Taboola CEO talks launching generative AI search engine for publishers
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
13 minutes ago
- Yahoo
After Gaining $394 Billion in Market Cap in 3 Days, Is Apple Stock on Its Way to Joining Nvidia and Microsoft in the $4 Trillion Club?
Key Points Apple's U.S. manufacturing investment could lower its tariff expense. The company's results are improving, but growth is still sluggish. Apple needs to justify its lofty valuation with AI-related product upgrades that are well-received by its diverse user base. 10 stocks we like better than Apple › After closing at $202.69 per share on Aug. 5, Apple (NASDAQ: AAPL) stock soared a staggering 13% in just three days to finish Aug. 8 at $229.09 per share. The move pole-vaulted the tech giant's market cap to $3.404 trillion -- a whopping $394 billion gain. That's like creating a company the size of Home Depot out of thin air. After languishing for most of the year, let's determine if Apple has what it takes to join Nvidia (NASDAQ: NVDA) and Microsoft (NASDAQ: MSFT) in the $4 trillion market cap club, and if the growth stock is a buy now. Apple's massive news Apple's sudden pop came in response to its $100 billion manufacturing program. Announced last week, the program will create American jobs and onshore some of Apple's complex supply chain. Due to Apple CEO Tim Cook's visit to the White House and Apple's manufacturing commitment, President Trump said that Apple would be 100% exempt from a specific tariff on imported semiconductors. The potential for Apple to reduce its costly tariff expense, and maybe even get government support for its onshoring efforts, is undoubtedly a boon for the company's near-term prospects. Apple isn't the only mega-cap company that is trying to work with the current administration on tariffs. On Monday, reports indicated that Nvidia made a deal with President Trump, allowing the chipmaker to resume exporting its H20 chips in exchange for giving the U.S. government 15% of its revenue from China. The H20 is a scaled-down version of Nvidia's most advanced chips, which are custom-built for Chinese markets to comply with trade restrictions. The current administration intends to retain certain tariffs, but it also appears willing to negotiate deals with big businesses. Apple's manufacturing news is positive, based on the near-term impact of tariffs. The investment could help Apple reduce its sensitivity to trade tensions and geopolitical risk. However, it's unclear how it impacts Apple's long-term investment thesis. Apple has mastered the art of managing a global supply chain to achieve cost advantages and boost its profit margins. Onshoring some of its supply chain could lead to higher costs. However, Apple has yet to make a meaningful splash in artificial intelligence (AI) -- which is one of the main reasons why the tech giant has been lagging behind the performance of other, more defined AI winners like Nvidia and Microsoft. In Apple's defense, the company has built on Apple Intelligence and released a new design update called Liquid Glass. Overall, the market is not impressed with the company's AI efforts, considering how sluggish Apple's growth has been in recent years. Apple's earnings growth doesn't justify its lofty valuation Apple has heavily relied on its high-margin services segment and stock buybacks to drive earnings to offset weak results from its product segment. Apple's services, which include iCloud, Apple Music, and Apple TV+, have been the standout for years now. But Apple's bottom line depends more on key products, like iPhone, Mac, iPad, and wearables. Investors breathed a sigh of relief after Apple's latest quarter -- the third quarter of fiscal 2025 -- which showed a significant improvement in its product segment. Revenue grew 10% and diluted earnings per share (EPS) jumped 12% including double-digit growth in iPhone, Mac, and services. Despite the solid quarter, Apple's net income has slightly declined over the last three years, so its earnings are only up due to buybacks. But the stock price has gone up substantially, which has made Apple relatively expensive. Apple's results are headed in the right direction, but the valuation is far from cheap. In fact, Apple's forward price-to-earnings (P/E) ratio, which is the stock price divided by analyst consensus EPS estimates over the next 12 months, is higher than its five-year and 10-year median P/E ratios. Even if Apple performs as expected and the stock price doesn't move for a year, it will still be relatively expensive. Apple has to earn $4 trillion the hard way Apple is taking the right approach to integrating AI across its product suite. Apple's competitive advantages are its design, user-friendly products, seamless integration of software and hardware, and comprehensive product offerings for consumers and businesses. In other words, the everyday usefulness of Apple's AI features is the most important performance indicator. Investors who agree with Apple's deliberate approach to AI may still want to consider buying the stock now, despite the premium valuation. However, given how pricey Apple is, its road to $4 trillion in market cap will likely need to come from earnings growth rather than valuation expansion. With a market cap of $3.418 trillion at the time of this writing, Apple would have to jump 17% to cross $4 trillion. It could certainly grow earnings by that much in a year or two. And if investors like what the company is doing with AI, it could maintain its higher-than-historical valuation. All told, I expect Apple to cross $4 trillion in market cap by the end of 2026 -- but investors shouldn't expect the company to get there overnight -- even after adding $392 billion in market cap in just three days. Should you invest $1,000 in Apple right now? Before you buy stock in Apple, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and Apple wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $663,630!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $1,115,695!* Now, it's worth noting Stock Advisor's total average return is 1,071% — a market-crushing outperformance compared to 185% for the S&P 500. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of August 13, 2025 Daniel Foelber has positions in Nvidia. The Motley Fool has positions in and recommends Apple, Home Depot, 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. After Gaining $394 Billion in Market Cap in 3 Days, Is Apple Stock on Its Way to Joining Nvidia and Microsoft in the $4 Trillion Club? was originally published by The Motley Fool Sign in to access your portfolio
Yahoo
38 minutes ago
- Yahoo
3 Tech Stocks That Could Go Parabolic
Key Points IonQ has the opportunity to be the big winner in quantum computing. SoundHound AI is looking to be a leader in voice and agentic AI. AppLovin has a huge opportunity to expand its AI adtech to areas other than gaming apps. 10 stocks we like better than IonQ › When it comes to investing, there are times when you're going to want to swing big. Not all these investments will pan out, but if one hits, your portfolio will greatly benefit. Just remember that these types of riskier picks should only account for part of an overall diversified portfolio. Let's look at three growth stocks that have the potential to go parabolic. 1. IonQ IonQ (NYSE: IONQ) is moving quantum computing from theory into the real world. The company is already delivering systems to commercial, government, and academic customers while working toward fault-tolerant machines that can run at scale. That's the breakthrough the industry needs to achieve mainstream success. IonQ is working from a position of strength. Following a recent equity offering, the company now has $1.6 billion in cash (as of July 9, 2025), making it one of the best-capitalized players in the field. In addition, the company is spending its money wisely by making key acquisitions to both expand its talent base and add new capabilities, such as space-based quantum networks. Its partnership with AstraZeneca, Amazon, and Nvidia, is working to demonstrate a quantum-accelerated computational chemistry workflow. This collaboration involves integrating IonQ's quantum processing unit with Nvidia's CUDA-Q platform, powered by Amazon's AWS infrastructure. It's showing early signs of success, with AstraZeneca seeing a 20-fold speed-up in drug development workflows. It has also recently formed a quantum networking division, making a move to become a leader in this space, as well. If quantum computing fulfills its promise, the market could be enormous. IonQ's combination of financial strength, key partnerships, and technology leadership puts it in a prime position to be one of the biggest winners in the space. 2. SoundHound AI SoundHound AI (NASDAQ: SOUN) is looking to carve out a leadership position in conversational and agentic artificial intelligence (AI). Its acquisition of Amelia last year gave it access to the company's advanced conversational intelligence, which it then combined with its "speech-to-meaning" and "deep meaning understanding" tech. The result is Amelia 7.0, a voice-first agentic AI platform that allows customers to create AI agents with little to no coding. These agents can complete tasks independently, which greatly expands the valuation proposition of SoundHound's platform. It's also added real-time AI visual recognition to its tech stack, making its platform even more powerful. SoundHound has long had a strong foothold in the automotive and restaurant sectors, where it continues to see strong success. Meanwhile, the Amelia acquisition gave it a solid foundation in other industry verticals, including financial services and healthcare, which are now major priorities. The strength of the combination was on full display in Q2, as SoundHound's revenue soared 217% year over year to $42.7 million, far outpacing expectations. It also raised its full-year guidance due to accelerating demand, and expects to reach adjusted earnings before interest, taxes, depreciation, and amortization (EBITDA) profitability by the end of 2025. This is still an early-stage, high-risk investment, but the market potential for voice-powered and multimodal agentic AI is huge. If SoundHound can become a leader in this space, the stock has tremendous upside from here. 3. AppLovin AppLovin (NASDAQ: APP) has been one of the market's most explosive growth stories, with its shares up more than 400% over the past year. However, its outperformance could be far from done. Following the sale of its legacy gaming app portfolio, AppLovin is now a pure-play adtech platform. Its secret sauce is its AI engine, Axon 2.0, which optimizes ad targeting, bidding, and placement, driving strong results for its gaming app clients. It sees the gaming app market alone growing at a 20% to 30% annual pace for the foreseeable future. However, it has more growth drivers ahead. It's currently testing its platform with e-commerce and web-based ads, expanding beyond just gaming apps. It also plans to open its platform to advertisers outside the U.S. and launch a self-serve ads manager next year. Management believes this will be the foundation for its next leg of growth, expanding its customer base and use cases well beyond gaming. While short-sellers have taken shots at the company, AppLovin has continued to deliver strong revenue, earnings, and free cash flow growth quarter after quarter. If Axon 2.0 proves as effective outside gaming apps as it has within them, the stock could continue its vertical ascent. Should you invest $1,000 in IonQ right now? Before you buy stock in IonQ, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and IonQ wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $668,155!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $1,106,071!* Now, it's worth noting Stock Advisor's total average return is 1,070% — a market-crushing outperformance compared to 184% for the S&P 500. Don't miss out on the latest top 10 list, available when you join Stock Advisor. See the 10 stocks » *Stock Advisor returns as of August 13, 2025 Geoffrey Seiler has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Amazon, AppLovin, and Nvidia. The Motley Fool recommends AstraZeneca Plc. The Motley Fool has a disclosure policy. 3 Tech Stocks That Could Go Parabolic 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
Atlantic
41 minutes ago
- Atlantic
This Year Will Be the Turning Point for AI College
A college senior returning to classes this fall has spent nearly their entire undergraduate career under the shadow—or in the embrace—of generative AI. ChatGPT first launched in November 2022, when that student was a freshman. As a department chair at Washington University in St. Louis, I witnessed the chaos it unleashed on campus. Students weren't sure what AI could do, or which uses were appropriate. Faculty were blindsided by how effectively ChatGPT could write papers and do homework. College, it seemed to those of us who teach it, was about to be transformed. But nobody thought it would happen this quickly. Three years later, the AI transformation is just about complete. By the spring of 2024, almost two-thirds of Harvard undergrads were drawing on the tool at least once a week. In a British survey of full-time undergraduates from December, 92 percent reported using AI in some fashion. Forty percent agreed that 'content created by generative AI would get a good grade in my subject,' and nearly one in five admitted that they've tested that idea directly, by using AI to complete their assignments. Such numbers will only rise in the year ahead. 'I cannot think that in this day and age that there is a student who is not using it,' Vasilis Theoharakis, a strategic-marketing professor at the Cranfield School of Management who has done research on AI in the classroom, told me. That's what I'm seeing in the classes that I teach and hearing from the students at my school: The technology is no longer just a curiosity or a way to cheat; it is a habit, as ubiquitous on campus as eating processed foods or scrolling social media. In the coming fall semester, this new reality will be undeniable. Higher education has been changed forever in the span of a single undergraduate career. 'It can pretty much do everything,' says Harrison Lieber, a WashU senior majoring in economics and computer science (who took a class I taught on AI last term). As a college student, he told me, he has mostly inhabited a world with ChatGPT. For those in his position, the many moral questions that AI provokes—for example, whether it is exploitative, or anti-intellectual, or ecologically unsound—take a back seat to the simple truth of its utility. Lieber characterized the matter as pragmatic above all else: Students don't want to cheat; they certainly don't want to erode the value of an education that may be costing them or their family a small fortune. But if you have seven assignments due in five days, and AI could speed up the work by tenfold for the cost of a large pizza, what are you meant to do? In spring 2023, I spoke with a WashU student whose paper had been flagged by one of the generally unreliable AI detectors that universities have used to stem the tide of cheating. He told me that he'd run his text through grammar-checking software and asked ChatGPT to improve some sentences, and that he'd done this to make time for other activities that he preferred. 'Sometimes I want to play basketball,' he said. 'Sometimes I want to work out.' His attitude might have been common among large-language-model users during that first, explosive year of AI college: If a computer helps me with my paper, then I'll have more time for other stuff. That appeal persists in 2025, but as these tools have taken over in the dorms, the motivations of their users have diversified. For Lieber, AI's allure seems more about the promise of achievement than efficiency. As with most students who are accepted to and graduate from an elite university, he and his classmates have been striving their whole life. As Lieber put it, if a course won't have 'a tangible impact on my ability to get a good job,' then 'it's not worth putting a lot of my time into.' This approach to education, coupled with a ' dismal ' outlook for postgraduate employment, justifies an ever more ferocious focus on accomplishment. Lieber is pursuing a minor in film and media studies. He has also started a profitable business while in school. Still, he had to network hard to land a good job after graduation. (He is working in risk management.) Da'Juantay Wynter, another rising senior at WashU who has never seen a full semester without AI, told me he always writes his own essays but feels okay about using ChatGPT to summarize readings, especially if he is in a rush. And like the other students I spoke with, he's often in a rush. Wynter is a double major in educational studies and American-culture studies; he has also served as president of the Association of Black Students, and been a member of a student union and various other campus committees. Those roles sometimes feel more urgent than his classwork, he explained. If he does not attend to them, events won't take place. 'I really want to polish up all my skills and intellect during college,' he said. Even as he knows that AI can't do the work as well, or in a way that will help him learn, 'it's always in the back of my mind: Well, AI can get this done in five seconds.' Another member of his class, Omar Abdelmoity, serves on the university's Academic Integrity Board, the body that adjudicates cases of cheating, with AI or otherwise. In almost every case of AI cheating he's seen, Abdelmoity told me, students really did have the time to write the paper in question—they just got stressed or preoccupied by other things, and turned to AI because it works and it is available. Students also feel the strain of soaring expectations. For those who want to go to medical school, as Abdelmoity does, even getting a 4.0 GPA and solid MCAT scores can seem insufficient for admission to the best programs. Whether or not this is realistic, students have internalized the message that they should be racking up more achievements and experience: putting in clinical hours, publishing research papers, and leading clubs, for example. In response, they seek ways to 'time shift,' Abdelmoity said, so they can fit more in. And that's at an elite private university, he continued, where the pressure is high but so is the privilege. At a state school, a student might be more likely to work multiple jobs and take care of their family. Those ordinary demands may encourage AI use even more. In the end, Abdelmoity said, academic-integrity boards such as the one he sits on can only do so much. For students who have access to AI, an education is what you make of it. If the AI takeover of higher ed is nearly complete, plenty of professors are oblivious. It isn't that they fail to understand the nature of the threat to classroom practice. But my recent interviews with colleagues have led me to believe that, on the whole, faculty simply fail to grasp the immediacy of the problem. Many seem unaware of how utterly normal AI has become for students. For them, the coming year could provide a painful revelation. Some professors I spoke with have been taking modest steps in self-defense: They're abandoning online and take-home assignments, hoping to retain the purity of their coursework. Kerri Tobin, an associate professor of education at Louisiana State University, told me that she is making undergrads do a lot more handwritten, in-class writing—a sentiment I heard many times this summer. The in-class exam, and its associated blue book, is also on the rise. And Abdelmoity reported that the grading in his natural-science courses has already been rejiggered, deemphasizing homework and making tests count for more. These adjustments might be helpful, but they also risk alienating students. Being forced to write out essays in longhand could make college feel even more old-fashioned than it did before, and less connected to contemporary life. Other professors believe that moral appeals may still have teeth. Annabel Rothschild, an assistant professor of computer science at Bard College, said she's found that blanket rules and prohibitions have been less effective than a personal address and appeal to social responsibility. Rothschild is particularly concerned about the environmental harms of AI, and she reports that students have responded to discussions about those risks. The fact that she's a scientist who understands the technology gives her message greater credibility. It also helps that she teaches at a small college with a focus on the arts. Today's seniors entered college at the tail end of the coronavirus pandemic, a crisis that once seemed likely to produce its own transformation of higher ed. The sudden switch to Zoom classes in 2020 revealed, over time, just how outmoded the standard lecture had become; it also showed that, if forced by circumstance, colleges could turn on a dime. But COVID led to little lasting change in the college classroom. Some of the students I spoke with said the response to AI has been meager too. They wondered why faculty weren't doing more to adjust teaching practices to match the fundamental changes wrought by new technologies—and potentially improve the learning experience in the process. Lieber said that he wants to learn to make arguments and communicate complex ideas, as he does in his film minor. But he also wonders why more courses can't assess those skills through classroom discussion (which is hard to fake) instead of written essays or research papers (which may be completed with AI). 'People go to a discussion-based class, and 80 percent of the class doesn't participate in discussion,' he said. The truth is that many professors would like to make this change but simply can't. A lot of us might want to judge students on the merits of their participation in class, but we've been discouraged from doing so out of fear that such evaluations will be deemed arbitrary and inequitable —and that students and their parents might complain. When professors take class participation into account, they do so carefully: Students tend to be graded on whether they show up or on the number of times they speak in class, rather than the quality of what they say. Erin McGlothlin, the vice dean of undergraduate affairs in WashU's College of Arts & Sciences, told me this stems from the belief that grading rubrics should be crystal clear in spelling out how class discussion is evaluated. For professors, this approach avoids the risk of any conflicts related to accommodating students' mental health or politics, or to bureaucratic matters. But it also makes the modern classroom more vulnerable to the incursion of AI. If what a student says in person can't be assessed rigorously, then what they type on their computer—perhaps with automated help—will matter all the more. Like the other members of his class, Lieber did experience a bit of college life before ChatGPT appeared. Even then, he said, at the very start of his freshman year, he felt alienated from some of his introductory classes. 'I would think to myself, What the hell am I doing, sitting watching this professor give the same lecture that he has given every year for the last 30 years? ' But he knew the answer even then: He was there to subsidize that professor's research. At America's research universities, teaching is a secondary job activity, at times neglected by faculty who want to devote as much time as possible to writing grants, running labs, and publishing academic papers. The classroom experience was suffering even before AI came onto the scene. Now professors face their own temptations from AI, which can enable them to get more work done, and faster, just as it does for students. I've heard from colleagues who admit to using AI-generated recommendation letters and course syllabi. Others clearly use AI to write up their research. And still more are eager to discuss the wholesome-seeming ways they have been putting the technology to use—by simulating interactions with historical authors, for example, or launching minors in applied AI. But students seem to want a deeper sort of classroom innovation. They're not looking for gimmicks—such as courses that use AI only to make boring topics seem more current. Students like Lieber, who sees his college education as a means of setting himself up for his career, are demanding something more. Instead of being required to take tests and write in-class essays, they want to do more project-based learning—with assignments that 'emulate the real world,' as Lieber put it. But designing courses of this kind, which resist AI shortcuts, would require professors to undertake new and time-consuming labor themselves. That assignment comes at the worst possible time. Universities have been under systematic attack since President Donald Trump took office in January. Funding for research has been cut, canceled, disrupted, or stymied for months. Labs have laid off workers. Degree programs have cut doctoral admissions. Multi-center research projects have been put on hold. The ' college experience ' that Americans have pursued for generations may soon be over. The existence of these stressors puts higher ed at greater risk from AI. Now professors find themselves with even more demands than they anticipated and fewer ways to get them done. The best, and perhaps the only, way out of AI's college takeover would be to embark on a redesign of classroom practice. But with so many other things to worry about, who has the time? In this way, professors face the same challenge as their students in the year ahead: A college education will be what they
