Articles about AI

Anyone holding out buying a new PC because they're waiting for Windows 12 should probably just bite the bullet. While many were hoping -- even expecting -- Microsoft to release Windows 12 in 2024, the latest rumors suggest that it's more likely to be in 2025.

But that's not to say 2024 is a write-off; far from it. Microsoft still has a lot in store for Windows 11 users, and the next big update -- codenamed Hudson Valley -- is thought to be dropping in September. Also known as Windows 11 24H2 ad the Windows 11 2024 Update, this is a major release which will Microsoft continuing to inject AI into the operating system.

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The last 12 months have been seismic for cybersecurity, with successful hacks and breaches continuing to make front-page news. The task of keeping networks and data safe is an ever-evolving one, with hackers and cybersecurity professionals in a constant state of cat-and-mouse as they try to outsmart one another.

Events of the past year, including the widespread adoption of, and interest in, AI, as well as new geopolitical challenges, have had a profound impact. They provide some clues as to what 2024 might hold.

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ComplyAdvantage has released its annual report, "The State of Financial Crime 2024," focusing on the rising trend of artificial intelligence being exploited for fraudulent activities. The report also reveals that, despite consumer apprehension about AI, many financial institutions are investing in technology to tackle this emerging threat.

According to the report, 66 percent of financial industry respondents view the criminal use of AI as a growing cybersecurity threat, with risks ranging from deepfakes to advanced cyber hacks and AI-generated malware. In response, 86 percent of respondents reported that their companies are investing in new technologies. However, only 53 percent prioritized explaining their AI usage to customers.

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AI is already revolutionizing whole industries and professions. New applications and projects appear regularly across every sector, limited only it seems by the boundary of our own inspiration. That means that AI workloads will be critical to organizations across the board; the question is: how can we ensure AI applications are stable, secure and accessible?

Many companies depend on the trusted backup to ensure fail-safety and security against data loss and outages. From a data protection perspective this makes sense, however, backups aren’t best suited to business continuity and disaster recovery (DR), particularly for the most important data and workloads, such as AI.

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History is littered with knee-jerk legislation, enacted with good intentions and often in response to genuine public fear. If you have ever traveled to the USA, you may be familiar with the I-94W Nonimmigrant Visa Waiver form that must be completed before entry. Among a number of questions asked, one is ‘Have you ever been or are you now involved in espionage or sabotage; or in terrorist activities -- Yes or No’. I’m sure many have often wondered whether those actually involved in such activities would be inclined to tick the ‘Yes’ box. This example effectively illustrates the challenges that all regulators and legislators should ask themselves at the outset, namely:

Are we doing this to address the problem or is it just a knee-jerk reaction to placate journalists and voters? (Remember that line from BBC political comedy Yes Minister -- “He’s suffering from Politician’s Logic. Something must be done, this is something, therefore we must do it.”)

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Generative artificial intelligence (GenAI) entered the public consciousness and debate about one year ago. As a science, it goes back several years but as an applicable piece of software, it is very much in its infancy. 

Text, images, and audio can be generated by GenAI models,but their integration into existing software tools worldwide is still in its early stages. Similarly, the majority of business leaders are only talking about GenAI, with some experimenting through proofs of concepts, while a small minority have deployed initial, and usually specific, use cases.

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Artificial Intelligence (AI) has become a buzzword in various industries and the world of online trading is no exception. With its ability to analyze vast amounts of data and make predictions, AI has the potential to revolutionize the way we trade online. Or maybe that's not the case at all. The point in fact is that AI has been integrated into various systems across numerous different industries already. 

However, using AI in the financial market, especially, in trading stocks, bonds, cryptocurrencies and other assets is up to debate. After all, is using AI's machine learning and predictive analysis considered cheating? How is it any different when investors rely on informer insights and leaked documents? The software is just better at processing data than human is. 

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Microsoft continues to throw everything at artificial intelligence, in particular its AI companion Copilot. The company's latest move sees it launching Copilot Pro, a subscription service which gives anyone -- not just businesses and organizations -- access to a more up-to-date and advanced version of the chatbot, including OpenAI's GPT-4 Turbo model.

Designed with "power users, creators and anyone looking to take their Copilot experience to the next level" in mind, Copilot Pro is a $20-per-month attempt by Microsoft to squeeze some money out of AI. The company has also expanded the availability of Copilot for Microsoft 365 to more commercial customers.

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In recent years, enterprises have increasingly turned to low-code and no-code platforms in order to streamline their development processes.

With the introduction of AI, this sector is evolving even faster and Wing To, general manager of Intelligent DevOps at Digital.ai, believes this needs organizations to develop a cautious approach. We spoke to him to find out why.

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In 2017, WannaCry caused significant disruption to the UK public and private sector. The disruption highlighted vulnerabilities within corporate and government systems, most notably within the UK. It impacted hospitals, healthcare facilities and social care, causing operations and admissions to be cancelled, delayed, or postponed.

The attack exposed a lack of robust cyber security measures, failings in basic IT administration and emphasized the importance of investing in strong defenses to safeguard critical public infrastructure. It prompted a renewed focus on cyber security within the UK and initiated efforts to enhance resilience against future cyber threats.

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The use of generative AI is becoming common across many industries, but while it undoubtedly offers benefits it can lead to problems too.

Legal firms in particular can fall foul of poor results, one firm was fined $5,000 after a court found that one of its lawyers had used ChatGPT to write a court brief which included false citations.

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Microsoft has announced a series of new artificial intelligence tools, options and capabilities which the company is using to empower retailers.

From copilot templates designed to help retailers provide personalized experiences for customers to generative AI tools for creating ads, Microsoft continues to push hard with AI. Of particular interest in the latest batch of tools is Retail Media Creative Studio, currently in preview.

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More than 10 percent of enterprise employees access at least one generative AI application every month, compared to just two percent a year ago, but there are security risks as a result.

New research from Netskope shows ChatGPT was the most popular generative AI application in 2023, accounting for seven percent of enterprise usage. The number of cloud apps the enterprise accessed also increased by an average of 19 percent per year, with users jumping from 14 to 20 different apps in just two years.

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AI is growing in popularity and this trend is only set to continue. This is supported by Gartner which states that approximately 80 percent of enterprises will have used generative artificial intelligence (GenAI) application programming interfaces (APIs) or models by 2026. However, AI is a broad and ubiquitous term, and, in many instances, it covers a range of technologies.

Nevertheless, AI presents breakthroughs in the ability to process logic differently which is attracting attention from businesses and consumers alike who are experimenting with various forms of AI today. At the same time, this technology is attracting similar attention from threat actors who are realising that it could be a weakness in a company’s security while it could also be a tool that helps companies to identify these weaknesses and address them.

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Closed AI products like Bard and ChatGPT (ironically from OpenAI) have already delivered a practical, powerful chatbot experience and are being employed by many businesses.

Open AI by contrast is still in its early stages and has not seen wide adoption. We spoke to Mike Finley, CTO and co-founder of AnswerRocket, to find out the differences between the two and how they're set to develop.

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