

While you might think that Nvidia is the pricier of the two stocks given its massive valuation, based on earnings, it’s actually the cheaper stock.

NVDA PE Ratio data by YCharts

Last year, AMD reported $1.6 billion in profit, while Nvidia, which has a fiscal year that ends in January, has generated an incredible $72.9 billion in earnings over its last four quarters. Not only has its business been experiencing explosive growth, but Nvidia’s bottom line has been growing quickly as its profit margin has averaged 56%. That has enabled its price-to-earnings (P/E) multiple to remain relatively low.

By comparison, AMD’s profit margin is just 6%. And with a more modest bottom line, it’s the more expensive stock of the two when taking into account its earnings per share.

Which AI stock may have the most upside?

Both stocks have been struggling this year but when looking at the past 12 months, Nvidia is still up around 29% while AMD has fallen by 33%. A case could be made that AMD may be due for a rally, especially if its AI chips prove to offer formidable competition to Nvidia’s high-priced options. AMD CEO Lisa Su previously forecast that the company could generate “tens of billions of dollars in annual revenue” in the near future due to its AI chips.

If AMD can generate that much growth, it can certainly help attract more investors and propel the stock to a much higher valuation. Thus far, it’s lagged behind Nvidia in a big way. Last year, AMD’s sales rose by 14%, while Nvidia more than doubled its revenue during its most recent fiscal year. But what also matters are AMD’s margins, which need improvement. Otherwise, its P/E multiple may not come down significantly even if its growth rate accelerates. And a high premium could deter investors.

Nvidia is in pole position today, dominating the market and still innovating and coming up with new AI chips. AMD has to prove that it can put up some formidable competition. And until it does, that could limit its upside both in the near term and the long term.

Nvidia is the stock I’d go with today

AMD can potentially be a great long-term investment but it has a lot of question marks around its operations; it’s far from a slam-dunk buy at this stage and it comes with some risk. Not only does it need to show that its chips can provide real competition to Nvidia, but the company also has to improve upon its single-digit profit margin.

With much stronger financials, a more attractive valuation, and a more dominant position in the market, Nvidia is the better AI stock to buy today.

Top AI Innovators Recognized in One of the
World’s Premier Business Awards Programs

SAN FRANCISCO, May 8, 2025 /PRNewswire/ — The Globee® Awards, known for organizing premier data-driven business awards programs with global participation, are proud to announce the 2025 winners of the Globee® Awards for Artificial Intelligence. This prestigious program honors excellence in AI innovation, recognizing individuals, teams, products, and organizations that are leading the way in applying artificial intelligence to drive meaningful change, improve efficiency, and redefine industries.

View the complete list of winners: https://globeeawards.com/artificial-intelligence/winners/

This year’s winners represent excellence across the entire spectrum of artificial intelligence. The awards honor individuals, teams, and organizations that have successfully developed or implemented AI technologies and solutions with meaningful impact—driving innovation, enhancing performance, and setting new benchmarks for what’s possible with AI.

“The 2025 Globee® Awards for Artificial Intelligence winners are a testament to the power of innovation and the transformative potential of AI,” said San Madan, President of the Globee® Awards. “From startups to global enterprises, these honorees are solving real-world problems and shaping the future with data, technology, and purpose.”

About the Judging Process
The Globee® Awards use a transparent, data-driven judging process. For the 2025 AI program, more than 2,995 industry experts and professionals from across the globe applied as judges. Each nomination was carefully scored based on innovation, impact, relevance, and execution.

View the complete list of 2025 judges: https://globeeawards.com/excellence/judges/

About the Globee® Awards
The Globee® Awards present recognition in ten programs and competitions, including the Globee® Awards for Achievement, Globee® Awards for Artificial Intelligence, Globee® Awards for Business, Globee® Awards for Excellence, Globee® Awards for Cybersecurity, Globee® Awards for Disruptors, Globee® Awards for Impact. Globee® Awards for Innovation (also known as Golden Bridge Awards®), Globee® Awards for Leadership, and the Globee® Awards for Technology. To learn more about the Globee Awards, please visit the website: https://globeeawards.com.

Follow: @globeeawards #globeeawards #globeeexcellence #businessawards

All trademarks belong to their respective owners.

SOURCE Globee Awards

Artificial intelligence (AI) has become the new electricity powering financial operations, and nowhere is this more apparent than in the office of the CFO.

“It’s no longer a nice-to-have,” Steve Wiley, VP of product management at FIS, told PYMNTS. “Artificial intelligence is a must-have, and that’s happened very, very quickly.”

Even as recently as a year or two ago, AI was considered a fringe benefit or experimental tool. Now, amid a backdrop of growing macro uncertainty, AI systems are becoming increasingly embedded in the core strategic infrastructure of finance departments, particularly across key functions such as treasury, payments and risk mitigation.

“Seventy-five percent of knowledge workers, and those are people in the office of the CFO, now use AI at work, and half of those started using it in the last year,” Wiley said. “There’s an expectation now that AI-based solutions will be embedded within these financial products.”

Still, why now? Historically, the office of the chief financial officer (CFO) has lagged in forward-facing functions like marketing or customer service when it comes to technology adoption. But ongoing inflationary pressures and volatile global markets have forced the hand of finance leaders when it comes to embracing digital transformation at pace.

“AI makes technology a real differentiator for a business,” Wiley said. “And the expectation will be for CFOs to adopt those technologies and work with partners who can facilitate that.”

Read also: FIS Introduces ‘Treasury GPT’ in Conjunction With Microsoft AI

AI Finds Its Footing in Finance

There are two main, and growing, categories of AI usage: qualitative applications, such as language-based interfaces that enhance knowledge discovery and communication, and quantitative applications, like predictive analytics, cash forecasting and fraud mitigation.

While qualitative tools can improve user engagement and reduce training overhead, it’s the quantitative applications that are radically shifting finance’s functional value.

“People were using tools like ChatGPT to formulate policies, learn best practices — all outside of the enterprise system,” Wiley said. “There was an immediate opportunity to embed that within the system. Tools like Treasury GPT from FIS are leveraging that AI technology to offer that data access specifically for the treasury industry.”

Take cash forecasting. Traditional methods rely on backward-looking statistical models. But generative AI can synthesize real-time market data, customer behaviors and economic signals to forecast future liquidity needs more accurately.

“Treasurers are expecting tools to improve cash forecasting,” Wiley said. “Now, instead of using traditional historical-based models, treasury departments are expecting generative AI to project cash flows. And that’s already the new normal.”

Yet not every organization is ready to use artificial intelligence. A wide technological maturity gap separates early adopters from legacy holdouts.

“We still encounter organizations who are living in pre-digital, really operational eras. They have inadequate technology, manual processes, limited data visibility,” Wiley said. “Those with inadequate cash forecasts are paying more for capital. They’re not able to really invest with precision, and they’re leaving money on the table.”

On the other end of the spectrum are finance departments that have already embraced cloud-based infrastructure, advanced analytics, and automation. These organizations are not only ready for AI but are demanding it.

ROI Recalibrated for the AI Era

One of the most persistent questions CFOs ask when evaluating new technologies is: how do we measure ROI? For his part, Wiley believes AI is not an exception to traditional SaaS metrics, but that it does expand the frame.

“On the receivables side, you have elements like DSO [days sales outstanding], which AI can improve. On the treasury side, it’s about liquidity optimization — improving investment performance, managing FX and interest rate risk,” he said, also calling attention to more overlooked areas that AI can affect, such as bank fee analysis, payment security and payment efficiency — all of which add up quickly in large enterprises processing hundreds of thousands of transactions per month.

What’s next for AI in finance?

“CFOs are wanting centralized reporting and decision-making, and AI is going to facilitate that,” he said. “Historically, CFOs have observed things like liquidity, payments, receivables in isolation, but now you’ll see AI-based dashboards that look at the relationship between these areas — automatically.”

Ultimately, Wiley envisions a unified command center powered by AI that bridges previously siloed functions, adding that this evolution from functional to integrated financial intelligence promises to transform not just efficiency, but strategic decision-making.

Putting aside the exceptional volatility we’ve witnessed on Wall Street since the beginning of April, the can’t-miss trend over the last two and a half years has unquestionably been the evolution of artificial intelligence (AI).

In its simplest form, AI empowers software and systems with the ability to reason and act on their own. This capacity to make split-second decisions without human oversight, as well as evolve to (potentially) learn new skills or jobs, gives this technology a truly jaw-dropping addressable market. In Sizing the Prize, PwC pegged this market potential at $15.7 trillion, globally, by the turn of the decade.

When most investors think of the AI revolution, Nvidia (NVDA 2.95%) is probably the first company that comes to mind. In less than two years, Nvidia went from being a fringe leader in the tech industry, with a $360 billion market cap, to the greatest thing since sliced bread, with a valuation that easily topped $3 trillion. Nvidia’s Hopper (H100) graphics processing units (GPUs) and successor Blackwell GPU architecture rapidly became the preferred hardware in Al-accelerated data centers.

But Nvidia has been usurped as Wall Street’s AI darling by data-mining specialist Palantir Technologies (PLTR 1.44%). Heading into this week, Palantir was worth $293 billion, and its shares had risen by roughly 1,840% since the start of 2023. It went from being one of many high-growth tech stocks to a foundational piece of the AI revolution.

Yet following the release of Palantir’s much-anticipated first-quarter operating results, there’s a new label that can be added: Wall Street’s biggest bubble stock.

Palantir’s moat and growth rate continue to dazzle Wall Street

Though I’ll explain how it’s a bubble stock in detail in a moment, let’s take a closer look at how Palantir has dazzled Wall Street and added $278 billion in market value in 29 months.

The biggest catalyst for Palantir is that its AI-driven software-as-a-service (SaaS) solutions can’t be duplicated at scale. While the company’s Gotham and Foundry platforms may contend with small-scale competition, there simply isn’t a one-for-one replacement for the services they provide. Nothing on Wall Street is more valued by investors than a sustainable moat — and Palantir certainly offers one.

Gotham continues to be the crown jewel. This is the segment that lands multiyear contracts with the U.S. federal government and its allies. Gotham handles data collection and analysis, as well as plays a critical role in military mission planning and execution. America’s robust defense spending has led to pretty consistent growth. In the March-ended quarter, U.S. government revenue soared by 45% from the prior-year period.

Foundry hasn’t been a slouch, either. This relatively newer platform leans on AI and machine learning to help businesses make sense of their data and streamline their operations. U.S. commercial revenue surged a whopping 71% during the first quarter, which is an indication that Palantir is just scratching the surface with this segment, as well as earning subscriptions from larger companies.

Another reason Palantir has excelled is its push to recurring profitability, which occurred well before anyone on Wall Street had expected. Profits help to validate Palantir’s dual-platform approach, and its sustained double-digit sales growth rate has clearly excited the investing community.

Lastly, Palantir closed out March with $5.43 billion in cash, cash equivalents, and marketable securities, which represents about a $200 million boost from where it ended 2024. Having a lot of cash and no debt means CEO Alex Karp and his team can aggressively reinvest in its AI-powered platforms, as well as undertake shareholder-friendly actions at times, such as share buybacks.

Image source: Getty Images.

Palantir’s operating results confirm it’s, arguably, Wall Street’s biggest bubble stock

Considering the uncertainty surrounding President Donald Trump’s tariff policy, as well as the possibility of the U.S. federal government reducing defense spending, investors were particularly interested in Palantir’s forward-looking sales and adjusted free cash flow (FCF) guidance for the recently completed quarter.

In early February, Palantir guided for $3.741 billion to $3.757 billion in full-year sales, with $1.5 billion to $1.7 billion in full-year adjusted FCF. On Monday, May 5, it upped its 2025 sales guide to $3.89 billion to $3.902 billion — an increase of $147 million at the midpoint — as well as lifted the high and low end of its adjusted FCF by $100 million to $1.6 billion to $1.8 billion.

While Palantir increasing the midpoint of its sales guidance by 3.92% might sound impressive, it comes on the heels of its stock tipping the scales at north of 100 times trailing-12-month sales entering this week.

Based on the midpoint of the company’s now-dated 2025 sales guidance ($3.749 billion), Palantir would have been valued at a price-to-sales (P/S) ratio of roughly 78 come February 2026 (i.e., when it reports its fourth-quarter operating results). Updating for the new guidance, which calls for a midpoint of $3.896 billion in full-year revenue, lowers its projected year-end P/S ratio to (drum roll) 75.2! It hardly makes a dent.

To put into context just how unbelievably expensive Palantir stock is relative to sales, take a closer look at how other market-leading businesses performed prior to bubble-bursting events.

MSFT PS Ratio data by YCharts.

Before the dot-com bubble burst, Microsoft, Amazon, and Cisco Systems all peaked at respective P/S ratios ranging from roughly 31 to 43. I added Nvidia to this chart, as well, which topped out at a P/S ratio of just over 42 last summer. Though there are other public companies with P/S ratios north of 100, what we don’t see is market-leading megacap businesses valued at P/S ratios north of 40 for any extended period — let alone a P/S ratio that’s camped out at more than 100!

To add fuel to the fire, every next-big-thing innovation for more than 30 years has navigated its way through a bubble-bursting event early in its expansion. Investors have persistently overestimated how quickly a new technology will be utilized and adopted, which eventually leads to outsized expectations not being met.

While a company like Nvidia would almost immediately feel the pain associated with an AI bubble-bursting event, Palantir Technologies would be partially insulated by its multiyear government contracts and Foundry subscription revenue. But “partially insulated” doesn’t mean immune. Palantir’s unjustifiable valuation premium would almost certainly come under fire if the AI bubble bursts, which history suggests will eventually happen.

Rarely are stock-specific bubbles this easy to recognize. Though I do believe Palantir is worthy of some level of premium due to its sustainable moat and recurring revenue, no market leader has been able to sustain a P/S ratio of 30, let alone 75 or 100. Palantir is, in my view, Wall Street’s biggest bubble stock.

The Pittsburgh Steelers are sitting in anticipation, as the possibility of landing veteran quarterback Aaron Rodgers remains the biggest question mark in their offseason plans. With each passing day, signals from within the organization suggest that the team is confident Rodgers will eventually call Pittsburgh home — but the clock keeps ticking, and the ink has yet to meet the paper.

Aaron Rodgers’ bizarre NFL journey mocked as more confusing than AI by Steelers part-owner Thomas Tull

Back in March, principal owner Art Rooney II made headlines when he confidently stated, “he does want to come here” — a sentiment that seemed to all but confirm Aaron Rodgers’ arrival. Yet, weeks later, Steelers fans are still left wondering if this much-discussed union will finally materialize. Adding to the intrigue, Thomas Tull, one of the team’s minority owners, offered his own take during an appearance on CNBC. When asked about the situation, Tull quipped, “I’m here to talk about AI, and that’s a more complex issue than artificial intelligence.”The remark drew laughter, but also underlined a serious truth. Rodgers’ future is as complicated and unpredictable as the quarterback himself — a player known for his introspection, cryptic messaging, and methodical decision-making. As Tull’s comment subtly implied, even seasoned executives within the Steelers’ hierarchy find themselves perplexed by the enigmatic signal-caller.Rodgers, for his part, hasn’t ruled out Pittsburgh. During an appearance on The Pat McAfee Show, he acknowledged ongoing conversations with the Steelers and expressed admiration for head coach Mike Tomlin. “I’ve been upfront with them,” Rodgers said. “I’ve said, listen, if you need to move on, by all means. … I am trying to be open to everything and not specifically attached to anything … I’m not holding anybody hostage.”The statement reflects both transparency and indecision. It’s clear that Rodgers appreciates the franchise’s legacy and leadership, but his own personal challenges have kept him from making a definitive move. Given his thoughtful nature, it wouldn’t be surprising if he waits until the NFL’s full 2025 schedule is released — expected next Wednesday — before making any commitments. As sources suggest, Rodgers may be watching to see how the Steelers fare in terms of prime-time games and competitive positioning, especially compared to a scenario where Mason Rudolph remains the starter.Despite the uncertainty, the Steelers’ behavior paints a picture of optimism. Rooney’s repeated hints and the team’s patience in negotiations all point to one thing: they believe Rodgers is coming. And they’re willing to wait — even if it’s uncomfortable — for the payoff.In the grand chess game of NFL quarterback movement, Aaron Rodgers remains one of the few true kings left on the board. Whether Pittsburgh becomes his final destination or just another conversation in a long offseason saga, one thing is certain: until his signature is on a contract, the story is far from over.Also Read: NFL sparks political firestorm by having President Trump announce 2027 Draft from the White House

The government of Singapore released a blueprint today for global collaboration on artificial intelligence safety following a meeting of AI researchers from the US, China, and Europe. The document lays out a shared vision for working on AI safety through international cooperation rather than competition.

“Singapore is one of the few countries on the planet that gets along well with both East and West,” says Max Tegmark, a scientist at MIT who helped convene the meeting of AI luminaries last month. “They know that they’re not going to build [artificial general intelligence] themselves—they will have it done to them—so it is very much in their interests to have the countries that are going to build it talk to each other.”

The countries thought most likely to build AGI are, of course, the US and China—and yet those nations seem more intent on outmaneuvering each other than working together. In January, after Chinese startup DeepSeek released a cutting-edge model, President Trump called it “a wakeup call for our industries” and said the US needed to be “laser-focused on competing to win.”

The Singapore Consensus on Global AI Safety Research Priorities calls for researchers to collaborate in three key areas: studying the risks posed by frontier AI models, exploring safer ways to build those models, and developing methods for controlling the behavior of the most advanced AI systems.

The consensus was developed at a meeting held on April 26 alongside the International Conference on Learning Representations (ICLR), a premier AI event held in Singapore this year.

Researchers from OpenAI, Anthropic, Google DeepMind, xAI, and Meta all attended the AI safety event, as did academics from institutions including MIT, Stanford, Tsinghua, and the Chinese Academy of Sciences. Experts from AI safety institutes in the US, UK, France, Canada, China, Japan and Korea also participated.

“In an era of geopolitical fragmentation, this comprehensive synthesis of cutting-edge research on AI safety is a promising sign that the global community is coming together with a shared commitment to shaping a safer AI future,” Xue Lan, dean of Tsinghua University, said in a statement.

The development of increasingly capable AI models, some of which have surprising abilities, has caused researchers to worry about a range of risks. While some focus on near-term harms including problems caused by biased AI systems or the potential for criminals to harness the technology, a significant number believe that AI may pose an existential threat to humanity as it begins to outsmart humans across more domains. These researchers, sometimes referred to as “AI doomers,” worry that models may deceive and manipulate humans in order to pursue their own goals.

The potential of AI has also stoked talk of an arms race between the US, China, and other powerful nations. The technology is viewed in policy circles as critical to economic prosperity and military dominance, and many governments have sought to stake out their own visions and regulations governing how it should be developed.