Articles about Artificial Intelligence

In Causal Artificial Intelligence: The Next Step in Effective, Efficient, and Practical AI, a team of dedicated tech executives delivers a business-focused approach based on a deep and engaging exploration of the models and data used in causal AI.

The book’s discussions include both accessible and understandable technical detail and business context and concepts that frame causal AI in familiar business settings.

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A new survey from Snow Software reveals that 72 percent of IT leaders believe their organization will be using more AI in the next two to three years.

The poll of 800 IT leaders from the United States, United Kingdom, Germany and Australia set out to assess how IT decision makers' priorities have shifted over the past 12 months and outline their top areas of focus as they head into the new year.

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Windows Copilot has been available to users of Windows 11 for a little while now, as Microsoft continues its march into the world of artificial intelligence. Now it seems that the company is looking bring the AI-powered assistant to Windows 10 as well.

This is, in some regards, a little surprising -- particularly given the age of Windows 10. But there are still over a billion Windows 10 users out there, so it makes a lot of sense for Microsoft to tap into this to extend the userbase for Copilot.

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Given all the interest in AI at the moment it's no surprise that cybercriminals are keen to cash in with a rise in AI themed attacks.

One way of doing this is with a .ai domain name. An unexpected beneficiary of this is the British Overseas Territory of Anguilla which has .ai as its country code.

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Financial market participants, including banks, insurance companies, pension funds, and hedge funds, are all actively exploring ways to leverage artificial intelligence (AI), and private equity (PE) firms are no exception.

Three areas that are showing a significant return on investment (ROI) for AI among PE firms are deal flow, investment pre-screening, and risk intelligence, because it’s these areas where AI is helping them shift their window to act earlier than their peers. The private companies that PE firms invest in are simply far less transparent than public ones: There’s just not as much information about them, and the information that exists is generally much harder to get.

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European lawmakers are plowing ahead with what could be one of the most important pieces of legislation in a generation. The EU AI Act will take a notably more proactive approach to regulation than current proposals in the US and UK. But experts have spotted a critical loophole introduced in amendments to the legislation that could expose rather than protect citizens and societies from AI risk.

In short, this loophole could undermine the entire purpose of the proposed law and it must be closed. To do this successfully, legislators need to take steps to prioritize machine identities as a way to enhance AI governance, accountability, security and trust. Time is running out.

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AI has been very much top of the agenda this week. We've had President Biden's executive order on AI, we've had the AI Safety Summit in the UK, we've even had Collins Dictionary choosing AI as its word of the year (not to be confused with the three-toed sloth beloved of Scrabble players).

Today we also have new research from SnapLogic looking at how generative AI is being used, viewed, and adopted within large enterprises.

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ChatGPT For Dummies demystifies the artificial intelligence tool that can answer questions, write essays, and generate just about any kind of text it’s asked for.

This powerful example of generative AI is widely predicted to upend education and business. In this book, you’ll learn how ChatGPT works and how you can operate it in a way that yields satisfactory results.

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Software is immensely pervasive and foundational to innovation and market leadership. You’ve likely heard the popular phrase coined by McKinsey that "all companies are software companies." It’s true that businesses are competing and winning in their markets based on their ability to digitize and innovate. Almost every major enterprise, no matter its industry, relies heavily on software to deliver services, manage operations internally or promote itself.

Software starts with code, which means that secure or insecure code starts in development. As long as we continue to view security as a bolt-on or an after-the-fact fix, we’ll continue to widen the chasm between the pace of digital innovation and security’s ability to keep up. With AI-generated code increasing the volume and speed of software production without an eye toward code quality, this problem will only worsen. The world needs Clean Code. Without it, the performance of software will suffer, negatively impacting the business. 

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Productivity has significant importance in the contemporary dynamic work environment. AI has the potential to enhance operational efficiency and optimize operations by eliminating unnecessary tasks. AI has the potential to automate many procedures, provide valuable insights, and enhance workflows, hence enhancing professional productivity and overall cloud data management.

This piece explores the potential of artificial intelligence (AI) to enhance productivity.

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The shift to remote and hybrid working has led to many problems for IT teams, not least that it offers an expanded attack surface. Add in the threat from cybercriminals looking to capitalize on advanced AI capabilities to create malware and you have some major challenges.

We spoke to Doug Kersten, CISO of enterprise collaboration specialist Appfire, to discuss the key security challenges product and DevOps teams face today and how to overcome them.

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It is only a couple of weeks since the debut of the Microsoft AI Bounty Program, and now Google has launched its own bug bounty program specific to generative AI.

Google has announced the expansion of its existing Vulnerability Rewards Program to reward for attack scenarios that relates to generative AI. The company says that it wants to incentivize research around AI safety and security, highlight potential issues, and make artificial intelligence safer for everyone.

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You can’t have failed to have noticed that Microsoft has gone all-in on artificial intelligence lately. The company has created Copilot, an AI assistant, and added it to a number of its products, including Bing, Edge, and Windows 11.

While it’s a worthy addition that’s only going to get more useful over time, not everyone wants AI invading their software. We’ve already shown you how to remove Copilot from Windows 11, but how about removing it from Microsoft Edge?

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It’s almost impossible to escape the hype around artificial intelligence (AI) and generative AI. The application of these tools is powerful. Text-based tools such as OpenAI’s ChatGPT and Google’s Bard can help people land jobs, significantly cut down the amount of time it takes to build apps and websites, and add much-needed context by analyzing large amounts of threat data. As with most transformative technologies, there are also risks to consider, especially when it comes to cybersecurity.

AI-powered tools have the potential to help organizations overcome the cybersecurity skills gap. This same technology that is helping companies transform their businesses is also a powerful weapon in the hands of cybercriminals. In a practice, that’s sometimes referred to as offensive AI, where cybercriminals use AI to automate scripts that exploit vulnerabilities in an organization’s security system or make social engineering attacks more convincing. There’s no doubt that it represents a growing threat to the cybersecurity landscape that security teams must prepare for.

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As artificial intelligence (AI) and machine learning technology continue to develop and find new applications, advances in this field have generally been focused on the development of isolated software data analysis systems or of control systems for robots and other devices. By applying model-based systems engineering to AI, however, engineers can design complex systems that rely on AI-based components, resulting in larger, more complex intelligent systems that successfully integrate humans and AI.

Engineering Intelligent Systems: Systems Engineering and Design with Artificial Intelligence, Visual Modeling, and Systems Thinking relies on Dr. Barclay R. Brown’s 25 years of experience in software and systems engineering to propose an integrated perspective to the challenges and opportunities in the use of artificial intelligence to create better technological and business systems.

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