Latest news with #advancedeconomies
Telegraph
2 days ago
- Business
- Telegraph
Politicians got used to cheap money. Now they're paying the price
Almost without exception, governments in advanced economies face an uneasy combination of high public debt and growth rates that are far too slow to fund rising public spending without resorting to even more borrowing or further anti-growth tax increases. Set against these serious policy challenges, it is no wonder that the surge in government borrowing costs that followed the gas-related inflation spike in 2022 has become a major source of concern for financial markets. In the UK and the US, 10-year government borrowing costs – a key market benchmark – have fluctuated in the 4pc-5pc range since the start of the year. Whenever borrowing costs edge towards 5pc, genuine panic seems to take hold. The commonly held view is that higher benchmark interest rates are a temporary issue that will disappear once inflation is under control, or that they are mostly a symptom of fiscal sustainability worries and can be resolved with sufficient budget discipline. But this is wrong. I am not arguing that governments and central banks should not take serious measures to improve policy discipline. Quite the opposite – this matters more than ever. Instead, my point is that even if we achieved both monetary and fiscal sustainability across the advanced world, my guess is that interest rates would fall only slightly. Why? Because the global economic forces that pushed interest rates to rock-bottom levels for more than a decade after the global financial crisis have gone into reverse. First, the global balance of savings and investment has shifted to a state that more closely resembles the pre-2008 era. In the wake of the crisis, demand for borrowing in Western economies collapsed. Along with a global rush to safety and excess savings in places like China, Japan and Germany, lower interest rates were required to balance global saving and investment. But Western debt demand is less depressed today, and the global savings glut is shrinking. In turn, the interest rates that balance these markets have risen. Second, global trade is flowing less freely as trade barriers increase and the geopolitical order fragments. US isolationism, the war in Ukraine and trouble in the Middle East put upward pressure on goods prices and increase the threat of conflict-related commodity price shocks. These inflation fears are reflected in interest rates. Third, a decades-long global demographic tailwind has turned into a headwind that will only worsen over time. As societies age, labour shortages push up wage costs and structural inflationary pressures. Fourth, with the return of inflation and the rise in global interest rates, central banks have ended their massive purchases of government debt — or quantitative easing (QE). In some cases, including the UK, central banks have been actively selling off their government debt portfolios. During the financial crisis, the argument against bailing out institutions was that it would foster moral hazard. Banks, betting on future bailouts, would take on much more risk than they otherwise would if they had to bear responsibility for their decisions. This rationale was partly behind the tragic decision to allow Lehman Brothers to fail. But, in a strange twist of fate, it was governments themselves that fell prey to moral hazard. We knew back in 2008 that government debt was at risk of spiralling out of control and that excessive deficits needed to be curtailed. That is why the UK and US both embarked on belt-tightening once the recession ended, and why parts of peripheral Europe were forced to endure excruciating austerity. But after a while, those fears about fiscal sustainability faded as structural forces drove down government borrowing costs and QE tranquillised bond investors. By the time Covid hit in 2020 – when borrowing costs reached their nadir and governments had convinced themselves that inflation would never return, and that interest rates would stay low forever – they had no misgivings whatsoever about ramping up borrowing. A German economist named Rüdiger Dornbusch, who spent most of his career in the US, said: 'Crises take longer to arrive than you can possibly imagine, but when they do come, they happen faster than you can possibly imagine.' This roughly captures the story of fiscal policy in advanced economies over the past two decades. After interest rates stayed low for much longer than anyone imagined, they normalised faster than anyone thought they could. The maths behind massive debt-financed green transitions, generous welfare states and rising defence spending – all while financing rising state pension costs and increased public healthcare demands – never really added up. But the era of ultra-low interest rates allowed policymakers to kick any hard policy choices into the long grass. Not any more.
Forbes
3 days ago
- Business
- Forbes
Top AI Degrees That Will Future-Proof Your Career
Artificial intelligence is reshaping our entire economic landscape at a pace that would have seemed impossible just a few years ago. The United Nations Conference on Trade and Development projects the global AI market will soar from $189 billion in 2023 to $4.8 trillion by 2033—a staggering 25-fold increase in just a decade. But here's what makes this revolution different from previous technological shifts: it's not just creating new industries, it's fundamentally changing how almost every industry operates. While about one-third of roles in advanced economies face automation risks, 27% of jobs stand to be enhanced, not eliminated, by AI according to the World Economic Forum. You'd naturally assume that computer science and engineering graduates would be the safest bets in an AI-driven world, right? The latest data from the Federal Reserve Bank of New York tells a more complex story that should make every student and parent reconsider their assumptions. Computer science is actually experiencing unemployment rates well above the national average. Anthropology, physics, and commercial art are showing some of the highest unemployment rates among recent graduates. Meanwhile, majors like nutrition sciences, special education, civil engineering, and nursing are enjoying low unemployment rates, some under 1.5%. This paradox reveals something crucial about our AI-driven future: The most valuable skills aren't always the most obvious ones. The $1.1 trillion annual loss our economy suffers from skills gaps shows a fundamental misalignment between what graduates are prepared for and what the economy actually needs. The following is a list of majors that offer the best combination of opportunity, stability, and AI readiness. Each represents a different pathway into our AI-enhanced future. My recommendation is to pair a technology-driven major with a non-technology driven major to build technical competencies alongside domain expertise. Computer science remains the foundational discipline for AI development, but here's the reality check: despite being at the heart of the AI revolution, computer science graduates are facing unemployment rates above the national average, likely due to AI taking the work of entry level computer science graduates. Facebook has even announced plans for replacing mid-level engineers. The field covers programming languages, algorithms, data structures, software engineering, and increasingly, machine learning and artificial intelligence fundamentals. Students develop critical thinking skills, mathematical reasoning, and the ability to solve complex problems systematically. Who should consider this path? Students who genuinely enjoy problem-solving, have strong analytical skills, and aren't deterred by increased is also wise to choose colleges that are incorporating AI into their curricula This is where the skills gap becomes apparent: employers aren't just looking for programmers anymore. They need computer scientists who can bridge the gap between technical capability and real-world application; who understand both the code and the context in which it operates. Those who combine computer science with domain expertise in healthcare, finance, or other fields are finding significantly better opportunities so I would recommend a double major in computer science and another subject such as systems engineering, business, or healthcare. Data science sits at the intersection of statistics, computer science, and domain expertise, and unlike pure computer science, it's experiencing strong job market performance. According to the U.S. Bureau of Labor Statistics, employment of data scientists is projected to grow 36% from 2023 to 2033, much faster than the average for all occupations. This difference highlights something crucial about the skills gap: employers need people who can bridge technical capability with practical application, not just coding ability. Students learn to extract insights from large datasets using statistical methods, machine learning algorithms, and data visualization techniques. The curriculum typically covers programming in Python and R, statistical analysis, database management, and machine learning. The field develops analytical thinking, statistical reasoning, and crucially, the ability to communicate complex findings to non-technical audiences. This communication component is where many technically skilled graduates fall short, contributing to the skills gap even in high-demand fields. Data science addresses the skills gap by producing graduates who understand both the technical and business sides of AI implementation. Every AI system relies on quality data and proper analysis, but more importantly, it needs people who can translate AI insights into actionable business decisions. Graduates find themselves building datasets that train AI models, developing algorithms that power recommendation systems, and creating analytics frameworks that measure AI system performance. Nursing represents one of the most striking examples of how unemployment data reveals hidden opportunities. With unemployment rates consistently under 1.5%—among the lowest of any field—nursing graduates are entering a market that desperately needs their skills. The curriculum covers anatomy, physiology, pharmacology, patient care, and increasingly, health informatics and AI-powered diagnostic tools. Students develop clinical skills, critical thinking under pressure, empathy, and the ability to make quick decisions with incomplete information. Healthcare transformation through AI-powered diagnostics, predictive analytics, and telehealth technologies requires nurses who understand these tools without losing the human touch. They're the ones ensuring AI recommendations enhance rather than replace clinical judgment, filling a critical role in our AI-enhanced healthcare future. Here's another field where the unemployment data tells a powerful story. Special education and early childhood education majors enjoy unemployment rates well below the national average, often under 2%. This reflects a critical skills gap that AI is actually widening rather than closing—we need more educators who can use AI to personalize learning while maintaining the human connection that makes education effective. The curriculum covers child development, learning theories, classroom management, and increasingly, educational technology and AI-powered personalized learning tools. Students develop patience, creativity, communication skills, and the ability to adapt teaching methods to different learning styles. Aerospace engineering combines complex technical challenges with cutting-edge AI applications. Students learn aerodynamics, propulsion, materials science, and control systems, along with AI-driven autonomous systems and design optimization techniques. The curriculum develops advanced mathematical skills, systems thinking, and the ability to work with incredibly complex, high-stakes projects. Students learn to balance multiple engineering constraints while maintaining absolute precision and safety standards. This field attracts students fascinated by flight and space exploration, who excel in mathematics and physics, and can handle the pressure of working on systems where failure isn't an option. You need attention to detail, strong analytical skills, and the ability to think in three dimensions. AI is revolutionizing aerospace through autonomous flight systems, predictive maintenance, optimized design algorithms, and advanced manufacturing processes. Engineers who understand both traditional aerospace principles and AI applications are developing the next generation of aircraft and spacecraft. Philosophy might seem like an unusual choice for an AI-focused career, especially given that some humanities fields like anthropology are showing higher unemployment rates among recent graduates. However, philosophy represents a different kind of opportunity that addresses a critical gap in AI development that most people don't even realize exists. Students study logic, ethics, critical thinking, and argumentation. The curriculum develops analytical reasoning, ethical decision-making, and the ability to think clearly about complex, abstract problems. Philosophy majors learn to identify assumptions, construct logical arguments, and consider multiple perspectives on difficult questions. The unemployment challenges in some humanities fields often stem from graduates not understanding how to translate their skills into AI-relevant careers. Philosophy graduates who can articulate their value in AI contexts—ethics, logical reasoning, policy development—find significantly better opportunities than those who don't make these connections explicit. This addresses a massive component of the skills gap: as AI systems become more powerful and widespread, we desperately need people who can think clearly about their ethical implications, societal impact, and proper governance. Philosophy graduates are uniquely positioned to work on AI ethics, policy development, and ensuring AI systems align with human values—roles that didn't exist five years ago but are becoming critical. Choosing your degree in an AI-driven world isn't about picking the "safest" option or chasing the highest starting salary. It's about understanding how your interests and strengths can contribute to a world where human and artificial intelligence work together. The most successful professionals will be those who build versatile skill portfolios—combining technical competency with creative thinking, ethical reasoning, and deep domain expertise. They'll be the ones who see AI not as a threat to human capability, but as a tool that amplifies what makes us uniquely human. The AI revolution is just beginning, and the opportunities it creates will go to those prepared not just to use AI, but to shape how it develops and integrates into society. Your degree choice today is your first step into that future.
The National
6 days ago
- Business
- The National
Why AI in your workplace could be a good thing - and a bad one
Artificial intelligence has been on a hot streak and, while it's a boon for some, it has been bane for jobs. Most of the attention has been drawn to the negatives – jobs displaced or wiped out – but studies have found the technology to be an opportunity to create more and reskill employees. Human resources departments, meanwhile, have also been trying to figure out how to balance tradition with the hot innovation. "The biggest change will be people working alongside AI, to capture the upside of 'augmented intelligence', so there will be a race to equip people with the right mindsets, skill sets and toolsets,' Lisa Lyons, regional transformation centre of excellence lead at New York-based professional services firm Mercer, tells The National. "Another bright side, is making work more interesting … employees report that their work today is mundane and repetitive, presenting an obvious opportunity for process and cognitive automation.' History repeating itself Analysts have drawn parallels to other industrial revolutions, in which the job market was disrupted, in what is considered its fourth iteration. The big difference is that the technology has set the pace faster, and everything else must keep in step. And while it is universally agreed upon that AI will indeed replace or displace jobs, figures have varied. But, in fact, jobs continue to be created as eras open up roles and demand. The International Monetary Fund estimates that 60 per cent of jobs in advanced economies would be affected by AI; that number drops to 40 per cent 26 per cent in emerging and low-income economies, respectively. "As AI continues to develop, it will become increasingly adept at performing a variety of roles that have traditionally been done by humans,' says Mohammed Alkhotani, a senior vice president at cloud services company Salesforce Middle East. For example, autonomous AI agents, built on natural language processing and powerful reasoning engines, can mimic human language – both written and spoken – and are ideally suited to handle a wide range of roles. "This particularly applies to customer services, where AI agents are already working alongside humans,' Mr Alkhotani tells The National. Customer services are forecast to be among the top declining roles through 2030, the World Economic Forum said in its Future of Jobs Report 2025. Multiple studies agree on what jobs are at risk from AI, or the jobs the functions of which can be mostly performed by AI in a more accurate and cost-efficient way. Among those roles that have been automated, or are at risk of being automated, are telemarketers, customer service representatives, manufacturing assembly line workers, proofreaders and translators. On the flipside, jobs that are less at risk – or are outright difficult to replace using the technology of today – are those that need people to provide emotional understanding, interpersonal skills, human judgment and adaptability, according to Kieran Gilmurray, an AI strategist who founded an IT services firm bearing his name in Northern Ireland. Those include jobs in health care (doctors, surgeons, nurses), the arts (sculptors, musicians), social workers and counsellors and skilled tradespeople (electricians, carpenters, plumbers). "AI should complement human expertise, not replace it … decision-making often requires nuance, negotiation and adaptability, which AI cannot fully replicate,' says Ibrahim Imam, Vienna-based construction software developer PlanRadar's chief executive for the Middle East and North Africa, and Asia-Pacific regions. "The key to successful AI integration is continuous training, contextual learning and a hybrid approach where AI handles data-heavy tasks, allowing professionals to focus on strategic, human-centric decisions.' The HR dilemma Much of the focus – and worries – of the apparent job disruption has been towards the workforce, and HR units of companies are feeling the pinch. For instance, while HR teams are likely to incorporate more AI tools, the idea of AI fully replacing human HR professionals is highly unlikely for a number of reasons. While AI can streamline recruitment, onboarding, and employee performance tracking, it lacks the emotional intelligence needed for complex human interactions, says Nicki Wilson, managing director of Dubai-based recruitment firm Genie. "It also becomes a bit of a spambot in the sense that AI can often seek out job roles for jobseekers and send hundreds, if not thousands, of applications to adverts, decision makers and HR teams,' she tells The National. In addition, using AI tools to create CVs are "actually counter productive', as most traditional software that recruiters and employers use cannot read these CVs, which are effectively images, she says. "This, honestly, is not helping anyone trying to hire.' The WEF agrees. AI systems still largely rely on self-reported candidate information, making them susceptible to inaccuracies, the jobs report says. It added that around 88 per cent of companies have already used some form of AI for initial candidate screening. However, that has already been a trend, even before the pandemic year – and way before ChatGPT burst into the scene, a study from US-based HR services firm SHRM finds. "What's more, these systems can also filter out highly qualified, high-skill candidates if their profiles don't match the exact criteria specified in the job description,' the WEF report stresses. Rolling with the punches In the US, inefficient career transitions and learning gaps are costing the world's biggest economy about $1.1 trillion annually, research from UK education conglomerate Pearson shows. That underscores the need for more effective workforce development solutions, as AI's role in workforce development "extends far beyond improving efficiency', a representative from the London-based company tells The National. Jobs that require human interaction, creativity, critical thinking, strategic decision-making, emotional intelligence and advanced technical expertise are best positioned to thrive amid the AI boom, recruitment consultants had previously told The National. "AI-driven platforms can offer personalised learning experiences … these platforms analyse employees' individual learning styles, strengths and weaknesses to deliver content tailored to their needs, helping to bridge skill gaps effectively and efficiently,' the Pearson representative says. That does not mean companies should just roll with the punches. A study from the California-based non-profit Rand Corporation finds that more than 80 per cent of AI projects don't succeed. That "emphasises the need for clear guidelines and practical applications', says Evgenii Pavlov, general manager at Yango Ads Middle East and Africa. "The technology landscape is littered with instances where AI was applied unnecessarily, resulting in failures and unmet expectations,' he tells The National. AI in circles The reliability of AI systems has always been under scrutiny. It is not uncommon for chatbots or – text-based or voice – which are increasingly replacing humans in call centres, to take users in circles. Some do not even have outright options to request for an actual person to speak to. The reason for this is issues such as limited understanding of complex queries, and poor training data, in addition to scaleability problems wherein bots still in development, with limited testing, have been rolled out, leading to inefficiencies. "Finally, the process of human-AI collaboration, such as escalating to a human agent, can sometimes be inadequately managed, leading to circular interactions,' says Louis Mottli, founder and chief executive of UK-based entertainment app developer Mottli. "At its core, AI has always been an enablement technology, designed not to replace but to enhance human thinking, decision-making and execution … businesses don't succeed by automating everything; they succeed by striking the right balance.'
The National
7 days ago
- Business
- The National
Can you hire AI for a job?
Artificial intelligence has been on a hot streak and, while it's a boon for some, it has been bane for jobs. Most of the attention has been drawn to the negatives – jobs displaced or wiped out – but studies have found the technology to be an opportunity to create more and reskill employees. Human resources departments, meanwhile, have also been trying to figure out how to balance tradition with the hot innovation. "The biggest change will be people working alongside AI, to capture the upside of 'augmented intelligence', so there will be a race to equip people with the right mindsets, skill sets and toolsets,' Lisa Lyons, regional transformation centre of excellence lead at New York-based professional services firm Mercer, tells The National. "Another bright side, is making work more interesting … employees report that their work today is mundane and repetitive, presenting an obvious opportunity for process and cognitive automation.' Analysts have drawn parallels to other industrial revolutions, in which the job market was disrupted, in what is considered its fourth iteration. The big difference is that the technology has set the pace faster, and everything else must keep in step. And while it is universally agreed upon that AI will indeed replace or displace jobs, figures have varied. But, in fact, jobs continue to be created as eras open up roles and demand. The International Monetary Fund estimates that 60 per cent of jobs in advanced economies would be affected by AI; that number drops to 40 per cent 26 per cent in emerging and low-income economies, respectively. "As AI continues to develop, it will become increasingly adept at performing a variety of roles that have traditionally been done by humans,' says Mohammed Alkhotani, a senior vice president at cloud services company Salesforce Middle East. For example, autonomous AI agents, built on natural language processing and powerful reasoning engines, can mimic human language – both written and spoken – and are ideally suited to handle a wide range of roles. "This particularly applies to customer services, where AI agents are already working alongside humans,' Mr Alkhotani tells The National. Customer services are forecast to be among the top declining roles through 2030, the World Economic Forum said in its Future of Jobs Report 2025. Multiple studies agree on what jobs are at risk from AI, or the jobs the functions of which can be mostly performed by AI in a more accurate and cost-efficient way. Among those roles that have been automated, or are at risk of being automated, are telemarketers, customer service representatives, manufacturing assembly line workers, proofreaders and translators. On the flipside, jobs that are less at risk – or are outright difficult to replace using the technology of today – are those that need people to provide emotional understanding, interpersonal skills, human judgment and adaptability, according to Kieran Gilmurray, an AI strategist who founded an IT services firm bearing his name in Northern Ireland. Those include jobs in health care (doctors, surgeons, nurses), the arts (sculptors, musicians), social workers and counsellors and skilled tradespeople (electricians, carpenters, plumbers). "AI should complement human expertise, not replace it … decision-making often requires nuance, negotiation and adaptability, which AI cannot fully replicate,' says Ibrahim Imam, Vienna-based construction software developer PlanRadar's chief executive for the Middle East and North Africa, and Asia-Pacific regions. "The key to successful AI integration is continuous training, contextual learning and a hybrid approach where AI handles data-heavy tasks, allowing professionals to focus on strategic, human-centric decisions.' Much of the focus – and worries – of the apparent job disruption has been towards the workforce, and HR units of companies are feeling the pinch. For instance, while HR teams are likely to incorporate more AI tools, the idea of AI fully replacing human HR professionals is highly unlikely for a number of reasons. While AI can streamline recruitment, onboarding, and employee performance tracking, it lacks the emotional intelligence needed for complex human interactions, says Nicki Wilson, managing director of Dubai-based recruitment firm Genie. "It also becomes a bit of a spambot in the sense that AI can often seek out job roles for jobseekers and send hundreds, if not thousands, of applications to adverts, decision makers and HR teams,' she tells The National. In addition, using AI tools to create CVs are "actually counter productive', as most traditional software that recruiters and employers use cannot read these CVs, which are effectively images, she says. "This, honestly, is not helping anyone trying to hire.' The WEF agrees. AI systems still largely rely on self-reported candidate information, making them susceptible to inaccuracies, the jobs report says. It added that around 88 per cent of companies have already used some form of AI for initial candidate screening. However, that has already been a trend, even before the pandemic year – and way before ChatGPT burst into the scene, a study from US-based HR services firm SHRM finds. "What's more, these systems can also filter out highly qualified, high-skill candidates if their profiles don't match the exact criteria specified in the job description,' the WEF report stresses. In the US, inefficient career transitions and learning gaps are costing the world's biggest economy about $1.1 trillion annually, research from UK education conglomerate Pearson shows. That underscores the need for more effective workforce development solutions, as AI's role in workforce development "extends far beyond improving efficiency', a representative from the London-based company tells The National. Jobs that require human interaction, creativity, critical thinking, strategic decision-making, emotional intelligence and advanced technical expertise are best positioned to thrive amid the AI boom, recruitment consultants had previously told The National. "AI-driven platforms can offer personalised learning experiences … these platforms analyse employees' individual learning styles, strengths and weaknesses to deliver content tailored to their needs, helping to bridge skill gaps effectively and efficiently,' the Pearson representative says. That does not mean companies should just roll with the punches. A study from the California-based non-profit Rand Corporation finds that more than 80 per cent of AI projects don't succeed. That "emphasises the need for clear guidelines and practical applications', says Evgenii Pavlov, general manager at Yango Ads Middle East and Africa. "The technology landscape is littered with instances where AI was applied unnecessarily, resulting in failures and unmet expectations,' he tells The National. The reliability of AI systems has always been under scrutiny. It is not uncommon for chatbots or – text-based or voice – which are increasingly replacing humans in call centres, to take users in circles. Some do not even have outright options to request for an actual person to speak to. The reason for this is issues such as limited understanding of complex queries, and poor training data, in addition to scaleability problems wherein bots still in development, with limited testing, have been rolled out, leading to inefficiencies. "Finally, the process of human-AI collaboration, such as escalating to a human agent, can sometimes be inadequately managed, leading to circular interactions,' says Louis Mottli, founder and chief executive of UK-based entertainment app developer Mottli. "At its core, AI has always been an enablement technology, designed not to replace but to enhance human thinking, decision-making and execution … businesses don't succeed by automating everything; they succeed by striking the right balance.'
Yahoo
10-05-2025
- Business
- Yahoo
Here Are the 2 Best Artificial Intelligence Stocks to Buy in May and 1 to Avoid
Over 3 billion people use Meta's apps daily, giving them an unmatched audience. Nvidia's CUDA platform gives it an incredibly resilient moat to grow its business. Palantir boasts impressive growth, but its valuation is just too high right now. These 10 stocks could mint the next wave of millionaires › If the promises of some of artificial intelligence's (AI) biggest champions come true, the technology will fundamentally reshape our world; nothing will be the same. Maybe this won't come to pass. Maybe the tech evangelists have oversold a technology's power once again. The thing is, it doesn't have to live up to the full extent of the hype to still have a massive economic impact. And it's not just tech CEOs making bold claims. The International Monetary Fund believes 40% of global employment will be affected by AI -- and 60% in "advanced economies" like the U.S. One of the Big Four accounting firms, PwC, believes AI will add $15.7 trillion to the global economy by 2030. But just because a company is involved in AI doesn't make it a good pick. Past technological revolutions have made it clear that when the dust settles, many of what seemed like promising companies get left behind. So, here are my two favorite AI picks in May -- and one to stay away from. Meta Platforms (NASDAQ: META), the parent company of Facebook and Instagram, is uniquely positioned to harness the power of AI. Why? A massive, highly engaged audience that is unmatched. Across its "family of apps," Meta reported more than 3.4 billion daily active users this quarter -- up 6% year over year. That sort of audience of captive users means Meta can focus on refining its AI features rather than building an audience from scratch. It's also what makes Meta's core business -- advertising, accounting for 99% of its revenue -- incredibly valuable. The company's top line has grown at a double-digit pace in four of the past five years, and now it's using AI to take that growth further. Meta is deploying the technology to both improve ad targeting and give advertisers creative tools that make their ads more effective and cheaper to produce. In the latest quarter, Meta said these efforts lifted conversion rates by 5% -- a figure that's likely to improve as its AI models mature. Looking ahead, Meta is betting on AI to define the future of how people interact with computing. The company says its Meta Glasses are the "ideal form factor" for AI and is developing a voice-based assistant with low latency to power them. If successful, I could see these smart glasses moving from novelty to necessity, even replacing smartphones for many users. Finally, Meta stock happens to be one of the most attractively priced among its big tech peers, trading at 23 times earnings. While that's not necessarily cheap, by tech standards, it's more than reasonable. No company dominates the AI GPU market like Nvidia (NASDAQ: NVDA), and the rewards have been massive. Fueled by surging chip sales and continued demand, Nvidia has maintained and even expanded its impressive margins over the last few years -- although these do seem to have found an upper limit in the mid-50s. Its chips are still miles ahead of those from its closest competitors, and its incredible free cash flow means it can spend lavishly on research and development to maintain its edge. Beyond its hardware edge, however, Nvidia's most significant edge may be on the software side. Its CUDA platform, a software layer that allows developers to program GPUs for complex tasks beyond the simple graphics they were created for, is what enables GPUs to be used for AI today. While other software like it exists, CUDA is ubiquitous throughout the industry. Most AI software is designed to work on top of CUDA, making it extremely costly and complex for customers to switch to another hardware provider. They would need to rework their own software to work with that company's CUDA equivalent, likely even needing to hire entirely new developers. That is extremely expensive. This "stickiness" ensures that clients remain loyal and willing to pay a premium, reinforcing Nvidia's dominant position in the AI chip market. There are real hurdles ahead, but I think Nvidia has proven its ability to innovate and adapt, and with its stock trading at one of its lowest price-to-earnings ratios (P/E) in many years, I think Nvidia is still a great pick. Palantir Technologies (NASDAQ: PLTR), an AI-powered intelligence and analytics company, is a great company in almost every way from an investing perspective. It is an innovative company delivering consistent double-digit growth and expanding margins, and the demand for its services remains very high. The value it provides to its clients is undeniable. However, its stock is just too expensive -- and that's putting it lightly. Palantir shares carry a P/E of nearly 500. That's more than 12 times the P/E of Nvidia, which is growing its top and bottom lines at a faster clip. Its valuation is simply divorced from reality, and I would caution you to stay away unless the stock falls significantly. Ever feel like you missed the boat in buying the most successful stocks? Then you'll want to hear this. On rare occasions, our expert team of analysts issues a 'Double Down' stock recommendation for companies that they think are about to pop. If you're worried you've already missed your chance to invest, now is the best time to buy before it's too late. And the numbers speak for themselves: Nvidia: if you invested $1,000 when we doubled down in 2009, you'd have $304,370!* Apple: if you invested $1,000 when we doubled down in 2008, you'd have $37,442!* Netflix: if you invested $1,000 when we doubled down in 2004, you'd have $617,181!* Right now, we're issuing 'Double Down' alerts for three incredible companies, available when you join , and there may not be another chance like this anytime soon.*Stock Advisor returns as of May 5, 2025 Randi Zuckerberg, a former director of market development and spokeswoman for Facebook and sister to Meta Platforms CEO Mark Zuckerberg, is a member of The Motley Fool's board of directors. Johnny Rice has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Meta Platforms, Nvidia, and Palantir Technologies. The Motley Fool has a disclosure policy. Here Are the 2 Best Artificial Intelligence Stocks to Buy in May and 1 to Avoid was originally published by The Motley Fool Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
