Articles about Artificial Intelligence

Senior security professionals view generative AI as a disruptive cybersecurity threat, with 46 percent of respondents to a new survey believing generative AI will increase their organization's vulnerability to attacks.

The study from Deep Instinct shows the top three generative AI threat issues are seen as growing privacy concerns (39 percent), undetectable phishing attacks (37 percent) and an increase in the volume and velocity of attacks (33 percent).

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Organizations have more data than ever, but unlocking the information it contains in order to make decisions can be a challenge.

The marriage of of real-time analytics and AI with vector search is a potential game changer for any business that has large amounts of data to crunch. We spoke to Rockset CEO and co-founder Venkat Venkataramani to find out more.

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A new survey of over 1,000 Americans reveals that people are deeply concerned about their personal data, believe their data is priceless, want a national privacy law, and are pessimistic about the rise of AI and personal data.

The study for PrivacyHawk, conducted by Propeller Research, shows 45 percent are very or extremely concerned about their personal data being exploited, breached, or exposed. Over 94 percent are generally concerned. Only 5.7 percent of the US population is not concerned at all about their personal data risk.

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A new study finds that 66 percent of researchers are overwhelmed by the quantity of published work they have to review.

The survey, by research platform Iris.ai, of 500 corporate R&D workers shows that 69 percent spend at least three hours a week reviewing research documents, with 19 percent of those spending over five hours. AI could help to address this problem but is not being widely used.

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I'm almost getting sick of hearing about AI and its ability to change the world for the better, for the worse, for who knows what? But when you get to the heart of what AI is and how it can be applied to unlock value in businesses and everyday life, you have to admit that we're standing on the edge of a revolution. This revolution is likely to change our lives significantly in the short term, and perhaps tremendously so in the medium term.

It wasn't that long ago I felt short-sold by the promise of AI. About eight years ago I saw someone demonstrating a machine's ability to recognize certain flowers. Although impressive, it was a clunky experience, and while I could imagine applications, it didn't excite me. Fast forward a few years, my real moment of surprise came when I found thispersondoesnotexist. My brain couldn't work out why these were not real people, and it stuck with me. My next big moment was podcast.ai and their first AI generated discussion between Joe Rogan and Steve Jobs. But just like everyone else on the planet, the real breakthrough was ChatGPT and the conversation I had with the 'Ghost in the Machine'.

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IT leaders say AI solutions will allow them to accomplish more tasks in a day (78 percent) or improve their work-life balance (70 percent).

But despite this a survey of 2,500 global IT leaders from chip maker AMD finds nearly half (46 percent) say their organization isn't ready to implement AI. Just 19 percent say their organization will prioritize AI within the next year, while 44 percent forecast a five-year timeline.

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Recent developments in generative AI have led to a good deal of debate around whether jobs are at risk. Since new AI applications like OpenAI Codex and Copilot can write code, developers could be among those under threat.

We spoke to Trisha Gee, lead developer evangelist at Gradle, to find out more about how AI is likely to change the way developers work.

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Cortana may have been Microsoft's response to Siri, but while Apple's digital assistant prevails, the Windows maker's offering has slipped into insignificance. Never much-loved by users, Microsoft's Cortana has been in its death throes for a while and now the company is finally moving on.

With the release of Windows 11 Build 25921 a few days ago, Microsoft has introduced the option to uninstall the Cortana app, and this is just the tip of the iceberg. The company had already announced plans to stop supporting Cortana in Windows as a standalone app, and that time has now come. A Microsoft Store update is also being used to forcibly deprecate the tool.

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Artificial intelligence is not a technology that stands still, and the same is true of its users. As people have become increasingly familiar with AI tool, and used to working with the likes of ChatGPT, they are becoming more demanding.

In response to this, OpenAI has announced a number of significant updates that will be rolling out to ChatGPT over the course of the next few days. Among the changes are suggestions for initial queries to put to the AI, as well as recommended replies so you can delve deeper into your research.

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In recent years, large language models (LLMs) have revolutionized the field of natural language processing (NLP) and artificial intelligence (AI). These sophisticated models are used widely in AI solutions, such as OpenAI's ChatGPT, and have been designed to understand and generate human-like text, enabling them to perform various language-based tasks. People are incredibly excited by the potential of this technology which is poised to revolutionize how we live and work. However, to understand the true potential of LLMs, it is crucial that people know how they function.

LLMs, at their core, are neural networks trained on vast amounts of text data. They learn to predict the next word in a sentence by analyzing patterns and relationships within the training data. Through this process, they develop an understanding of grammar, syntax, and even semantic nuances. By leveraging this knowledge, these models can generate coherent and contextually relevant responses when given a prompt or query.

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Cybersecurity has become one most crucial aspects of many organizations due to the speed at which cyber threats evolve. The "speed of cybersecurity" makes it vital to have timely and agile defense measures to detect, analyze, and mitigate cyber risks -- as it is the only way to stay ahead of attackers and protect assets in an increasingly dynamic and interconnected world. 

New technologies like cloud computing and automation have led to transformative changes in cybersecurity, though these changes weren’t immediate. The use of the cloud within other IT teams advanced much faster than it did in cybersecurity departments, as security teams were hesitant to cede control to technologies in the hands of others.  

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Generative AI is the big trending topic right now, and understandably is featuring prominently in the news. The popularity of platforms such as Open AI’s ChatGPT, which set a record for the fastest-growing user base by reaching 100 million monthly active users just two months after launching is unquestionably on the minds of businesses globally.

These tools can increase productivity and efficiency by automating repetitive tasks and letting employees focus on higher-value work. They can foster enhanced creativity and innovation by assisting in brainstorming and ideation processes and generating novel solutions to complex problems. Today, AI’s applications have already been well-documented in fields such as eCommerce, security, education, healthcare, agriculture, gaming, transport, and astronomy. The business, productivity, and efficiency gains that it provides these industries are enabling them to flourish and open up new revenue streams.

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A new study of 1,000 office workers across the US and UK shows half of us already use AI tools at work, one-third weekly and 12 percent daily.

But the report from Cybsafe finds 38 percent of users of generative AI in the US admit to sharing data they wouldn't casually reveal in a bar to a friend.

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The global financial landscape is witnessing a transformation as institutions increasingly embrace the power of artificial intelligence (AI) to combat money laundering and fraud. AI's technical capabilities present an array of benefits for Anti-Money Laundering (AML) processes, particularly in its proficiencies for data analysis and pattern recognition.

Though, as AI integration gains momentum, it also brings significant challenges that demand thoughtful consideration. Issues such as limited training data and over-reliance without human supervision can have serious implications for AML efforts.

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Artificial intelligence is finding its way into many areas of business. But its value depends on the quality of the training data and user prompts it receives.

Dynatrace is looking to address this with an update to its Davis AI engine that creates what it calls a 'hypermodal artificial intelligence', combining fact-based, predictive- and causal-AI insights with new generative-AI capabilities.

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