Meta Acquires Voice AI Startup PlayAI, Continuing to Add Talent
The 'entire PlayAI team' is set to join Meta next week, according to an internal memo that was reviewed by Bloomberg. The PlayAI group will report to Johan Schalkwyk, who recently joined Meta from a separate voice AI startup called Sesame AI Inc. Bloomberg News previously reported that the companies were discussing the acquisition.
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AI helped save the chip industry. What happens if it turns out to be a bust?
Nvidia is now the first company to surge past $4 trillion in market capitalization, rebounding from its DeepSeek-induced slump earlier this year. Other AI chipmakers, including AMD and China's Huawei, are reporting strong financial results. Nearly every major chipmaker is now centering its strategy on AI. But what if AI doesn't work out? This isn't just a hypothetical question. Some signs suggest that AI growth is stalling, or at least slowing down. New models no longer show significant improvements from scaling up size or the amount of training data. Nobel laureate Demis Hassabis recently noted that 'we are no longer getting the same progress' on AI development. Andreessen Horowitz, one of the most prominent investors in AI, similarly shared concerns that AI model capabilities appeared to be plateauing. One reason for AI's slowing performance might be that models have already consumed most available digital data, leaving little left over for further improvement. Developers are instead turning to synthetic data, but it might be less effective—and might even make models worse. AI development is also enormously capital intensive. Training the most advanced models requires compute clusters costing billions of dollars. Even a single training run can cost tens of millions of dollars. Yet while development costs keep going up, monetary rewards are limited. Aside from AI coding assistants, there are few examples of AI generating returns that justify these immense capital investments. Some companies are already scaling back their AI infrastructure investment due to cost. Microsoft, for example, is 'slowing or pausing some early-stage projects' and has canceled equipment orders for several global data center projects. Meta, AWS and Google have all reportedly cut their GPU orders. Chip bottlenecks, power shortages, and public concerns are also barriers to mass AI adoption. If the AI boom peters out, that's bad news for the chip industry, which has used this new technology to avoid a serious slump. Chips are getting more expensive to make. Developing new manufacturing processes cost billions of dollars; building new plants can cost tens of billions of dollars. These costs are all passed onto consumers but, outside of AI, customers aren't keen on buying more expensive chips. The fancy technologies in today's AI processors aren't that useful for other purposes. AI delayed an industry reckoning: Manufacturing is getting more expensive, while performance gains are shrinking. The economic promise of AI justifies high chip prices, but if that goes away, the chip industry needs to find something else to persuade people to sustain investment in advanced chip manufacturing. Otherwise, advanced chipmaking will become unsustainable: New technologies will cost more and more, while delivering less and less. A chip industry slump will upend several geopolitical and economic objectives. Governments have poured billions of dollars into building domestic chip industries. U.S. President Donald Trump routinely threatens to use tariffs to bring semiconductor manufacturing back home. The U.S.'s supposed lead on chip development may prove to be a mirage, particularly as China dominates legacy chip production. And an AI reversal would shake up the world's tech sector, forcing Big Tech to rethink its bets. Given these stakes, policymakers need to encourage further innovation in AI by facilitating easier access to data, chips, power, and cooling. This includes pragmatic policies on copyright and data protection, a balanced approach to onshore and offshore chip manufacturing, and removing regulatory barriers to energy use and generation. Governments shouldn't necessarily apply the precautionary principle to AI; the benefits are too great to handicap its development, at least at these early stages. Nor should large-scale AI applications, such as autonomous vehicles or home robotics, face unreasonably high requirements for implementation. Investors should also explore alternate AI approaches that don't require as much data and infrastructure, potentially unlocking new AI growth. The industry must also explore non-AI applications for chips, if only to manage their risk. To ensure the chip industry can survive a slowdown, it must reduce the cost of advanced chipmaking. Companies should work together on research and development, as well as working with universities, to lower development costs. More investment is needed in chiplets, advanced packaging, and reconfigurable hardware. The industry must support interoperable standards, open-source tools, and agile hardware development. Shared, subsidized infrastructure for design and fabrication can help smaller companies finalize ideas before manufacturing. But, importantly, the drive to onshore manufacturing may be counterproductive: Doing so carelessly will significantly increase chip costs. The future of chips and AI are now deeply intertwined. If chips are to thrive, AI must grow. If not, the entire chip sector may now be in jeopardy. The opinions expressed in commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune. This story was originally featured on 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
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an hour ago
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Humphrey Yang Reveals How He Would Invest $1,000 If He Had To Start All Over
Benzinga and Yahoo Finance LLC may earn commission or revenue on some items through the links below. Financial guru Humphrey Yang has been answering people's personal finance questions for several years, and he recently entertained what he would do if he had to start all over again with $1,000. Yang's insights aren't specific to him. They can help people who aren't sure how to get started with investing and give them ideas of how they can use their money. "You want individual companies that will still be around in 40 years," Yang mentioned in the video. He elaborated on how he would divvy up the $1,000 and offered valuable lessons along the way. Don't Miss: Warren Buffett once said, "If you don't find a way to make money while you sleep, you will work until you die." Here's , starting today. $100k+ in investable assets? – no cost, no obligation. Yang starts by saying that he would put $400 into an S&P 500 ETF. That comes to 40% of his $1,000. He specifically mentions the Vanguard S&P 500 ETF (NYSE:VOO) and the SPDR S&P 500 ETF Trust (NYSE:SPY), but any fund that tracks the S&P 500 will produce nearly identical results. It's typically the largest holding in any of Yang's starter portfolios, and it's roughly doubled over the past five years. The S&P 500 contains the 500 largest publicly traded U.S. corporations, and it places a strong emphasis on the Magnificent Seven stocks. Each stock in the fund must be profitable, and the index regularly cycles out of bad stocks and replaces them with better ones. S&P 500 ETFs are also known for their low expense ratios since they don't require active management. For instance, VOO has a 0.03% expense ratio and SPY has a 0.09% expense ratio. Low expense ratios let you keep almost all of the profits you generate from your shares. Trending: The secret weapon in billionaire investor portfolios that you almost certainly don't own yet. Yang then suggests putting $200 into the Invesco QQQ Trust (NASDAQ:QQQ), which tracks growth stocks that are primarily in the tech sector. You can also get the Invesco NASDAQ 100 ETF (NASDAQ:QQQM), which is the same exact fund, but with a lower expense ratio. The fund has more than doubled over the past five years. It has a stronger concentration in tech stocks and the Magnificent Seven stocks than the S&P 500. QQQ regularly outperforms VOO and SPY during bullish market cycles, but it is more vulnerable to corrections. Younger investors who have lengthy time horizons can benefit more from growth and tech ETFs like QQQ. However, if you are just getting started, you may want less volatility in your portfolio. That may be why Yang suggests putting more money into VOO or SPY than you have those two ETFs, Yang suggests finding three individual stocks and putting $100 into each pick. These stocks give you the opportunity to outperform a benchmark like the S&P 500 or the Nasdaq Composite. Yang suggests narrowing the search to companies that will likely be around 40 years later. It's better to make some money than to make a high-risk investment that falls to zero. If you're just getting started, it is easier to make that type of mistake with an asset that you don't know very well. That accounts for $900 of the $1,000. Yang suggests putting the remaining $100 into a high-yield savings account. That way, your money will collect risk-free interest. It offers a safety net as your stocks and ETFs compound in the background. Read Next: Over the last five years, the price of gold has increased by approximately 83% — Investors like Bill O'Reilly and Rudy Giuliani are . This article Humphrey Yang Reveals How He Would Invest $1,000 If He Had To Start All Over originally appeared on 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
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an hour ago
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Why C3.ai Fell 29% in the First Half of 2025
Shares of fell sharply in February in part as the company underwhelmed with its fiscal third-quarter earnings report. The company continues to be significantly unprofitable. Share dilution and share-based compensation are also concerns. 10 stocks we like better than › Shares of (NYSE: AI) pulled back through the first half of the year The software-as-a-service (SaaS) company bills itself as offering "AI for the Enterprise" as well as AI-based application software. It continued to post wide losses in its earnings report and fell sharply in February as business and consumer sentiment began to weaken on fears of a trade war. While the stock recovered a bit in the second quarter of the year, it wasn't enough to make up for its struggles earlier in the year. According to data from S&P Global Market Intelligence, the stock was down 29% through the first half of the year. The chart below shows how the stock's losses came during a brief period in February. The stock started to slide in February on signs of weakening business and consumer sentiment and as the broad market fell from its peak. stock then fell 10% on Feb. 27 as the company posted another wide loss in its Q3 earnings report. Revenue rose 26% to $98.8 million. On the bottom line, the company continued to be unprofitable as it reported an adjusted loss per share of $0.12. However, its generally accepted accounting principles (GAAP) net loss of $80.2 million shows it's still losing nearly as much money as it's making in revenue, and its unit economics are barely improving as that loss rose from $72.6 million in the quarter a year ago. has spent heavily on share-based compensation historically, and that pattern continued with $174.4 million in share-based compensation through the first three quarters of the year, or nearly 75% of revenue for that period. In its Q4 report in May, posted similar numbers with revenue up 26% to $108.7 million and an adjusted loss of $0.16 per share. Its GAAP net loss came in at $79.7 million, up from $72.9 million. While the company made progress with its partnerships and added new customers, the business doesn't seem to be growing fast enough to offset the losses, and its gross margins remain low for a software company at 62% in Q4. The company's revenue growth has improved, but still seems to have a long way to go to build the scale necessary to generate a profit and prove its viability. Given its exposure to AI and its growth, the stock has potential over the long term, but the downside risks and the share dilution seem to outweigh those for now. Before you buy stock in consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and 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 $674,432!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $1,005,854!* Now, it's worth noting Stock Advisor's total average return is 1,049% — a market-crushing outperformance compared to 180% for the S&P 500. Don't miss out on the latest top 10 list, available when you join . See the 10 stocks » *Stock Advisor returns as of July 7, 2025 Jeremy Bowman has no position in any of the stocks mentioned. The Motley Fool recommends The Motley Fool has a disclosure policy. Why Fell 29% in the First Half of 2025 was originally published by The Motley Fool Error while retrieving data Sign in to access your portfolio Error while retrieving data Error while retrieving data Error while retrieving data Error while retrieving data
