SoftBank Group aims to capitalize on soaring demand for the computing capacity that underpins artificial intelligence applications. SoftBank Group agreed to buy private equity firm DigitalBridge Group for about $3 billion in cash, part of the Japanese conglomerate's push to invest in data centers and other digital infrastructure fueling the artificial intelligence boom. SoftBank will pay $16 per share for New York-listed DigitalBridge, the companies said in statement Monday, confirming an earlier Bloomberg News report. The offer -- valued at $4 billion, including debt -- is a 65% premium to DigitalBridge's closing share price on Dec. 4, the last trading day before talks between the two companies were reported. SoftBank's billionaire founder Masayoshi Son aims to capitalize on soaring demand for digital infrastructure, driven by the AI boom.

Autonomous weapons systems (AWS) change the way humans make decisions, the effect of those decisions and who is accountable for decisions made. We must remain vigilant, informed and human-centred as we tackle our deliberations on developing norms regarding their development, use and justification. Ways to enhance compliance in international humanitarian law (IHL) include: Training weapons decision makers in IHL; developing best practice in weapons reviews including requirements for industry to ensure that any new weapon, means or method of warfare is capable of being used lawfully; develop human-centred test and evaluation methods; invest in digital infrastructure to increase knowledge of the civilian environment in a conflict and its dynamics; invest in research on the real effects and consequences of civilian harms to the achievement of military and political objectives; improve secure communications between stakeholders in a conflict; and finally to upskill governments and NGOs in what is technically achievable with emerging technologies so that they can contribute to system requirements, test and evaluation protocols and operational rules of use and engagement. Governments are responsible for setting requirements for weapons systems. They are responsible for driving ethicality as well as lethality. Governments can require systems to be made and used to better protect civilians and protected objects. The UN can advocate for compliance with IHL, human rights, human-centred use of weapons systems and improved mechanisms to monitor and trace military decision making including those decisions affected by autonomous functionality.

From 2022 to 2030, the X-ray imaging systems segment is projected to maintain its lead in the Medical Digital Imaging System market, as per the recent analysis. The segment emerged as the dominant method in 2021, with the increasing prevalence of cardiovascular, respiratory, and gastrointestinal disorders driving the demand for X-ray imaging systems. Furthermore, the rising demand for minimally invasive procedures supports the market's growth. Technological advancements, such as portable and wireless X-ray devices, are expected to expand the segment further. SkyQuest's research suggests that the Asia Pacific region is also a major player in the Medical Digital Imaging System market.

Today, cybersecurity is in a state of continuous growth and improvement. In this on-demand webinar, learn how two organizations use a continuous AI feedback loop to identify vulnerabilities, harden defenses and improve the outcomes of their cybersecurity programs. The security risk landscape is in tremendous flux, and the traditional on-premises approach to cybersecurity is no longer enough. Remote work has become the norm, and outside the office walls, employees are letting down their personal security defenses. Cyber risks introduced by the supply chain via third parties are still a major vulnerability, so organizations need to think about not only their defenses but those of their suppliers to protect their priority assets and information from infiltration and exploitation.

Environmental impacts are far reaching, the effects of climate change devastating, and organizations are striving to shape their business in a way that is environmentally sustainable and equipped to thrive in the future. Ronald van Loon is a Huawei partner, and discussed green solutions at Huawei's Global Analyst Summit in Shenzhen China, where Huawei highlighted the importance of building a green intelligent world for 2030. The intelligent world in 2030 will emphasize low carbon living, virtual tourism and classrooms, buildings that consume lower energy, electric and intelligent vehicles, virtual factories, better ways for businesses and people to collaborate in real-time, and more renewable energy solutions will go mainstream. Huawei released a report called "Green Development 2030" that focuses on how green development will change people's lives and industries. According to Huawei, "by 2030, we expect 80% of energy to come from renewable sources and energy efficiency to increase 100 times."

There's been a renewed focus on digital transformation (opens in new tab) over the past two years, driven in part by the pandemic. Whilst it was already on many organizations' agendas and a central component of their business strategy, the pandemic led to a significant need to speed up the digital transformation that was underway. Craig Stewart is CTO at SnapLogic (opens in new tab). Accompanying this shift, there has also been the growing need for better data (opens in new tab) literacy across all employees (opens in new tab). However, the importance that businesses place on data literacy awareness and training, and the benefits that greater data literacy can bring, often fades into the background when introducing new technologies or initiatives.

SINGAPORE, February 3rd, 2022 – Businesses and public sector organizations will need to accelerate the modernization of their IT infrastructure and operations to be able to build a sustainable competitive advantage in the next 2 to 3 years. The ability to align to the digital paradigm is not only contingent upon investing in next-generation cloud-native IT infrastructure technologies, platforms, and solutions, but also how CIOs will help transform to autonomous IT operations using AI / ML technologies, delivering business resilience, agility, flexibility, and adaptability. The rapid proliferation of data-driven edge workloads, growing number of ransomware and malware attacks, and blistering growth in the volume of structured and unstructured data are creating significant challenges, as a result of which by 2023, most C-Suite will implement business-critical KPIs tied to data availability, recovery, and stewardship. IDC believes this will help to sustain data-driven innovation. "The CIO and IT decision-makers will need to do some serious thinking beyond modernizing the technology building blocks and platforms if they truly intend to align to digital business outcomes, SLAs, and KPIs. Cultural and mindset change is going to be one of the keystones of digital infrastructure paradigm, which goes far and beyond just embracing cloud as the defacto delivery platform or using OPEX based as-a-service IT consumption models. Digital Infrastructure represents the dawn of a new era for IT decision-makers to make an inedible mark in helping their organization lead into the future," says Rajnish Arora, Vice President Enterprise Infrastructure Research at IDC Asia/Pacific.

Until this point, there's the awareness that AI can automate many tasks, increase productivity and make our lives easier while also enabling us to solve problems that are simply too complicated for humans to solve alone. However, AI is not without its challenges. As we see AI becoming increasingly pervasive in our society and affecting every aspect of our lives, it also creates a host of new ethical and moral questions that have never been faced before. This means there's no real way for consumers to protect themselves from having their data misused by companies or being discriminated against due to the biases programmed into machine learning systems. It also means that companies have little incentive to use their customers' data responsibly.

The pivotal role that the digital infrastructure plays in delivering critical societal, economic and governmental functions has become clearer than ever before as a result of the COVID-19 pandemic. There is now a high level of awareness in both business and society that availability, reliability, affordability and sustainability are all essential aspects of the digital infrastructure that must be ensured in both the short and long term. At the same time, the cyberphysical convergence is picking up speed, highlighting the need for advanced network technologies to support use cases that blur the boundaries between physical and digital realities. The rapid acceleration in the adoption rate of digitalization during the pandemic would not have been possible without the existing capabilities of both the mobile and the fixed communications infrastructure. Going forward, 5G will be the main digital infrastructure for consumers with mobile and fixed wireless residential access supporting augmented/virtual reality and artificial intelligence (AI) based services.

Artificial intelligence (AI) systems operate in increasingly diverse areas, from healthcare to facial recognition, the stock market, autonomous vehicles, and so on. While the underlying digital infrastructure of AI systems is developing rapidly, each area of implementation is subject to different degrees and processes of legitimization. By combining elements from institutional theory and information systems-theory, this paper presents a conceptual framework to analyze and understand AI-induced field-change. The introduction of novel AI-agents into new or existing fields creates a dynamic in which algorithms (re)shape organizations and institutions while existing institutional infrastructures determine the scope and speed at which organizational change is allowed to occur. Where institutional infrastructure and governance arrangements, such as standards, rules, and regulations, still are unelaborate, the field can move fast but is also more likely to be contested. The institutional infrastructure surrounding AI-induced fields is generally little elaborated, which could be an obstacle to the broader institutionalization of AI-systems going forward.