By Sydney Price ( January 22, 2025, 10:16 PM EST) — Automation software firm UiPath Inc. has urged a New York federal judge to toss a consolidated action from investors accusing it of falsely promoting the success of a new development strategy, saying they haven’t shown their losses stem from any misleading statements or misreporting from the firm…. 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

Last week, Flexera announced intent to acquire Spot by NetApp to the tune of $100 million, a considerable drop from the $450 million that NetApp paid to acquire Spot (and that does not account for NetApp’s CloudCheckr acquisition that followed shortly). Both Spot and CloudCheckr are included in the Flexera deal, which is expected to close in March 2025. From a FinOps lens, news of the acquisition is surprising. As recently as mid-2024, NetApp had hinted at a forthcoming Spot/CloudCheckr offering, one that did not rely on weak integrations between the two portals. This was on the heels of a years-long effort for the data infrastructure company to insert itself into the public cloud narrative through a string of cloud operations-focused acquisitions: Spot.io (2020), CloudCheckr (2021), and Data Mechanics (2021). As organizations made the frenzied rush to public cloud during the pandemic, NetApp joined the long list of on-premises infrastructure providers that were attempting to insert themselves into the public cloud narrative. NetApp is heading back to its infrastructure roots. NetApp’s journey into cloud cost management never really fit with the storage and data infrastructure focus of the company, nor did it achieve the synergy needed to maintain its acquisitions. Though Spot has released some tantalizing capabilities with Ocean’s workload migration for Kubernetes or Elastigroup and Ocean’s automated reverting of reserved instances and savings plans to Spot instances. On the CloudCheckr front, the solution’s innovation stalled even before its NetApp acquisition. At the time of acquisition in 2021, it was missing key commoditized capabilities, such as Google Cloud optimization, that all leading cloud cost management and optimization (CCMO) solutions had developed. The promised convergence of CloudCheckr and Spot from 2021 never materialized, and the brief foray into cost management didn’t seem to pan out. While the company has reported on-target revenue growth, as a percentage of revenue, its free cash flows have been declining, which may be related to trimming underperforming assets in the portfolio. As NetApp refocuses on its core strengths, a quick divestment from Spot and CloudCheckr to a more aligned FinOps owner in Flexera makes a lot of sense. In recent years, NetApp has worked to bridge the gap between the intelligent services portfolio and its storage offerings through Instaclustr. These services more closely fit into NetApp’s original mission to simplify the deployment of infrastructure and make it easier for businesses to deliver value on top of deployed infrastructure. Through Instaclustr, NetApp is making a bet that the on-demand deployment of software services fits into a future of data-focused infrastructure enabled with AI. Flexera is doubling down on FinOps. Flexera has been a market leader in the CCMO space and has gained significant traction through the combined offering of its asset management capabilities with its CCMO solution. Still, the company has stayed steadily out of the number one spot, with a smaller market presence and less advanced capabilities than its competitors. The company did make inroads through partnerships with Kubecost as an add-on container cost management function and with IBM as a market reseller. But both access to the IBM audience and Kubecost’s capabilities were lost when IBM acquired Apptio, rendering Flexera’s partnership to an asset management play, and when IBM acquired Kubecost, thus nullifying most of Flexera’s container cost management capabilities. The Spot acquisition is a boon for Flexera both in market presence with CloudCheckr’s dominant channel presence and with the added capabilities of Spot’s Eco (purchase commitments), Elastigroup (spot automation), and Ocean (container management), which all fill major gaps. Plus, the price point is a nice bonus, having acquired the combined Spot and CloudCheckr solutions for less than a quarter of their NetApp purchase prices. What does this mean for Flexera and NetApp customers? Flexera customers can expect to gain in capabilities and a richer portfolio, such as a whole slew of advanced purchase commitment automation and container cost management and optimization capabilities. They should also expect price hikes and slowed innovation for at least a couple years as Flexera works to integrate Spot and its recent Snow acquisition into its Flexera One offering. On the plus side, customer support and implementation will increase by inheriting CloudCheckr’s channel presence, though much of that presence is due to the $0 CloudCheckr price tag. Questions remain whether Flexera will continue to support that price point. NetApp customers taking advantage of both its Data Infrastructure Insights (DII) and Spot solutions have a continued commitment from both companies to continue to support the joint solution. We expect that customer support will continue with little disruption, as both companies stand to gain from growing this customer base. Beyond support, NetApp customers should expect accelerated innovation as NetApp refocuses on its original offerings. What does the future hold? From NetApp, expect greater integration and cohesion between the various elements of the NetApp portfolio. Some examples might be direct integrations between Instaclustr and tools such as BlueXP; leveraging DII for specific on-demand services from Instaclustr and connecting those services to NetApp storage; or leveraging data classification services in ONTAP or the universal metadata layer. For Flexera, expect a more dominant position in the CCMO market. It may have lost a few steps with IBM acquisitions, but Spot seems to have put it in lockstep with its biggest competitors. source

By Bonnie Eslinger ( January 22, 2025, 11:08 PM EST) — Intuitive Surgical’s president testified Wednesday in a $140 million California federal antitrust trial over claims the da Vinci surgical robot maker abuses its market power by blocking hospitals from having third parties refurbish a crucial robot component, saying there’s no monopoly since Intuitive competes with traditional and laparoscopic surgery offerings…. 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 Sydney Price ( January 22, 2025, 6:41 PM EST) — Artificial intelligence-driven pharmaceutical company Exscientia PLC has asked a New Jersey federal court to toss a suit alleging it is responsible for share price declines following the termination of its CEO after claims emerged he participated in inappropriate relationships with employees, arguing the alleged misconduct is not securities fraud…. 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

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Inference-time scaling is one of the big themes of artificial intelligence in 2025, and AI labs are attacking it from different angles. In its latest research paper, Google DeepMind introduced the concept of “Mind Evolution,” a technique that optimizes responses of large language models (LLMs) for planning and reasoning tasks.  Inference-time scaling techniques try to improve LLMs’ performance by allowing them to “think” more when generating their answers. Practically, this means that instead of generating its answer in one go, a model is allowed to generate several answers, review and correct its answers, and explore different ways to solve the problem.  Evolving LLM responses Mind Evolution relies on two key components: search and genetic algorithms. Search algorithms are a common component in many inference-time scaling techniques. They allow LLMs to find the best reasoning path for the optimal solution. Genetic algorithms are inspired by natural selection. They create and evolve a population of candidate solutions to optimize a goal, often referred to as the “fitness function.”  Mind Evolution algorithm (source: arXiv) Mind Evolution starts by creating a population of candidate solutions expressed in natural language. The solutions are generated by an LLM that has been given a description of the problem along with useful information and instructions. The LLM then evaluates each candidate and improves it if it does not meet the criteria for the solution. The algorithm then selects the parents for the next generation of solutions by sampling from the existing population, with higher-quality solutions having a greater chance of being selected. It next creates new solutions through crossover (choosing parent pairs and combining their elements to create a new solution) and mutation (making random changes to newly created solutions). It reuses the evaluation method to refine the new solutions. The cycle of evaluation, selection and recombination continues until the algorithm reaches the optimal solution or exhausts a preset number of iterations. Refinement process for proposed solutions in the Mind Evolution algorithm (source: arXiv) One of the important parts of Mind Evolution is the evaluation function. Evaluators of inference-time scaling techniques often require the problem to be formalized from natural language into a structured, symbolic representation that can be processed by a solver program. Formalizing a problem can require significant domain expertise and a deep understanding of the problem to identify all the key elements that need to be represented symbolically and how they relate to one another, which limits its applicability.  In Mind Evolution, the fitness function is designed to work with natural language planning tasks where solutions are expressed in natural language. This allows the system to avoid formalizing problems, as long as a programmatic solution evaluator is available. It also provides textual feedback in addition to a numerical score, which allows the LLM to understand specific issues and make targeted improvements. “We focus on evolving solutions in natural language spaces instead of formal spaces. This removes the requirement of task formalization, which requires significant effort and expert knowledge for each task instance,” the researchers write. Mind Evolution also uses an “island” approach to make sure it explores a diverse set of solutions. At each stage, the algorithm creates separate groups of solutions that evolve within themselves. It then “migrates” optimal solutions from one group to another to combine and create new ones. Mind Evolution in planning tasks The researchers tested Mind Evolution against baselines such as 1-pass, where the model generates only one answer; Best-of-N, where the model generates multiple answers and chooses the best one; and Sequential Revisions+, a revision technique where 10 candidate solutions are proposed independently, then revised separately for 80 turns. Sequential Revisions+ is the closest to Mind Evolution, though it does not have the genetic algorithm component to combine the best parts of the discovered solution. For reference, they also include an additional 1-pass baseline that uses OpenAI o1-preview. Performance on the Trip Planning benchmark. As the complexity of the task increases, the gap between Mind Evolution and other methods grows (source: arXiv). The researchers carried out most tests on the fast and affordable Gemini 1.5 Flash. They also explored a two-stage approach, where the Gemini 1.5 Pro model is used when the Flash model can’t address the problem. This two-stage approach provides better cost-efficiency than using the Pro model on every problem instance. The researchers tested Mind Evolution on several natural-language planning benchmarks for tasks such as trip and meeting planning. Previous research shows that LLMs can’t achieve good performance on these tasks without the aid of formal solvers. For example, Gemini 1.5 Flash and o1-preview achieve a success rate of only 5.6% and 11.7% on TravelPlanner, a benchmark that simulates organizing a trip plan based on user preferences and constraints expressed in natural language. Even exploiting Best-of-N over 800 independently generated responses, Gemini 1.5 Flash only achieves 55.6% success on TravelPlanner. Performance on the TravelPlanner benchmark. As the complexity of the task increases, Mind Evolution remains consistently high-performing while other methods falter (source: arXiv). In all their tests, Mind Evolution outperformed the baselines by a wide margin, especially as the tasks got more difficult.  For example, Mind Evolution achieves a 95% success rate on TravelPlanner. On the Trip Planning benchmark, which involves creating an itinerary of cities to visit with a number of days in each, Mind Evolution achieved 94.1% on the test instances while other methods reached a maximum of 77% success rate. Interestingly, the gap between Mind Evolution and other techniques increases as the number of cities grows, indicating its ability to handle more complex planning tasks. With the two-stage process, Mind Evolution reached near-perfect success rates on all benchmarks. Mind Evolution also proved a cost-effective approach for solving natural-language planning problems, using a fraction of the number of tokens used by Sequential-Revision+, the only other technique that comes close to its performance.  “Overall, these results demonstrate a clear advantage of an evolutionary strategy that combines

By Jeff Montgomery ( January 23, 2025, 5:02 PM EST) — Rejecting stockholder claims of misstated or omitted deal terms, a Delaware vice chancellor on Wednesday dismissed a suit accusing managers of software-as-a-service venture Zendesk Inc. of taking the company private at a $10.2 billion price far below earlier offers…. 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

After over 12 years of leading Forrester’s research on agile and, from 2011, publishing a biennial Forrester report on the global state of agile adoption, we have just published The State Of Agile Development, 2025: It’s Still Relevant, With Benefits And Challenges. In this blog, I am just quickly highlighting some of the key takeaways to hopefully motivate you to go and read the full report if you are a Forrester client. So let’s go … Agile — The Disputed Champion Of Modern Business, Still Going Strong In times when everything changes so quickly and artificial intelligence, especially generative AI (genAI), captures the imagination of tech enthusiasts and professionals alike, one technology that remains a foundational pillar of the tech industry is agile. Consider the narrative of a tech startup navigating the tumultuous waters of market demands and rapid innovation. At their core, agile methodologies enable this team to remain adaptable, collaborative, and efficient. Drop that team in an enterprise and multiply the team by 10, and what happens? Can those 10 teams still strive together in the same way as the tech startup team? Well, yes and no. But the new report reveals a striking insight: Despite the buzz around agile’s supposed decline, a commanding 95% of professionals affirm its critical relevance to their operations. This statistic, coupled with the 58% of business and technology professionals prioritizing agile adoption, paints a clear picture: Agile is not just surviving; it’s still thriving and not going away, yet it does need improvement. Agile’s Journey And Collaboration Is A Testament To Resilience Agile’s resilience is underscored by its widespread and enduring adoption across many organizations. In fact, a significant majority, 61%, report deploying agile practices for over five years, demonstrating a strong enduring commitment to its principles over older methodologies such as waterfall, which continues to see a decline. This dedication to agile reflects a broader industry trend toward valuing collaboration and flexibility over rigid hierarchies and siloed organizations. Agile teams, characterized by diverse roles including developers, testers, and scrum masters, embody this shift toward a more inclusive and dynamic approach to product development. Our survey data also proves that organizations could achieve even greater success by fully embracing agile’s collaborative ethos, values, and principles and investing in the leadership necessary to guide this cultural shift. Leaders have to do more than just commit to agile; they must lead the change! Agile Leadership Requires Foresight And Emerging Tech Adoption Despite agile’s proven benefits, the data shows that organizations face challenges in scaling agile practices and fostering a culture conducive to its adoption. Proficiency levels among teams vary, with only 7% achieving full proficiency for great agile practices but quite a higher number just being average or good, indicating room for more improvement. Overcoming these hurdles requires a strategic blend of agile frameworks tailored to each organization’s unique needs, coupled also with a commitment to modernizing all angles of the organization with continuous learning and adaptation. Businesses are not immune to that change, and there is quite more to do there. Moreover, the integration of agile with emerging technologies like generative AI and TuringBots offers a promising avenue for enhancing agile’s impact even further. TuringBots, AI, and genAI-infused tools not only streamline routine tasks but also provide valuable insights that can refine sprint planning and project prioritization. With nearly half of the respondents already leveraging genAI in their agile practices, the future of agile seems destined to be intertwined with technological advancements, driving innovation and efficiency in software development. Agile Remains An Unshakable Foundation As the tech world continues to evolve at a breakneck pace, agile values, principles, and practices stand as testament to the enduring need for adaptability, collaboration, transparency, and speed. Agile’s widespread adoption and the challenges it faces reflect an approach that is not static but dynamic, one that clients need to continuously evolve and adapt to meet the demands of an ever-changing industry landscape. Will the integration of agile and AI technologies herald a new era of software development, one where efficiency, innovation, and quality are paramount? I hope it will. As organizations navigate the complexities of digital transformation, agile remains an unshakable foundation, guiding teams toward success in the age of AI and beyond. Over the years, our research has also shown that client organizations cannot make this transition alone — you need valuable partners to work with you. This is why I see the strong connection of this research with my recently published Forrester Wave™ evaluation of modern application development services, of which agile services are mandatory table stakes. Read the full report to access more data and understand our thinking behind it. Also, reach out to me ([email protected]) or schedule an inquiry or a guidance session to get help — I’m here to assist you. I also want to thank my great senior research associate, Merve Kandemir, for her dedication to this research and amazing work to get it published. source

瑞銀非常榮幸能成為太陽馬戲團（Cirque du Soleil）世界級鉅作《KOOZA》香港站的主贊助商。由娛樂製作公司 Great Entertainment Group 及 Mast International 攜手合作，太陽馬戲團自2018 年後首次重臨香港，並以香港作為其傳奇亞洲巡演的首站。從 2025年5 月 21 日起，觀眾將可在中環海濱活動空間的大帳幕內欣賞驚心動魄的精彩表演。 《KOOZA》於 2007 年首演，以驚險震撼的表演呈現太陽馬戲團的原創特色，包括高空雜技，奇幻角色、奢華服裝、豐富多彩的佈景、滑稽幽默的小丑藝術以及激動人心的現場配樂。《KOOZA》的演出充滿驚險、刺激、歡笑和奇幻元素 ，帶給觀眾一系列無間斷的歡樂。演出將為你娓娓道來主角The Innocent（天真）在The Trickster（魔幻師）的注視下探索一個奇幻世界的故事。 瑞銀投資銀行亞太區主管高橋太一表示：「我們很高興地宣佈太陽馬戲團重返香港，為這個充滿活力的城市帶來歡樂。瑞銀致力於回饋社區，為香港帶來獨家體驗。作為國際和本地文化無縫連接的亞洲中心，我們深信香港是舉辦世界知名活動的理想舞台。」 圖片説明 Great Entertainment Group 首席執行官Randy Bloom (左) 及瑞銀投資銀行亞太區主管高橋太一(右)與太陽馬戲團（Cirque du Soleil）演員合照。 LinkedIn Email Facebook Twitter WhatsApp The post 瑞銀為太陽馬戲團（Cirque du Soleil）鉅作《KOOZA》香港站贊助商 appeared first on VeriMedia. source

Learn more about IDC’s research for technology leaders OR subscribe today to receive industry-leading research directly to your inbox. International Data Corporation (IDC) is the premier global provider of market intelligence, advisory services, and events for the technology markets. IDC is a wholly owned subsidiary of International Data Group (IDG Inc.), the world’s leading tech media, data, and marketing services company. Recently voted Analyst Firm of the Year for the third consecutive time, IDC’s Technology Leader Solutions provide you with expert guidance backed by our industry-leading research and advisory services, robust leadership and development programs, and best-in-class benchmarking and sourcing intelligence data from the industry’s most experienced advisors. Contact us today to learn more. Bob Multhaup is an adjunct research advisor with IDC’s IT Executive Programs (IEP), focusing on IT business and financial management. He has had extensive experience as a CIO, including serving as the divisional information officer for two Sandoz divisions, as vice president of IT for Henkel N.A., and as vice president of IT for Cognis Corp. In these positions, Bob worked in Europe managing large international IT organizations, developing strategic IT plans, aligning IT to business goals, and consolidating global IT costs and organizations. source