Month: August 2024

The Google Pixel 7 Pro was my favourite phone for switching away from Apple’s ecosystem – and after a week with the Pixel 9 Pro XL, I remember why I loved it so much

It’s difficult to break out of the Apple ecosystem. Sure, plenty of people find it a comfortable place to be, as Apple provides an exceptionally well crafted user experience and interface, but for folks wanting a little bit more out of a device – particularly for better compatibility with Windows devices and a greater range of apps – Android is there for you… If you can deal with Android. Thankfully, Google offers the best Apple detox.

Back in 2022, I switched from the iPhone 12 Mini to the Google Pixel 6a, and I loved it. I instantly fell in love with Google’s assortment of apps and the on par experience offered by Google. The search giant completely mastered the ins and outs of a competitive Android experience, backed up by a range refresh with the Pixel 6 phones from the year prior. It’s no surprise why I liked the phone so much; while Samsung and Oppo are both competitive smartphone rivals in terms of performance and stats, Google went all in on user experience and mastering the camera.

And in my opinion, this remains the secret sauce of the Google Pixel range – which I have rediscovered with the Google Pixel 9 Pro XL. Samsung’s phones are brilliant, and the Samsung Galaxy S24 Ultra remains my personal phone because of its immense performance. Google Pixels are, however, the best iPhones that Apple doesn’t make.

Looking to quit Apple? Start with a Pixel

(Image credit: Zachariah Kelly / Techradar)

Using the Google Pixel 9 Pro XL over the past week has been brilliant. Google’s phones remain the easiest Android devices to get used to, without unnecessary bloatware heaped on top of the OS. The bloatware problem remains an annoying disadvantage to phones from, for example, Oppo and Asus – and to a lesser extent Samsung.

Instead of a slurry of apps from a wide range of developers, Google sticks to its own in-house developed apps and nothing more until you hop on the Play Store. The company already has the best maps app in the world, along with what I would consider to be the best cloud-based drive and photos app, so those bases are well covered. 

For many Android phones, setup is an awkward tap dance between services linked to Google and services linked to the phonemaker. Many of the apps made available to me on my Samsung Galaxy S24 Ultra have gone unused because I simply don’t want to use Samsung’s version of them (for example, Samsung Gallery and Samsung Pay) when I can simply use Google’s versions.

On a Pixel, setup is simple and reliant on a Google account that you probably already have (by virtue of Gmail being the world’s most popular emailing service, which doubles as a Google account). If you don’t, that’s fine, you can use a non-gmail account to create a Google account. It’s an extremely clean process that’s helped by a really user-friendly OS design. 

And then once all of this is done – you’re free. Install the apps that you want and enjoy the wider compatibility with non-Apple devices (including Android and Windows devices). There’s absolutely nothing wrong with sticking to Apple… But the Pixel represents an easy way out.

Not only does Google’s approach to software make it an attractive Apple alternative, but the hardware side of things has gotten noticeably more premium in recent years.

The camera bar, introduced with the Pixel 6 range, made the phones look both unique and exceptionally premium, while also ushering in a new camera system that put Pixels on the same stage as the iPhone and Galaxy S range. The Pixel 9 range includes a fairly redesigned camera bar that’s much more rounded, essentially making the use of a case necessary for how much it protrudes out. 

But it’s not all Pixel perfect

(Image credit: Zachariah Kelly / Techradar)

In fairness, Google has squandered one of the more competitive aspects of the Pixel range. A modest price jump for the Pixel 8 and Pixel 8 Pro in 2023, followed by another price jump in 2024 for the Pixel 9 and Pixel 9 Pro XL (spurred by the introduction of the Pixel 9 Pro as a separate device from the Pro XL) has made the phone noticeably less competitive on the price front. 

Keep in mind that Google’s proprietary Tensor processors, now the Tensor G4 chip with the latest phones, is historically less powerful than its competition from Apple and Samsung. This performance gap was previously alleviated by a much lower cost, but it’s now exasperated by costs that put it in more heated rivalry with those other companies. Most people probably wouldn’t notice a performance gap, but it’s something that might irk power users who use hugely demanding apps or play graphically intensive games.

Google has also opted out of a ‘Titanium’ model, bucking a trend established by Apple with the iPhone 15 Pro and followed by Samsung with the Galaxy S24 Ultra. Unlike higher-end Samsungs, which also followed through with a price increase, there’s also no vapour cooling chamber to speak of and a noticeable lack of UFS 4.0 storage (Google uses 3.1) which results in slower read/write speeds compared to the S24 range.

So this is where my head is at; if you’re looking to try out an Android phone for the first time, then I would strongly recommend the Google Pixel 8a as a starter phone. If you want something more powerful, then consider gravitating to the Pixel 9 for better performance, or the Pixel 9 Pro and Pixel 9 Pro XL for better photography. 

If you’re comfortable with the Android world, then I would highly recommend the phones from the Samsung Galaxy S24 range or many other phones.

Read More 

Democratizing AI is crucial for unlocking its potential, breaking down cost barriers, and empowering innovation across all businesses.

The promise of AI is intriguing, offering businesses the potential to unlock unprecedented efficiency, innovation and growth. Yet, for many, this potential remains frustratingly out of reach. The high cost of entry, driven by factors like unpredictable cloud pricing models and demanding compute requirements, is creating a significant barrier to adoption, particularly when it comes to powerful new tools like Generative AI.

The solution lies in democratizing access to AI – making this game-changing technology affordable, accessible and achievable for businesses of all sizes. By breaking down the cost barrier, businesses can empower a new wave of innovation and unlock the true potential of AI tools across every industry. Fortunately, we are already seeing signs of progress.

Breaking Down the Barriers: Commoditizing AI for All 

Just as cloud computing transformed the technology landscape by making computing power widely accessible, AI is on a similar trajectory. The commoditization of AI, driven by factors like standardized models and accessible platforms, will be crucial in making it affordable and attainable for all types of businesses.

Crucially, this journey towards accessible AI will rely heavily on collaboration and partnership. By working together, businesses can pool resources, share expertise, and develop tailored AI solutions that address their specific needs while navigating the cost and efficiency challenges of high-compute workloads. This collaborative approach will be essential in ensuring that AI benefits everyone.

The potential applications of AI are vast, spanning every industry imaginable. As AI becomes more commoditized, we can expect to see a surge in innovation as businesses of all types discover how to leverage this technology to solve their unique challenges.

From Cloud to Edge: The Technologies Democratizing AI Access 

One of the key technologies driving the democratization of AI is Edge computing. Edge computing brings AI capabilities closer to data sources, enabling real-time processing and decision-making in various industries. No-code/low-code AI platforms empower users with limited programming knowledge to build and deploy AI models without extensive coding, broadening the accessibility of AI development. AutoML tools automate model selection, training, and optimization, simplifying the AI development process for non-experts.

Additionally, federated learning allows AI models to be trained across decentralized edge devices, addressing privacy concerns and enabling wider participation in AI model training. These advancements are poised to expand access, simplify development, and facilitate the deployment of AI in diverse applications and environments.

Another area of democratizing innovation has been allowing some AI models to run on CPUs instead of GPUs. Large Language Models (LLMs) process massive datasets during training, and most of their computations during both training and inference involve matrix multiplications, typically performed in parallel. GPUs, with their thousands of cores, are inherently designed to support highly parallel computation much better compared with CPUs. This is one key reason GPUs are far more suitable for running LLMs as compared with CPUs. In addition, the high memory bandwidth of GPUs is better suited to shuttling the many intermediate data points involved in LLM calculations between memory and processing units.

However, with recent improvements such as quantization, State Space Models, and frameworks like MLX which use unified memory, we are starting to make it possible to run SLMs (Small Language Models) or some quantized LLMs on CPUs. This is another clear example of technologists understanding more about how to harness AI’s capabilities and apply technology in a practical way

A Future Powered by AI: Unlocking Potential Across Industries and Society 

The trajectory of AI suggests that it may be poised to redefine the fabric of not only underlying technology, but also the process of how we work, collaborate, and even communicate. This profound shift will foster innovation, economic growth, and societal advancement. The key will be to ensure this shift is completed ethically and safely so that it remains a positive and not a negative transition. 

To foster wider AI adoption, organizations need to address these multifaceted barriers through a holistic approach that encompasses technical, organizational, ethical, and regulatory considerations. But before we reach there it is important to address the challenges that are hindering AI adoption. The prevalent skills shortage will be a huge challenge for AI adoption. From a senior leadership point of view, the skills shortage would make AI implementation harder as no one can help handle the complexity of integrating AI solutions with existing systems and workflow.

As a first step to remedying this, there is the need to upskill workers so that there is limited resistance to change within organizations and so that employees with the correct skills can work alongside AI systems. This would alleviate concerns around data privacy and security concerns of the AI systems as there will be a trust from all workers on AI systems.

I’m confident that today’s generation of leaders are up to the challenge of democratizing AI. The signs of progress are everywhere, from the rise of edge computing to the ability to run AI models on CPUs, demonstrating a commitment to making AI more accessible and affordable. This drive towards democratization will unleash a wave of innovation across every sector, reshaping not just our technology but also how we work and connect.

We list the best business cloud storage.

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

Read More 

The Sinkclose vulnerability allows threat actors to run malicious code inside the System Management Mode.

AMD has had a change of heart when it comes to patching the Sinkclose vulnerability on Ryzen 3000 desktop chips.

As per the latest update to its SMM Lock Bypass Security Bulletin, the famed silicon will receive an update after all – but other older chips, unfortunately, are still being given the cold shoulder.

It was recently revealed most AMD chips built over the past 18 years are vulnerable to Sinkclose, a critical severity flaw which could allow threat actors to break into the target system – unseen. At the time, the company said that it will be patching newer models, but older ones – especially those who had reached end-of-life – are left for dead, despite some of them being extremely popular among the consumers.

Stealing from the archives

“There are some older products that are outside our software support window,” AMD said at the time, meaning products in the Ryzen 1000, 2000, and 3000 series, as well as the Threadripper 1000 and 2000 models, were being left behind.

On the other end, all generations of AMD’s EPYC processors for the data center, the latest Threadripper, and Ryzen processors, as well as the MI300A data center chips, have all been patched.

The Sinkclose vulnerability allows threat actors to run malicious code inside the System Management Mode (SMM) of AMD processors, which is a high-privilege area reserved for critical firmware operations. To be able to exploit the vulnerability, an attacker would first need to compromise the endpoint separately. Fortunately, there is currently no evidence that any malicious actors discovered, or used, this flaw in the past.

The update should arrive on August 20, 2024, meaning by the time this article gets published, the patch should be available for download.

Ryzen Threadripper 3000, Threadripper Pro 3000WX, Zen 2 EPYC (7002), Ryzen 3000 mobile, and Ryzen 3000/4000 APUs have all been patched, already. As things stand now, Zen processors are still being left for dead.

Via Tom’s Hardware

More from TechRadar Pro

Some of the most iconic AMD chips have a serious security flaw — which the company says it probably won’t patch nowHere’s a list of the best firewall software around todayThese are the best endpoint security tools right now

Read More