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How AI is shaping the future of higher ed (opinion) – Inside Higher Ed

March 22, 2023 | Author: admin

Artificial intelligence is emerging as one of the most powerful agents of change in higher education, presenting the sector with unprecedented academic, ethical and legal challenges. Through its algorithmic ability to adapt, self-correct and learn, AI is pushing the boundaries of human intelligence, making the future of higher education inextricably intertwined with AI.

To disentangle the intertwined relationship between AI and higher education, I will briefly discuss the opportunities and the challenges of AI, review some of the emerging applications of AI in higher education, and offer some recommendations for the way forward.

As an umbrella term that includes machine learning, deep learning and natural language processing, AI relies on extensive computing power and massive amounts of data processed by algorithms. As it continues to seep into the fabric of our society, AI is being used to solve problems in cybersecurity, health care, agriculture, climate change, manufacturing, banking and fraud detection, among other areas. By using computing power to process and to learn from data, AI is augmenting our ability to automate routine tasks; to streamline processes; to recognize and classify images, patterns and speech; to make predictions; and even to make decisions.

Search over 40,000 Career Opportunities in Higher EducationWe have helped more than 2,000 institutions hire the best higher education talent.

Not surprisingly, some AI enthusiasts are predicting the emergence of a super AI intelligence capable of rivaling, if not surpassing, human intelligence. As AI capabilities grow, debates about the moral and ethical implications of its use are likely to accelerate. For example, AI-powered facial and emotion recognition technology often exhibits bias against nonwhite people and women and can be weaponized for mass surveillance. Currently, however, as part of an emerging trend of responsible AI practices, researchers are attempting to address issues of bias and discrimination by improving both the algorithmic transparency and the data that feed AI models.

AI is quietly disrupting higher educations administrative, teaching, learning and research activities. Here are a few examples:

Together, these transformative processes have the potential to redefine and reduce the number of positions in areas such as admissions, administrative support, instructional design, teaching and information technology support. With the continued advancement of AI-generated multimodal content, as demonstrated by the recent release of ChatGPT-4, the efficiency and productivity of these areas will continue to improve.

Although its still prone to inaccuracies and sometimes fabrications, ChatGPT, developed by the OpenAI research lab, is now being used to write articles, novels, poems, stories, dialogues, reviews and news reports; to develop web applications; to write programming code; and even to author an academic paper about itself. Educators use ChatGPT to draft course syllabi, lecture content, assignments and grading rubrics. With this ability to produce academic writing, many fear that ChatGPT is poised to disrupt academic scholarship, even though AI is still far from replicating the complex metacognitive activities involved in the scholarly writing process.

Paving the road ahead for the future of AI in higher education requires a strategic and holistic approach that integrates education, planning and research.

First, institutions need to engage in campuswide discussions about the impact of AI on administrative, teaching and research practices. It is crucial to develop administrators and faculty members understanding of the promises and limitations of AI. These discussions must be transparent and address issues like data collection and ownership, intellectual property, data storage, security, and the rights and privacy of various stakeholders. Additionally, institutions must create a framework for the ethical governance of AI, such as the Rome Call for AI Ethics and the Data Ethics Decision Aid. These frameworks will help institutions use AI to advance teaching, learning and research, while preventing the misuse and unintended consequences of AI.

Furthermore, higher education institutions must carefully assess how AI will affect the labor market in the future. This analysis should lead to a rethinking of educational pathways to prepare students for a hybrid labor market in which AI will play a significant role.

Second, stakeholders ought to explore an AI-across-the-curriculum approach by engaging departments and their faculty development centers to identify ways to integrate current AI applications and competencies into the curriculum. AI competencies should be transdisciplinary, reflecting the various areas of expertise involved in AI development: mathematics, machine learning, deep learning, programming, data science, writing, ethics, business management, etc. This transdisciplinary approach would allow universities to lay the groundwork for a holistic and integrated approach to AI education, while fostering collaboration and partnership between faculty from different disciplines.

Third, universities should consider establishing an interdisciplinary longitudinal research agenda to examine the social, ethical and pedagogical challenges associated with AI, making sure to include experts in the humanities and social sciences in these discussions. It is imperative that universities take the lead in identifying and understanding the complexities and challenges that AI will bring to the academic landscape. Moreover, universities should collaborate with industry and the public sector to create integrated, transparent and impartial AI programs while equipping students with lifelong learning skills to make our soon-to-be AI-driven society both better and more just.

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How AI and Machine Learning Are Impacting the Litigation Landscape – Cornerstone Research

March 22, 2023 | Author: admin

Mike DeCesaris and Sachin Sancheti detail how expert witnesses are incorporating artificial intelligence and machine learning into their testimony in a variety of civil cases.

Artificial intelligence has long been present in our everyday activities, from a simple Google search to keeping your car centered in its lane on the highway. The public unveiling of ChatGPT in late 2022, however, brought the power of AI closer to home, making it accessible to anyone with a web browser. And in the legal industry, we are seeing the use of AI and machine learning ramp up in litigation, especially when it comes to expert witness preparation and testimony.

The support of expert witnesses has always required leading-edge analytical tools and data science techniques, and AI and machine learning are increasingly important tools in experts arsenals. The concept of technology being able to think and make decisions, accomplishing tasks more quickly and with better results than humans, conjures thoughts of a Jetsons-like world run by robots. However, unlike the old Jetsons cartoons of the 1960s, where flying cars were the de facto mode of transport and robot attendants addressed every need, the futuristic ideas around the impact of AI were not that far off from a rapidly approaching reality. In fact, as older, rules-based AI has evolved into machine learning (ML) where computers are programmed to accurately predict outcomes by learning from patterns found in massive data sets, the legal industry has found that AI can do far more than many imagined.

In the world of litigation, the power of AI and ML have been understood for years by law firms and economic and financial consulting firms. AI is ideally suited to support, qualify, and substantiate expert work in litigation matters, which formerly relied on a heavily manual process to improve the efficiency or quality of the data presented in testimony. Moreover, over the last several years, AI and ML have been used directly in expert testimony by both plaintiff and defense side experts.

Somewhat ironically, humans are at least partially responsible for driving the increased use of AI and ML in expert work as we produce ever-growing volumes of user-generated content. Consumer reviews and social media posts, for example, are becoming increasingly relevant in regulatory and litigation matters, including consumer fraud and product liability cases. The volume of this content can be overwhelming, so one familiar approach involves leveraging keywords to identify a more manageable subset of data for review. This is limiting, however, as it often produces results that are irrelevant to the case while omitting relevant results containing novel language. By contrast, ML-based approaches can consider the entire text, using context and syntax to identify the linguistic elements that most accurately indicate relevance.

To see this approach in action, consider litigation involving alleged marketing misrepresentations or defamatory statements, which require an examination of the at-issue content. The most robust analyses are systematic and objective, making them ideal for outsourcing to the noncontroversial training data and impartial models that are hallmarks of state-of-the-art AI and ML approaches.

AI and ML have also proven to be valuable tools for experts across a broad spectrum of consumer fraud and product liability matters. While some scenarios may be obvious, humans possess the creativity to adapt a solution to other use cases. Here, these novel uses include:

Domain-specific sentiment analysis Publicly available sentiment models perform well on many problems but often fail on tasks that feature domain-specific linguistic structures. Such failure might arise when tasked with measuring the sentiment surrounding an entity in an industry whose discussion features novel or counterintuitive language. Consider a defamation suit filed by a fitness influencer. Terms like confusion, resistance, and to failure generally have negative connotations, but in the fitness space, are often used to describe a successful workout. Likewise, slang terms like guns and shredded mean something entirely different in the fitness context than in conventional use. In these cases, a general-purpose sentiment model may mischaracterize or overlook such language, while training a domain-specific sentiment model will provide a more accurate assessment of the sentiment contained in allegedly defamatory statements. This training process could involve gathering hundreds of thousands of user-generated reviews for industry products, and then directing a context-aware language model to predict the review score from the text. This custom model will quantify the polarity of the discussion surrounding the influencer, which can then be tracked through time and around certain critical events.

Assessing marketing influence on social media To assess allegations that a company steered an online discussion through social media marketing, AI and ML can compare the companys posts to those generated by unaffiliated users (earned media). This can be done using language models and text similarity metrics that quantitatively and objectively assess whether earned media immediately following the companys posts were more like the companys posts than either earned media preceding the posts or selected at random.

Image object detection To assess the incidences of client logos and products appearing across images posted to social media, a custom object detection model can be trained and applied to a random sample of millions of social media images.

Public press topic modeling To quantify the extent and timing of the public awareness of a marketing claim at issue, AI and ML can be applied to articles published in media outlets. This approach helps isolate the at-issue topic from other closely related but distinct topics. Such distinctions can then facilitate an analysis that is more narrowly focused on the claim at hand.

Multimedia characterization Where there are allegations of product misrepresentation or improper marketing, AI and ML can characterize the nature of a companys social media presence. A model trained on text and image content from unaffiliated but topically relevant brands can learn to distinguish content along the lines of broad brand identities (e.g., healthy vs. unhealthy, eco-friendly vs. climate-damaging). Applying such a model to at-issue social media content can quantify whether it conveys each of these brand features.

The nature of allegedly defamatory statements Even in the presence of clearly negative statements, defamation is notoriously difficult to prove. Defendants may claim that statements were expressed not as fact but as opinion, possibility, entertainment or satire. By leveraging datasets and models that identify the degree of certainty present in natural language examples, experts can objectively measure the degree to which reasonable consumers may interpret the information as fact.

Product liability One growing area of research concerns the quantification and isolation of specific entities referenced in a broader text. Product liability cases, for instance, may examine user-generated product reviews to identify the importance and sentiment surrounding at-issue product features. Rather than assess the review as a whole, aspect-based sentiment analysis focuses on at-issue features only, allowing for the extraction of strong indicators from nuanced or mixed reviews.

Class certification A successful class certification challenge will demonstrate that the circumstances of putative class members were sufficiently varied to require individual treatment. Any of the methods discussed above can be taken together to quantify the heterogeneity of the at-issue materials. For example, a case concerning marketing misrepresentations may train a classifier to distinguish at-issue marketing content from content not at issue, model the topics targeted throughout multiple distinct marketing campaigns, and summarize images to demonstrate differing appeal to different consumers.

For centuries, the ability of humans to mold available resources to serve their needs has separated them from less-evolved species. We see it in all walks of life, and the above examples demonstrate it in our small corner of the world. And we will continue to see it as the availability of voluminous social media and other user-generated data continues to expand and become more complex. In its simplest terms, AI and ML are critical in helping us efficiently search through the haystack to find the needle. Those who try to find the needle by hand will inevitably be left behind.

This article was originally published byLaw.com in March 2023.

The views expressed herein do not necessarily represent the views of Cornerstone Research.

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KX and Microsoft Expand Partnership, Offer a Data Timehouse – Database Trends and Applications

March 22, 2023 | Author: admin

KX is expanding its partnership with Microsoft, now offering kdb Insights Enterprise on Microsoft Azure.

According to KX, this represents an industry-first Data Timehouse, a new class of data and AI management platform designed for temporal data generated by digital transformation.

It provides data scientists and application developers with precision access to temporal data on real-time and massive historical datasets with the Azure native tools they use today.

"In partnership with KX, we're excited to launch one of the industry's first data timehouse on the Azure platform. While in preview, we have already seen impressive results for customers in capital markets, healthcare, manufacturing, and energy. We look forward to working with KX to help businesses achieve transformative growth with kdb Insights Enterprise on Azure, said Corey Sanders, corporate vice president of Microsoft Cloud for Industry.

Engineered by KX, kdb Insights Enterprise on Microsoft Azure enables businesses to transform into real-time intelligent enterprises, with preview customers reporting up to 100x the performance at one tenth of the cost of competing solutions, according to the vendors.

"The launch of kdb Insights Enterprise on Microsoft Azure as a first party service is a watershed moment for KX, said Ashok Reddy, KX CEO. Representing the industry's first Data Timehouse, it enriches data warehouse and lakehouse technologies and gives customers access to the power and performance of kdb with all the benefits of the Azure platform. It enables companies in all sectors to accelerate their AI and ML analytics workloads, putting data driven decision science at the very heart of their business for enhanced operational and commercial outcomes. We continue to see enormous opportunity for our strategic partnership with Microsoft, helping to underpin our growth expectations."

For more information about this news, visit http://www.kx.com.

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NVIDIA Launches DGX Cloud, Giving Every Enterprise Instant … – NVIDIA Blog

March 22, 2023 | Author: admin

Oracle Cloud Infrastructure First to Run NVIDIA AI Supercomputing Instances; Microsoft Azure, Google Cloud and Others to Host DGX Cloud Soon

GTCNVIDIA today announced NVIDIA DGX Cloud, an AI supercomputing service that gives enterprises immediate access to the infrastructure and software needed to train advanced models for generative AI and other groundbreaking applications.

DGX Cloud provides dedicated clusters of NVIDIA DGX AI supercomputing, paired with NVIDIA AI software. The service makes it possible for every enterprise to access its own AI supercomputer using a simple web browser, removing the complexity of acquiring, deploying and managing on-premises infrastructure.

Enterprises rent DGX Cloud clusters on a monthly basis, which ensures they can quickly and easily scale the development of large, multi-node training workloads without having to wait for accelerated computing resources that are often in high demand.

We are at the iPhone moment of AI. Startups are racing to build disruptive products and business models, and incumbents are looking to respond, said Jensen Huang, founder and CEO of NVIDIA. DGX Cloud gives customers instant access to NVIDIA AI supercomputing in global-scale clouds.

NVIDIA is partnering with leading cloud service providers to host DGX Cloud infrastructure, starting with Oracle Cloud Infrastructure (OCI). Its OCI Supercluster provides a purpose-built RDMA network, bare-metal compute and high-performance local and block storage that can scale to superclusters of over 32,000 GPUs.

Microsoft Azure is expected to begin hosting DGX Cloud next quarter, and the service will soon expand to Google Cloud and more.

Industry Titans Adopt NVIDIA DGX Cloud to Speed SuccessAmgen, one of the worlds leading biotechnology companies, insurance technology leader CCC Intelligent Solutions (CCC), and digital-business-platform provider ServiceNow are among the first AI pioneers using DGX Cloud.

Amgen is using DGX Cloud with NVIDIA BioNeMo large language model software to accelerate drug discovery, including NVIDIA AI Enterprise software, which includes NVIDIA RAPIDS data science acceleration libraries.

With NVIDIA DGX Cloud and NVIDIA BioNeMo, our researchers are able to focus on deeper biology instead of having to deal with AI infrastructure and set up ML engineering, said Peter Grandsard, executive director of Research, Biologics Therapeutic Discovery, Center for Research Acceleration by Digital Innovation at Amgen. The powerful computing and multi-node capabilities of DGX Cloud have enabled us to achieve 3x faster training of protein LLMs with BioNeMo and up to 100x faster post-training analysis with NVIDIA RAPIDS relative to alternative platforms.

CCC, a leading cloud platform for the property and casualty insurance economy, is using DGX Cloud to speed and scale the development and training of its AI models. These models power the companys innovative auto claims resolution solutions, helping to accelerate the intelligent automation of the industry and improve the claims experience for millions of business users and their consumers every day.

ServiceNow is using DGX Cloud with on-premises NVIDIA DGX supercomputers for flexible, scalable hybrid-cloud AI supercomputing that helps power its AI research on large language models, code generation, and causal analysis. ServiceNow also co-stewards the BigCode project, a responsible open-science generative AI initiative, which is trained on the Megatron-LM framework from NVIDIA.

Open a Browser to NVIDIA AI Supercomputing and SoftwareEnterprises manage and monitor DGX Cloud training workloads using NVIDIA Base Command Platform software, which provides a seamless user experience across DGX Cloud, as well as on-premises NVIDIA DGX supercomputers. Using Base Command Platform, customers can match their workloads to the right amount and type of DGX infrastructure needed for each job.

DGX Cloud includes NVIDIA AI Enterprise, the software layer of the NVIDIA AI platform, which provides end-to-end AI frameworks and pretrained models to accelerate data science pipelines and streamline the development and deployment of production AI. New pretrained models, optimized frameworks and accelerated data science software libraries, available in NVIDIA AI Enterprise 3.1 released today, give developers an additional jump-start to their AI projects.

Each instance of DGX Cloud features eight NVIDIA H100 or A100 80GB Tensor Core GPUs for a total of 640GB of GPU memory per node. A high-performance, low-latency fabric built with NVIDIA Networking ensures workloads can scale across clusters of interconnected systems, allowing multiple instances to act as one massive GPU to meet the performance requirements of advanced AI training. High-performance storage is integrated into DGX Cloud to provide a complete solution for AI supercomputing.

DGX Cloud features support from NVIDIA experts throughout the AI development pipeline. Customers can work directly with NVIDIA engineers to optimize their models and quickly resolve development challenges across a broad range of industry use cases.

AvailabilityDGX Cloud instances start at $36,999 per instance per month. Organizations can contact their NVIDIA Partner Network representative for additional details.

Watch Huang discuss NVIDIA DGX Cloud in his GTC keynote on demand, and tune in to the GTC panel with NVIDIA DGX Cloud pioneers.

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NVIDIA and Microsoft to Bring the Industrial Metaverse and AI to … – NVIDIA Blog

March 22, 2023 | Author: admin

Microsoft Azure to Host NVIDIA DGX Cloud for AI Supercomputing, and NVIDIA Omniverse Cloud for Building and Operating 3D Worlds; Companies to Connect Omniverse Platform to Microsoft 365 Applications

GTCNVIDIA today announced a collaboration with Microsoft to provide hundreds of millions of Microsoft enterprise users with access to powerful industrial metaverse and AI supercomputing resources via the cloud.

Microsoft Azure will host two new cloud offerings from NVIDIA: NVIDIA Omniverse Cloud, a platform-as-a-service giving instant access to a full-stack environment to design, develop, deploy and manage industrial metaverse applications; and NVIDIA DGX Cloud, an AI supercomputing service that gives enterprises immediate access to the infrastructure and software needed to train advanced models for generative AI and other groundbreaking applications.

Additionally, the companies are bringing together their productivity and 3D collaboration platforms by connecting Microsoft 365 applications such as Teams, OneDrive and SharePoint with NVIDIA Omniverse, a platform for building and operating 3D industrial metaverse applications.

The collaboration will accelerate enterprises ability to digitalize their operations, engage in the industrial metaverse and train advanced models for generative AI and other applications.

The worlds largest companies are racing to digitalize every aspect of their business and reinvent themselves into software-defined technology companies, said Jensen Huang, founder and CEO of NVIDIA. NVIDIA AI and Omniverse supercharge industrial digitalization. Building NVIDIA Omniverse Cloud within Microsoft Azure brings customers the best of our combined capabilities.

The next wave of computing is being born, between next-generation immersive experiences and advanced foundational AI models, we see the emergence of a new computing platform, said Satya Nadella, chairman and CEO of Microsoft. Together with NVIDIA, we're focused on both building out services that bridge the digital and physical worlds to automate, simulate and predict every business process, and bringing the most powerful AI supercomputer to customers globally.

With Omniverse connected to Azure Cloud Services Digital Twins and Internet of Things, companies can link real-time data from sensors in the physical world to their digital replicas. This will enable enterprises to build and operate more accurate, dynamic, fully functional 3D digital twins that automatically respond to changes in their physical environments. Azure provides the cloud infrastructure and capabilities needed to deploy enterprise services at scale, including security, identity and storage.

A GTC keynote demo developed by Accenture amplifies the utility of integrating NVIDIA Omniverse with Microsoft Teams to enable real-time 3D collaboration. Running on Omniverse Cloud, and leveraging a Teams Meeting featuring Live Share, the Accenture demo showcases how this integration can shorten the time between decision-making, action and feedback.

Omniverse Cloud, powered by NVIDIA OVX computing systems, will be available on Azure in the second half of the year.

DGX Cloud will be available running in Azure beginning next quarter, providing enterprises with dedicated clusters of NVIDIA DGX AI supercomputing and software, rented on a monthly basis.

Learn more about the collaboration and watch the GTC keynote. Register free for GTC to attend Omniverse sessions with NVIDIA and industry leaders.

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F5s multi-cloud networking capabilities simplify operations for … – Help Net Security

March 22, 2023 | Author: admin

F5 announced multi-cloud networking (MCN) capabilities to extend application and security services across one or more public clouds, hybrid deployments, native Kubernetes environments, and edge sites.

F5 Distributed Cloud Services are differentiated in providing connectivity and security at both the network and application layers. As an overlay across separate cloud provider offerings (including native cloud services), Distributed Cloud Services let F5 customers easily integrate network operations, application performance optimization and troubleshooting, and visibility through a single management console.

According to F5s just released 2023 State of Application Strategy (SOAS) Report, 85% of organizations operate distributed application deployments, spanning traditional and modern architectures and multiple hosting environments. However, these distributed deployments add operational complexity and cost, obscure visibility, and increase the surface area for potential cyberattacks.

F5 delivers a platform-based approach that is cloud-agnostic and purpose-built to meet the needs of traditional and modern appsall without increasing complexity or losing granular control and necessary visibility. Specifically, this introduction of Distributed Cloud App Connect and Distributed Cloud Network Connect unlocks enhanced MCN use cases.

Traditional network design and infrastructure models are unable to accommodate the demands of modern apps and the digital experiences they provide, largely because newer microservices-based apps rely on distributed Kubernetes cluster services and APIs, and are not constrained to a single cloud location or even a single cloud provider.

Per the 2023 SOAS Report, the top-rated multi-cloud challenges are managing the complexity of associated tools and APIs, applying consistent security across apps, and optimizing app performance. To properly address these challenges, a more comprehensive approach to secure MCN is requiredone that provides:

Secure app-to-app connectivity is obviously a goal for every digital organization, but how this is achieved has become increasingly important, said Michael Rau, SVP and GM, F5 Distributed Cloud Platform and Security Services. The proliferation of cloud and hybrid architectures has coincided with the rise of microservices and API-heavy distributed applicationsall of which contribute complexity and diminish visibility. Distributed Cloud Services greatly expand our ability to serve customers hybrid and multi-cloud use cases, providing unparalleled agility and security for global infrastructure and app environments.

F5 is uniquely positioned to deliver necessary enabling technologies for MCN by connecting and securing any app and any API anywhere, ensuring fast network-to-network and workload-to-workload connectivity across different cloud locations, data centers, hybrid environments, and enterprise edge sites.

In the year since the introduction of Distributed Cloud Services, F5 has continued to expand the capabilities delivered as SaaS and managed services, including the recent addition of Distributed Cloud App Infrastructure Protection. This announcement furthers the reach of Distributed Cloud Services through the following new SaaS offerings:

Distributed Cloud App Connect provides an integrated stack approach through a single console to combine comprehensive app networking with full app security, faster provisioning, and ease of use.

Distributed Cloud Network Connect makes it highly secure and simple to deploy connectivity across cloud locations and cloud providers.

Enterprises cloud strategies are evolving from multiple apps spread across multiple clouds to true multi-cloud architectures with distributed workloads. That will require cloud and network architects to design their multi-cloud networks to provide both network- and application-layer connectivity, said Zeus Kerravala, principal analyst, ZK Research. F5 has long been a leader in application networking, and their Distributed Cloud Services provide a fully integrated set of layer 37 services for securely connecting across clouds and workloads, even those deployed at the edge or branch office.

Our clients have begun embracing the concept of distributing workloads and entire applications across different cloud providers, as well as hybrid architectures that include data centers or edge locations, said Colin Williams, Business CTO, Networking & Security, Computacenter UK. With that strategy comes the challenge of reducing infrastructure complexity across multiple and varied environments, especially when connecting both networks and applications while maintaining consistent security and visibility. F5 Distributed Cloud Services provide easy-to-use SaaS-based multi-cloud networking to help our clients quickly and securely connect their distributed cloud instances and workloads.

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US Signal Names Daniel Watts Chief Executive Officer – PR Newswire

March 22, 2023 | Author: admin

GRAND RAPIDS,Mich., March 21, 2023 /PRNewswire/ -- US Signal Company, LLC (US Signal), a leading IT solutions provider and portfolio company of Igneo Infrastructure Partners (Igneo), has named Daniel Watts as chief executive officer, effective March 20.

Richard Postma, US Signal's former owner, chairman and CEO, left the company in February following its acquisition by Igneo, a global infrastructure investment manager with US$16.5 billion in assets.

Based in Grand Rapids, Mich., US Signal provides network, data center, connectivity, and cloud services to enterprise customers and large national telecommunications carriers. It operates a 9,500 route mile fiber network and eight data centers across nine states in the upper Midwest.

Before joining US Signal, Watts was chief operating officer for Segra, one of the nation's largest independent fiber companies, where he worked for almost seven years. Previously he was president of TSAChoice, Inc., a business technology integrator headquartered in Asheville, North Carolina. Prior to TSAChoice he served in a variety of sales and operations roles at Windstream. He is a veteran of the United States Army.

"Dan is an accomplished industry veteran who has successfully executed growth strategies at a number of leading firms," said Michael Ryder, chairman of US Signal and co-head of Igneo in North America. "We are excited to recruit Dan to lead the talented team at US Signal, one of Igneo's key platform investments."

"I am thrilled to join US Signal to lead the next phase of growth. I look forward to working with the team to build on a great legacy of quality service and support as we scale our innovative solutions across the United States," Watts said.

About US Signal

US Signal, founded in 2001, is a leading IT solutions provider, offering network, data center, connectivity, cloud hosting, colocation, data protection, and disaster recovery servicespowered by its wholly owned and operated fiber network. US Signal also helps customers optimize their IT resources through the provision of managed and professional services. For more information, visitwww.ussignal.com.

About Igneo Infrastructure Partners

Igneo Infrastructure Partners invests in high-quality, mid-market infrastructure companies in North America, the UK, Europe, Australia and New Zealand. It is an autonomous investment team in the First Sentier Investors Group. Operating since 1994, the team works closely with portfolio companies to create long-term sustainable value through innovation and proactive asset management. Igneo manages US$16.5 billion in assets as of Dec. 31, 2022 on behalf of more than 120 institutional investors around the world. For more information, visit igneoip.com.

Media inquiries

For US Signal

Katie McCormick616-233-5380[emailprotected]

For Igneo Infrastructure Partners

Newton Park PR:Margaret Kirch Cohen/Richard ChimbergE: [emailprotected]E: [emailprotected]T: +1 847-507-2229T: +1 617-312-4281

Important information

This press release is intended for information only, aimed solely at the media and should not be further distributed to individual and/or corporate investors, and financial advisers and/or distributors. The information included within this document and any supplemental documentation provided should not be copied, reproduced or redistributed without the prior written consent of First Sentier Investors.

SOURCE US Signal

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Stock market today: Dow ends higher on UBS-Credit Suisse rescue; Fed meeting eyed – Yahoo Finance

March 22, 2023 | Author: admin

By Yasin Ebrahim

Investing.com -- The Dow closed higher Monday, driven by improved sentiment in the banking sector after UBS agreed to buy struggling rival Credit Suisse. The rescue comes as investor attention shifts to the Federal Reserve's two-day meeting slated for Tuesday.

The Dow Jones Industrial Average gained 1.2%, or 382 points, the S&P 500 was up 0.9%, and Nasdaq Composite was up 0.4%.

UBS (NYSE:UBS), Switzerlands largest bank, agreed to buy Credit Suisse for $3.2 billion in an emergency rescue deal.

In a further boost to financial stability in Europe, European Central Bank President Christine Lagarde said the central bank was ready to respond as necessary to preserve eurozone stability.

The rescue deal for Credit Suisse (NYSE:CS) helped strengthen sentiment on banks, with regional banks including Fifth Third Bancorp (NASDAQ:FITB), Lincoln National Corporation (NYSE:LNC) and New York Community Bancorp (NYSE:NYCB) leading to the upside.

New York Community Bancorp jumped more than 31% as its subsidiary, Flagstar Bank, agreed to buy a large part of Signature Bank in a $2.7B deal following the banks recent collapse.

First Republic Bank (NYSE:FRC), however, wasnt among the gainers and plunged 47% after Standard&Poors cut the ailing banks creditworthiness deeper into junk territory amid ongoing liquidity concerns.

The downgrade comes just days after 11 banks pumped $30B into the regional bank. But S&P said the move is unlikely to solve the First Republics liquidity problems and warned another downgrade was possible.

Tech was pressured by a slide in Microsoft Corporation (NASDAQ:MSFT) and Amazon.com Inc (NASDAQ:AMZN), with the latter announcing 9,000 job cuts in its cloud hosting division Amazon Web Services.

A climb in U.S. Treasury yields also kept a lid on tech just ahead of the Feds two-day meeting, which kicks off on Tuesday.

At the conclusion of its two-day meeting Wednesday, the Fed is expected to hike rates by 0.25%, but much uncertainty remains about the path forward for further hikes in the wake of the turmoil in the banking sector.

Story continues

About 70% of traders expect a rate hike, but Goldman Sachs said it expected a pause at the March meeting this week because of stress in the banking system.

Energy stocks were also in the ascendency shrugging off a wobble in energy prices amid ongoing jitters that the banking crisis could hurt global growth and energy demand.

APA Corporation (NASDAQ:APA), Hess Corporation (NYSE:HES), and EQT Corporation (NYSE:EQT) led the gains in energy, up more than 2% on the day.

Oil prices have plunged despite the China demand boom given banking stress, recession fears, and an exodus of investor flows, Goldman Sachs after nudging down its Brent forecasts to $94 per barrel for 12 months ahead from $100 previously.

In other news, Virgin Orbit Holdings Inc (NASDAQ:VORB) is reportedly planning to file for bankruptcy should the commercial space company fail to secure funding, according to several media outlets. Its shares sank 19%.

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ANS adds financial heavyweight to group board – BusinessCloud – BusinessCloud

March 22, 2023 | Author: admin

Appointments

Digital transformation specialist ANS Group has appointed a new chief financial officer as it lays foundations to deliver on its growth ambitions.

Former Deloitte, DWF, Keoghs and Davies Group executive Alex Hodgson joins the Manchester-headquartered tech firm with a brief to spearhead its financial operations with a strategic, data-based approach.

Hodgson comes with an impressive track record, following nine years at big four accountancy firm Deloitte and a spell at global law firm DWF, where he held the role of finance director as the company grew turnover from 80m to 180m in just five years.

With significant experience of overseeing acquisitions as well as rapid organic growth, the new CFO joins Richard Thompson (CEO), Toria McCahill (CPO), Qaiser Akhtar (CCO), Joe Wolksi (CRO) and Nicola Frost (general counsel) on ANSs group board.

Trustpilot CEO to step down

Hodgson said: ANS is a rare combination. A company thats already a winner in its sector, but is also seen as one to watch for the future. Its in a high-growth market and customers speak incredibly highly of the services they receive.

My role is to work hard for our people to create an environment in which everyone in the business can thrive and deliver the best possible service to customers. Im also excited to work closely with our private equity partners, Inflexion, with whom we have a genuine two-way partnership.

The appointment comes shortly after ANSs acquisition of Preact, a 65-strong Microsoft Dynamics 365 CRM partner.

ANS now employs more than 800 people, offering public and private cloud, hosting, security, DevOps, applications and data services to more than 7,000 customers, from enterprise to SMB and public sector organisations.

Thompson said of the appointment: Alex is a fantastic fit for ANS and a brilliant addition to our leadership team. His huge range of experience and knowledge will be invaluable as we continue to deliver on our strategy and make true digital transformation a reality for our customers.

Growing FinTech recruits former director of Barclays Payments

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DoD driving dramatic change to outpace foes, line up with National Cyber Strategy – Breaking Defense

March 22, 2023 | Author: admin

Networks / Cyber, Pentagon

WASHINGTON The Biden administrations National Cyber Strategy directly aligns with what a top Pentagon official said were dramatic efforts already underway at the Defense Department to revamp the militarys cyber posture.

The National Cyber Strategy challenges us to set the agenda on our terms to outpace our adversaries, DoD CIO John Sherman said in a statement to Breaking Defense this week. This vision directly aligns with the Departments cloud and software modernization efforts which aim to drive a resilient, zero-trust based cyber foundation in the cloud. Now is the time to drive the dramatic change necessary to make cyber threats far more difficult and far more costly for our adversaries.

The White House released its National Cyber Strategy earlier this month, outlining steps the government must take to secure the countrys digital future and defend its digital ecosystem against foreign adversaries like China and Russia. The strategy calls for rebalancing the responsibility of defensive cybersecurity to the most capable and best positioned actors in the US, essentially shifting it towards industry.

RELATED: National Cyber Strategy Seeks To Rebalance Cyber Responsibility Towards Industry

Thats especially true for the military, which relies on an army of private industry contractors, and Sherman told Breaking Defense that DoD recognizes the fundamental role it plays in collaborating with industry and, ultimately, the success of warfighters.

Our partners realize that protecting DoD information that resides within the defense industrial base (DIB) and cloud service providers is necessary to maintain the Departments edge over near-peer competitors, Sherman said. To that end, the Department has made it a priority to collaborate with and exchange information with our DIB and IT partners. Our DIB Cybersecurity Program [PDF] spearheads this enduring effort to ensure we are all equipped to meet evolving cybersecurity threats.

Beyond industry, the national strategy is also well aligned with DoDs own ongoing cloud and cybersecurity efforts, he said. The Pentagon in its fiscal 2024 request, released on Monday, asked for $13.5 billion in funding for its cyberspace activities. That includes increasing cybersecurity support to the DIB, funding five additional cyber mission force teams and operationalizing DoDs zero trust framework.

Under the zero-trust concept, no user is ever fully trusted to be on the network and is continuously validated through every stage. DoD released its zero-trust strategy last year, setting an ambitious timeline to achieve a targeted level of zero trust a set of minimal requirements DoD and its components need to achieve across its enterprise by FY27 followed by a more advanced level.

Gurpreet Bhatia, DoDs acting deputy chief information security officer, told Breaking Defense that the zero-trust approach will ensure a secure DoD information enterprise that enables data-informed decision-making, from the warfighter to our nations most senior leaders and that DoD is continuously addressing cybersecurity risks.

DoD components must meet those standards by FY27, and we continue to look toward industry leaders for potential solutions to accelerate the DoDs execution of its [zero trust] strategy, Bhatia said.

The department is also getting ready to award the first set of task orders under the Joint Warfighting Cloud Capability (JWCC) multi-vendor, multi-cloud contract. Under JWCC, four vendors Google, Microsoft, Oracle and Amazon Web Services will compete for individual task orders to build out DoDs key military cloud computing backbone.

RELATED: JWCC, Zero Trust, User Experience & A New Cyber Talent Strategy: DoD CIO Sets FY23 Priorities

Those task orders are in the pipeline,Sharon Woods, director of the Defense Information Systems Agencys Hosting and Compute Center, said on Tuesday. She added that the vendors will also get an opportunity to bid on secret-level offerings under JWCC in the coming weeks followed by top secret-level offerings in the summer.

Thats a capability we really dont have in the department, an enterprise top secret cloud environment, Woods said. You know, the intelligence community does, but the departmentis not able to leverage that contract and so that is one of those capability gaps that JWCC is meeting.

Deputy DoD CIO Lily Zeleke told Breaking Defense in a statement that through JWCC, DoDhas established a direct relationship with the commercial cloud vendors to deliver, and continuously improve, a modern, resilient computing platform.

Building on the commercial cloud platform, collaborative engagement with industry partners, academia, and other government agencies is delivering the secure components and software practices needed for protecting sensitive applications and data from advanced persistent cyber threats, Zeleke added.

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