By Hisan Kidwai Oppo has started teasing its Find X9 lineup, confirming an October 2025 launch in China. A…
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By Hisan Kidwai The NYT’s Spelling Bee is a super fun word-hunting game where you have to guess as…
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By Dainius Kavoliūnas Startup wisdom is a new TNW series offering practical lessons from experts who’ve helped build great companies. This week, Dainius Kavoliūnas, head of no-code platform Hostinger Horizons, shares his tips on vibe coding. Vibe coding has become an indispensable tool, especially for entrepreneurial thinkers building apps and platforms for solving everyday problems, streamlining business processes, or enhancing digital experiences. It represents a paradigm shift in software development. Instead of writing lines of code, you can now describe your requirement and have AI bring it to life. Vibe coding is fast, intuitive and opens up a new realm of possibilities where code…This story continues at The Next Web

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The United Nations has launched a call for countries to agree to what it refers to as AI red lines: “do-not-cross limits for artificial intelligence, [to be established] by the end of 2026 to prevent the most severe risks to humanity and global stability.” 

The UN statement issued Monday said, “without binding international rules, humanity faces escalating risks [ranging] from engineered pandemics and large-scale disinformation to global security threats, systematic human rights abuses and loss of human control and oversight over advanced systems.”

In a UN Q&A document about the initiative, the global body offered a wide range of possible AI bans, including barring its use in nuclear command and control, lethal autonomous weapons, mass surveillance, human impersonation involving “AI systems that deceive users into believing they are interacting with a human without disclosing their AI nature,” and cyber malicious use, which it defined as “prohibiting the uncontrolled release of cyberoffensive agents capable of disrupting critical infrastructure.”

The UN also wants prohibitions against autonomous self-replication, which it said is the “deployment of AI systems capable of replicating or significantly improving themselves without explicit human authorization,” as well blocking “the development of AI systems that cannot be immediately terminated if meaningful human control over them is lost.”

And, it emphasized, “any future treaty should be built on three pillars: a clear list of prohibitions; robust, auditable verification mechanisms; and the appointment of an independent body established by the Parties to oversee implementation.”

Many analysts and observers, however, have concerns about whether such global restrictions are practical, enforceable, or even in time to limit damages.

Analyst concerns focused not on what the UN is attempting, but on whether enough countries would support it, whether its end of 2026 target implementation is soon enough to make a difference, and whether it’s meaningfully enforceable. 

They noted that the applicability/enforceability of the rules would have an impact on enterprises, mostly via compliance rules, but the UN’s requirements are really intended to impact hyperscalers and other AI vendors, as opposed to their customers. 

AI rules that could impact enterprises might include limits on using AI to screen job applicants, make loan decisions or on training models on confidential customer data. 

Enterprises would still have to comply if they are operating in any country that signed the UN agreement. Then again, those countries, such as Germany, Canada, Switzerland or Japan, would likely have their own AI compliance rules, making the UN mandate potentially irrelevant. 

Valence Howden, an advisory fellow at Info-Tech Research Group, said that he understands and applauds the intent behind the UN’s effort, even if he questions how viable it would be.

“How do we protect organizations [given that] the risks are not tied to country boundaries?” Howden asked. “There is more general agreement that it is necessary than people think. America is an outlier; they don’t want to regulate or control where AI can go. Even China is saying the right things.”

“A lot of the players that I thought would oppose it didn’t,” he noted.

In fact, the only country other than the United States that expressed strong hesitation was France, Howden said, “because they have the same concern [as the US] that innovation will be stifled,” but he added that France is likely supportive, but it said those things because of other delegates in the room.

Howden also expressed concern about the UN target of implementing these restrictions by the end of next year. 

“A lot of this has to happen, and it has to happen quickly,” he said, but with the UN, “the governance and protections are moving at the speed of bureaucracy.” 

Howden said that the AI vendor space is approaching what he called “the point of ungovernability,” and that the industry is “very close to that state right now, being beyond the point of no return.”

He noted that even if the UN effort passed, it’s doubtful that the major hyperscalers, who offer most of the genAI models, would comply. 

“Can we trust the large scale enterprise vendors to do this? No. They don’t do it now,” Howden said.

Brian Levine is a former federal prosecutor who today serves as the executive director of a directory of former government and military specialists called FormerGov. His US Justice Department role included involvement in many global standards efforts, including work with Interpol on international ransomware coordination and serving on the law enforcement Joint Liaison Group (JLG) with China.

Levine said that he expects the UN measure will likely happen because most members will agree on the fundamental principles. “But,” he said, “those principles will be so high level that they won’t really move the ball forward in any meaningful way.”

Levine added that agreeing to the UN proposal is fairly low risk, as countries will likely think, “Don’t worry. It isn’t enforceable anyway.”

The UN has engaged in similar efforts before, with little to show for it. About 11 years ago, the UN tried to ban autonomous killing robots. 

Peter Salib, an assistant professor of law at the University of Houston Law Center, said that the real world deployments of genAI systems today make the threat of AI harm much more concrete than was the threat of autonomous killer robots back in 2014.

But as for the UN effort announced this week, Salib said that he doubts much will come from it. 

“Probably nothing happens that matters,” Salib said. “The countries don’t care very much and don’t care enough to give up their sovereignty.”

Source:: Computer World

By Hisan Kidwai Apple Pay is a super convenient payment type that lets users add their credit/debit card to…
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By Hisan Kidwai Durability in smartphones has come a long way from the days of handling them with utmost…
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By Joseba Villate The global battery market is experiencing unprecedented growth, with projections showing the sector will reach $400bn by 2030. Yet European entrepreneurs often feel locked out, watching Chinese giants like CATL dominate headlines with record-breaking IPOs while homegrown champions like Northvolt file for bankruptcy, exposing the harsh realities of competing against established Asian supply chains. Still,  Europe will never be entirely independent in green energy and will want to cooperate with Asia. Yet the continent has strong demand for on-shoring supply, including green power and critical manufacturing.  There are also genuine competitive advantages available to European green battery startups: proximity to…This story continues at The Next Web

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By Daniel Stenberg On July 16, the European Commission proposed a €2tn seven-year budget – the largest in the EU’s history – to boost autonomy, competitiveness, and resilience. The spending plan addresses cybersecurity, innovation, and other key digital pillars, but omits a crucial component: open source. Open source software – built and maintained by communities rather than private companies alone, and free to edit and modify – is the foundation of today’s digital infrastructure. Since the 1990s, it has been ever-present in the digital infrastructure that European industry and public sector institutions depend on, creating huge dependencies on open source applications and libraries. From…This story continues at The Next Web

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Once upon a time, horses had horns, illness crept upon us, treatments were based on superstition, and lives were short. My, how things have changed. Today, you can be warned of early signs of sickness by your smartphone and other wearable devices, including the Apple Watch and (more recently) AirPods.

Apple has updated those two latter products, enhancing their existing health-focused tools with hypertension detection/alerts on the watch and heart rate-sensing on AirPods 3. (Apple’s own white paper suggests hypertension monitoring could alert up to 1 million hitherto undiagnosed sufferers about their condition.)

Apple and its ambient AI

What’s interesting about these features is the extent to which they rely on on-device artificial intelligence to work. The hypertension detection tool, for example, relies on photoplethysmography (PPG) data, gathered over time by shining light into the skin and measuring the light reflected in return. This information feeds an algorithm (developed across 100,000 study participants) that identifies whether you are at risk, then lets you know.

There are many other health-focused features on both devices that use AI to give you useful information. But what ties all of these tools and services together is their ambience. You see, rather than thrusting artificial intelligence in your face (even though it is quite literally putting AI inside your ears with those new AirPods), Apple is opting for an approach in which technology augments your daily life. 

Unflooding the zone

Apple CEO Tim Cook famously alluded to this when he explained how Apple wants to build products that connect you to others rather than wrapping you in a tech bubble. The idea is to maintain your own connection with the reality around you while also augmenting your day with tools, features, and services that benefit you. 

In the case of hypertension monitoring on AirPods, that’s means flagging potential heart issues. But if you scratch beyond the surface at nearly every AI feature Apple is bringing to market, it becomes clear that building tech solutions that get out of the way is critical to the approach. 

In Apple’s model, AI does not interfere with your perceived reality or your experience of exploring it, but is there in the background to help you in an ambient way (through health sensors, for example), while also being available to assist in specific tasks on request. As I see it, those specific requests can be seen as moments when AI is being asked to help in an active, rather than an passive, way.

Apple and the human AI interface

But this idea of delicate, human-centered augmentation is really just a 21st century evolution of Apple’s long-held human interface design principles.

Apple wants to build technologies that help you get things done — “bicycles of the mind” — as Steve Jobs once put it. When it comes to AI deployment, the logical extension of that way of thinking is evidenced by background tools, health-supporting features, and the innate capacity to run less ambient AI functions on request. That’s a discreet technological augmentation in which humans retain control.

What about privacy?

Then there’s privacy. Apple’s privacy commitments are allowed to exist — and that can’t be taken for granted, given the energy governments seem to be putting into undermining these protections — help reassure us that our data, including AI-gathered information, will not be used against us in some way. 

These protections help ward off surveillance advertising. It’s, after all, plausible to imagine “personalized” ads appearing on digital advertising screens on every corner of every street you travel down, based on your unique user data. Just because you’ve had a hypertension warning doesn’t mean you want your eyes exposed to an endless supply of keep fit, anti-cholesterol drinks and life insurance ads as you go to your local mall, after all.

What happens if?

My concern is that once the bulwark of privacy and personal security is removed, what then? When a population is accustomed to the convenience of wearable AI, at what point will the greed of surveillance-at-a-profit business models stop? As the AI juggernaut penetrates every part of life, where is the political will to define privacy rights?

Where, in other words, do people become information to be monitored, managed, and monetized? Where, even, is the conversation to define the answers to these questions?

We know Apple wants to offer world class tech while also protecting human dignity and privacy. But with competitors and government forcing its hand, perhaps it’s time for a grown-up conversation to define internationally supported privacy standards. This would at least define the market before, not after, the data is collected.

You can follow me on social media! Join me on BlueSky,  LinkedIn, and Mastodon.

Source:: Computer World

In a recent episode of the First Person podcast  we met with Stephen Kaufman, who has spent 25 years architecting solutions on behalf of Microsoft. Stephen told us that his defining characteristic is curiosity, and how his first memory was of taking things apart and putting them back together, more or less successfully. He explained how that led him to a hobby in computers which in turn led him to a computer science degree. He chose to major in both marketing and computers, because for him success is in solving problems with technology, for people.

In this conversation and article we look at how successful technology solutions involved understanding the people involved and the problem to be solved, and then applying technology based on hands on experience and testing. As Stephen told us: “I am a technologist. I love solving problems. I love using technology to match with business problems and find solutions.”

You can view our interview here, listen to it here, or watch in the box below:

Solving problems, getting started

So how did Stephen get here?

“I didn’t know what I wanted to do when I went to the university,” he told us. “It was always interesting to me to interact with people and figure out what do people want and how do you really put it together.”

And his advice for those starting out? “Be curious, get hands on, understand both the technology and interacting with people. That is going to really be essential as you go throughout the career with trying to understand requirements and solutions and figuring out what the problems are.” (See also: How to be a great Chief Product Officer.)

The architect’s mindset

Stephen explained to us that his makeup makes for the perfect architect. A mix of curiosity, interest in people and their problems, and deep thirst to understand technologies top to bottom. He said that applying technology to solve a problem means you need to understand both.

“I’m just curious,” he said. “I want to know how things work. Creating an application or creating a solution. How do you match what those requirements are that customers are looking for? How do you be creative to come up with solutions that meet their needs?”

“Here are the choices. Here are the trade-offs. Here is why this might not work.”

“You learn technologies, you learn ways to interact with customers, you learn what’s needed,” Stephen said. “I read to get an umbrella picture of something. But then I get hands on. I go play with the technology and see how it works.”

Stephen was interested in the way that organizations are approaching AI. He said he feels that some organizations are asking ‘how can we use AI’ rather than ‘how do we solve this problem, and could AI help?’.

“AI is driving lots of perceived need and need within organizations,” Stephen told us. “Does it fit or doesn’t it fit? Is this the right solution? Are we doing things because it’s the trend or because that’s what’s really needed?” (See also: how to be a successful startup founder.)

The job of a solutions architect

In the end for Stephen, the satisfaction comes from understanding people, problems and technology. Then using tech to solve problems. We asked him to describe his role.

“Help the customers really understand what the solution could be or what the technology is and what it isn’t,” he said. “Then helping them come up with some of the decisions.”

He told us that a lot of his role revolves around building trust and relationships with his customers.

“Trust is an important aspect, especially in technology,” he said. “Tech is only one portion of it. But it’s really about listening to customers and understanding what are they trying to achieve. Is this a pain point or is this something that they’re trying to change a business process or get into new markets?”

“Listening to the customer about what they’re trying to achieve is as important as the technology and as the solution,” Stephen told us. “If this was wrong, what are some of the other things that I thought I knew? Did I make an assumption? Then you start to validate and you start to question. You go through other use cases.”

And when a solution is found and implemented, that’s when Stephen wins.

“The greatest thing for me is the satisfaction of seeing something be implemented successfully,” he told us. “Where the customer is elated by what was done, the impact it had, and the benefits that come from that. It is amazing how much joy comes from that successful implementation.”

Before you go: Watch First Person and meet the most interesting people in IT.

Source:: Computer World

By Hisan Kidwai The NYT’s Spelling Bee is a super fun word-hunting game where you have to guess as…
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By Hisan Kidwai For all the music enthusiasts, Spotle is a super fun puzzle game where, instead of words,…
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By Hisan Kidwai For all the music enthusiasts, Spotle is a super fun puzzle game where, instead of words,…
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By Hisan Kidwai Wordle is the super fun game from the NYT, where you put your vocabulary to the…
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By Hisan Kidwai For all the music enthusiasts, Spotle is a super fun puzzle game where, instead of words,…
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By Hisan Kidwai Wordle is the super fun game from the NYT, where you put your vocabulary to the…
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All too often when it comes to AI, enterprises get stuck in a sort of experimentation limbo as deploying AI tools that deliver tangible ROI continues to be a struggle.

Atlassian aims to get them over that hurdle with its definitive agreement to acquire DX, an analytics platform that helps enterprises track their engineering teams’ performance and identify bottlenecks in development and deployment.

The acquisition will allow Atlassian to offer an all-in-one platform with integrated collaboration, project management, and developer productivity measurement tools to help enterprises move from AI testing to deployment.

“What a lot of leaders are saying is, the time for experimenting has passed,” Thomas Randall, research director at Info-Tech Research Group, told Computerworld. “It’s time to now actually put together the solid business case, and greater observability helps.”

Augmenting Atlassian’s ‘System of Work’ strategy

The DX platform was developed to help engineering leaders measure, benchmark, and improve developer productivity. Its tools will fit into Atlassian’s “System of Work” platform, which is designed to speed up processes by connecting business, service, product, leadership, and software teams across an enterprise.

According to the company, DX’s integration into Atlassian’s software development lifecycle (SDLC) will help customers measure AI adoption and impact, pinpoint and address bottlenecks, and gain visibility into developer experience, productivity and system health.

Atlassian has been investing significantly in the software space, with new offerings in Bitbucket Pipelines and Rovo Dev augmenting its Jira, Bitbucket, and Compass tools. The company is also staking a claim in the nascent AI-browser space with an acquisition of The Browser Company of New York.

“For any technology-driven organization, software teams are pivotal for your continued success,” Mike Cannon-Brookes, Atlassian CEO and co-founder, said in a YouTube video accompanying the DX acquisition announcement. “These teams are at a critical moment. AI is transforming how software teams work. This creates both incredible potential, and a whole new set of questions.”

Atlassian has 300,000-plus global customers, and a significant portion of DX’s customers, including Dell, BNY, Chime, Pinterest, GoodRX, Etsy, Vanguard, Pfizer, and Docker, already use Atlassian products.

“By joining forces, Atlassian and DX will help hundreds of thousands of software teams amplify their impact,” said Cannon-Brookes.

Providing insight into friction points, developer satisfaction

Organizations still struggle to pinpoint use cases for AI in their internal workflows and products, Info-Tech’s Randall noted.

“It’s been a bit more of throwing a lot of things at various pieces, or bottom up approaches from departments trying out different things,” he said. “A lot of time and money has been lost because too many projects and tests are going on.”

The integration of DX into Atlassian’s platform will offer observability and context, so teams aren’t just getting caught up in endless testing and experimenting loops, he said. “The core benefit is far greater visibility into where their work is slowing down. They can figure out which investments are actually working, which are having weaker impact.”

For instance, they can gain insight into code reviews or test delays. Many software teams are also adopting code assistants and automated testing tools, which DX can benchmark, Randall noted. They can also use it to gauge developer satisfaction and friction points, allowing them to set norms around measuring progress, and identify best practices and new opportunities for automation.

“It will help reduce technical debt by improving flow, lowering cycle times, reducing delays, expediting incident resolutions and risk management,” said Randall.

A ‘nice perk’ for existing Atlassian customers

The integration is a “nice perk” and “value add” for Atlassian customers, Randall contended. The company can now offer a “comprehensive package” featuring build and run software, matrix and feedback loops.

Enterprises must always be mindful about execution, he emphasized. How well will this integrate into their change management, such as by convincing engineering teams to adopt certain metrics? These tools surveil behavior, so it’s important to consider developer personas and identify what will motivate them and help them do their best work, he pointed out.

With any AI project, enterprise leaders should consider their core business goals, and objectives and key results (OKRs), then determine how AI tools can support them, rather than just adopting AI for the sake of it, said Randall.

“Because,” he noted, “a lot of the time it’s, ‘do you even need AI for that? This could just be straightforward automation with a rules-based system.’”

Source:: Computer World

IT service desks have long been viewed as expensive but necessary cost centers that play an essential role in keeping organizations operational. However, this perception is rapidly changing as intelligent IT service management (ITSM) platforms demonstrate their ability to transform service operations from expense drains into efficiency engines that deliver measurable cost savings and strategic value.

Traditional IT service desks face the daily challenge of managing an ever-increasing volume of routine requests while maintaining quality service within constrained budgets. Password resets, access provisioning, and basic software troubleshooting all consume enormous amounts of staff time, creating bottlenecks that frustrate users and limit IT’s ability to focus on strategic initiatives.

When skilled IT professionals spend much of their time on repetitive tasks, organizations not only pay premium wages for routine work but also sacrifice the innovation and strategic thinking these professionals could apply elsewhere. Manual processes also introduce human error, inconsistent service delivery, and delays that ripple through the organization.

The AI-powered transformation

Intelligent ITSM represents a fundamental shift in how service desks operate. Unlike basic automation tools that simply execute predefined scripts, ITSM systems powered by artificial intelligence (AI) analyze historical data, identify patterns, and continuously learn from ongoing operations to improve service delivery.

“The transformation we’re seeing with intelligent ITSM goes far beyond simple cost reduction,” says Karl Triebes, chief product officer at Ivanti. “Organizations are discovering that when you automate routine service desk tasks and free IT staff to focus on strategic initiatives, you’re not just saving money; you’re also unlocking innovation capacity that drives business growth.”

For instance, intelligent ITSM can provide:

Automated incident routing that ensures that requests reach the right resources immediately

AI-powered chatbots that resolve common issues without human intervention

Predictive analytics that identify potential problems before they impact users

Intelligent workflows streamline approvals and escalations, and self-service portals empower users to resolve many issues independently.

Organizations that employ intelligent ITSM report improvements in resolution times, with many routine requests handled instantly through automated workflows. As for the more complex issues that require human intervention, these platforms enable IT to prioritize work based on business impact rather than simply responding to the loudest complaints. The upshot: Users spend less time waiting for IT support and more time on value-generating activities.

Intelligent ITSM also delivers compliance benefits, reducing the risk of costly regulatory violations while ensuring standardized service delivery across the organization. Enterprises can also move out of a reactive stance, leveraging intelligent ITSM’s real-time visibility into service health to enable proactive management and continuous improvement, further optimizing operational efficiency.

Also, intelligent ITSM enables organizations to strategically reallocate IT resources. When routine tasks are automated, skilled technicians can focus on digital transformation initiatives, security improvements, and innovative solutions. This shift transforms IT from a cost center into a function that enables the business to achieve its objectives faster and more efficiently.

One example of an intelligent ITSM platform is Ivanti Neurons for ITSM , which integrates AI-powered virtual agents, incident correlation, generative AI, and automated workflows into a comprehensive service management ecosystem. The platform’s self-service portal enables users to resolve issues independently, and advanced analytics help IT teams identify optimization opportunities and prioritize work based on business impact.

Promoting scalability and flexibility, Ivanti supports hybrid and remote environments while demonstrating how intelligent ITSM can deliver faster, more cost-effective service experiences to enable you to work smarter, not harder.

Discover how Ivanti can help your organization take a proactive, automated approach to ITSM.

Source:: Computer World

By Deepti Pathak Spotify has introduced a big update for its free users, removing one of the biggest restrictions…
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By Alex Menn Europe’s AI startups are losing ground to the US — and their own investors are to blame. Only 5% of global venture capital is raised in the EU, according to the European Commission. The US, by contrast, attracts more than half, while China takes 40%. Yet Europe isn’t capital-poor: households save €1.4tn a year, nearly twice as much as in America. Still, very little of that money finds its way into startups, despite a plethora of incentives like the UK’s EIS tax relief for business angels.   Even when funding is available, Europe’s venture capital firms are slow and cautious. Funds…This story continues at The Next Web

Source:: The Next Web