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Economists say, what happens in Vegas matters nationally because it often reflects broader trends on consumer confidence and the overall health of the U.S. economy.

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Let us help you cut through the noise and pick the right streaming service.

Unlike other tech giants, many music-streaming services like Spotify are not currently taking steps to label AI-generated content. But experts say more transparency is key.

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U.S. District Judge Allison Burroughs is presiding over two Harvard cases challenging Trump's moves to cut federal funding from the university and to ban it from enrolling international students.

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NASA is accelerating plans to have a nuclear reactor on the moon by 2030.

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The new school year can be exciting, but also stressful. Kids may be feeling anxious. Parents may be juggling new responsibilities. Experts share tips on how to manage this season of change.

• A video of an iPhone 17 Pro dummy unit in orange has leaked
• This shade is far more eye-catching than most Pro iPhone colors
• Viewers are very mixed on whether it's a good color or not

Leaks suggest that – along with understated black, white, and dark blue shades – the iPhone 17 Pro and iPhone 17 Pro Max might be sold in orange, and now a video has given us our best look yet at a dummy unit in that color.

Shared by leaker Majin Bu, you can see that this is quite a striking shade, and far more colorful than Apple’s Pro models tend to be. Whether it’s a good color is more debatable – Bu says it “looks so good”, but many of the replies to their post are a lot more negative.

@AnxiousHolly, for example, said “this looks hideous”, while @black0nder said “the worst color in iPhone history”. But @YSL_Laurentttt said “Let that be official and I’m getting the 17 Pro”, and @vernons said “if it really looks like that, it could be the winner in this year's upgrade.” So, this really does seem to be a love-it-or-hate-it shade.

iPhone 17 Pro orange looks so good pic.twitter.com/N9ehzP6ldnAugust 7, 2025

A good move

Whatever you think of this specific color choice, though, we’d say it’s a positive sign that Apple might offer such a shade, as it could mean the company is getting more comfortable with the idea that its Pro phones don’t always have to be sold in smart, understated shades.

We’ve long been calling for more colorful premium phones, so perhaps Apple is finally listening. But whether we’ll see more might depend on how well this orange shade sells.

And that’s assuming Apple really does launch an iPhone 17 Pro in this color. For now, we’d take this rumor with a pinch of salt, but we should find out soon, as the iPhone 17 series is likely to land in early September, with one leak pointing to September 9.

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• The iPhone 17 Air might come in these 4 colors – and there's an interesting claim about its chipset too

Enterprise cloud demands have evolved beyond the early drivers of adoption. Now, more than ever, businesses must be prepared to scale at a moment’s notice. Meeting unexpected user demand while maintaining service levels is an ongoing challenge. At the same time, cloud computing workloads are becoming increasingly specialized, requiring optimized solutions across CPUs, DPUs, and AI accelerators to fully harness cloud-native architectures and frameworks.

As a result, cloud spending has become a critical operational priority. According to Flexera, nearly half of all workloads and data are now in the public cloud. In fact, 72% of IT decision-makers (ITDMs) are prioritizing cloud optimization as a key organizational initiative to drive cost savings.

These trends highlight the importance of right-sizing cloud solutions. Enterprises must ensure that their infrastructure is optimized for their specific business needs and workload requirements. The right cloud strategy delivers flexibility, security, performance, and cost efficiency, all of which are fundamental to maintaining a competitive edge.

Why the Time is Now

Cloud computing has long been the backbone of modern digital infrastructure, primarily built around general-purpose computing. However, the era of one-size-fits-all cloud solutions is rapidly fading in a business environment increasingly dominated by AI and high-performance computing (HPC) workloads. Legacy cloud solutions struggle to meet the computational intensity of deep learning models, preventing organizations from fully realizing the benefits of their investments.

At the same time, cloud-native architectures have become the standard, as businesses face mounting pressure to innovate, reduce time-to-market, and optimize costs. Without a cloud-optimized IT infrastructure, organizations risk losing key operational advantages—such as maximizing performance efficiency and minimizing security risks in a multi-cloud environment—ultimately negating the benefits of cloud-native adoption.

Moreover, running AI workloads at scale without an optimized cloud infrastructure leads to unnecessary energy consumption, increasing both operational costs and environmental impact. This inefficiency strains financial resources and undermines corporate sustainability goals, which are now under greater scrutiny from stakeholders who prioritize green initiatives.

Beyond performance gains, security is yet another critical consideration when selecting cloud-optimized hardware that often goes underappreciated. Cloud-optimized hardware often provide a strong suite of advanced security features, such as confidential computing. These technologies ensure that sensitive data remains encrypted while in use, reducing the risk of physical DIMM (Dual In-line Memory Module) attacks or virtual threats in hyperconverged infrastructure environments.

As the risks of data breaches continue to escalate – both in financial and reputational terms – organizations must recognize that leaving cloud environments unprotected is no longer an option. The rise of sophisticated cyber threats, from rogue hackers to nation-state-sponsored actors, makes enhanced cloud security a non-negotiable priority.

Your 2025 cloud optimization playbook

Furthermore, as industries push forward with the adoption and deployment of AI tools, IT leaders must ensure that their cloud infrastructure can support compute-intensive workloads while balancing cost, security, and efficiency considerations. While each organization's computing needs are unique, IT teams embarking on hardware modernization should consider the following:

Performance: Are your cloud instances equipped for the level of compute performance your business requires? Cloud infrastructure must support a range of workloads, from web front-end applications to in-memory analytics and heavy transactional processing.

Cost and efficiency: Can you reduce your cloud footprint by running the same workloads on fewer servers? Prioritizing instances with high compute density allows businesses to run more VMs or containers per server, achieving significant cost and energy efficiency benefits.

Security: Does your cloud instance provide the level of data protection you require? Confidential computing helps mitigate security risks by protecting data in use, reducing vulnerabilities in virtualized environments.

Ecosystem: Opting for processors powered by industry-standard x86 architecture simplifies cloud environments, making it easier to develop, maintain, and migrate applications with minimal disruption.

Unseen optimization, tangible impact

For IT decision-makers, understanding the cost implications of each 'unit of work' is crucial when selecting cloud instances. Traditional infrastructure forces enterprises to choose between overprovisioning resources – leading to unnecessary expenses – or under provisioning, which can cause performance bottlenecks. Cloud-optimized hardware changes this equation by enabling businesses to achieve more with fewer resources while maintaining high levels of performance, security, and efficiency.

As cloud technologies continue to evolve, enterprises that prioritize modernization will reap the benefits of seamless scalability, improved sustainability, and a resilient digital foundation for future innovation. In a world where agility is critical, cloud optimization is no longer a luxury—it is a business imperative for staying competitive in 2025 and beyond.

We list the best IT management tool.

This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

An executive order from President Trump would extend the opportunity for 401k fund managers to include private equity in retirement portfolios. What are the risks and benefits?

Rayford Junior Miles — a World War II veteran from Alabama — came across as a classic tough guy. But to his granddaughter Melanie Harrison, he was just 'Papa.' Melanie spoke with her father, Jim Miles, to remember a grandfather with a soft heart and a comical communication style.

The human brain tends to slow down as we age — even healthy brains shrink. That can make learning and memory harder as people age. But some people’s brains shrink more slowly than their peers. This lucky group is called “SuperAgers.” They’re people aged 80 or older. But they have the memory abilities of someone 50-to-60 years old. This week in the journal Alzheimer's & Dementia, researchers from Northwestern University’s SuperAging Program summarized some of the secrets they’ve learned in the last 2.5 decades. 

Want to hear about more stories about human health and aging? Email us and let us know at shortwave@npr.org.

Listen to every episode of Short Wave sponsor-free and support our work at NPR by signing up for Short Wave+ at plus.npr.org/shortwave.

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Finding it hard to concentrate? Are you glued to social media for longer than you’d like? Well, maybe it’s not you… maybe it’s the phones. Brittany is joined by Magdalene Taylor, writer, cultural critic and senior editor at Playboy, and Fio Geiran, producer at TED Radio Hour and a writer of their Body Electric newsletter, to discuss this phrase: “it’s the phones.” They get into the effects that smartphones have on our brains and our culture, why some people are returning to “dumbphones,” and why it might take more than willpower to manage our relationships with our phones.

(Image credit: Nanzeeba Ibnat)

‘Your scientists were so preoccupied with whether they could, they didn’t stop to think if they should’. While this famous line from Jurassic Park is a poignant reminder of the dangers of unchecked ambition, it can also be applied to today’s rapidly evolving and fragmented AI landscape.

The mainstream availability of AI has compounded issues with shadow IT, as employees increasingly sidestep governance to deploy powerful, self-service AI tools. In this environment, many businesses are faced with how to manage the element of control when unmanaged AI systems start making critical business decisions based on fragmented, unverified data.

Like John Hammond’s ambitious yet doomed theme park, some organizations are now creating something powerful without fully understanding the risks or having proper containment measures in place.

It’s become a business imperative to find ways to ensure AI-ready data is trusted, compliant, and seamlessly connected. Here we explore the unintended consequences of AI-driven shadow IT and why businesses need a structured approach to data management to avoid costly mistakes.

The rise of AI-powered shadow IT

Shadow IT is not a new challenge, but AI takes it to a new level. With so many generative tools now readily available, employees can solve problems, generate content, or make recommendations at speed. This happens often without needing any technical expertise or approval.

This speed is both a blessing and a risk. In their enthusiasm to experiment and move fast, teams often pull data from disparate sources, bypassing enterprise-grade controls in favor of quick, isolated fixes. Over time, these short-term solutions accumulate, and organizations are left with a patchwork of systems, models and insights that don’t speak the same language.

The risk isn’t just that teams are duplicating efforts or misinterpreting data. Business-critical decisions affecting customers, supply chains, product development and strategic direction are increasingly being made based on unverified siloed information. When AI systems operating on flawed data foundations make recommendations that influence growth strategies, the potential for bias or error multiplies exponentially.

Unify and trust your data

The antidote to this growing risk is not to clamp down on experimentation. It’s to build the right data foundation, one that supports innovation while maintaining context and integrity.

This means giving employees access to high-quality, AI-ready data from across the business. It’s essential to build one harmonized layer that connects all business AI applications and ensures that everyone from developers to decision-makers can rely on a single source of truth.

This foundation keeps context intact, so the entire business can see where, how, when and why data was produced, building trust and accurately informing decisions. When data is unified, it also supports regulatory demands and keeps the business agile to future compliance requirements.

The cost of siloed data and duplicated spend

There’s a significant cost benefit to this too. When growth is the unanimous business goal, organizations cannot afford to hemorrhage spend on an inefficient IT landscape.

It’s estimated that organizations today spend up to 50% of their IT budgets on data and analytics, with a significant portion of that going on attempts to harmonize disconnected data sources. Yet, despite these efforts, many businesses still lack a continuous, unified data layer that brings these sources together in a coherent, usable way.

That’s not just inefficient, it’s a missed opportunity. In the age of AI, the power of data lies not just in how much you have, but in how well it’s connected. Without a shared foundation, AI models risk drawing the wrong conclusions or being trained on outdated information.

This in turn leads to additional budgetary pressures. Businesses need to confidently scale AI across functions, knowing insights are accurate, secure and compliant.

From raw data to business outcomes

To move from raw data to real business outcomes, organizations need more than just infrastructure. They need a strategic approach to data and analytics that supports decision-making at every level.

This means combining new technologies with existing business processes to create enriched, curated data products that deliver meaningful value. It means equipping users with advanced analytics, benchmarking tools and AI-powered insights applications that can both interpret the data and recommend actions.

This strategic approach helps limit the spread of shadow IT by reducing the need for employees to seek out unapproved tools or shortcuts. By aligning data initiatives with established governance frameworks and cultural values, organizations can ensure consistency, compliance and trust in the data being used. At the same time, it creates space for innovation and agility, enabling teams to move quickly and confidently within a well-defined structure.

When done right, the benefits are clear: smarter decisions, faster responses and better outcomes across the board.

Creating a culture of AI confidence

Ultimately, the question businesses need to ask is not whether they’re prepared to use AI, but whether they’re ready to do it responsibly and reliably.

Readiness starts with a strong data foundation, ensuring that information is accurate, accessible and well-governed. It means empowering teams with tools and guidance to innovate responsibly, creating a culture where experimentation with the right tools is encouraged.

The lesson from Jurassic Park was not that innovation is dangerous. It’s that innovation without structure, without guardrails and without consideration of the bigger picture can quickly spiral out of control.

We list the best data visualization tool and the best business intelligence platform.

This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

The U.S. Air Force said Thursday it would deny all transgender service members who have served between 15 and 18 years the option to retire early and would instead separate them without retirement benefits.

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Israel's Security Cabinet approved a plan to take over Gaza City despite demands by families of hostages and mounting international calls for Israel to end the war.

(Image credit: Jehad Alshrafi)