Latest news with #CortexAgents
Techday NZ
4 days ago
- Business
- Techday NZ
Snowflake boosts AI with real-time licensed content access
Snowflake has introduced Cortex Knowledge Extensions, allowing enterprises to supplement their AI agents with real-time, licensed content from third-party publishers, with Stack Overflow among the first partners to join the Snowflake Marketplace. The introduction of Cortex Knowledge Extensions enables enterprise customers to enrich their AI applications and agents with updated, reliable content from publishers such as Stack Overflow, USA TODAY, and Packt. This approach ensures proper attribution and licensing of content, distinguishing it from other systems that use scraped material without consent from original publishers. According to Snowflake, this new capability is designed to address challenges faced by both enterprises and publishers. Enterprises often struggle to gain access to timely external information for their AI systems, limiting accuracy and depth of insight. Meanwhile, publishers are seeking a secure and fair way to allow their content to be used by enterprise AI, with assurance of both compensation and control. "Building powerful AI apps and agents at scale hinges on enterprises having access to a wealth of internal and external data that adds rich context to AI outputs. Snowflake is raising the bar on enterprise-wide collaboration to make it even easier for customers to fuel their AI initiatives with AI-ready data and harness the power of agentic apps — regardless of whether the data and apps reside within their own four walls or come from trusted third-party sources. Our latest innovations enable teams to turn possibilities into reality with data and AI, all without worrying about security and governance risk," Prasanna Krishanan, Head of Apps & Collaboration and Horizon at Snowflake, commented on the launch. With Cortex Knowledge Extensions, publishers are able to list their content, such as news articles, textbooks, and research papers, on the Snowflake Marketplace. Enterprises can then purchase this content and integrate it into their AI-powered apps and agents, including Cortex Agents, Cortex Search, and the soon-to-be-available Snowflake Intelligence. This functionality enables AI systems to provide responses informed by timely and relevant information while allowing publishers to monetise their intellectual property under agreed licensing terms. The mechanism for delivering content through Cortex Knowledge Extensions relies on retrieval-augmented generation and is underpinned by Snowflake's Zero-ETL Sharing functionality. This setup empowers publishers to revoke access to content if necessary, while always displaying clear attribution and links to the original source, thereby enhancing reliability and provenance. Alongside Cortex Knowledge Extensions, Snowflake has introduced Semantic Model Sharing, which is currently in private preview. Semantic Model Sharing allows enterprises to integrate and interact with AI-ready structured data within their Snowflake Cortex AI applications — whether the data originates from internal sources or third-party providers. The use of semantic models helps ensure consistency in how data and business concepts are defined and applied across different systems, contributing to more trustworthy and accurate AI outputs. By mapping internal data to standardised semantic models, enterprises can accelerate insights, support more uniform decision-making, and access industry-standard metrics while maintaining governance and version control. Snowflake reports that these advances are intended to eliminate the manual effort required to create semantic models internally, while supporting high-quality, context-rich, and accurate AI responses. Users can directly interact with their data using Semantic Model Sharing in Cortex AI, including Cortex Analyst, Cortex Agents, and Snowflake Intelligence. In addition to content and model sharing, Snowflake is adding support for Agentic Native Apps in its marketplace. This feature provides customers with access to third-party agentic applications, which can securely combine provider and consumer data within the enterprise's governance framework. Data remains within the customer's environment while agents perform tasks such as portfolio management and optimisation, using proprietary algorithms and datasets. Currently, Snowflake Marketplace connects enterprises with over 750 providers, offering more than 3,000 live data, application, and AI products. The introduction of Agentic Native Apps is intended to give providers new ways to distribute and monetise their offerings while allowing enterprises to drive additional value from their data without compromising privacy or security.
Business Wire
4 days ago
- Business
- Business Wire
USA TODAY Network Joins Snowflake Marketplace
New York, NY--(BUSINESS WIRE)-- Gannett Co., Inc. (NYSE: GCI) today announced an agreement with Snowflake, the AI Data Cloud company, to join Snowflake Marketplace. Snowflake Marketplace enables enterprises to enrich their AI apps and agents with proprietary unstructured data from third-party providers, while allowing providers to protect their intellectual property and ensure proper attribution. This includes real-time news and content from USA TODAY and the USA TODAY Network of over 200 local publications across the country. 'We are excited to be part of Snowflake Marketplace, a pioneering ecosystem that empowers publishers to monetize their content for enterprise AI applications under just and transparent licensing terms,' said Michael Reed, Chairman and Chief Executive Officer, Gannett. 'As we all navigate the same challenges around unauthorized AI use of content, Snowflake offers a proactive solution that prioritizes both attribution and fair compensation.' Through Snowflake Marketplace, enterprises can further contextualize their AI-powered apps and agents in Snowflake Cortex AI, including Cortex Agents (generally available soon), Cortex Search, and Snowflake Intelligence (public preview soon). This allows enterprises to harness real-time insights across news, research, and publications to enrich their AI outputs, alongside the wealth of proprietary knowledge in their own organization's documents. 'The USA TODAY Network is the largest local-to-national publishing and digital media organization in the country, with 195 million average monthly unique visitors relying on our trusted content to stay connected to the stories and cultural moments happening in their communities,' said Renn Turiano, Chief Consumer and Product Officer, Gannett. 'We are thrilled to join Snowflake Marketplace among the first news publishers to provide our trusted content for enterprise AI use in an equitable manner that respects our intellectual property rights while ensuring compensation for the value created for end users. This marks an important step forward in establishing a mutually beneficial ecosystem for AI companies, enterprises, content owners, and publishers to strategically partner, while driving innovation forward.' Organizations interested in learning how Gannett | USA TODAY Network can support their AI strategic efforts in areas including marketing analysis, targeted advertising, consumer research, and advanced analytics should contact gannettinfo@ ABOUT GANNETT Gannett Co., Inc. is a diversified media company with expansive reach at the national and local level dedicated to empowering and enriching communities. We seek to inspire, inform, and connect audiences as a sustainable, growth focused media and digital marketing solutions company. Through our trusted brands, including the USA TODAY NETWORK, comprised of the national publication, USA TODAY, and local media organizations, including our network of local properties, in the United States, and Newsquest, a wholly-owned subsidiary operating in the United Kingdom, we provide essential journalism, local content, and digital experiences to audiences and businesses. We deliver high-quality, trusted content with a commitment to balanced, unbiased journalism, where and when consumers want to engage. Our digital marketing solutions brand, LocaliQ, supports small and medium-sized businesses with innovative digital marketing products and solutions. ABOUT USA TODAY Since its introduction in 1982, USA TODAY has been a cornerstone of the national media landscape under its recognizable and respected brand. It also serves as the foundation for our newsroom network which allows for content sharing capabilities across our local and national markets. Through USA TODAY, we deliver high-quality, trusted content with a commitment to balanced, unbiased journalism, where and when consumers want to engage. Across our digital platforms we reach an audience of approximately 73 million unique visitors each month (based on December 2024 Comscore Media Metrix ®). USA TODAY NETWORK USA TODAY NETWORK, part of Gannett Co, Inc. (NYSE: GCI), is the leading news media publisher in the U.S. in terms of circulation and has the largest digital audience in the News and Information category, excluding news aggregators, based on the December 2024 Comscore Media Metrix ® Desktop + Mobile. Our Domestic Gannett Media segment is comprised of USA TODAY, daily and weekly content brands in approximately 220 local U.S. markets across 43 states and our community events business, USA TODAY NETWORK Ventures. With deep roots in local communities spanning the U.S., we engage approximately 140 million monthly unique visitors, on average, through a diverse portfolio of multi-platform content offerings and experiences. For more information, visit Cautionary Note Regarding Forward-Looking Statements This press release contains forward-looking statements within the meaning of Section 27A of the Securities Act of 1933, as amended, Section 21E of the Securities Exchange Act of 1934, as amended, and the safe harbor provisions of the U.S. Private Securities Litigation Reform Act of 1995, that relate to our current expectations and views of future events, which may include but not be limited to all statements other than statements of historical facts contained in this press release, including statements relating to the collaboration and our , beliefs, intentions, estimates or strategies regarding the future, which may not be realized. In some cases, you can identify forward-looking statements by terms such as 'believe,' 'may,' 'estimate,' 'continue,' 'anticipate,' 'intend,' 'should,' 'plan,' 'expect,' 'predict,' 'potential,' 'could,' 'will,' 'would,' 'ongoing,' 'future' or the negative of these terms or other similar expressions that are intended to identify forward-looking statements, although not all forward-looking statements contain these identifying words. Forward-looking statements are based largely on our current expectations and projections about future events and financial trends that we believe may affect our financial condition, results of operations, business strategy, short-term and long-term business operations and objectives and financial needs. These forward-looking statements involve known and unknown risks, uncertainties, contingencies, changes in circumstances that are difficult to predict and other important factors that may cause our actual results, performance, or achievements to be materially and/or significantly different from any future results, performance or achievements expressed or implied by the forward-looking statement. For a discussion of some of the risks and important factors that could cause actual results to differ materially from our expectations, see the risks and other factors detailed in 'Item 3. Key Information - Risk Factors' in Gannett's 2024 Annual Report on Form 10-K and Gannett's quarterly reports on Form 10-Q and Gannett's other filings with the SEC, in each case as such factors may be updated from time to time. Any forward-looking statements contained in this press release speak only as of the date hereof and accordingly undue reliance should not be placed on such statements. Gannett disclaims any obligation or undertaking to update or revise any forward-looking statements contained in this press release, whether as a result of new information, future events or otherwise, other than to the extent required by applicable law.
Business Wire
5 days ago
- Business
- Business Wire
Monte Carlo Announces Integration with Snowflake to Bring Data + AI Observability Solution to Snowflake Cortex Agents
SAN FRANCISCO--(BUSINESS WIRE)--Monte Carlo, the leader in data + AI observability, today announced at Snowflake's annual user conference, Snowflake Summit 2025, a strategic collaboration with Snowflake, the AI Data Cloud company, to support Snowflake Cortex Agents, Snowflake's AI-powered agents that orchestrate across structured and unstructured data to provide more reliable AI-driven decisions, within the Snowflake Cortex AI platform. This collaboration reflects Monte Carlo's continued commitment to ensuring trust and reliability across the complete data + AI lifecycle in Snowflake. By bringing its data + AI observability solution to Cortex Agents, Monte Carlo can help teams confidently scale AI initiatives with reliable, high-quality data, addressing the growing demand for trustworthy, production-ready data + AI systems. Cortex Agents enable enterprises to build, customize, and deploy AI agents for complex tasks, all within Snowflake's unified platform. As AI investments grow, ensuring the reliability of data pipelines and AI systems is crucial. Monte Carlo's data and AI observability solutions will help to deliver the foundation for trustworthy AI agents by ensuring the quality, reliability, and performance of the underlying data powering these solutions, including structured, semi-structured, and unstructured sources. "By addressing the critical need for consistent reliability across the entire data + AI stack, we're enabling organizations to build confident, production-ready AI products, while maintaining full visibility into the health and performance of their data + AI estate,' said Lior Gavish, co-founder and CTO of Monte Carlo. "As enterprises build more sophisticated AI agents within Cortex AI, observability of both the data powering the agents, and the agents themselves, becomes critical for their reliability and trust," said Kieran Kennedy, VP, Data Cloud Product Partners, Snowflake. "Monte Carlo's expertise in delivering end-to-end data + AI observability that can help our joint customers and ensure their AI systems operate on high-quality data and deliver accurate, dependable results." Monte Carlo is exploring new ways to extend its data + AI observability leadership to Cortex AI, to help organizations confidently scale the development of reliable AI agents in Snowflake's AI Data Cloud. This continued focus reflects Monte Carlo's commitment to supporting the next generation of data-driven AI use cases with the trust, quality, and visibility teams need to move from experimentation to production. Attending Snowflake Summit? Visit Monte Carlo's booth at #1508 or check out our other events at the conference: / Monte Carlo created the data + AI observability category to help enterprises drive mission critical business initiatives with trusted data + AI. NASDAQ, Honeywell, Roche, and hundreds of other data teams rely on Monte Carlo to detect and resolve data + AI issues at scale. Named a 'New Relic for data' by Forbes, Monte Carlo is rated the #1 data + AI observability solution by G2 Crowd, Gartner Peer Reviews, GigaOm, ISG, and others.
Yahoo
29-05-2025
- Business
- Yahoo
Had You Bought This Artificial Intelligence (AI) Stock When Warren Buffett Sold It, You'd be Sitting on a 47% Return Now
Berkshire made a puzzling decision to buy shares in Snowflake in 2020 -- a company that met almost none of Warren Buffett's usual investing criteria. Berkshire sold its entire position in Snowflake last year for a minimal gain over its estimated purchase price. Snowflake stock has soared by 47% since Berkshire sold it, but that doesn't mean Buffett and his team made the wrong move. 10 stocks we like better than Snowflake › Warren Buffett has served as the CEO of Berkshire Hathaway (NYSE: BRK.A)(NYSE: BRK.B) since 1965. He'll step down from the role at the end of 2025, capping off an incredible run during which he delivered consistent, market-crushing returns for its shareholders. Buffett prefers to invest in companies with steady growth, reliable earnings, and strong management teams that favor shareholder-friendly policies like paying dividends and repurchasing their shares. That's why it was surprising to many when Berkshire bought Snowflake (NYSE: SNOW) stock in 2020 ahead of its initial public offering (IPO) -- the cloud data warehouse giant hardly ticked any of Buffett's usual boxes. That means one of his lieutenants probably was the key decision-maker behind the purchase. However, Berkshire Hathaway sold its entire position in Snowflake in 2024's second quarter, and the exit price suggests it booked hardly any gain on the investment. Had you bought shares of Snowflake at the moment the conglomerate sold, you'd be sitting on a 47% return right now -- but I still think Buffett and his team made the right decision. Snowflake's flagship product is its data cloud, which helps businesses unify their valuable information from across multiple cloud platforms such as Amazon Web Services and Microsoft Azure. This allows them to perform detailed analyses on a complete data set, which produces more useful insights than analyzing fragmented data sets stored on different cloud platforms. Developing the best artificial intelligence (AI) software requires easy access to massive volumes of data, so Snowflake is perfectly positioned to help its customers deploy this game-changing technology. It launched a new platform in late 2023 called Cortex AI that provides businesses with access to large language models (LLMs) from leading third-party developers like Meta Platforms and Anthropic. Businesses can plug their internal data into those LLMs to rapidly create AI software for a range of purposes. But Snowflake continues to empower Cortex with new capabilities. It offers a tool called Document AI which extracts valuable data from unstructured sources like contracts and invoices, which businesses can plug into their AI models. Then there is the Cortex Agents tool, which allows businesses to create custom virtual assistants to complete specific tasks. For example, a business could train an agent to autonomously create transcripts of conversations between salespeople and customers, and then train another agent to analyze those transcripts for opportunities to generate more revenue. In the past, those tasks would take human workers hours or even days to complete, which is why agentic AI is becoming so popular. Snowflake had 11,578 total customers at the end of its fiscal 2026 first quarter (which ended April 30), and about 5,200 of them were using its AI products and services on a weekly basis. That suggests rapid uptake considering the Cortex AI platform is barely 18 months old. Snowflake's product revenue grew 26% year over year in its fiscal 2026 first quarter to $996.8 million. That was its slowest rate of increase on that metric since the company went public in 2020. In fact, Snowflake's revenue growth is consistently trending lower with each passing quarter. Slowing revenue growth isn't necessarily a bad thing if a company is spending less money on things like marketing to improve its bottom line. But that isn't the case with Snowflake, because it continues to ramp up its spending. The company's operating costs grew by 26% during the first quarter, which resulted in a blowout net loss of $430.1 million. That was a whopping 35% larger than its net loss from the year-ago period. Snowflake's net loss would have remained stable or even declined if its increased spending resulted in accelerating revenue growth rather than decelerating growth. However, there is no sign of that trend reversing, because the company is forecasting even slower revenue growth of 25% in its fiscal 2026 second quarter (which ends July 31). Even Snowflake's remaining performance obligations (RPOs) are flashing signs of weakness. Despite growing by 34% year over year to $6.6 billion during the first quarter, they actually shrank from their peak of $6.8 billion from the previous quarter three months earlier. RPOs are essentially an order backlog that can be expected to eventually convert into booked revenue, so any dip in that figure could be a signal of future weakness for the company's top line. Snowflake went public at a price of $120 per share, and Berkshire Hathaway bought the stock right before it listed, so its entry price was probably around that level. Berkshire sold its position during the second quarter of 2024, when the stock was hovering at around $135, which translated into a gain of just 12.5% over four years. A risk-free asset like U.S. Treasuries might have yielded a better return. But Snowflake stock has soared by 47% to around $200 since Berkshire sold. Does that mean Buffett and his team made a mistake? I don't think so, because I would argue it's now overvalued. The stock is trading at a price-to-sales (P/S) ratio of 17.3, which is significantly more pricey than cloud and AI leaders like Amazon, Microsoft, and Alphabet: Snowflake ticks at least two of Buffett's boxes, with a caveat on both counts: The company is growing its revenue quite fast, but that won't last long if its current rate of deceleration continues. The company is also returning money to shareholders through a stock buyback program, but that can't last forever if it keeps losing money. On the flip side, Snowflake's valuation and its steep losses would normally have excluded it as an investment option for Berkshire entirely, so I'm not surprised the conglomerate eventually exited its position. Besides, that stake was worth just $800 million at the time of sale, so it represented a tiny sliver of Berkshire's $276 billion portfolio. In summary, it doesn't matter if you're Buffett or an average retail investor -- some stocks will rise after you sell them. That's part of the investing journey, and we have to accept that timing the market reliably is impossible. It's better to focus on the fundamentals of the business in question, and on that basis, I think Berkshire made the right call. Before you buy stock in Snowflake, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and Snowflake 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 $653,389!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $830,492!* Now, it's worth noting Stock Advisor's total average return is 982% — a market-crushing outperformance compared to 171% 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 May 19, 2025 Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. 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. John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Anthony Di Pizio has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Alphabet, Amazon, Berkshire Hathaway, Meta Platforms, Microsoft, and Snowflake. 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. Had You Bought This Artificial Intelligence (AI) Stock When Warren Buffett Sold It, You'd be Sitting on a 47% Return Now was originally published by The Motley Fool
Yahoo
09-03-2025
- Business
- Yahoo
Did Warren Buffett Sell This Artificial Intelligence (AI) Stock Too Soon?
Warren Buffett is the CEO of the Berkshire Hathaway (NYSE: BRK.A)(NYSE: BRK.B) holding company, where he helps manage a $287 billion portfolio of stocks, in addition to numerous privately held subsidiaries. His notoriously simple investing strategy has led to market-beating returns for the last 59 years. Buffett invests in companies with steady growth, reliable profits, and strong management teams. He especially likes those with shareholder-friendly initiatives, like dividends and stock buyback programs. One thing the investing legend never does is chase the latest stock market themes -- not even those as powerful as artificial intelligence (AI). Berkshire invested in a cloud computing company called Snowflake (NYSE: SNOW) in 2020. It didn't appear to tick many of Buffett's usual boxes at the time. As a result, I wasn't surprised when the conglomerate sold its entire position last year. However, Snowflake stock has soared by approximately 30% since the sale. Did Buffett and his team exit too soon, and could this be a good long-term buying opportunity for investors? Snowflake's Data Cloud enables companies to aggregate their data onto one platform, where it can be analyzed more effectively to extract valuable insights. It's a highly useful tool for large, complex organizations that spread their cloud workloads across multiple providers, meaning their critical data winds up in silos and becomes fragmented. Since data is the nectar of most AI software applications, Snowflake is becoming an ideal place to develop and deploy this revolutionary technology. The company launched the Cortex AI platform in late 2023, which provides businesses with access to large language models (LLMs) from leading third parties like Anthropic, OpenAI, DeepSeek, and Meta Platforms. They can plug their internal data into those LLMs to create custom AI software. Snowflake expanded the platform this year with the launch of Cortex Agents, which can be used to build virtual assistants capable of handling specialized tasks. For example, a business could create an intelligent sales assistant that can analyze data, and even conversation transcripts between salespeople and customers, to rapidly find important information on demand. This can save employees a significant amount of time that would otherwise be spent manually digging through documents. Snowflake had 11,159 total customers at the end of fiscal 2025 (which ended on Jan. 31), and management said that over 4,000 of them were already using the company's AI products on a weekly basis. When Berkshire invested in Snowflake ahead of the tech company's initial public offering (IPO) in 2020, Snowflake was consistently growing its annual revenue by triple-digit percentages. It's unrealistic to expect any company to expand at that pace in perpetuity, but Snowflake has experienced a significant deceleration in its top-line growth, despite increasing its costs to acquire more customers and build new products. Snowflake generated a record $3.4 billion in product revenue during fiscal 2025, but it represented growth of 30%. This was the slowest pace in its tenure as a public company. Snowflake grew its operating expenses by 28.8% to $3.8 billion during fiscal 2025, which included a 38.5% increase in research and development spending to fuel the company's expansion into AI. The increase in costs led to a whopping $1.3 billion net loss, which soared by 53.7% compared to the prior year. If Snowflake's aggressive spending drove accelerating revenue growth rather than decelerating growth, its net loss likely would have remained stable or even declined. However, the company is making a risky bet that its significant investments into AI will pay off at some point in the future. Some early signs suggest that could be the case, because Snowflake's remaining performance obligations (RPOs) jumped 32.6% year over year in the fourth quarter of fiscal 2025, coming in at a record $6.8 billion. RPOs are like an order backlog, so they signal clear demand for the company's services, which stretches into the future. However, Snowflake only expects to convert 48% of its RPOs into actual revenue over the next 12 months, and there's no guarantee that the rest will convert in a timeframe that will result in actual growth at the top line. Moreover, management's guidance for fiscal 2026 suggests Snowflake's product revenue will come in at $4.2 billion, which would represent growth of just 24%. We don't know exactly what price Berkshire paid for Snowflake, but it went public at $120 per share. Berkshire sold its entire position in the second quarter of 2024 (ended June 30, 2024), and while the exact sale price isn't clear either, the stock was trading at $135 at the end of the quarter. As a result, Berkshire probably earned a return of around 12.5% over the four years it held the stock. That isn't very impressive, considering the conglomerate has averaged a return of 19.9% every year dating back to 1965. Snowflake stock was basically a drag on its overall performance. Snowflake stock has climbed by 30% since Berkshire sold, so did Buffett and his team make a mistake? I don't think so, because the stock is quite pricey, and the company's decelerating growth and blowout losses make its valuation difficult to justify. It trades at a price-to-sales (P/S) ratio of 16.2, so it's considerably more expensive than other cloud and AI leaders like Microsoft, Alphabet, and Amazon. It's unlikely that Buffett himself made the decision to add Snowflake to Berkshire's portfolio. He typically sticks to businesses he fully understands, and early-stage technology companies are normally outside his wheelhouse (based on some of the stocks he has bought, like Coca-Cola and Bank of America). One of Buffett's lieutenants likely made the purchase, but given Snowflake's valuation and the current state of its business, I wasn't surprised one bit by the sale last year. Missing out on further upside doesn't mean selling a stock was the wrong move. Investors can only make decisions based on the information at hand, and there wasn't a clear fundamental reason for Snowflake to continue climbing, considering some of the challenges I highlighted earlier. As a result, I think investors should follow Berkshire's lead and remain on the sidelines when it comes to Snowflake stock. 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 $292,207!* Apple: if you invested $1,000 when we doubled down in 2008, you'd have $45,326!* Netflix: if you invested $1,000 when we doubled down in 2004, you'd have $480,568!* Right now, we're issuing 'Double Down' alerts for three incredible companies, and there may not be another chance like this anytime soon.*Stock Advisor returns as of March 3, 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. John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Anthony Di Pizio has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Alphabet, Amazon, Berkshire Hathaway, Meta Platforms, Microsoft, and Snowflake. 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. Did Warren Buffett Sell This Artificial Intelligence (AI) Stock Too Soon? was originally published by The Motley Fool Sign in to access your portfolio
