Articles about Artificial Intelligence

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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In AI-Driven Project Management: Harnessing the Power of Artificial Intelligence and ChatGPT to Achieve Peak Productivity and Success, veteran IT and project management advisor Kristian Bainey delivers an insightful collection of strategies for automating the administration and management of projects.

In the book, the author focuses on four key areas where project leaders can achieve improved results with AI's data-centric capabilities: minimizing surprises, minimizing bias, increasing standards, and accelerating decision making.

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In the realm of digital communication, crafting the perfect email is both an art and a science, especially when the goal is to convert that email into a meeting or a tangible outcome. With the advent of Large Language Models (LLMs) like GPT (Generative Pre-trained Transformer), the stakes have been raised, offering unprecedented opportunities for personalization, efficiency, and effectiveness in email outreach. At the heart of this revolution lies a seemingly simple yet profoundly impactful element: the prompt.

A prompt, in the context of LLMs, is more than just a starting point for generating text; it's the steering wheel that guides the AI in a specific direction, ensuring that the output aligns with the sender's intentions, tone, and objectives. The importance of prompts becomes even more pronounced when considering the goal of converting an email into a meeting -- a task that requires precision, personalization, and persuasion. Prompts provide:

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With the official launch of Copilot+ PCs, Microsoft has also unleashed Windows 11 24H2. This most recent update to Windows 11 has been a long time in the works, and there have been numerous preview builds available.

What is interesting is the way in which this launch is taking place. Copilot+ PC are now available with Windows 11 24H2 pre-installed, and it is also available to Insiders. The fact that systems have this version of the operating system installed means that development is complete (well, as complete as such work ever is), but the launch is dividing the Windows userbase into haves and have-nots -- in more ways than one.

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The use of AI copilots is already helping businesses save time and gain productivity. One recent study found that employees who gain proficiency using copilots saved 30 minutes a day, the equivalent of 10 hours a month, while the average employee saved 14 minutes a day, or nearly five hours each month.

AI copilots essentially allow people to interact with business productivity tools for greater efficiency. You can ask these tools questions, synchronize data and perform automated actions in an easier and better way. In the survey referenced above, 70 percent of users reported greater productivity while 68 percent said it improved the quality of their work. However, while the business benefits are significant, these copilots can also introduce new security risks that organizations must be aware of -- and have a plan for.

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Learn the art of writing effective AI prompts and break into an exciting new career field.

Writing AI Prompts For Dummies, is a comprehensive guide that will teach you how to confidently write effective AI prompts so you can unlock the full power of generative AI.  Whether it's text, images, or even videos and music you're aiming to create, this book provides the foundational knowledge and practical strategies needed to produce impressive results.

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NIST's recent AI Risk proposal, AI RMF Generative AI Profile, aims to assist organizations in comprehending AI risks internally and from third-party vendors. While GenAI adoption is on the rise across various sectors, compliance managers are more cautious about incorporating AI into their compliance programs. Despite all the hype about AI, a survey conducted by The Wall Street Journal among approximately 300 compliance professionals revealed that only one-third currently incorporate GenAI within their compliance programs.

Collaborative efforts between entities like NIST and prominent organizations including OpenAI and Microsoft are underway to expedite the development of standards and recommendations for the responsible deployment of AI. Amidst grappling with the implementation of GenAI, it becomes imperative to understand how third parties are integrating this technology to better evaluate corporate risk, consequently enhancing regulatory and compliance reporting.

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As artificial intelligence (AI) continues to advance, its impact on cybersecurity grows more significant. AI is an incredibly powerful tool in the hands of both cyber attackers and defenders, playing a pivotal role in the evolving landscape of digital threats and security defense mechanisms. The technology has seen use both by attackers to conduct cyber attacks, and defenders to deter and counter threats.

The incorporation of AI into malicious social engineering campaigns creates a new era where cyber threat actors are more convincingly deceptive. With access to a vast amount of data, cyber threat actors can both increase the success and effectiveness of large-scale phishing campaigns, or use this access to huge amounts of data to spread disinformation online.

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At its WWDC yesterday, Apple unveiled its first major foray into modern artificial intelligence, or "Apple Intelligence" as it prefers to call it.

The company may have been slow to adopt the technology, but it’s now going all-in. Apple Intelligence will be baked into the upcoming iOS 18, iPadOS 18, and macOS Sequoia, offering new writing tools for rewriting, proofreading, and summarizing text across apps, Genmoji for personalized emojis, and a significantly improved Siri.

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For all of the excitement currently surrounding artificial intelligence, there are also a lot of concerns. Not only are people worried about the power of AIs, but there is also a great deal of apprehension about the privacy and security of ChatGPT and other tools of its ilk.

Stepping up with a solution is privacy-centric firm DuckDuckGo. With the newly launched DuckDuckGo AI Chat, it offers "anonymous access to popular AI models, including GPT-3.5, Claude 3, and open-source Llama 3 and Mixtral". There is also the promise that chats will not be used to train AI models.

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The field of AI has been around for decades, but its current surge is rewriting the rules at an accelerated rate. Fueled by increased computational power and data availability, this AI boom brings with it opportunities and challenges.

AI tools fuel innovation and growth by enabling businesses to analyze data, improve customer experiences, automate processes, and innovate products -- at speed. Yet, as AI becomes more commonplace, concerns about misinformation and misuse arise. With businesses relying more on AI, the risk of unintentional data leaks by employees also goes up. For many though, the benefits outweigh any risks. So, how can companies empower employees to harness the power of AI without risking data security?

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Last year was an AI milestone marked by enthusiasm, optimism, and caution. AI-powered productivity tools promise to boost productivity by automating repetitive coding and tedious tasks and generating code.  A year later, organizations are struggling to quantify the impact of their AI initiatives and are reevaluating metrics to ensure they reflect the desired business outcomes.

Measuring developer productivity has historically been a challenge, with or without the introduction of AI-powered developer tools. Last year, McKinsey & Company described developer productivity measurement as a “black box,” noting that in software development, “the link between inputs and outputs is considerably less clear” than other functions.

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It was surely only a matter of time before AI made its way to the Raspberry Pi and today sees the launch of the  Raspberry Pi AI Kit. Developed in close collaboration with Hailo, it provides a way of seamlessly integrating local, high-performance, power-efficient inferencing into a number of applications.

The Raspberry Pi AI Kit comprises the M.2 HAT+ preassembled with a Hailo-8L AI accelerator module. Installed on a Raspberry Pi 5, the AI Kit allows users to build AI vision applications, running in real time, with low latency and low power requirements.

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