Latest news with #IBMs
Yahoo
24-04-2025
- Business
- Yahoo
IBM Tanks 6.8%--But Its $6B AI Engine Might Be the Real Story
IBM (NYSE:IBM) just threw a curveball into the market narrative. After years of sidestepping quarterly forecasts, Big Blue decided its time to talk numbers. The company issued rare Q2 revenue guidance between $16.4 billion and $16.75 billiontopping Wall Street estimatesand doubled down on its 2025 target of at least 5% revenue growth. First-quarter earnings came in hot: $1.60 per share on $14.5 billion revenue, beating expectations. The kicker? Its not just legacy hardware or consulting. IBMs high-margin software unit did the heavy lifting this time, backed by the companys growing AI bets. But not everything was smooth sailing. IBM disclosed that 15 U.S. government contractsworth around $100 millionwere abruptly canceled under a federal cost-cutting push. That news sent the stock down 6.8% at 6.52am in the premarket trading today. While the financial hit is small (less than 1% of consulting backlog), the psychological blow landed hard. Investors, already jittery about macro volatility and shifting U.S. policies, were quick to react. Unlike peers more exposed to federal spending, IBM has the advantage of diversificationespecially into enterprise software and AI, which have been its safety net in stormy times. Heres where it gets interesting: IBMs AI Book of Business jumped by another $1 billion this quarter, pushing the total above $6 billion. Its a strong signal that the companys pivot to AI isnt just PRits translating into deals. For a company that once posted 20 straight quarters of revenue declines, this is a full-blown turnaround. IBMs evolution from old-school IT to modern-day AI powerhouse is starting to look realand increasingly investable. This article first appeared on GuruFocus. Sign in to access your portfolio
Forbes
10-04-2025
- Business
- Forbes
Do Mainframes Have A Role In The AI Era?
AI-Generated, AI-Enabled Mainframe Francis Sideco A couple of years after generative AI first entered mainstream consciousness, every industry segment is attempting to leverage it to improve efficiency and offer new products and services. While training will continue to evolve and drive innovation, inferencing will drive value creation through advanced AI capabilities such as chain of thought reasoning, multi-modal functionality and multi-model support combining different types of generative AI models with predictive AI. Most of the conversations on delivering these inferencing solutions gravitate around AI data centers, edge infrastructure, and/or on-device processing. This begs the question: Does the mainframe have a role in the AI Era? What Is A Mainframe? While servers are designed more for supporting general-purpose applications and multiple clients or functions like website hosting and email servers, mainframes are designed for high-volume, mission-critical tasks such as financial transaction processing and are often used in heavily regulated industries. As such, mainframes require a higher degree of capacity, reliability and security enabled with advanced virtualization, disaster recovery, backwards compatibility and built-in redundancy. Additionally, workloads are typically handled by a centralized mainframe system whereas a distributed architecture to spread workloads over many systems is commonly used in a server architecture. With the capacity, reliability and security that mainframes provide along with their ubiquity in supporting high-volume, high-value transactions and data processing, the answer to whether mainframes have a role in the AI Era is an unequivocal 'Yes!' IBM, the leader in mainframe solutions with 70% of all global financial transactions going through their mainframes, is a prime example. A Mainframe For The AI Era Telum II By The Numbers Francis Sideco IBM recently announced the latest in its Z family of mainframes, the Z17, with the goal of addressing the needs of the AI Era while still delivering on the rigorous expectations associated with mainframes. According to IBM, this Z17 generation is powered by its 5nm 5.5GHz Telum II CPU, which, compared to the previous generation, delivers an 11% increase in single-thread performance, up to 20% capacity expansion and up to 64 TB of memory, while also doing so with up to 27% power reduction. Additionally, Telum II has an enhanced on-board AI accelerator capable of predictive and some generative AI workloads. For the generative AI workloads that require more acceleration, the Z17 can also be upgraded with the new Spyre Accelerator PCIe card. Spyre Accelerator By The Numbers Francis Sideco Based on IBMs reported performance numbers, the Z17 provides 7.5x more AI throughput than the Z16 generation delivering up to 450 billion AI inferences with 1ms response times per day. What AI Workloads Need A Mainframe? Due to their heavy use in financial transactions and mission-critical data processing, mainframes are most effective when using a combination of predictive and generative AI models. For example, because of the high-volume, central processing, and multi-model capabilities, mainframes can effectively and efficiently analyze patterns from the transactions and data passing through the system and infer conclusions that can be used in advanced fraud detection and anti-money laundering applications for improved accuracy and fewer false positives. Mainframes also combine these capabilities with mission-critical business data to help enable business, code and operations assistants to increase productivity and reduce the time needed for skills training, and autonomous agentic AI applications like automated trading and healthcare applications. Other areas where AI-enabled mainframes are being used include, but are not limited tom loan risk mitigation, insurance claims fraud detection and prevention, payments fraud, geospatial analysis, climate change impact, loan risk mitigation, cybersecurity and sentiment analysis. These are just a small subset of applications where predictive, generative and even agentic AI leverage the mainframe for business outcomes that would otherwise be inefficient or not available because of the data and/or security requirements on standard server configurations especially in heavily regulated industries in which mainframes are typically deployed. The Future Of Mainframes In The AI Era According to IBM, there are already more than 250 client-identified AI use cases on the Z mainframe platform and growing. But it's not all about the hardware. IBM leverages its other AI assets like watsonx, Granite, InstructLab and even their consulting services, across IBMs solutions, including the Z platform, positioning the company as a strong partner for the age of enterprise AI. Competitors such as Dell, Fujitsu, and Unisys are also looking to leverage AI for mainframe workloads. Next generation mainframe development typically takes 5-7 years and if they're anything like IBM, it is safe to say that the next few generations of AI-enabled mainframes are already in the works. Not only are mainframes surviving in the AI Era, they are thriving.
Forbes
20-03-2025
- Business
- Forbes
Pentagon Efficiency Cuts Are Less Than Meets the Eye
WASHINGTON, DC - MARCH 9: White House Senior Advisor Elon Musk walks to the White House after ... [+] landing in Marine One on the South Lawn with U.S. President Donald Trump (not pictured) on March 9, 2025 in Washington, DC. Trump was returning to the White House after spending the weekend at Mar-a-Lago, his private club in Florida. (Photo by) It's been more than a month since President Trump told the Department on Government Efficiency (DOGE) to take a close look at the Pentagon. But before we evaluate how the review of the Pentagon has gone thus far, it's important to note that the current efficiency drive is not worthy of the name. It is moving too fast to make thoughtful decisions about what to cut and what to keep. For example, the Agency for International Development suffered deep across-the-board cuts with no apparent attempt to analyze what works and what doesn't, or which programs provide real, life sustaining assistance. A true efficiency drive would require some careful consideration, not quick decisions implemented within a matter of weeks, with little time for reflection. With that as background, we can look at what has been happening at the Pentagon. The announcement this week that the administration will seek to cut 60,000 civilian employees in the department has persuaded some that the efficiency drive at the Pentagon is real. But as large as it sounds, a 60,000 cut, if it is in fact implemented, represents less than 10% of the more than 700,000 civilians who work in the Department of Defense. The proposed personnel cuts at the Pentagon are a far cry from what happened to agencies like AID, which had its work force almost completely eliminated, going from 10,000 employees to 300, or the Department of Education, which is slated for closure. And this doesn't even account for the fact that the Pentagon employs over half a million people as contractors. While DOGE is reviewing contractors as well, there is no indication thus far that their numbers will go down significantly. What is missing from DOGE's recommendations about the Pentagon to date is anything that would significantly reduce the revenue of weapons contractors. This is true despite the fact that a number of the systems they build – from the F-35 to the new ICBM – have had large cost overruns and serious performance problems that should prompt consideration about whether to cancel or scale back the programs. The F-35 is grounded for maintenance almost half the time. Independent analysts like the Project for Government Oversight have suggested that the plane has so many performance issues – including 800 unresolved defects – that it may never be fully ready for combat. The new ICBM – the Sentinel – has had 81% cost growth since the start of the program. In addition, former secretary of defense William Perry has called IBMs 'some of the most dangerous weapons we have' because a president would have only a matter of minutes to decide whether to launch them on warning of an attack, increasing the risk of an accidental nuclear war based on a false alarm. A New York Times analysis found that only a couple of major contractors have had reductions in contract revenue as a result of actions by the DOGE, with General Dynamics suffering a loss of less than one percent and Leidos suffering a 7% loss. Even if the Trump administration were engaged in a genuine efficiency drive, it would not be getting to the heart of the matter. America has built a war machine that is hugely expensive, but has not prevailed in a conflict in this century. These failures are not due to any failure on the part of members of the armed forces, but because of unrealistic expectations of what military force can achieve – like regime change that leads to stable democratic allies versus problematic governments. A number of governments that have come to power on the heels of U.S. intervention, like the post-Saddam Hussein leadership in Iraq, did more to sow division and enable extremist groups than they did to provide security and stability in their nations or regions. And in Afghanistan, 20 years of war ended with the Taliban in power, the exact opposite of America's goal. If one takes a broad definition of waste, the $8 trillion that the Costs of War project at Brown University calculates that America has spent on its post-9/11 wars has largely been wasted. A genuinely efficient military would be more selective about what conflicts to engage in, more realistic about what force can and cannot accomplish. And it would be backed by civilian leadership that is more willing to engage in serious diplomacy before intervening militarily in a conflict overseas. Such a military could be smaller, better trained, and armed with simpler, more reliable weapons that can be more easily maintained and replaced than current high tech systems. By all means let's push the DOGE to cut unnecessary systems within the Pentagon budget, but let's not lose sight of what is really needed – a new, more realistic military strategy paired with an effort to reduce the role of special interests in shaping our budgets and our foreign policy.
