Latest news with #Watsonx
TechCrunch
2 days ago
- Business
- TechCrunch
IBM acquires data analysis startup Seek AI, opens AI accelerator in NYC
IBM on Monday said that it has acquired Seek AI, an AI platform that allows users to ask questions about enterprise data using natural language, for an undisclosed sum. Seek CEO and founder Sarah Nagy said that the startup's technology will be a key part of Watsonx AI Labs, IBM's new NYC-based AI accelerator, which IBM also announced today. '[W]e'll scale our platform, deploy mission-critical solutions for IBM clients, empower the next generation of AI developers, and grow our team significantly,' wrote Nagy in a LinkedIn post. IBM's acquisition of Seek comes as the former looks to grow its investments in AI, particularly AI for the enterprise. It's a strategy that's worked well for IBM so far. The tech giant's Q1 earnings beat estimates, driven by software growth and strong AI demand. NYC-based Seek, which Nagy founded in 2021, offers an array of tools designed to help businesses better leverage their data. The company's software allows users to interact with data using a chatbot-like interface, automatically translating natural language questions into database queries and performing high-level data analysis and summarization. Prior to its exit, Seek AI managed to raise around $10 million from investors including Battery Ventures, Conviction Partners, and NJP Ventures. The startup will move its headquarters to One Madison, the location of Watsonx AI Labs and IBM's new Manhattan offices, once the deal closes. '[W]atsonx AI Labs is where the best AI developers gain access to world-class engineers and resources and build new businesses and applications,' IBM GM of Data and AI Ritika Gunnar said in a statement. 'By anchoring this mission in New York City, we are investing in a diverse, world‑class talent pool and a vibrant community whose innovations have long shaped the tech landscape.' Techcrunch event Save now through June 4 for TechCrunch Sessions: AI Save $300 on your ticket to TC Sessions: AI—and get 50% off a second. Hear from leaders at OpenAI, Anthropic, Khosla Ventures, and more during a full day of expert insights, hands-on workshops, and high-impact networking. These low-rate deals disappear when the doors open on June 5. Exhibit at TechCrunch Sessions: AI Secure your spot at TC Sessions: AI and show 1,200+ decision-makers what you've built — without the big spend. Available through May 9 or while tables last. Berkeley, CA | REGISTER NOW In a press release, IBM said that Watsonx AI Labs will bring together IBM researchers and engineers in a 'collaborative hub' to build AI solutions for companies. Watsonx AI Labs will also seek collaborations with local colleges and research institutions. Startups that successfully launch products at the accelerator will have access to IBM resources as well as potential investment from the company's corporate VC wing, IBM Ventures, and its $500 million enterprise AI fund.
Yahoo
13-05-2025
- Business
- Yahoo
Oracle Partners With seQure To Bolster Cybersecurity For Governments, Enterprises
Oracle Corporation (NYSE:ORCL), along with seQure, a cybersecurity firm and its partner, disclosed the availability of seQure's Ground-Truth service on Oracle Cloud Infrastructure (OCI). The company said that Ground-Truth is a cybersecurity and data observability service that helps automate the detection of threats and vulnerabilities and can reduce event alerts by 90%. Previously an on-premises solution, Ground-Truth can now be deployed across Oracle's various cloud offerings, including public, government, sovereign, and dedicated cloud with Oracle's security framework allows seQure to offer customers sophisticated, AI-powered threat detection while meeting data localization needs. This enables operational flexibility in intricate environments, compliance with regulatory, security, and performance standards, and unlocks the complete advantages of cloud and sovereign AI capabilities. Rand Waldron, vice president, Oracle said, 'This partnership helps our combined customers identify unknown cyber threats and anomalies faster and more accurately. In addition, it enables customers to benefit from OCI's built-in security, leading performance, and flexibility.' Jason Turner, chairman and CEO Entanglement stated, 'OCI's high-performance infrastructure and scaling was essential for deploying this solution and enabling us to provide our customers with the benefits of automated scaling, robust security features, and predictable pricing.' Last week, IBM disclosed a collaboration with Oracle to integrate IBM's premier AI platform, Watsonx, with Oracle Cloud Infrastructure (OCI). Investors can gain exposure to the stock via Pacer Funds Pacer Data and Digital Revolution ETF (NYSE:TRFK) and iShares Expanded Tech-Software Sector ETF (BATS:IGV). Price Action: ORCL shares are up 0.70% at $158.32 at the last check on Tuesday. Image by Mdisk via Shutterstock UNLOCKED: 5 NEW TRADES EVERY WEEK. Click now to get top trade ideas daily, plus unlimited access to cutting-edge tools and strategies to gain an edge in the markets. Get the latest stock analysis from Benzinga? ORACLE (ORCL): Free Stock Analysis Report This article Oracle Partners With seQure To Bolster Cybersecurity For Governments, Enterprises originally appeared on © 2025 Benzinga does not provide investment advice. All rights reserved.
Yahoo
03-05-2025
- Business
- Yahoo
2 Artificial Intelligence Stocks to Buy in May
The AI industry isn't immune to macroeconomic uncertainty, making picking AI stocks tricky. IBM focuses on enterprise AI, with a mix of consulting, software, and hardware racking up generative AI wins. Cloudflare puts an emphasis on small, cheap AI models for inference workloads, and its massive customer base is a huge advantage. The AI industry is staring down an uncertain and volatile macroeconomic environment, as well as some signals that demand for AI infrastructure may be starting to cool. AI server manufacturer Super Micro Computer slashed its guidance earlier this week as customers delayed purchasing decisions, and some tech giants reportedly have been pulling back on data center expansion. But investors remain keen on investing in artificial intelligence (AI). What are the best AI stocks to buy in May? Personally, I'd steer clear of AI hardware companies like Super Micro and Nvidia, as well as hyperscalers like Microsoft that are pouring incredible amounts of capital into AI data centers to power the latest compute-hungry AI models. Instead, I'd focus on companies that are betting on AI inference and small, efficient, specialized AI models and agents. My top two picks this month are International Business Machines (NYSE: IBM) and Cloudflare (NYSE: NET). Where to invest $1,000 right now? Our analyst team just revealed what they believe are the 10 best stocks to buy right now. Continue » There are multiple components to IBM's AI strategy, and all of them focus on real-world use cases for enterprise clients. The company has booked $6 billion in generative-AI-related business so far, adding $1 billion to that total in the first quarter, and much of that comes from the consulting business. While clients are being cautious with discretionary spending, generative AI projects are still getting the green light. The consulting business feeds into the software business, where IBM's Watsonx AI platform headlines the company's AI efforts. Watsonx enables enterprise clients to build, test, deploy, and manage AI models and agents. The focus here is on small, fine-tuned models aimed at doing specific tasks well. IBM claims that enterprises can reduce costs by as much as 98.5% by switching away from expensive, general-purpose AI models. Lastly, there's IBM's mainframe business. While the mainframe isn't as prolific as it once was, some industries continue to depend on the ultra-powerful systems due to their reliability and backward compatibility with decades-old code. The upcoming z17 mainframe, set to launch in June, can churn through 450 billion AI inferencing operations per day with latency of around 1 millisecond. This makes the system ideal for real-time AI inferencing tasks like detecting credit card fraud. Taken altogether, IBM has built a broad portfolio of enterprise AI services, software, and hardware. While the company isn't immune to an economic slowdown, AI projects meant to reduce costs or boost efficiency should continue to be in demand from IBM's enterprise clients. Cloudflare is all about speed. A developer can stick Cloudflare's platform between a user and a web application, performing ultra-fast computations on the fly when a user makes a request. There are many use cases that are covered by Cloudflare's platform, including handling redirects, enforcing authentication, and returning different responses based on the user's location. Another use case is running AI inference tasks using small, efficient, fast models without needing to worry about managing infrastructure or scaling resources. Cloudflare's AI platform supports more than 50 open-source AI models, including models capable of generating text, classifying images, translating text, converting text into speech, and summarizing content. These models integrate tightly with Cloudflare Workers, the company's serverless computing product, allowing them to be programmatically accessed in response to user requests. Because Cloudflare focuses on AI inference and running smaller AI models, the company doesn't need the absolute fastest AI accelerators that are typically used for computationally intensive AI training workloads. Instead, the company has some leeway to install older, less expensive AI accelerators while still achieving the necessary performance and latency for AI requests. This takes Cloudflare out of the scramble to secure the latest and greatest GPUs from Nvidia and likely reduces costs considerably. Cloudflare's revenue grew by 27% year over year in the fourth quarter of 2024, and it gained a record number of large customers spending at least $1 million annually on the platform. With nearly 240,000 paying customers, Cloudflare's AI products are an easy choice for customers looking to deploy AI inference workloads. Before you buy stock in International Business Machines, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and International Business Machines 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 $610,327!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $667,581!* Now, it's worth noting Stock Advisor's total average return is 882% — a market-crushing outperformance compared to 161% 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 April 28, 2025 Timothy Green has positions in International Business Machines. The Motley Fool has positions in and recommends Cloudflare, International Business Machines, 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. 2 Artificial Intelligence Stocks to Buy in May was originally published by The Motley Fool
Globe and Mail
02-05-2025
- Business
- Globe and Mail
2 Artificial Intelligence Stocks to Buy in May
The AI industry is staring down an uncertain and volatile macroeconomic environment, as well as some signals that demand for AI infrastructure may be starting to cool. AI server manufacturer Super Micro Computer slashed its guidance earlier this week as customers delayed purchasing decisions, and some tech giants reportedly have been pulling back on data center expansion. But investors remain keen on investing in artificial intelligence (AI). What are the best AI stocks to buy in May? Personally, I'd steer clear of AI hardware companies like Super Micro and Nvidia, as well as hyperscalers like Microsoft that are pouring incredible amounts of capital into AI data centers to power the latest compute-hungry AI models. Instead, I'd focus on companies that are betting on AI inference and small, efficient, specialized AI models and agents. My top two picks this month are International Business Machines (NYSE: IBM) and Cloudflare (NYSE: NET). Winning in enterprise AI There are multiple components to IBM's AI strategy, and all of them focus on real-world use cases for enterprise clients. The company has booked $6 billion in generative-AI-related business so far, adding $1 billion to that total in the first quarter, and much of that comes from the consulting business. While clients are being cautious with discretionary spending, generative AI projects are still getting the green light. The consulting business feeds into the software business, where IBM's Watsonx AI platform headlines the company's AI efforts. Watsonx enables enterprise clients to build, test, deploy, and manage AI models and agents. The focus here is on small, fine-tuned models aimed at doing specific tasks well. IBM claims that enterprises can reduce costs by as much as 98.5% by switching away from expensive, general-purpose AI models. Lastly, there's IBM's mainframe business. While the mainframe isn't as prolific as it once was, some industries continue to depend on the ultra-powerful systems due to their reliability and backward compatibility with decades-old code. The upcoming z17 mainframe, set to launch in June, can churn through 450 billion AI inferencing operations per day with latency of around 1 millisecond. This makes the system ideal for real-time AI inferencing tasks like detecting credit card fraud. Taken altogether, IBM has built a broad portfolio of enterprise AI services, software, and hardware. While the company isn't immune to an economic slowdown, AI projects meant to reduce costs or boost efficiency should continue to be in demand from IBM's enterprise clients. Fast AI inference at the edge Cloudflare is all about speed. A developer can stick Cloudflare's platform between a user and a web application, performing ultra-fast computations on the fly when a user makes a request. There are many use cases that are covered by Cloudflare's platform, including handling redirects, enforcing authentication, and returning different responses based on the user's location. Another use case is running AI inference tasks using small, efficient, fast models without needing to worry about managing infrastructure or scaling resources. Cloudflare's AI platform supports more than 50 open-source AI models, including models capable of generating text, classifying images, translating text, converting text into speech, and summarizing content. These models integrate tightly with Cloudflare Workers, the company's serverless computing product, allowing them to be programmatically accessed in response to user requests. Because Cloudflare focuses on AI inference and running smaller AI models, the company doesn't need the absolute fastest AI accelerators that are typically used for computationally intensive AI training workloads. Instead, the company has some leeway to install older, less expensive AI accelerators while still achieving the necessary performance and latency for AI requests. This takes Cloudflare out of the scramble to secure the latest and greatest GPUs from Nvidia and likely reduces costs considerably. Cloudflare's revenue grew by 27% year over year in the fourth quarter of 2024, and it gained a record number of large customers spending at least $1 million annually on the platform. With nearly 240,000 paying customers, Cloudflare's AI products are an easy choice for customers looking to deploy AI inference workloads. Should you invest $1,000 in International Business Machines right now? Before you buy stock in International Business Machines, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and International Business Machines 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 $610,327!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $667,581!* Now, it's worth noting Stock Advisor 's total average return is882% — a market-crushing outperformance compared to161%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 April 28, 2025
Forbes
01-04-2025
- Business
- Forbes
IBM's Enterprise AI Strategy: Trust, Scale, And Results
I Watsonx AI IBM generative AI platform displayed on a smartphone. On 10 August 2023 in Brussels, ... More Belgium. (Photo illustration by Jonathan Raa/NurPhoto via Getty Images) BM has rapidly established itself as a serious enterprise AI contender. It combines a full-stack platform strategy, proprietary models, deep integration with Red Hat hybrid cloud infrastructure, and global consulting scale. It's executing a multi-pronged approach that is already delivering operational leverage and financial upside. Its approach is paying off. In its most recent earnings, IBM disclosed that it'd grown its book of AI-related business to $5 billion in less than two years, with approximately 80% of that stemming from consulting engagements and the remainder from software subscriptions. IBM detailed its AI strategy at its recent investor day. It's a strategy centered on a pragmatic, enterprise-first approach that can deliver trusted, efficient, and domain-relevant AI solutions. IBM's AI straetgy brings together infrastructure software from Red Hat, foundation models from IBM Research, customer enablement capabilities from IBM Consulting, and integration with a broad ecosystem of partners. Unlike some competitors focused on developing massive general-purpose models, IBM's bet is on smaller, specialized models, deployed across hybrid cloud environments, and tightly integrated with its consulting services and data platforms. The goal is to help businesses operationalize AI in a way that's scalable, secure, and aligned with real-world enterprise needs. This is an approach particularly well-suited for companies in regulated industries — such as financial services, healthcare, and government — where data security, governance, and compliance concerns are paramount. At the core of IBM's AI stack is watsonx, an end-to-end platform designed to support the entire AI lifecycle. Watsonx allows businesses to build and train models using both IBM's proprietary tools and open-source models while also enabling them to fine-tune those models using their proprietary data. One of the most critical components of this platform is Granite, IBM's family of smaller, purpose-built foundation models tailored for enterprise use cases like code generation, document processing, and virtual agents. These cost-efficient, interpretable models are built to perform well in sensitive, highly regulated environments. IBM has even open-sourced several Granite models to support transparency and community-led development. IBM's AI technology is further strengthened by its integration with Red Hat's hybrid cloud tools. OpenShift AI and RHEL AI provide the infrastructure to build, deploy, and manage AI applications across on-premises, private, and public cloud environments. This hybrid model offers flexibility for enterprises that need control over their data while still wanting the agility of cloud-native services. Global system integrators are integral to helping IT organizations navigate complex new technologies, especially enterprise AI. Enterprises often struggle to understand the new technology while also attempting to extract value quickly. GSIs thrive in this market, promising quick time-to-value for AI transformation projects. A defining strength of IBM's approach is the synergy between its AI stack and its global consulting business. IBM Consulting, with its 'hybrid by design' approach, is central in driving client adoption of watsonx and Granite. This helps enterprises bring AI into mission-critical workflows across HR, procurement, customer service, and supply chain operations. IBM Consulting competes directly against companies like NTT DATA, Deloitte, Cognizant, and Capgemini. Each of these companies has AI platforms in place and AI-specific engagement models that offer a compelling choice for enterprises. Partnerships play a critical role in IBM's AI strategy. The company has built a rich ecosystem of collaborators that includes hyperscalers, chipmakers, open-source communities, and enterprise software vendors. Rather than trying to build and control every component internally, IBM focuses on integrating and orchestrating AI capabilities across a broad range of technologies. This strategy enables IBM to deliver value through its innovations and the strength of its partner network. A example of this is IBM's integration of watsonx with platforms like SAP, Salesforce, and ServiceNow. Operating within familiar business applications allowsd customers to leverage IBM's AI without disrupting existing workflows. T Collaboration extends to the systems integrators and hardware vendors that form the backbone of many enterprise deployments. IBM is working alongside companies like Dell, Lenovo, and Nokia to deliver AI-ready infrastructure, and has formed go-to-market alliances with integrators and resellers to accelerate customer adoption. Financially, IBM's AI bets are translating into real momentum. In its latest earnings release, the company reported that its book of AI business has grown to over $5 billion, and its software division posted double-digit growth in 2024 — its strongest in years — mainly fueled by demand for AI and hybrid cloud solutions. Free cash flow climbed to $12.7 billion, and IBM reports that for every dollar spent on watsonx, clients invest five to six dollars more across IBM's broader software and consulting portfolio. This multiplier effect highlights the strength of IBM's integrated offerings. Most AI-related revenue still comes from consulting, reflecting the power of IBM's services-led go-to-market model. However, the company's strategy of combining Red Hat infrastructure, watsonx software, and consulting expertise is clearly gaining traction. The tight integration of its software, infrastructure, and services sets IBM apart in the enterprise AI space. Red Hat's OpenShift and RHEL AI form the infrastructure foundation of IBM's AI strategy, powering the deployment of watsonx across diverse cloud and edge environments. IBM Consulting brings the human element, delivering AI solutions tailored to industry-specific challenges in sectors such as banking, healthcare, manufacturing, and government. Together, these arms of IBM provide the technological muscle and domain expertise needed to bring AI from concept to production at enterprise scale. IBM's end-to-end approach, spanning model development, deployment, governance, and business transformation, is a strategy that's clearly working. It's also a strategy that's difficult for competitors to match. As bookings grow, platform adoption accelerates, and ecosystem partnerships deepen, IBM is reshaping its identity around AI, hybrid cloud, and consulting. The company's ability to commercialize AI through a tightly connected stack of products, platforms, and people makes it one of the most interesting and credible enterprise AI players today. Disclosure: Steve McDowell is an industry analyst, and NAND Research is an industry analyst firm, that engages in, or has engaged in, research, analysis and advisory services with many technology companies; the author has provided paid services to many of the companies named in this article in the past and may again in the future, including IBM. Mr. McDowell does not hold any equity positions with any company mentioned.
