Four common AI pitfalls -- and how to avoid them
Artificial intelligence (AI) is transitioning from an emerging technology to a business mainstay. While many businesses are already reaping the benefits of strategic AI implementation, others are adopting AI solutions without first considering how to integrate the tools strategically. While some AI tools offer tangible gains in automation and efficiency, others overpromise and underdeliver, leading to costly investments with little return.
Distinguishing marketing buzz from real-world impact is critical for businesses looking to make AI a true driver of operational success. Despite AI’s potential, many businesses fall into common pitfalls that prevent them from realizing the full value of innovative technology. From unclear objectives to poor integration and security risks, these challenges can turn AI from a competitive advantage into an expensive mistake.
Google warns DOJ breakup plan could destroy Android and Chrome -- plus hurt the US economy
Google is hitting back at the Department of Justice over a proposed plan that could force massive changes to how the company operates. The DOJ, which sued Google back in 2020 over search distribution practices, is now pushing for remedies that Google says go way too far -- and could end up hurting American consumers, innovation, and even national security!
In a new blog post, the search giant says the proposed changes are not only unnecessary but also dangerous. At the heart of the issue is how Google partners with phone makers and browsers to make its search engine the default. According to Google, people use its search because they want to -- not because they’re forced to. The company says blocking these deals would just make it harder for people to get to the services they prefer, with alternatives like Microsoft’s Bing being pushed on users instead.
Enhancing data security in an AI-driven era
For many years, the IT community has consistently emphasized the inherent value and significance of data. Data is one of the greatest resources within a business, even referred to as an organization’s crown jewels, and as a result, has become a vital part of business’ security strategies.
However, as the global interconnectivity of technology continues to grow, securing data and its integrity has become one of the most complex parts of cybersecurity. The driving factor behind this increasing complexity is the broadening use of generative AI (GenAI) and large language models (LLMs), for which training data has largely become the world’s publicly available data.
Beyond words: What AI is really learning -- and what it knows that we never taught it
Imagine you had to finish every sentence in every book ever written -- with just your best guess of the next word. That’s how large language models (LLMs) like GPT-4 start learning.
LLMs use self-supervised learning, meaning they don’t need someone to label or explain the data to them. Instead, they learn by reading vast amounts of text from books, code, academic papers, Wikipedia (and its 57 million+ articles), Reddit forums, and news articles, in addition to billions of others, and then predicting what word comes next in a sentence -- over and over again.
Microsoft thinks its controversial Recall feature is ready for some Windows 11 users to try out... install it if you dare
When Microsoft first added the AI-powered Recall feature to Windows 11, it could hardly have been expecting the backlash that came from users. Concerns about privacy and security forced the company to delay the rollout of the activity and screen monitoring snapshot tool.
Now Microsoft thinks it has made the improvements required to calm the concerns of those who spoke out very loudly against the tool. A new preview version of Recall is making its way to some users right now.
Is AI adoption the next great risk to data resilience?
With cyberattacks surging across every sector from critical national infrastructure to commercial businesses, it’s never been more vital for organizations to get control of their digital footprint and restrict access to their most sensitive data. Instead, organizations are being pulled in the opposite direction by AI, which is demanding access to as much data as possible to deliver much-hyped business solutions.
Organizations worldwide are pouring resources into AI innovation, with spending set to hit an astronomical $632 billion by 2028, according to Gartner. Some are even redesigning their organizational structure, introducing new AI-focused roles and even rerouting workflows as they deploy generative AI into day-to-day operations. At the same time, AI organizations are generating unthinkable amounts of investment with OpenAI raising another $40 billion already this year. It’s clear that AI is here to stay, but have organizations lost sight of their data resilience in a bid to keep up with the AI race?
Microsoft makes a browser-based, AI-generated version of Quake II to promote Copilot -- play it now!
Continually seeking new ways to make Copilot seem appealing, Microsoft has turned to retro gaming as a lure. The company has released a browser-based version of Quake II to serve as a Copilot Gaming Experiences demonstration of AI capabilities.
Microsoft has married its own Research lab’s MuseWorld and Human Action Model (WHAM) to show some of the different powers of generative AI. The company says that “by generating gameplay in real time, the underlying Muse shows how classic games like Quake II can be reimagined through modern AI techniques”. But what will matter to most people is that it is available to try out now, for free.
The intersection of wellness and technology: How AI is revolutionizing personalized health
Today’s patients expect medical care with a level of efficiency, accuracy, and convenience than ever before. Unfortunately, in a world where medical professionals are overworked and there is a significant shortage in the availability of labor in the healthcare industry, achieving this is easier said than done, which is why many medical professionals have turned to tools like artificial intelligence to boost their efficiency.
In the medical industry, AI has already been used by medical researchers for years, helping them with their experiments and research. However, innovators throughout the health and wellness industry -- including doctors and leaders of supplement companies -- are beginning to find ways to leverage the power of AI to make their operations more efficient and effective.
AI-driven video is ushering in a new era of collaboration
The shift to hybrid and remote jobs continues to redefine the modern workplace. For the past several years, video conferencing has made global collaboration possible, breaking down barriers that once made a fully remote workforce seem like a far reality. And while this technology will continue to be a core component of day-to-day business, it has only scratched the surface of how video can support increasingly dispersed teams.
In fact, it actually may no longer be enough to sustain remote environments. As workers and employers continue to clash around return to office (RTO) mandates and employee engagement reaches a record low, it’s clear that we need a new approach.
Microsoft is making Copilot+ experiences available to more systems, and that’s great news for accessibility
When talking about AI in general -- including Copilot -- the focus tends to be on the impressive time-saving capabilities and futuristic features. What is often overlooked is the potential for artificial intelligence to improve accessibility.
But this is exactly what Microsoft is doing with the features it has for Copilot+ PCs. And now the company has made many of the Copilot+ experiences available to a wider range of processors, so systems with AMD Ryzen AI 300 series, Intel Core Ultra 200V and Snapdragon X Series chips can feel the benefits. There are huge advances in accessibility to be explored.
Agentic AI might take years to transform security, but cyber defenders must prepare now
For the past two years, the world has been swept up in a rising tide of GenAI hype. The technology has evolved from a data science curiosity to a pervasive part of our everyday lives. ChatGPT alone has over 300 million weekly users worldwide -- and people use Large Language Models (LLMs) every day to generate text, images, music and more.
Despite GenAI’s widespread success, difficulty in developing robust applications that make use of trustworthy AI systems has proven difficult. This is most clear when noting the delta between consumer-facing GenAI applications relative to B2B integration of GenAI. But, with agentic AI this is about to change.
Exploring the security risks underneath generative AI services
Artificial intelligence has claimed a huge share of the conversation over the past few years -- in the media, around boardroom tables, and even around dinner tables. While AI and its subset of machine learning (ML) have existed for decades, this recent surge in interest can be attributed to exciting advancements in generative AI, the class of AI that can create new text, images, and even videos. In the workplace, employees are turning to this technology to help them brainstorm ideas, research complex topics, kickstart writing projects, and more.
However, this increased adoption also comes with a slew of security challenges. For instance, what happens if an employee uses a generative AI service that hasn’t been vetted or authorized by their IT department? Or uploads sensitive content, like a product roadmap, into a service like ChatGPT or Microsoft Copilot? These are some of the many questions keeping security leaders up at night and prompting a need for more visibility and control over enterprise AI usage.
Beyond traditional metrics: How to redefine AI success
In the past year, AI made great strides in moving past hype, so much so, that it’s hard to recall the early days of AI when the initial value of the technology was questioned. Today, as AI initiatives start to deliver widespread returns, enterprise CIOs are faced with competing forces of driving down core IT costs, while investing heavily in AI to drive business transformation.
A recent study of 2,400 IT decision makers, commissioned by IBM and developed with Lopez Research, underscores this optimism. The findings reveal that the vast majority of companies are making headway on their AI strategies, with nearly half already reporting positive financial returns from their deployments. The cost benefits have been especially pronounced for organizations using open-source AI tools -- 51 percent of surveyed companies harnessing open-source solutions reported seeing positive ROI, compared to just 41 percent of those that are not.
Would AI super agents mean goodbye to apps as we know them?
In the Western world, we now have an app for everything. Shopping, banking, gaming, and even controlling the temperature in your home - you name it, there’s an app for it. The iOS app store began in 2008 with 500 apps, yet, now there are over four million apps available across iOS and Android platforms. Each of these apps serve individual needs and consumers have learnt to ignore the digital clutter in favor of app loyalty.
Asia went the opposite way. Instead of narrow-purpose-built apps, they built the 'everything app' long before Elon started dreaming about it with platforms like Paytm, Grab and WeChat. But what would it take for the West to catch up? AI super agents might be the answer to that one.
IT teams, don't fall behind the AI curve
In the new age of AI, companies are looking for ways to integrate the groundbreaking technology cross-functionally to enhance efficiency, innovation and inform decision-making. Like any business department, IT teams are eager to learn how AI and automation can help alleviate more of the menial and burdensome tasks that consume large portions of their workday.
IT professionals are overworked, burnt out and feeling increasing pressure to do more with less. According to a recent survey of IT professionals, 78 percent reported that work stressors are preventing them from upskilling, and 44 percent said their workload is outweighing their ability to be productive. AI and automation can significantly help alleviate these burdens, but they must be implemented strategically and securely.
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