It's a common belief that the law often has to play catchup with technology, and this remains apparent today as the latter continues to evolve at a fast pace. With the advent of generative artificial intelligence (Gen AI), for instance, some important legal questions still need to be addressed. First, policymakers must decide how to best balance the use of data to train AI models with the need to protect the rights of creators, said Jeth Lee, chief legal officer for Microsoft Singapore. Also: Generative AI brings new risks to everyone. Here's how you can stay safe Choosing one extreme can stifle or kill innovation in AI, but it's also not possible to allow free-for-all access to all content and data, Lee said in a video interview.

With generative artificial intelligence gaining rapid adoption worldwide, private-sector businesses in Japan are starting to embrace related information search technologies to enhance operational efficiency. Conventional information searches require users to enter relevant keywords and manually browse selected websites to locate the desired information. The process can be time-consuming, however, and users may not always find the exact content they need. By contrast, generative AI searches enable users to input queries using natural language or images. After interpreting the user's wishes, the AI retrieves relevant information from websites and other sources, providing concise, natural-sounding answers.

Yet, difficulty successfully deploying generative AI continues to hamper progress. Companies know that generative AI could transform their businesses--and that failing to adopt will leave them behind--but they are faced with hurdles during implementation. This leaves two-thirds of business leaders dissatisfied with progress on their AI deployments. And while, in Q3 2023, 79% of companies said they planned to deploy generative AI projects in the next year, only 5% reported having use cases in production in May 2024. "We're just at the beginning of figuring out how to productize AI deployment and make it cost effective," says Rowan Trollope, CEO of Redis, a maker of real-time data platforms and AI accelerators.

We explore how startups and large organizations are leveraging this technology to streamline generative AI deployment, enhance customer service, and drive innovation across domains, including chatbots, document analysis, and video generation. Our discussion focuses on overcoming key challenges such as deployment complexity, security, and cost management. We also discuss how microservices can help executives realize business value with generative AI while maintaining control over data and intellectual property.

From fake images designed to cause fears of an immigrant "invasion" to other demonisation campaigns targeted at leaders such as Emmanuel Macron, far-right parties and activists across western Europe are at the forefront of the political weaponisation of generative artificial intelligence technology. This year's European parliamentary elections were the launchpad for a rollout of AI-generated campaigning by the European far right, experts say, which has continued to proliferate since. This month, the issue reached the independent oversight board of Mark Zuckerberg's Meta when the body opened an investigation into anti-immigration content on Facebook. The inquiry by the oversight board will look at a post from a German account featuring an AI-generated image emblazoned with anti-immigrant rhetoric. It is part of a wave of AI-made rightwing content on social media networks.

Creators who sell assets on itch.io will now have to be a lot more upfront about using generative AI. The marketplace for independent digital creators has introduced a new rule that requires users to label their projects if they were produced using generative AI tools, such as ChatGPT and Midjourney. Users will see an AI generation disclosure box when they upload their projects. If they confirm that their project contains AI-generated output, they'll be required to indicate what kinds of content were made with generative AI, whether they're graphics, sounds, text and dialogue or code. If they have a public asset page, they'll see a dialog box when they access their dashboard, making it easy to bulk tag their projects.

Digital transformation is so last year. CEOs and their boardroom colleagues have heard about the potential power of generative artificial intelligence (Gen AI), and they want their CIOs to deliver a new type of data-led change program: AI transformation. Gabriela Vogel, a senior director analyst in the Executive Leadership of Digital Business (ELDB) practice at tech analyst Gartner, told ZDNET that her firm's 2024 CEO Survey suggests many bosses are responding to the hype about Gen AI by demanding AI rather than digital transformations. The survey shows how CEOs' use of the term "digital" increased for a decade but has declined over the last two years, just as their use of "AI" has started to rise. AI is mentioned much more in CEOs' top two strategic priorities for 2024 (24%) than in the 2023 survey (4%).

The US Patent and Trademark Office banned the use of generative artificial intelligence for any purpose last year, citing security concerns with the technology as well as the propensity of some tools to exhibit "bias, unpredictability, and malicious behavior," according to an April 2023 internal guidance memo obtained by WIRED through a public records request. Jamie Holcombe, the chief information officer of the USPTO, wrote that the office is "committed to pursuing innovation within our agency" but are still "working to bring these capabilities to the office in a responsible way." Paul Fucito, press secretary for the USPTO, clarified to WIRED that employees can use "state-of-the-art generative AI models" at work--but only inside the agency's internal testing environment. "Innovators from across the USPTO are now using the AI Lab to better understand generative AI's capabilities and limitations and to prototype AI-powered solutions to critical business needs," Fucito wrote in an email. Outside of the testing environment, USPTO staff are barred from relying on AI programs like OpenAI's ChatGPT or Anthropic's Claude for work tasks.

Comprehensive quality engineering and testing are a must for today's software-driven organizations. Perhaps not surprisingly, generative artificial intelligence (Gen AI) is emerging as a cutting-edge component of the quality and testing phase of the software development lifecycle. However, long-term success in software-testing automation is about establishing the necessary organizational will and resources. In short, to paraphrase management guru Peter Drucker's oft-cited phrase: Culture eats software-quality strategies for breakfast. "The debate on which quality engineering and testing activities will benefit most from Gen AI remains unresolved," said the co-authors of an OpenText study involving 1,755 tech executives state.

Generative artificial intelligence (gen AI) is paving the way for everyone to become their own software developers. But at the same time, AI may render many extraordinary skills unnecessary. For starters, they point out that with low-code and no-code tools, robotic process automation, and now AI, the gates of software development are open to all. "Technology is no longer owned by any one department of function," they explain. "Data and its analyses are no longer the property of only the PhDs and the hard-core number crunchers. From now on, all employees have the ability to be system designers, data analysts, coders, and creators."