Articles about AI

In an age where cyber threats are becoming increasingly sophisticated, the management and verification of digital identities are at a critical juncture. As various sectors rapidly evolve, decentralized identity (DCI) systems emerge as a revolutionary approach to managing and verifying user identities. These autonomous systems promise to change how we access and use online services. However, many organizations need help with adopting this promising technology.

A recent survey by Ping Identity, which included responses from 700 IT decision-makers worldwide, highlights these challenges. In the UK, 82 percent of IT decision-makers see value in decentralized identities for their customers and employees, yet only about a third (34.5 percent) currently offer this option. A significant reason for this gap is the need for more clarity about the benefits, with 31 percent of respondents unsure what advantages decentralized IDs would bring.

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Often described as the lifeblood of an organization, data drives business operations and decision-making. But while the raw data itself is valuable, it’s the intelligence and insights that can be gleaned from it that truly fuel innovation and growth. This vital intelligence is the foundation on which organizations build long-term strategies, optimise processes, and identify new opportunities.  

However, with IoT and AI creating volumes of data at an unprecedented rate, it has come to a point where many large enterprises have data lakes and warehouses overflowing with untapped potential. 

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AI for Absolute Beginners begins with an engaging introduction to the world of Artificial Intelligence, making it approachable for those with little to no knowledge on the subject.

The book unravels the mysteries of AI's evolution, from its historical roots to the cutting-edge technologies shaping our future. By explaining complex concepts in simple terms, this guide aims to illuminate the path for those curious about how AI impacts our world.

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This month’s update for Windows 11 is pretty impressive. There are the typical bug fixes that you would expect, but there are also lots of additions and improvements to the operating system.

Like Windows 10, Windows 11 Copilot now offers a more app-like experience, and there is the very welcome return of the Show Desktop button on the taskbar. Other improvements mean that it is now possible to create 7-Zip and Tape Archive (TAR) files using the context menu, and there is newly added support for Emoji 15.1. But that’s just for starters.

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Copilot being added to Windows 10 was something of a surprise for an operating system that is very much breathing its last. And more than just bringing the AI-powered assistant to Windows 10, Microsoft is continuing to update it with big changes.

The release of the KB5040427 update for Windows 10 this Patch Tuesday is a good example. Microsoft has used this update to fix lots of OS bugs -- including an infuriating taskbar niggle – and also tweaked Copilot to make it function like an app.

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Modern cybersecurity leaders are expected to balance an almost comical number of responsibilities. Threat intelligence, vulnerability management, asset tracking, identity management, budgeting, third-party risk -- and that’s just what the company is willing to put in the job description.

To be a cybersecurity expert is to spend your entire career deepening your well of knowledge in one or a few domains. To be a cybersecurity leader, on the other hand, is to spend your career attempting to drink an ocean through a straw. What makes this moment in cybersecurity so interesting is that generative artificial intelligence (AI) brought a fundamental change to both the ocean and the straw.

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Researchers on Google's Connectomics team have achieved the largest AI-assisted digital reconstruction of human brain tissue to date. Now, they are turning their attention to the mouse brain to further unravel the mysteries of neural connections.

The recent accomplishment involved mapping just 1 cubic millimeter of human brain tissue, a task that required an astounding 1.4 petabytes of data. This tiny section, equivalent to half a grain of rice, revealed unexpected structures within neurons. "We found some of the wires will wrap themselves into these giant knots," says Google Research Scientist Viren Jain. "We have no idea why -- nobody's ever seen it before."

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Since the arrival of generative AI, its potential to increase challenges associated with privacy and cyber security has become a major concern. As a result, government bodies and industry experts are hotly debating how to regulate the AI industry.

So, where are we heading and how is the crossover between AI and cyber security likely to play out? Looking at the lessons learnt from previous efforts to regulate the cyber security market over the past few decades, achieving anything similar for AI is a daunting prospect. However, change is essential if we are to create a regulatory framework that guards against AI's negative potential without also blocking the positive uses that AI is already delivering.

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Supply-chain vulnerabilities loom large on the cybersecurity landscape, with threats and attacks such as SolarWinds, 3CX, Log4Shell and now XZ Utils underscoring the potentially devastating impact of these security breaches. The latter examples of Open Source Software (OSS) attacks are a growing attack vector. In fact, nearly three-quarters (74 percent) of UK software supply chains have faced cyber attacks within the last twelve months.

Expect attacks on the open source software supply chain to accelerate, with attackers automating attacks in common open source software projects and package managers. Many CISOs and DevSecOps teams are unprepared to implement controls in their existing build systems to mitigate these threats. In 2024, DevSecOps teams will migrate away from shift-left security models in favor of “shifting down” by using AI to automate security out of the developers’ workflows.

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In Practical Artificial Intelligence Programming with Python: From Zero to Hero, veteran educator and photophysicist Dr. Perry Xiao delivers a thorough introduction to one of the most exciting areas of computer science in modern history.

The book demystifies artificial intelligence and teaches readers its fundamentals from scratch in simple and plain language and with illustrative code examples.

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With AI-generated content now proliferating the internet, companies are scrabbling to put polices in place to handle such material on their platforms. Among them is YouTube, and the Google-owned video site has updated its privacy guidelines to better take into account artificial intelligence.

It is now possible for anyone to issue a request to YouTube to remove content if it simulates their face or voice. This is separate to the way in which deepfakes are handled, and it is interesting to see such AI-generated content being seen as a potential violation of an individual's privacy.

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Artificial Intelligence (AI) and Machine Learning (ML) are more than just trending topics, they’ve been influencing our daily interactions for many years now. AI is already deeply embedded in our digital lives and these technologies are not about creating a futuristic world but enhancing our current one. When wielded correctly AI makes businesses more efficient, drives better decision making and creates more personalized customer experiences.

At the core of any AI system is data. This data trains AI, helping to make more informed decisions. However, as the saying goes, "garbage in, garbage out", which is a good reminder of the implications of biased data in general, and why it is important to recognize this from an AI and ML perspective.

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Artificial intelligence is the biggest topic of 2024. While some are already tired of seeing AI constantly in the headlines, it will only become more prevalent. Keeping up with how it changes business practices is then critical. AI is undeniably disrupting most digital industries, including cybercrime.  

As a result, it is important to cut through the hype and get to the facts about AI. A lot has been said about AI's potential impact on the global ransomware threat, but what is the real impact?

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AI will generate 10 percent of all new data in 2025, according to Gartner. This statistic has significant ramifications for business leaders in the digital age.

First, it hints at another substantial development: Overall data generation will skyrocket alongside advanced AI and machine learning (ML) tools. Statista predicts that humans will create, process and consume 180 zettabytes of data in 2025, up nearly 300 percent since 2020. This prediction foreshadows worsening data sprawl, a problem wherein organizations have more data than they can process or understand.

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Artificial intelligence (AI) and machine learning (ML) solutions are being adopted across every industry today. Quite often, these initiatives involve deploying ML models into operational settings where the model output ends up being a widget on the screens or a number on the reports that are put in front of hundreds, if not thousands, of front-line employees. These could be underwriters, loan officers, fraud investigators, nurses, teachers, claims adjusters, or attorneys. No industry is immune to these transformations.

These initiatives are typically driven from the top down. Management monitors and looks for ways to improve KPIs, and increasingly, AI/ML initiatives are identified as a means to this end. Certainly, there’s plenty of communication among executive, finance, data science, and operational leaders about these initiatives. Unfortunately, in many of the organizations I’ve worked with, the group of folks who are most commonly left out of the discussion are the front-line employees.

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