Articles about AI

The AI Value Playbook is a crucial resource for those who want to understand how to leverage AI to drive business value, drawn from the firsthand experience of those who have been implementing this technology successfully.

The book focuses on questions frequently posed by leaders and boards. How can businesses adapt to these emerging technologies? How can they start building and deploying AI as a strategic asset to drive efficiency? What risks or threats need to be considered? How quickly can value be created? This book is a response to those demands.

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The advent of artificial intelligence inspired a great deal of fear in the workplace, especially regarding job displacement. As AI's potential became more apparent, workers in virtually every industry feared they would be replaced by an AI-driven alternative that could work faster and for less pay.

To date, those fears have been mostly unfounded. In fact, a recent study of nearly 3,000 different workplace skills determined none of them were “very likely” to be replaced by generative AI.

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Branding is important, and this is something we’ve already seen with digital assistants like Siri. Moving into the artificial intelligence era, companies have been falling over themselves to get their own stamp on their version of AI.

Apple has opted for the reasonably predictable “Apple Intelligence”, while Microsoft’s approach has been a little more haphazard. But now there are clues that suggest the company has finally come to understand the importance of giving people an overarching term to cover all of its AI-related offerings. Say hello to Windows Intelligence.

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It seems that even legacy apps are not immune to artificial intelligence. Microsoft has just rolled out a new Insider build of Windows 11 that sees the arrival of AI-powered features in Paint and Notepad.

While these are both stalwarts of the Windows app arena, they also feel like unusual targets for updating with such cutting-edge features. But this is precisely what Microsoft is doing, furnishing Notepad with a handy AI-driven Rewrite feature, and Paint with clever fill and erase options.

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The legal industry is not traditionally recognized as one that is quick to embrace change, but recently, some professionals have been embracing emerging technology maybe a little too quickly, leading to all kinds of problems. The use of generative AI tools has exploded in popularity since OpenAI’s ChatGPT debuted in late 2022, and some lawyers have turned to this generative AI (GenAI) technology to help them with everything from legal research to contract drafting.

However, these GenAI models aren’t foolproof. In fact, they’re likely to “hallucinate” information that seems accurate but is actually entirely made up. If lawyers using this tech don’t take the time to double-check their outputs, they run the risk of working with factually incorrect information, which is embarrassing at best and grounds for legal repercussions at worst.

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Learn how to simplify your life with AI in The ChatGPT Revolution -- now fully updated and revised, with even more ideas to spark creativity and boost efficiency.

The ChatGPT Revolution is the ultimate quick-start guide to unlocking the power of generative AI. We’re on the edge of an AI revolution… but what does that mean for you? It’s time to get curious about how the latest tech can help you handle your everyday load, at work and at home! Whether you’re overwhelmed by repetitive, time-consuming tasks or you’re simply looking for a fresh injection of creativity, ChatGPT has got your back.

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AI empowers developers to co-create the software that powers our world with greater efficiency and improved security. That’s why businesses are already making significant investments in AI. According to GitLab’s 2024 DevSecOps report, 98 percent of UK respondents said they are currently using AI in software development or plan to use it. It’s therefore no surprise that today, many companies are shipping software at least twice as fast as last year.

Here are eight ways developers can tap into AI’s potential:

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The app economy is big business. Apple’s App Store ecosystem alone generated a staggering $1.1 trillion in total billings and sales for developers in 2022. But as users demand more relevant and immediate experiences, often driven by AI, developers increasingly need competitive advantages to stand out. 

Real-time analytics, supercharged by generative AI, can provide a critical edge by allowing developers to extract key insights and quickly adapt their apps to reflect changing user expectations. But only 17 percent of enterprises today have the ability to perform real-time analysis on large volumes of data, and adoption remains slow. Meanwhile, even when companies are able to perform real-time analytics, there are several common mistakes that can prevent them from reaping its full benefits:

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With the increased popularity of artificial intelligence technology, many human workers have expressed concern that AI models will replace them or make their positions obsolete. This is particularly the case with occupations like coding and software design, where artificial intelligence has the opportunity to automate several essential processes. Although AI is a powerful tool that has the potential to revolutionize the coding process, the role of human workers is still invaluable, as this technology is still in its infancy.

Software development teams are among the ranks of workers most profoundly affected by the AI revolution. Some of the ways in which software development teams have begun to use artificial intelligence include:

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Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms.

The book covers in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters.

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Agile decision-making is often hampered by the volume and complexity of unstructured data. That’s where AI can help.

In 2022, the U.S. Congress passed the Inflation Reduction Act (IRA), which allocated billions in investment to clean energy. This set off a race among private equity and credit firms to identify potential beneficiaries -- the companies throughout the clean energy supply chain that may need additional capital to take advantage of the new opportunities the IRA would create. It turned out to be quite a data challenge.

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AI + The New Human Frontier: Reimagining the Future of Time, Trust + Truth by Erica Orange, a renowned futurist, offers a compelling exploration of generative AI's potential to enhance human creativity rather than replace it. This pivotal book navigates how AI tools will help shape the human experience, and aid in augmenting human ingenuity and imagination.

The author eloquently argues that the essence of human intelligence -- our curiosity, critical thinking, empathy, and more -- is not only irreplaceable but will become increasingly valuable as AI evolves to take on routine tasks. AI + the New Human Frontier is a clarion call for embedding trust, human oversight and judgement into AI development, ensuring that the technology amplifies our most human capabilities. At a time when the lines between what is real, fake, true and false are becoming more blurred, reliance on human-centric solutions, not just technological ones, will become more critical.

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Worldwide spending on chatbots is expected to reach $72 billion by 2028, up from $12 billion in 2023, and many organizations are scrambling to keep pace. As companies race to develop advanced chatbots, some are compromising performance by prioritizing data quantity over quality. Just adding data to a chatbot’s knowledge base without any quality control guardrails will result in outputs that are low-quality, incorrect, or even offensive.

This highlights the critical need for rigorous data hygiene practices to ensure accurate and up-to-date conversational AI software responses.

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Software-driven digital innovation is essential for competing in today's market, and the foundation of this innovation is code. However, there are widespread cracks in this foundation -- lines of bad, insecure, and poorly written code -- that manifest into tech debt, security incidents, and availability issues.

The cost of bad code is enormous, estimated at over a trillion dollars. Just as building a housing market on bad loans would be disastrous, businesses need to consider the impact of bad code on their success. The C-suite must take action to ensure that its software and its maintenance are constantly front of mind in order to run a world-class organization. Software is becoming a CEO and board-level agenda item because it has to be.

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Large-language models (LLMs) and other forms of generative AI are revolutionizing the way we do business. The impact could be huge: McKinsey estimates that current gen AI technologies could eventually automate about 60-70 percent of employees’ time, facilitating productivity and revenue gains of up to $4.4 trillion. These figures are astonishing given how young gen AI is. (ChatGPT debuted just under two years ago -- and just look at how ubiquitous it is already.)

Nonetheless, we are already approaching the next evolution in intelligent AI: agentic AI. This advanced version of AI builds upon the progress of LLMs and gen AI and will soon enable AI agents to solve even more complex, multi-step problems.

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