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Top Game Changers for IT Organisations, Users From 2014

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Omobola Johnson, Minister of Communications Technology
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Gartner its top predictions, recently, for IT organisations and IT users for 2014 and beyond combined several disruptive topics including Digital Industrial Revolution, Digital Business, Smart Machines and the Internet of Things, the analyst strongly believes these are to serve as more game changers beyond just the IT function.

Gartner Symposium/ITxpo is the world’s most important gathering of CIOs and senior IT executives. This event delivers independent and objective content with the authority and weight of the world’s leading IT research and advisory organization, and provides access to the latest solutions from key technology providers.

“Gartner’s 2013 CEO survey suggests CEOs feel that business uncertainties are declining and yet, CIOs awake each day into a world of technology uncertainty and change,” says Daryl Plummer, managing vice president and analyst, Gartner.

“The savvy CIO will get his or her CEO to recognise the change being brought about by disruptive shifts is coming at an accelerated pace and at a global level of impact.”

Presenting their findings during Gartner Symposium/ITxpo, Gartner’s top 10 predictions are broken out into four categories as follows:

Digital Industrial Revolution
IT is no longer just about the IT function. Instead, IT has become the catalyst for the next phase of innovation in personal and competitive business ecosystems.
One place where this is evident is in the beginnings of a Digital Industrial Revolution that threatens to reshape how physical goods are created using 3D printing.
By 2018, 3D printing will result in the loss of at least $100 billion per year in intellectual property globally.
At least one major western manufacturer will claim to have had intellectual property (IP) stolen for a mainstream product by thieves using 3D printers who will likely reside in those same western markets rather than in Asia by 2015.

The plummeting costs of 3D printers, scanners and 3D modeling technology, combined with improving capabilities, makes the technology for IP theft more accessible to would-be criminals. Importantly, 3D printers do not have to produce a finished good in order to enable IP theft.
The ability to make a wax mold from a scanned object, for instance, can enable the thief to produce large quantities of items that exactly replicate the original.
By 2016, 3D printing of tissues and organs (bioprinting) will cause a global debate about regulating the technology or banning it for both human and nonhuman use. 
The U.S. Food and Drug Administration or comparable agency in a developed nation that is charged with evaluating all medical proposals will introduce guidelines that prohibit the bioprinting of life-saving 3D printed organs and tissues without its prior approval by end of 2015.
Bioprinting is the medical application of 3D printers to produce living tissue and organs. The day when 3D bioprinted human organs are readily available is drawing closer.
The emergence of 3D bioprinting facilities with the ability to print human organs can leave people wondering what the effect of it will be on society.
Beyond these questions, however, there is the reality of what 3D bioprinting means in helping people who need organs that are otherwise not readily available.

Digital Business
Digital business refers to business created using digital assets and/or capabilities, involving digital products, services and/or customer experiences, and/or conducted through digital channels and communities.
Gartner’s digital business predictions focus on the effect digital business will have on labor reductions, on consumer goods revenue, and on use of personal data.
 While these do not cover the sum total of digital business, they do highlight critical areas of medium to long-term impact.
By 2017, more than half of consumer goods manufacturers will receive 75 percent of their consumer innovation and R&D capabilities from crowdsourced solutions.
Consumer goods companies that employ crowdsourced solutions in marketing campaigns or new product development will enjoy a 1 percent revenue boost over noncrowdsourced competitors by 2015.
Engineers, scientists, IT professionals and marketers at consumer goods companies are engaging crowds much more aggressively and with increasing frequency using digital channels to reach a larger and more anonymous pool of intellect and opinion.
Gartner sees a massive shift toward applications of crowdsourcing, enabled by technology, such as: advertising, online communities, scientific problem solving, internal new product ideas, and consumer-created products.
By 2020, the labor reduction effect of digitization will cause social unrest and a quest for new economic models in several mature economies.
A larger scale version of an “Occupy Wall Street”-type movement will begin by the end of 2014, indicating that social unrest will start to foster political debate.
Digitization is reducing labor content of services and products in an unprecedented way, thus fundamentally changing the way remuneration is allocated across labor and capital.
Long term, this makes it impossible for increasingly large groups to participate in the traditional economic system — even at lower prices — leading them to look for alternatives such as a bartering-based (sub)society, urging a return to protectionism or resurrecting initiatives like Occupy Wall Street, but on a much larger scale.
Mature economies will suffer most as they don’t have the population growth to increase autonomous demand nor powerful enough labor unions or political parties to (re-)allocate gains in what continues to be a global economy.
By 2017, 80 percent of consumers will collect, track and barter their personal data for cost savings, convenience and customization.
The number of Kickstarter-based auctions of personal data will increase by triple-digit percentages by the end of 2014.
The escalation of consumer awareness of data collection practices has set the stage for offering consumers more control over the disposition of personal data — collected both online and offline. As increasing demand and scarcity drives up the value of such data, incentives grow to entice consumers to share it voluntarily.
Meanwhile, consumer interest in self-tracking also suggests that consumers are investing more time and energy in collecting data about themselves.
They increasingly view such data as a key asset for life improvement, which is potentially consistent with the idea of trading it for value under the right circumstances.
 By 2020, enterprises and governments will fail to protect 75 percent of sensitive data, and declassify and grant broad/public access to it.
By 2015, at least one more Snowden or WikiLeaks moment will occur, indicating an upward trend in corporations and governments’ acceptance that they cannot protect all sensitive information.
The amount of data stored and used by enterprises and governments is growing exponentially, such that any attempt to protect it all is unrealistic. Instead of facing an unfathomable task of protecting all data, enterprises and governments will focus on protecting only a small part of it, but protecting it well. Wider society will also gain from this approach, enabling it to establish better control over government and business, preventing abuses of power and engendering greater trust.

Smart Machines
The emergence of smart machines adds opportunity and fear as “cognizant and cognitive systems” and can enhance processes and decision making, but could also remove the need for humans in the process and decision effort.
CIOs will see this as a means of delivering greater efficiency, but will have to balance between the active human workforce and the cold efficiency of machines that can learn.
By 2024, at least 10 percent of activities potentially injurious to human life will require mandatory use of a nonoverideable “smart system.”
Economically priced cars with “automated assist” technology added as standard equipment will increase by through 2014 as an indicator of adoption.
The increasing deployment of “smart systems” capable of automatically responding to external events is increasing all the time, but there remains a deep-seated resistance to eliminating the option for human intervention.
The capability, reliability and availability of appropriate technology are not the issue. The willingness of the general population to accept initial widespread deployment and increasing removal of manual override options is the issue.
By 2020, a majority of knowledge worker career paths will be disrupted by smart machines in both positive and negative ways.
Virtual personal assistant usage in business grows more quickly in 2017 and 2018 than iPad usage did in 2010 and 2011/
Gartner forecasts that smart machines will upend a majority of knowledge workers’ career paths by 2020.
Smart machines exploit machine learning and deep-learning algorithms. They behave autonomously, adapting to their environment.
They learn from results, create their own rules and seek or request additional data to test hypotheses.
They are able to detect novel situations, often far more quickly and accurately than people. IT professionals need to recognize that smart machines can create substantial competitive advantages, as well as entirely new businesses.
By 2017, 10 percent of computers will be learning rather than processing.
In 2014, the number of speech recognition applications running on deep neural network algorithms will double.
Deep learning methods, based on deep neural networks, are currently being applied in speech recognition systems as well as some object recognition applications.
Quality of life improves when society is able to derive useful information from the copious amounts of unstructured data collecting in the Internet.
The most important implication of a learning computer is that it expands much less energy to recognize more complex patterns.

Internet of Things
The Internet of Things cements the connection between machines, people and business interactions in the modern era.
With the advent of massively connected devices, businesses, governments and people now have access to more information about themselves and their surroundings than they can actually act on.
Gartner’s prediction focuses on the opportunity to build applications and services that can use that information to create new engagement models for customers, employees and partners, and to foster a new set of business and marketing models that make the word “engagement” a truly valuable asset.
By 2020, consumer data collected from wearable devices will drive 5 percent of sales from the Global 1000.
The number of smartphone apps requesting to share consumer data will increase twofold by 2015, indicating a rise in the number of marketers or proprietors who seek access to customer profile data.
Wearable computing, or wearables, is quickly moving into mainstream society, led by the growing, multibillion dollar health and fitness markets.
Within five years, consumer wearables will become more sophisticated, capturing what the user sees, hears or even feels through biorhythmic responses.
The technical hurdles that have stalled the adoption of wearables (battery life, augmented reality, chip evolution and bandwidth) are quickly eroding; opening doors to creative minds determined to exploit this technology for commercial gain as evidenced by sizable investments in wearable technology from Samsung, Google, Apple and Microsoft.
“While some of these disruptive topics might seem as if they do not have a direct impact on the IT function, we must embrace the notion that IT is now a part of everything,” said Mr. Plummer. “As the structure of businesses and industries change, the IT systems that support them will change and so will the skills, processes and controls needed to keep them functioning. The day when 3D-printed computer architecture exists is upon us, and the days when the digital business, smart machines or the Internet of Things change what computers are may not be far off.”

Culled from: www.gartner.com


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Trump Threatens More Strikes in Nigeria

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President Donald Trump has warned that the United States could carry out further military strikes in Nigeria if Christians continue to be killed, reigniting a sensitive debate over religious violence and foreign intervention in Africa’s most populous nation.

Trump Threatens More Strikes in Nigeria

President Donald Trump

Trump made the remarks in an interview with The New York Times, published on Thursday, while responding to questions about a US military strike carried out in Nigeria on Christmas Day.

At the time, the US military said the operation targeted Islamic State militants in north-west Nigeria and was conducted at the request of the Nigerian government.

Nigeria, however, described the operation as a joint counterterrorism effort, stressing that it was aimed at armed groups designated as terrorists and “had nothing to do with a particular religion”.

“I’d love to make it a one-time strike,” Trump was quoted as saying. “But if they continue to kill Christians, it will be a many-time strike.”

Pressed on comments by his own Africa adviser that extremist groups such as Islamic State and Boko Haram have killed more Muslims than Christians in Nigeria, Trump acknowledged that Muslims were also victims but insisted that Christians were being targeted disproportionately.

“I think that Muslims are being killed also in Nigeria. But it’s mostly Christians,” he said.

Trump has repeatedly raised alarms about the safety of Christians in Nigeria, beginning in late October when he warned that Christianity faced what he described as an “existential threat” in the country. He has accused Nigerian authorities of failing to adequately protect Christian communities and has openly threatened US military intervention if the violence continues.

Nigeria has firmly rejected claims of systematic persecution of Christians. The government maintains that the country’s security challenges are complex and largely driven by insurgency, banditry and criminal violence rather than religious targeting.

With a population of more than 230 million people, Nigeria is almost evenly divided between Christians, who are concentrated mainly in the south, and Muslims, who predominate in the north. Islamist insurgencies, particularly Boko Haram and its offshoots, have plagued parts of northern Nigeria for more than a decade, killing thousands and displacing millions.

Nigerian authorities have repeatedly pointed out that militant attacks have claimed the lives of both Muslims and Christians, arguing that framing the violence along religious lines oversimplifies the crisis and risks inflaming tensions.

Following Trump’s earlier threats, the Nigerian government said it was willing to continue cooperating with Washington in combating terrorism but rejected language suggesting that Christians alone were under threat.

The latest comments are likely to strain diplomatic relations further, as Nigeria balances its partnership with the United States against concerns over sovereignty, security cooperation and the portrayal of its internal conflicts on the global stage.


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OpenAI Launches ChatGPT Health

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OpenAI maker of ChatGPT is rolling out a health-focused feature to the generative artificial intelligence (AI) tool that’s used by nearly a billion users.

Named ChatGPT Health, the new feature aims to provide users with health and wellness information. This, as health is one of the most common ways people use ChatGPT, according to OpenAI.

In a blog post, Microsoft-backed OpenAI says de-identified analysis of conversations show that over 230 million people globally ask health and wellness-related questions on ChatGPT every week.

ChatGPT Health will also “securely” connect medical records and wellness apps to ground conversations with a user’s own health information, making responses more relevant and useful.

“Designed in close collaboration with physicians, ChatGPT Health helps people take a more active role in understanding and managing their health and wellness – while supporting, not replacing, care from clinicians.”

According to OpenAI, health information is often scattered across portals, apps, wearables, PDFs, and medical notes making it hard to see the full picture, and people are left to navigate a complex healthcare system on their own.

“ChatGPT Health builds on these so responses are informed by your health information and context. You can now securely connect medical records and wellness apps – like Apple Health, Function, and MyFitnessPal – so ChatGPT can help you understand recent test results, prepare for appointments with your doctor, get advice on how to approach your diet and workout routine, or understand the trade-offs of different insurance options based on your healthcare patterns.”

According to the company, ChatGPT Health is designed to support, not replace, medical care, adding that it is not intended for diagnosis or treatment. “Instead, it helps you navigate everyday questions and understand patterns over time – not just moments of illness – so you can feel more informed and prepared for important medical conversations.

“To keep your health information protected and secure, Health operates as a separate space with enhanced privacy to protect sensitive data. Conversations in Health are not used to train our foundation models. If you start a health-related conversation in ChatGPT, we’ll suggest moving into Health for these additional protections.”

OpenAI adds that access to ChatGPT Health has started with a small group of early users to learn and continue refining the experience, adding that users with ChatGPT Free, Go, Plus, and Pro plans outside of the European Economic Area, Switzerland, and the UK are eligible.

“As we make improvements, we plan to expand access and make Health available to all users on web and iOS in the coming weeks.

“Medical record integrations and some apps are available in the US only, and connecting Apple Health requires iOS.”


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Kaspersky Shares AI Cybersecurity Predictions for 2026

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Kaspersky experts outline how the rapid development of AI is reshaping the cybersecurity landscape in 2026, both for individual users and for businesses. Large language models (LLMs) are influencing defensive capabilities while simultaneously expanding opportunities for threat actors.

Deepfakes are becoming a mainstream technology, and awareness will continue to grow. Companies are increasingly discussing the risks of synthetic content and training employees to reduce the likelihood of falling victim to it. As the volume of deepfakes grows, so does the range of formats in which they appear.

At the same time, awareness is rising not only within organisations but also among regular users: end consumers encounter fake content more often and better understand the nature of such threats. As a result, deepfakes are becoming a stable element of the security agenda, requiring a systematic approach to training and internal policies.

Deepfake quality will improve through better audio and a lowering barrier to entry. The visual quality of deepfakes is already high, while realistic audio remains the main area for future growth.

At the same time, content generation tools are becoming easier to use: even non-experts can now create a mid-quality deepfake in just a few clicks. As a result, the average quality continues to rise, creation becomes accessible to a far broader audience, and these capabilities will inevitably continue to be leveraged by cybercriminals.

Online deepfakes will continue to evolve but remain tools for advanced users. Real-time face and voice swapping technologies are improving, but their setup still requires more advanced technical skills. Wide adoption is unlikely, yet the risks in targeted scenarios will grow: increasing realism and the ability to manipulate video through virtual cameras make such attacks more convincing.

Efforts to develop a reliable system for labelling AI-generated content will continue. There are still no unified criteria for reliably identifying synthetic content, and current labels are easy to bypass or remove, especially when working with open-source models. For this reason, new technical and regulatory initiatives aimed at addressing the problem are likely to emerge.

Open-weight models will approach top closed models in many cybersecurity-related tasks, which create more opportunities for misuse. Closed models still offer stricter control mechanisms and safeguards, limiting abuse.

However, open-source systems are rapidly catching up in functionality and circulate without comparable restrictions. This blurs the difference between proprietary models and open-source models both of which can be used efficiently for undesired or malicious purposes.

The line between legitimate and fraudulent AI-generated content will become increasingly blurred. AI can already produce well-crafted scam emails, convincing visual identities, and high-quality phishing pages.

At the same time, major brands are adopting synthetic materials in advertising, making AI-generated content look familiar and visually “normal.” As a result, distinguishing real from fake will become even more challenging, both for users and for automated detection systems.

AI will become a cross-chain tool in cyberattacks and be used across most stages of the kill chain. Threat actors already employ LLMs to write code, build infrastructure, and automate operational tasks.

Further advances will reinforce this trend: AI will increasingly support multiple stages of an attack, from preparation and communication to assembling malicious components, probing for vulnerabilities and deploying tools. Attackers will also work to hide signs of AI involvement, making such operations harder to analyse.

“While AI tools are being used in cyberattacks, they are also becoming a more common tool in security analysis and influence how SOC teams work. Agent-based systems will be able to continuously scan infrastructure, identify vulnerabilities, and gather contextual information for investigations, reducing the amount of manual routine work.

“As a result, specialists will shift from manually searching for data to making decisions based on already-prepared context. In parallel, security tools will transition to natural-language interfaces, enabling prompts instead of complex technical queries,” adds Vladislav Tushkanov, Research Development Group Manager at Kaspersky.

 


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