This article is part of VentureBeat’s special issue, “AI at Scale: From Vision to Viability.” Read more from this special issue here. This article is part of VentureBeat’s special issue, “AI at Scale: From Vision to Viability.” Read more from the issue here. If you were to travel 60 years back in time to Stevenson, Alabama, you’d find Widows Creek Fossil Plant, a 1.6-gigawatt generating station with one of the tallest chimneys in the world. Today, there’s a Google data center where the Widows Creek plant once stood. Instead of running on coal, the old facility’s transmission lines bring in renewable energy to power the company’s online services. That metamorphosis, from a carbon-burning facility to a digital factory, is symbolic of a global shift to digital infrastructure. And we’re about to see the production of intelligence kick into high gear thanks to AI factories.  These data centers are decision-making engines that gobble up compute, networking and storage resources as they convert information into insights. Densely packed data centers are springing up in record time to satisfy the insatiable demand for artificial intelligence.  The infrastructure to support AI inherits many of the same challenges that defined industrial factories, from power to scalability and reliability, requiring modern solutions to century-old problems. The new labor force: Compute power In the era of steam and steel, labor meant thousands of workers operating machinery around the clock. In today’s AI factories, output is determined by compute power. Training large AI models requires massive processing resources. According to Aparna Ramani, VP of engineering at Meta, the growth of training these models is about a factor of four per year across the industry. That level of scaling is on track to create some of the same bottlenecks that existed in the industrial world. There are supply chain constraints, to start. GPUs — the engines of the AI revolution — come from a handful of manufacturers. They’re incredibly complex. They’re in high demand. And so it should come as no surprise that they’re subject to cost volatility.  In an effort to sidestep some of those supply limitations, big names like AWS, Google, IBM, Intel and Meta are designing their own custom silicon. These chips are optimized for power, performance and cost, making them specialists with unique features for their respective workloads. This shift isn’t just about hardware, though. There’s also concern about how AI technologies will affect the job market. Research published by Columbia Business School studied the investment management industry and found the adoption of AI leads to a 5% decline in the labor share of income, mirroring shifts seen during the Industrial Revolution.  “AI is likely to be transformative for many, perhaps all, sectors of the economy,” says Professor Laura Veldkamp, one of the paper’s authors. “I’m pretty optimistic that we will find useful employment for lots of people. But there will be transition costs.” Where will we find the energy to scale? Cost and availability aside, the GPUs that serve as the AI factory workforce are notoriously power-hungry. When the xAI team brought its Colossus supercomputer cluster online in September 2024, it reportedly had access to somewhere between seven and eight megawatts from the Tennessee Valley Authority. But the cluster’s 100,000 H100 GPUs need a lot more than that. So, xAI brought in VoltaGrid mobile generators to temporarily make up for the difference. In early November, Memphis Light, Gas & Water reached a more permanent agreement with the TVA to deliver xAI an additional 150 megawatts of capacity. But critics counter that the site’s consumption is straining the city’s grid and contributing to its poor air quality. And Elon Musk already has plans for another 100,000 H100/H200 GPUs under the same roof. According to McKinsey, the power needs of data centers are expected to increase to approximately three times current capacity by the end of the decade. At the same time, the rate at which processors are doubling their performance efficiency is slowing. That means performance per watt is still improving, but at a decelerating pace, and certainly not fast enough to keep up with the demand for compute horsepower.  So, what will it take to match the feverish adoption of AI technologies? A report from Goldman Sachs suggests that U.S. utilities need to invest about $50 billion in new generation capacity just to support data centers. Analysts also expect data center power consumption to drive around 3.3 billion cubic feet per day of new natural gas demand by 2030. Scaling gets harder as AI factories get larger Training the models that make AI factories accurate and efficient can take tens of thousands of GPUs, all working in parallel, months at a time. If a GPU fails during training, the run must be stopped, restored to a recent checkpoint and resumed. However, as the complexity of AI factories increases, so does the likelihood of a failure. Ramani addressed this concern during an AI Infra @ Scale presentation.  “Stopping and restarting is pretty painful. But it’s made worse by the fact that, as the number of GPUs increases, so too does the likelihood of a failure. And at some point, the volume of failures could become so overwhelming that we lose too much time mitigating these failures and you barely finish a training run.” According to Ramani, Meta is working on near-term ways to detect failures sooner and to get back up and running more quickly. Further over the horizon, research into asynchronous training may improve fault tolerance while simultaneously improving GPU utilization and distributing training runs across multiple data centers.  Always-on AI will change the way we do business Just as factories of the past relied on new technologies and organizational models to scale the production of goods, AI factories feed on compute power, networking infrastructure and storage to produce tokens — the smallest piece of information an AI model uses. “This AI factory is generating, creating, producing something of great value, a new commodity,” said Nvidia CEO Jensen Huang during his Computex 2024 keynote. “It’s

In today’s digital age, the need for reliable data backup and recovery solutions has never been more critical. Cyberthreats, hardware failures, and human errors are constant risks that can disrupt business continuity. Addressing these challenges by integrating advanced Artificial Intelligence (AI) and Machine Learning (ML) technologies into data protection solutions can enhance data backup and recovery, providing real-world applications and highlighting the benefits of these technologies. The role of AI and ML in modern data protection AI and ML transform data backup and recovery by analyzing vast amounts of data to identify patterns and anomalies, enabling proactive threat detection and response. According to the Veeam 2024 Data Protection Trends Report, integrating AI and ML into cybersecurity tools is crucial for modern data protection. This integration facilitates real-time monitoring, anomaly detection, and automated responses to potential threats, significantly enhancing an organization’s security posture. For example, Veeam’s AI-driven solutions monitor data environments in real-time, detecting unusual activities that may indicate a cyberthreat, such as unauthorized access attempts or abnormal data transfers. This proactive approach enables swift responses, mitigating potential damage. Additionally, ML algorithms optimize the backup process by learning from historical data, ensuring critical data is protected and readily available for recovery. Impact on backup and recovery efficiency AI and ML can automate many manual tasks traditionally associated with backup and recovery, reducing the risk of human error. Automated systems handle routine tasks such as data validation, backup scheduling, and anomaly detection without human intervention. This ensures backups are performed consistently and accurately, freeing IT staff to focus on more strategic initiatives. Predictive analytics and proactive recovery One significant advantage of AI in backup and recovery is its predictive capabilities. Predictive analytics allows systems to anticipate hardware failures, optimize storage management, and identify potential threats before they cause damage. By learning from historical data, AI systems can predict when a system might fail and automatically initiate preventative measures. This enhances system reliability and ensures data recovery processes are initiated before a failure is fully realized. Improved incident response AI-driven backup and recovery systems significantly improve incident response times. In the event of a system failure or cyberattack, AI can quickly diagnose the issue and execute a predefined recovery plan, minimizing downtime and ensuring business continuity. For example, AI systems can monitor for signs of ransomware attacks by analyzing patterns and detecting unusual data access behaviors, triggering automatic responses to isolate and neutralize threats. Integration with IT operations Modern AI-powered backup solutions integrate seamlessly with broader IT operations. This integration facilitates better visibility and management of the entire IT environment, making it easier for organizations to maintain compliance and ensure data integrity. Tools like Veeam’s AI-driven solutions dynamically adjust backup processes based on current system performance and workload demands, optimizing resource utilization and ensuring that service level agreements (SLAs) are consistently met. Continuous improvement and learning AI and ML systems continuously learn and improve from the data they process. This means backup and recovery systems become more efficient over time, adapting to new threats and operational changes without requiring manual updates. This self-optimization ensures backup processes are always aligned with the latest best practices and technological advancements. Veeam’s approach to addressing integration challenges Veeam provides comprehensive training programs that equip IT professionals with the necessary skills to manage and optimize AI-driven data protection systems. These programs cover various aspects of AI and ML, from basic concepts to advanced implementation techniques. By offering these educational resources, Veeam helps bridge the skills gap, empowering organizations to build the required expertise in-house. Future trends in AI-driven data protection As AI and ML technologies continue to advance, their impact on data protection strategies will only grow. Emerging trends include AI-driven data privacy and compliance, self-healing systems, AI in threat intelligence, decentralized data protection, adaptive backup strategies, and sustainable data protection. Conclusion Integrating AI and ML into data backup and recovery processes enhances how organizations protect their vital information. These technologies streamline data protection, improve recovery times, and fortify defenses against new threats. Veeam’s AI-powered solutions provide a reliable framework, ensuring businesses maintain continuity and resilience. As AI and ML advance, adopting these technologies will equip organizations to handle evolving data challenges and enhance their security measures. With Veeam’s innovative solutions you can leverage the tools necessary to stay ahead in a dynamic digital environment. Learn more about how Veeam is bringing backup into the future with AI. About the author Veeam Dave Russell is Vice President, Enterprise Strategy at Veeam Software. Dave has 33 years of experience in the backup/recovery and storage management industry as a developer (IBM), industry analyst (Gartner) and strategist (IBM and Veeam). At Veeam, Dave is responsible for driving strategic product and go-to-market programs, spearheading industry engagement, and evangelizing Veeam’s vision for Modern Data Protection and Veeam in the Enterprise at key events across the globe. Follow Dave on Twitter @BackupDave, or LinkedIn www.linkedin.com/in/backupdave/. source

By Zak Kostro ( January 17, 2025, 2:24 PM EST) — In this week’s Taxation With Representation, Eli Lilly and Co. buys a precision breast cancer program, Applied Digital Corp. enters a financing agreement for its high-performance computing business, Clearwater Analytics buys Enfusion, and Lantheus Holdings Inc. buys Life Molecular Imaging Ltd…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

Samsung announced the release of its next flagship phone, the Galaxy S25, on Jan. 22 at the Samsung Galaxy Unpacked S25 presentation. As is essential for any tech presentation in 2025, generative AI was at the forefront of the event. “We are making it [AI] a reality right here right now,” said ™ Roh, Samsung’s president and head of Mobile Experience. “To make the shift possible, we built an AI OS from the ground up.” Samsung Galaxy S25 offers business as usual outside the AI The Samsung Galaxy S25 comes in three standard variants: The base model Samsung Galaxy S25 has a 6.2-inch display and up to 256 GB of storage. The Samsung Galaxy S25 Plus has a 6.7-inch display and up to 512 GB of storage. The Samsung Galaxy S25 Ultra has a 6.9-inch display and up to 1TB of storage. All three variants include the Snapdragon 8 Elite for Galaxy chip and Google Gemini as its AI assistant. The largest model, the Ultra, weighs just 218g. The Samsung Galaxy S25 can be preordered now, with the phones hitting store shelves on Feb. 7. Samsung offers Gemini Advanced and 2TB of cloud storage with purchase. The S25 retails at: $799.99 for the base model. $999.99 for the Samsung Galaxy S25 Plus. $1,299.99 for the Samsung Galaxy S25 Ultra. Samsung says the S25 offers the longest battery life of a Samsung phone yet — up to 31 hours of video. The S25 Ultra offers more camera lenses than the S25 or S25 Plus. Image: Samsung Mobility must-reads Google Gemini stretches through all aspects of the S25 With the rest of the specifications not varying much from the S24, Samsung wants AI — and particularly its partnership with Google — to provide a reason to upgrade. After introducing the S24 with Google Gemini last year, Samsung has woven AI even more deeply into the S25. A dedicated side button will activate Google Gemini. This replaces most of the requests a user might have made to Samsung’s own Bixby digital assistant before. Gemini is multimodal, able to respond to voice commands, answer questions about live video, or identify music being played. It can create transcripts and summaries of calls during the call. SEE: OpenAI and Microsoft joined an AI infrastructure initiative that pledged $500 billion over four years to data centers and more. AI will have access to any app on the phone and can draw information from all of them. An AI-curated “Now Brief” on the home screen will collect information like weather, upcoming meetings, and sports scores from Google every morning. An “Evening Brief” sums up the day at night. As expected from generative AI nowadays, Gemini on Samsung will be able to generate text, summarize text, edit images, and answer questions about pictures. AI data stays on the device “As AI becomes more powerful, it must also become more personal to deliver class leading personalization we are introducing the Personal Data Engine,” said Roh. “Now you can enjoy tailored experiences while keeping your personal information secured on your device, not in the cloud.” Essentially, the Personal Data Engine means AI data from individual phones is not used for model training or advertising, Samsung said. Some AI queries may be deleted after the interaction is complete. To protect copyright and disclose when AI has created an image, Samsung has adopted C2PA cryptography. One UI 7 emerges from beta Underneath the hood of the S25 is the One UI 7 OS. Roh said that Samsung is leveraging the operating system to reimagine Android “with AI at the core.” One UI 7, debuting in general availability with the S25 series, enables: Expanded writing tools, including call transcripts. The “Now Bar,” which includes timely notifications on the lock screen. Redesigned camera UX. Developers and partners will soon have access into the new UI, Roh said. AI is the new normal on smart phones The Samsung Galaxy S25 series competes primarily with: A slim version of the S25 is coming At the end of the Unpacked presentation, Samsung dropped a tease of Galaxy S25 Edge, the upcoming ultra-slim variant. A release date or details have not yet been announced. source

Technology innovations attract significant interest among CIOs, CTOs, and technology leaders, who are always looking for ways to improve business results with the use of innovative and transformational technologies. Causal, predictive, and generative artificial intelligence (AI) have become commonplace in enterprise IT, as the hype around what AI solutions can deliver is turning into reality and practical use cases. Innovative organizations, however, are pushing AI even further, introducing more opportunities for enterprise to transform IT work through advanced AI solutions. Transformational power of agentic AI By autonomously working alongside humans and other AI tools, agentic AI aims to completely transform enterprise IT work. Autonomous AI agents are software entities capable of performing tasks on their own, rather than only responding to queries from humans. Agentic AI agents analyze current environments, including historical IT and lines of business-specific issues and resolutions to drive automated issue resolutions or present IT and enterprise users with recommendations on the best actions to take. These agents can surface key insights in real time and with full context, which is essential for teams working on resolving critical IT incidents. BMC recently introduced a series of AI agents within the BMC Helix platform. They are powered by BMC HelixGPT to perform a variety of different roles for internal teams acting as digital assistants, including data analysis and reporting, curation of knowledge content, self-service management, and more. Democratizing data insights: The BMC Insight Finder is an autonomous AI agent that simplifies data analysis and reporting by enabling users to interact with complex data through natural language. This agent autonomously surfaces timely insights to help employees make better data-driven decisions in a fraction of the time a worker would need to analyze huge data sets. Enhancing knowledge base usability: The Knowledge Curator AI bot acts like a digital librarian, continuously optimizing knowledge resources by ensuring content is current, unduplicated, and easily accessible. The AI agent reduces the load on service desks and even guides authors with intelligent suggestions to improve research findings and the readability of final outputs. Improving enterprise-wide productivity: The Employee Navigator agentic AI bot helps employees quickly resolve IT issues, submit HR requests, or retrieve critical information for improving work performance. By intelligently pulling data from multiple sources to provide a single, concise answer, the AI agent drastically improves resolution time and enhances overall productivity. Recent enhancements to BMC Helix AIOps integrate service management, observability, and vulnerability data with automated workflows, helping IT manage complexity and alert noise. BMC Helix AIOps helps teams accelerate incident response, manage change risks, and resolve vulnerabilities before they impact the business. Reducing change failures in complex systems: Managing change risks is crucial to preventing incidents. The BMC Helix AIOps Change Risk Advisor uses agentic AI to predict the risk of changes, providing a change risk score that helps IT teams focus on high-risk changes, while fast-tracking low-risk updates. As a result, they improve CI/CD velocity and cross-team collaboration, particularly between DevOps and service management teams. Eliminating exposure to vulnerabilities: Managing vulnerabilities is constant, and the new BMC Helix Vulnerability Resolver helps IT Ops, security operations, and DevOps teams improve compliance and risk management with automated patching or workarounds, using AI-powered Vulnerability Best Action Recommendations (VBAR). The Google collaboration Google and BMC began a partnership based on the shared vision of transforming enterprise IT with the power of AI. As Chris Thompson, Head of GTM, Strategic AI, and ISV Growth at Google says: “We’ve been working together for some time, and I’d love to give BMC credit. They were, what I would consider, a very early adopter.” BMC HelixGPT supports Gemini, Google Cloud’s set of generative AI (genAI) models, to power the AI journey of mutual customers. With BMC Helix now integrated with Gemini models, the collaboration is empowering IT teams with enhanced flexibility, faster resolutions, and deeper insights, all while delivering cost savings. As Thompson further notes about BMC: “They decided to be very bold and very forward thinking and adopt not just generative AI but then to move into the agentic workflows.” Open platform improves IT efficiency while keeping costs under control BMC Helix, powered by BMC HelixGPT, features an open-architecture deployment that allows customers to retain their enterprise data in place. This open approach enables IT organizations to take advantage of hyperscaler credits available to them. In addition, BMC HelixGPT offers a bring-your-own-AI approach, empowering enterprises to maintain control over data governance, optimize costs, and bring their AI project to life faster. To see how BMC Helix can help you transform enterprise IT work with agentic AI, visit here for more information or contact BMC. About the author:Stela Udovicic is the senior director, solutions marketing management at BMC Software. source

By Sydney Price ( January 21, 2025, 9:03 PM EST) — The U.S. Securities and Exchange Commission on Tuesday told a California federal court that an electrical engineering professor has agreed to pay about $785,000 to settle a lawsuit accusing him of improperly trading shares of a radio technology company at which he previously served as an advisory committee member…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

00:00 100:00:03,880 –> 00:00:05,600Welcome to CIO Leadership Live.200:00:05,600 –> 00:00:09,520I’m Lee Rennick, executive directorof CIO communities for cio.com.300:00:09,920 –> 00:00:12,160And I’m very excitedand honored to welcome400:00:12,160 –> 00:00:15,920Annette Cooper, director of dataanalytics at Graham, to the show today.500:00:15,960 –> 00:00:17,640Annette, could you pleaseintroduce yourself600:00:17,640 –> 00:00:20,600and maybe tell us a little bitabout your current role?700:00:20,600 –> 00:00:20,840Yeah.800:00:20,840 –> 00:00:24,800So as you see in Annette Cooper I’mthe director of data and analytics here900:00:24,800 –> 00:00:25,760at Graham Construction.1000:00:25,760 –> 00:00:29,400So Graham is one of the largestconstruction companies in Canada.1100:00:29,840 –> 00:00:33,200And we also have a pretty big presencedown in the United States.1200:00:33,320 –> 00:00:36,600my role is leading the data and analyticspractice here.1300:00:36,720 –> 00:00:40,800And I’ve been at Graham about three yearsand I was the first one of me.1400:00:41,080 –> 00:00:43,800So data and analytics is new to Graham.1500:00:43,800 –> 00:00:46,120and we’re all going onthe journey together.1600:00:46,120 –> 00:00:47,320That is wonderful.1700:00:47,320 –> 00:00:48,440That must be incredible.1800:00:48,440 –> 00:00:51,720Well, I really appreciate you joiningus here today and thank you so much.1900:00:52,040 –> 00:00:53,400So we’ve develop this series,2000:00:53,400 –> 00:00:56,400to support the technology leaderin their tech and leadership journey.2100:00:56,760 –> 00:00:59,480So first question and I ask everyonethis question.2200:00:59,480 –> 00:01:00,840Could you please tell us a little bit2300:01:00,840 –> 00:01:03,840about your own careerpath and leadership journey today?2400:01:04,160 –> 00:01:06,560Any lessons learned along the waythat you could share?2500:01:06,560 –> 00:01:09,280Just sharinggenerally about your journey so far?2600:01:09,280 –> 00:01:12,400I think the lesson at the end of itall, I’ll do that.2700:01:12,400 –> 00:01:16,680First is there’s no one way to havea career path, particularly not in it.2800:01:17,200 –> 00:01:20,080And when I started outworking 20 years ago,2900:01:20,080 –> 00:01:23,080there wasn’t reallyeven this role that I’m sitting in now.3000:01:23,120 –> 00:01:27,160So I think the biggest lesson is,you know, do it your way.3100:01:27,160 –> 00:01:30,600There’s no there’s no pathway,there’s no prescription.3200:01:30,960 –> 00:01:35,560So I started offas, a researcher working in academics,3300:01:36,040 –> 00:01:40,320very much on the analysisside of the data world, and then ended up3400:01:40,400 –> 00:01:43,560working in central governmentin New Zealand for a long time3500:01:44,040 –> 00:01:45,840as a policy researcher.3600:01:45,840 –> 00:01:49,320And then I got offered the opportunityto move into a leadership role.3700:01:49,320 –> 00:01:52,600And I think that’s where I foundmy first real fit,3800:01:53,080 –> 00:01:55,680or feeling likethat was something that I did really well3900:01:55,680 –> 00:01:58,680and something that I really enjoyedand could bring skill to.4000:01:58,760 –> 00:02:01,560And then I’ve sort of grown from thereso much.4100:02:01,560 –> 00:02:05,640Like I said, it’s been a very non-linearmillennial style,4200:02:05,640 –> 00:02:10,040kind of twisty turny career,and I’ve followed my interests.4300:02:10,840 –> 00:02:12,960and I’ve also followed4400:02:12,960 –> 00:02:16,520other leaders that I thought were peoplethat I could learn from.4500:02:16,520 –> 00:02:19,080And as opportunities have come along,I’ve taken them.4600:02:19,080 –> 00:02:23,800So I moved away from governmentand into core technology4700:02:23,800 –> 00:02:25,800like I am now, because it was something4800:02:25,800 –> 00:02:28,120that I hadn’t done before,and it was something that interests me.4900:02:28,120 –> 00:02:31,240So just leveraging the wide rangeof skills that I had,5000:02:31,680 –> 00:02:36,360sort of in and around other leadersthat I was interested in learning from.5100:02:36,520 –> 00:02:37,560I love that, and,5200:02:37,560 –> 00:02:41,200you know, you have a lot of experiencein different areas, especially government.5300:02:41,560 –> 00:02:45,000But I’m sure there’s a lot of processand ways of processing things5400:02:45,000 –> 00:02:49,960and developing things that werevery different to, how you do things now.5500:02:50,000 –> 00:02:52,960But it probably helps and impacts on your,your role.5600:02:52,960 –> 00:02:56,880you know, there at Graham,every different place that I’ve worked5700:02:56,880 –> 00:03:00,240has given me a slightly different wayof looking at the world and also5800:03:00,240 –> 00:03:04,560a slightly different set of skillsfor analyzing how to get things done.5900:03:05,120 –> 00:03:08,560You know, is this a place where wewe really focused on process?6000:03:08,600 –> 00:03:11,280Is this a place wherewe’re really focused on relationship?6100:03:11,280 –> 00:03:15,520You know, what matters to the peoplesitting at the top table?6200:03:16,080 –> 00:03:17,840That’s the samewhether you’re working for,6300:03:17,840 –> 00:03:21,640elected official or,you know, the people that I work for here.6400:03:21,640 –> 00:03:22,400So, yeah,6500:03:22,400 –> 00:03:26,880it’s all just about that skill of howdo you get done what you need to get done.6600:03:27,120 –> 00:03:30,960And the diversity of my experiencehas given me lots of opportunities6700:03:30,960 –> 00:03:32,480to flex that muscle.6800:03:32,480 –> 00:03:34,200Well that’s wonderful.Thank you for sharing that.6900:03:34,200 –> 00:03:35,720I really appreciate that.7000:03:35,720 –> 00:03:39,240And congratulationsto Graham on the CIO Canada Award winning7100:03:39,240 –> 00:03:41,120project on enterprise data.7200:03:41,120 –> 00:03:43,600So I would love to learn a little bitmore about the project7300:03:43,600 –> 00:03:45,440and maybe how it transformed the business.7400:03:46,640 –> 00:03:46,920Yeah.7500:03:46,920 –> 00:03:50,720So Enterprise Data Platform was a greatbig audacious7600:03:50,720 –> 00:03:54,080goal, that I setwhen it came in about three years ago.7700:03:54,080 –> 00:03:57,120we as a business7800:03:57,120 –> 00:04:00,720were a little bit behind onsome of our use of data.7900:04:00,720 –> 00:04:04,640And I think that’s probablyjust the reality of a lot of businesses.8000:04:04,960 –> 00:04:06,560We all like to talk about that.8100:04:06,560 –> 00:04:07,800We’re really data enabled.8200:04:07,800 –> 00:04:09,560But reality is right.8300:04:09,560 –> 00:04:11,920It costs money and it takes time.8400:04:11,920 –> 00:04:16,200So because Graham has grown significantlythrough the journey acquisition,8500:04:16,480 –> 00:04:20,840one of the key things was we neededa platform that was going to be agnostic8600:04:20,840 –> 00:04:25,200to our main ERP or the ERP,you know, all the other things.8700:04:25,560 –> 00:04:28,320We wanted to have somethingthat was data specific.8800:04:28,320 –> 00:04:31,920So we went about building the platformitself,8900:04:32,120 –> 00:04:36,600where we could bring informationfrom across all of our major organizations9000:04:36,800 –> 00:04:40,560and across Graham’s disparate systemstogether9100:04:40,880 –> 00:04:44,880in a place that we could use itparticularly focused on operations.9200:04:44,880 –> 00:04:48,040So project operations, building9300:04:48,040 –> 00:04:51,600bridges, building giant highrises, the stuff we do at grain.9400:04:52,640 –> 00:04:52,960The other9500:04:52,960 –> 00:04:57,080thing that that in and of itself wasa big task, but the other thing was about9600:04:57,080 –> 00:05:01,440how do you get that out to people in a waythat is useful and usable9700:05:01,880 –> 00:05:05,760and recognizing the challengesof the folks in our field,9800:05:06,040 –> 00:05:09,040so they’re not sitting at desksall day long.9900:05:10,200 –> 00:05:13,440so we also built what we refer to as our,insights hub.10000:05:13,920 –> 00:05:17,120So that’s the thing that sitson top of the enterprise data platform.10100:05:17,120 –> 00:05:19,960That’s where all of our reports arethat we’ve built,10200:05:19,960 –>

By Zachary Parks, Derek Lawlor and Andrew Garrahan ( January 22, 2025, 4:24 PM EST) — With a game-changing advisory opinion on political coordination for a Texas PAC, 2024 started out with a bang at the Federal Election Commission.[1] Other consequential opinions, enforcement actions and regulations continued in the following months, challenging the notion that the politically divided commission cannot find consensus…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

By Christopher Cole ( January 22, 2025, 8:03 PM EST) — The Republican-led Federal Communications Commission on Wednesday reinstated complaints of alleged news distortion against ABC, CBS and NBC stations that the agency tossed in the final days of the Biden administration…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source

By Rachel Scharf ( January 21, 2025, 10:45 PM EST) — The owner of a now-defunct LED screen distribution company lied to his Korean manufacturing partner about repaying an over $10 million debt in order to keep receiving shipments and pay himself a hefty salary, jurors heard as a civil fraud trial opened in California federal court on Tuesday…. Law360 is on it, so you are, too. A Law360 subscription puts you at the center of fast-moving legal issues, trends and developments so you can act with speed and confidence. Over 200 articles are published daily across more than 60 topics, industries, practice areas and jurisdictions. A Law360 subscription includes features such as Daily newsletters Expert analysis Mobile app Advanced search Judge information Real-time alerts 450K+ searchable archived articles And more! Experience Law360 today with a free 7-day trial. source