Why ChatGPT won't solve your real-time translation needs
New technologies debut almost every day. This constant barrage of novel tools creates a perpetual cycle of overshadowing -- someone is always introducing a new technology that eclipses the previous innovation, and then something even newer comes out, and the cycle repeats itself. However, OpenAI’s ChatGPT broke that cycle.
Since ChatGPT’s debut in late 2022, the generative AI tool has exploded in popularity. It took just two months for the platform to reach 100 million users, a speed that shattered the previous record for fastest-growing app. The creators of ChatGPT expect the tool to generate $200 million this year and project that number will grow to $1 billion next year. Other businesses, like Google and Grammarly, are taking note. Both of these organizations have developed their own generative AI tool to enhance their business operations.
Five tips to inform your AI and data science strategy and maximize your investments
Data science and AI leaders are rushing to accelerate new technology adoption. According to Forrester, generative AI alone will see an average annual growth rate of 36 percent for the next seven years, taking 55 percent of the AI software market. The analyst firm also estimates that by 2030, $79 billion will be spent annually on specialized generative AI applications and $42 billion will be spent annually on generalized generative AI use cases.
Even if Forrester is off by a few billion dollars, moving fast is still critical to achieving success, but so is having an optimal AI strategy. Leaders must ensure that practitioners have the technology they need to innovate. At the same time, they must ensure innovation does not exceed budgets or introduce new risks.
Three ways AI is changing the private equity game
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.
Three E-signature adoption trends that may surprise you
It’s well documented that the pandemic supercharged digital transformation speeds for countless organizations and disrupted how we work, live, and transact.
In the shift from ink to e-signatures across industries, I have witnessed three important yet somewhat under-the-radar adoption trends that support the recent IDC findings that 86 percent of IT decision-makers say that they have invested in e-signature software in the past year and 85 percent plan to do so in the next 12-18 months.
Leveraging AIOps to keep pace with cloud-native complexity
Companies have massively increased their cloud infrastructure investment in the relentless pursuit of innovation. Cloud-native apps, hybrid clouds, microservices, and serverless all enable companies to serve their customers with greater agility -- and at greater scale -- than ever before.
But the rapid adoption of these technologies has also created distributed cloud environments that are immensely difficult to understand and monitor with conventional observability tools.
Connected cars -- Safety gained or safety lost?
Connected technology is everywhere and influences every part of our lives. On average, there are nine connected devices in every UK household, and according to the UK Department of Culture, Media, and Sport. This is estimated to grow to twenty-four billion connected devices by 2050.
While connected devices provide a range of benefits, there are now growing concerns around the data they are collecting, and the subsequent loss of consumer privacy. One very real example is the recent announcement from the California Privacy Protection Agency (CPPA), which advised that its enforcement division will review the data privacy practices of connected vehicle manufacturers, stating that they are "connected computers on wheels" and should be treated as such.
Introducing Apple Declarative Device Management: A comprehensive guide for Mac administrators
As a Mac administrator, managing a fleet of Apple devices across your organization requires consistent practices and robust security measures. With numerous system services and background tasks to oversee, maintaining uniform configurations and safeguarding organizational data are formidable challenges.
Apple has introduced a powerful new Declarative Device Management (DDM) approach to address these challenges. This update to the Mobile Device Management (MDM) protocol represents a paradigm shift in device management, offering an efficient and secure means of administering macOS devices. DDM enables tamper-resistant configurations and facilitates simplified monitoring of system services and background tasks. Declarative status reports allow administrators to know about a device's current state.
How machine identity can close a critical AI accountability gap in the EU AI Act
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.
Unveiling the true value of privacy
Ask your clients, your friends, or anyone on the street: nobody likes to share their data, especially with people or companies they don't know. We routinely press 'no' on pop-ups asking for cookies in our browser, and of course you’re just as likely to say 'no' to any proposal to share your data to improve a product, even anonymously. People value privacy, even if that's somehow in contradiction with the fact that some of us also share the most private moments on social media.
Does this diffused privacy awareness influence how companies relate to their customers and manage their products and services? Well, not quite. Most of the time, organizations simply don't implement anything which would truly protect the privacy of their users. They typically say things like "your data is protected" or "we are trusted by big companies". And even where regulations and policies are in place, this might not always force these organizations to have particular protections, even when it comes to very sensitive data like health data or financial information. Why? Is it not possible to do more?
5 criteria for evaluating free vs. paid migration tools
Microsoft’s once-free solution for tenant-to-tenant migration is no more. Quietly, Microsoft changed its Cross Tenant User Data Migration terms of use for Enterprise Agreement customers, meaning they’ll need to purchase a license.
If you've been using Microsoft’s free migration solution, it makes sense you’d look for another free alternative. But, before committing to a new migration tool, it’s important to consider the potential pitfalls of free services. That is to say, while cost-efficient, free solutions may lack advanced features, scalability, support, and customization, potentially leading to more complex and prolonged migration processes. Here are five things IT managers need to consider when looking at free or paid migration tools.
Streamlining public transportation CX with AI-powered chatbots
Public transportation systems have a rich history dating back over a century, with iconic examples like the 1863-established London Underground and New York City's subway, which began operations in 1904. While these systems have evolved alongside technological advancements and urban growth, the expenses involved in maintaining and modernizing them often surpass the available resources.
In the U.S., these upgrades tend to be notably more expensive than in other countries. For example, the installation of protective screen doors at just three subway stations in New York is estimated to cost a staggering $100 million. As a result, public transportation experiences often fall short of contemporary expectations, leading to delays, complex route planning and frustrations arising from the need to cross-reference information. All these elements contribute to reduced commuter satisfaction in comparison to alternative modes of transportation, such as cycling or driving.
Secure software depends on clean code -- AI-generated or not
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.
Mission data privacy: Empowering consumers in an era of rapid change
Whether browsing online for clothes or catching up on the latest news, we’ve all had that unwanted internet cookie pop-up appear. At face-value they may seem harmless, but cookies are a goldmine of private information, posing a serious risk to your data privacy. Today, consumers face a new predicament surrounding attitudes toward their valuable data. When personal data is stolen by a cybercriminal, that offense is the online equivalent of a physical robbery, but the severity of data theft is being overlooked.
From a regulatory standpoint, concerns over data privacy have prompted stricter actions from governments and organizations globally as they try to grapple with the challenge of striking a balance between data security and user privacy. Now, in response to increasingly sophisticated criminal tactics, there must be a shift from slow, reactive regulation towards adopting more proactive strategies that both anticipate and mitigate against potential risks. This will be key to shaping a secure, privacy-conscious future.
How to supercharge your productivity with AI: Tips and tools to work smarter, not harder
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.
What IT teams need to know about Google's privacy changes
It’s no secret the depreciation of third-party cookies has been a popular topic of conversation in the industry. Now, however, Google is making changes that will eventually lead to the demise of third-party cookies. The tech giant is rolling out its Privacy Sandbox initiative in the latest version of Chrome and for Android. With any big privacy change, there is a ton of controversy and impending regulations that may mean the Privacy Sandbox is not the futureproof solution brands hope it is.
So, what can IT teams do to help marketers take back control of their data collection strategies and ethically reach customers during this time of change?
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