News

• PDP has revealed a new version of one of its best controllers
• The Turtle Beach Victrix Pro BFG Reloaded features an enhanced fightpad module and Hall effect thumbsticks and triggers
• It's up for pre-order in the US, and out now in the UK

Turtle Beach's competitive gaming accessory brand Victrix has revealed the successor to one of its best controllers.

The Turtle Beach Victrix Pro BFG Reloaded is an overhauled version of the popular Victrix Pro BFG, already one of of the best PS5 controllers today. It retains all the modular functionality of the original but boasts an enhanced design with an improved fightpad module designed for a better claw grip.

It also comes with Hall effect thumbsticks and triggers right out of the box, two major upgrades that should improve precision and help reduce wear over the years.

In addition to the PlayStation variant, an Xbox version will also be available. Both come in either black or white colorways, and cost $209.99 / £179.99.

Although the controller is out now in the UK, it's currently exclusively available to attendees of EVO 2025 in the US. It's up for pre-order on the Turtle Beach website, though, for a wider September 28 release.

The Victrix Pro BFG stands apart from most controllers thanks to its unique modularity. It can be customized and tweaked via a range of interchangeable components, such as alternate d-pads, thumbstick caps, and gates.

It also boasts a range of high-end features, including remappable rear buttons, a hair-trigger mode, and a robust companion app.

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If you’re not including And Just Like That… season 3 in your best HBO Max shows of 2025 list, I can hardly blame you. Since its debut in 2021, the Sex and the City (SATC) sequel has had a rocky ride on screen, frequently being lambasted on social media for how it’s changed the core personalities of Carrie (Sarah Jessica Parker), Charlotte (Kristen Davis) and Miranda (Cynthia Nixon). While Miranda left Steve (David Eigenberg) in the dust and transformed into a legal intern lesbian, Charlotte felt out of touch with her helicopter parenting of kids Rock (Alexa Swinton) and Lily (Cathy Ang).

I couldn’t even tell you who any of the middling replacements for Samantha (Kim Cattrall) are, with Cattrall herself making the career move of a lifetime by staying well away from this absolutely underwhelming car crash (well, all except for that excruciating season 2 finale cameo). The point is, none of our other stars come anywhere near her, but as much as we might want Samantha’s miraculous return in the season 3 finale to scold everyone for making such terrible television, it’s not going to happen.

So, what will happen, or perhaps the more important question is: what needs to happen? If you’ve been managing to stay awake while watching the HBO Max show, you’ll have noticed Carrie is slowly edging closer to the version of herself she used to be in Sex and the City. She’s easily the biggest stumbling block in And Just Like That… (ATLJ), and if we have to watch two more episodes until it’s over, she better have the best damn fictional U-turn TV has ever seen.

Spoilers for And Just Like That… season 3 episodes 9 and 10 ahead.

If you’re a seasoned SATC watcher like me, you’ll have probably thought Carrie was the worst of the quartet in the 90s too… and you’d be right. Never taking responsibility for her own actions and feelings, and instead placing the blame anywhere else, she was too frustrating to consistently warm to (even if she was dressed immaculately). Watching her make the same mistakes over again was relatable and somewhat charming for the first few seasons, but after six seasons, two standalone movies and now three seasons of a sequel series, it all wears awfully thin.

That doesn’t mean Carrie hasn’t been through it in AJLT: she’s been through the fictional death of husband Big (Ron Galotti), the real-life death of Willie Garson, who played BFF Stanford, and she’s picked back up a tired-out situationship with Aidan (John Corbett). We’ve got to have some kind of sympathy for her, right? Wrong! For the bulk of ATLJ, Carrie’s been a burden on her friends, an even bigger burden on us, and the biggest burden of all to herself. All those years of living life in the city on screen, and she doesn’t seem to have learned a single lesson from them.

However, that’s slowly started to change. Just before breaking up with Aidan (finally) and striking up a sexy new attraction to Duncan (Jonathan Clarke), we see Miranda confront Carrie about her evasive defences after Charlotte’s house party in season 3 episode 9. Miranda points out the amount of continued distrust between Carrie and Aidan, and for a split second, AJLT becomes the closest thing we’ve ever seen to a true SATC revival. Finally cutting ties with what isn’t serving her is the healthiest move Carrie has made in years, but can she sustain it?

Here’s my pitch for the AJLT season 3 ending. Miranda stays with Joy (Dolly Wells) and continues to build a healthy relationship (nothing wrong with these two, so live and let live). Harry’s (Evan Handler) prostate cancer is cleared, leaving Charlotte space to thrive as the good friend and mother we know her to be, and the others… well, they can do whatever they like as we won’t be paying attention.

But Carrie needs to dump any and all men, work on herself in the therapeutic ways she’d always dismissed in SATC, and actually start to be a good person. We can’t bow out in good conscience if she still remains a threat to New York City’s female friendships, and there will truly be no evolution in her character if she leaves in an even worse state than when she started. In the most dramatic case, the best thing for Carrie would be to get out of New York completely, which could mean moving back to England with Duncan. Frankly, I don’t care where in the world she ends up, both Carrie and AJLT need to not be insufferable the first time ever in its final moments. I know it’s hard, but pretty please?

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A new NYT Connections puzzle appears at midnight each day for your time zone – which means that some people are always playing 'today's game' while others are playing 'yesterday's'. If you're looking for Monday's puzzle instead then click here: NYT Connections hints and answers for Monday, August 4 (game #785).

Good morning! Let's play Connections, the NYT's clever word game that challenges you to group answers in various categories. It can be tough, so read on if you need Connections hints.

What should you do once you've finished? Why, play some more word games of course. I've also got daily Strands hints and answers and Quordle hints and answers articles if you need help for those too, while Marc's Wordle today page covers the original viral word game.

SPOILER WARNING: Information about NYT Connections today is below, so don't read on if you don't want to know the answers.

Today's NYT Connections words are…

• DRESS
• SCARF
• SUBWAY
• GRATE
• PIPE
• TUBE
• CUBE
• ZIP
• HEALTH
• CARROT
• UNDERGROUND
• SECRET
• METRO
• MINCE
• COAL
• SLICE

What are some clues for today's NYT Connections groups?

• YELLOW: Urban trains
• GREEN: Veg reduction 
• BLUE: The weather outside is frightful 
• PURPLE: Password 

Need more clues?

We're firmly in spoiler territory now, but read on if you want to know what the four theme answers are for today's NYT Connections puzzles…

What are the answers for today's NYT Connections groups?

• YELLOW: SUBTERRANEAN TRANSIT 
• GREEN: MAKE INTO SMALLER PIECES WHILE COOKING 
• BLUE: USED TO DECORATE A SNOWMAN 
• PURPLE: CODE 

Right, the answers are below, so DO NOT SCROLL ANY FURTHER IF YOU DON'T WANT TO SEE THEM.

The answers to today's Connections, game #786, are…

• YELLOW: SUBTERRANEAN TRANSIT METRO, SUBWAY, TUBE, UNDERGROUND
• GREEN: MAKE INTO SMALLER PIECES WHILE COOKING CUBE, GRATE, MINCE, SLICE
• BLUE: USED TO DECORATE A SNOWMAN CARROT, COAL, PIPE, SCARF
• PURPLE: CODE DRESS, HEALTH, SECRET, ZIP

• My rating: Hard
• My score: Perfect

Did you know that if you were to lay all the track of the New York SUBWAY from end to end it would reach all the way to Chicago?

I know this because today’s Connections sent me down a Wikipedia rabbit hole looking at the world’s SUBTERRANEAN TRANSIT systems.

Anyway, I digress. This was a great game for me, as I completed it in color order and it made me feel smarter than I am.

This was mainly down to getting USED TO DECORATE A SNOWMAN – giving us this group in the middle of the summer is a bit sneaky, but seeing COAL and CARROT beside each other I knew what we were looking for.

• YELLOW: ARTHROPODS APHID, BEETLE, MITE, TICK
• GREEN: TREES BEECH, CEDAR, PINE, YEW
• BLUE: [LETTER] (IS) FOR __ APPLE, COOKIE, EFFORT, VENDETTA
• PURPLE: WORDS THAT SOUNDS LIKE TWO LETTERS DECAY, EASY, GEO, ZITI

NYT Connections is one of several increasingly popular word games made by the New York Times. It challenges you to find groups of four items that share something in common, and each group has a different difficulty level: green is easy, yellow a little harder, blue often quite tough and purple usually very difficult.

On the plus side, you don't technically need to solve the final one, as you'll be able to answer that one by a process of elimination. What's more, you can make up to four mistakes, which gives you a little bit of breathing room.

It's a little more involved than something like Wordle, however, and there are plenty of opportunities for the game to trip you up with tricks. For instance, watch out for homophones and other word games that could disguise the answers.

It's playable for free via the NYT Games site on desktop or mobile.

An AI Accelerator is a deep learning or neural processor created specifically for inference and to improve the performance of an AI task. While Graphics Processing Units (GPUs) are the most common type, other specialized accelerators include Tensor Processing Units (TPUs), Data Processing Units (DPUs), Field-Programmable Gate Arrays (FPGAs), and Application-Specific Integrated Circuits (ASICs).

With so many acronyms to remember (and even more accelerator types left unnamed), we will focus on GPUs because their highly parallel architecture makes them incredibly versatile for a wide range of AI workloads.

GPUs are an in-demand commodity throughout the IT industry. Manufacturers like NVIDIA and AMD are powering the world's insatiable appetite for artificial intelligence and machine learning applications.

An AI GPU accelerator is responsible for making hundreds of thousands of calculations in parallel, and it's used in every facet of AI, large language models (LLMs), data analytics, and high-performance computing.

Such widespread adoption not only highlights their critical role in advancing modern technology but also explains why GPU demand continues to outpace supply. This leads us to a crucial question: Can your cloud hosting provider truly deliver the AI GPU hosting you need? Let's dive into what that really means with 5 things you need to know.

This might sound like common sense, but it’s important to understand the GPU accelerator hardware available from your hosting provider. GPUs are not created equal; they vary massively in specification and capability.

It's important to know what VRAM does, what tensor cores are, and what an NVLink interconnect does; otherwise, it's very easy to overspec and overpay for GPU resources if you don't understand exactly what's needed.

Understand your workload: Do you want to train your own AI model, use private LLMs, or perhaps need a chatbot application? Different AI tasks require different GPU specifications.

Understand data size and IO: AI models are typically trained on huge datasets, so you need a GPU that can process data at a good rate, and you need underlying storage, ideally NVMe SSDs that can keep up to prevent bottlenecks.

Consider future scalability: Ask yourself: Will your AI project grow? You need a hosting provider that can grow with you because you may need a bigger server (more memory, faster CPU) in the near future.

Get developer feedback when choosing a framework: Does the hosting environment support your preferred framework tools out of the box? Ask your devs what they want to use; popular AI frameworks include TensorFlow, PyTorch, and JAX.

GPUs are very important for AI workloads, but it's also important to consider the underlying hardware and ensure that it's fit for purpose. Network architecture and interconnects are critical for maximizing the performance of AI accelerators when hosted in the cloud.

Don't forget the importance of CPUs: CPUs are still critical for AI as they control the throughput of data to all aspects of the cloud platform. You need a provider that uses the latest CPU architectures, such as Intel Xeon or AMD EPYC, and examines the number and the speed of the CPU cores.

Go beyond high-speed networking: Fiber-optic connected networking is essential for AI platforms to function with low latency. There are 3 types of networking commonly deployed:

InfiniBand provides very low-latency and high-bandwidth communication between nodes (servers) containing GPUs. This is ideal for large-scale distributed AI clusters.

NVLink is NVIDIA's high-speed interconnect for direct GPU-to-GPU communication within a single server. It's needed for multi-GPU setups and is great for preventing bottlenecks.

High-Bandwidth Ethernet (e.g., 100GbE+) offers affordable performance for distributed AI and high-performance storage.

Latency: The ultimate goal is to choose the best hardware that will achieve the lowest latency. This is crucial because rapid GPU IO prevents bottlenecks and improves efficiency.

One major benefit of GPU hosting is the fact that it's easy to integrate with existing services from a provider. Pick managed services that work for you. Popular integrations include hooking into cloud storage layers, picking managed security services, and backups.

If you are a business, server management options are a great way to ensure optimal performance and uptime, letting you focus on developing your AI application whilst the provider manages the underlying infrastructure, load balancing, MFA, Antivirus, Intrusion Prevention, and DDoS Protection behind the scenes.

It's essential to keep on top of your operational expenditure, especially when using GPU accelerators. Costs can spiral if you make inefficient deployment decisions, overspecify your server requirements, or leave resources running idle around the clock. Costs vary significantly, so shop around and pick a provider that offers the hardware you need for a cost that is sustainable.

Cloud GPU hosting is the way forward (unless you can afford about $40,000 for a decent-spec GPU), do not forget about all the cooling and power requirements too. Remember to optimize your instance sizing, monitor and turn off idle resources, and take advantage of multi-instance GPU capabilities, where providers essentially slice up a GPU into smaller and very affordable partitions.

These factors underline a provider's ability to deliver GPU hosting that meets the needs of modern business. You may run into blockers or issues that could prevent you from releasing on schedule. Having 24x7x365 support skilled in AI/ML available for when things go wrong is vital to business continuity.

Look for strong uptime guarantees and providers that back up their claims with service credits if the unexpected happens. They should also demonstrate proven redundancy capabilities, disaster recovery, and a proactive approach to monitoring to safeguard your expensive GPU operations.

Beyond that, ensure your chosen provider meets all necessary compliance standards for your industry, whether it's GDPR, HIPAA, or SOC 2. Understand where your data will reside and confirm the provider has strong security controls like encryption and proper access management in place. Finally, always clarify the shared responsibility model so you know exactly what security aspects the provider handles versus what falls to you.

Choosing the right cloud GPU hosting means looking beyond just raw power. It's about picking a provider that meets your specific requirements, delivers strong, flexible server infrastructure, and offers comprehensive tools for integration.

By optimizing costs and prioritizing critical areas like expert support, reliability, and adherence to compliance standards, you ensure your operations run efficiently and without unexpected hitches.

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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

• Attackers can build bigger campaigns faster with generative AI
• They're also attacking enterprise agentic AI tools
• Humans are still a major weak point

New research from CrowdStrike confirms that hackers are exploiting AI to help them deliver more aggressive attacks in less time, with the tech also democratizing lesser-skilled hackers to more advanced code.

However, besides this, they're also exploiting the same AI systems that are being used by enterprises – according to CrowdStrike, hackers are targeting the tools used to build AI agents, allowing them to gain access, steal credentials, and deploy malware.

CrowdStrike is most worried about agentic AI systems, suggesting that they've now become a "core part of the enterprise attack surface."

The security company says it observed "multiple" hackers exploiting vulnerabilities in the tools used to build AI agents, which marks a major shift from patterns of old. Until now, humans have almost always been the primary entry point into a company, but now, CrowdStrike is worried that "autonomous workflows and non-human identities [are] the next frontier of adversary exploitation."

"We’re seeing threat actors use GenAI to scale social engineering, accelerate operations, and lower the barrier to entry for hands-on-keyboard intrusions," Head of Counter Adversary Operations Adam Meyers explained.

Funklocker and SparkCat are two examples of GenAI-built malware in the real world, while DPRK-nexus Famous Chollima has also been observed using generative AI to automate its insider attack program across all phases. Scattered Spider, a group believed to consist of UK and US nationals, even managed to deploy ransomware within 24 hours of accessing systems.

"Adversaries are treating these agents like infrastructure, attacking them the same way they target SaaS platforms, cloud consoles, and privileged accounts," Meyers added.

Still, even though technologies like AI are playing an increasing role in speeding up attacks, CrowdStrike found that four in five (81%) interactive intrusions were malware-free – relying on human hands on keyboards to stay undetected.

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