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Are you on the naughty or nice list for responsible AI adoption?

Over the past year, artificial intelligence (AI) has proved its worth as a long-term investment for businesses. It brings a range of perfectly wrapped presents to the table, making a significant impact on productivity, efficiency, and automation across business functions. With almost 40% of companies worldwide already using AI in some form, it’s undeniable that it has the capability to revolutionise business operations.

For example, Santa’s workshop would benefit from AI adoption in automation of its supply chain orders, faster and more accurate analysis of wish list data, and tracking of items that have made it into his sleigh.

To ensure he makes the most of AI’s benefits, Santa will have brought it on board with ethical guidelines and responsible practices in mind. But have you? Whether you’ve already adopted and want to make sure you’re using AI responsibly, or you’re yet to adopt and are looking to integrate ethical standards into your plan – time’s running out to get onto Santa’s nice list before Christmas.

Getting into the good books with responsible adoption

Adopting AI responsibly isn’t just about avoiding risks, it’s also a way of setting the stage for sustainable growth, efficiency, and innovation. If you jump on the AI bandwagon without building a solid foundation and outlining a clear strategy, a myriad of risks can await your business. Data breaches, ethical challenges, and financial losses are all risks businesses face if they ignore the importance of responsible adoption.

The most effective way of adopting AI to mitigate these risks is a responsible one, and it’s not as easy as plugging in your Christmas lights. Smart and strategic choices are the key to protecting business data and aligning AI initiatives with business goals.

Santa’s top tips for adopting responsibly

Like writing a Christmas shopping list, AI adoption can be too daunting to start for lots of businesses. With so much information out there, where are you meant to start?

The key is pushing fear to the side and making any type of start, even if it’s small. Those who start now and invest in AI will stay ahead of the curve. But like Rudolph and his crew, the AI gap is real, and businesses who don’t get on board now will be left behind. So, what do you need to consider to adopt AI responsibly?

  • Make sure your data shines like a bauble

Squeaky clean data is crucial to getting reliable insights from AI. Getting AI ready means prepping business operations for AI systems to easily slot in, so business data needs to be accurate, void of bias, and ready for action.

The same way you wouldn’t send Santa a disorganised wish list, you wouldn’t give AI messy data. Making sure data is up to date, without errors or duplicates, is critical to ensuring your AI delivers real value. This comes hand-in-hand with assessing your internal resources, and making sure your infrastructure can handle the scale and power of AI demands. More flexible Cloud platforms like AWS, Google Cloud, and Azure can help business scale AI cost-effectively.

  • Embrace elf-level organisation

Training is a key part of onboarding AI. Do you think Santa’s elves are expected to wrap presents without being trained first? Preparation for AI use is essential to allowing your employees to understand its benefits and using it effectively.

As it affects every team in the business, not just the IT department, the entire workforce needs to be prepped for AI adoption. Whilst this can seem like a costly task, investing in your people is how AI will create valuable results. Change management is a key component to preparing workforces for the changes you need to adopt AI. Fostering a culture of readiness and continuous compliance is key to ensuring it becomes an asset.

Knowing your business objectives and making sure your AI strategy aligns with and contributes to them is key to maximising its capabilities. Whether improving customer experiences, automating repetitive tasks, or personalising services is your business goal, use AI to drive that strategy.

Prioritising AI applications that solve real problems as well as boosting productivity is key to boosting business growth. Do you need help with recommending products to your customers to increase sales? This is a tangible problem AI can solve for you. Like following a gingerbread recipe, baking a strategic AI plan will produce the best goods.

Santa’s secret weapon – Responsible AI

Long-term success is the outcome of adopting AI through responsible practices and with ethical guidelines in mind. High-quality data aligned business goals, and a prepped workforce are the key to thriving rather than falling behind.

If Santa’s already on board, why aren’t you? After all, it’s how he gets his presents from the North Pole to under your tree.

Get onto the nice list this Christmas – start small, think big, and stay responsible.

Kyle Hill is chief technology officer at ANS, a digital transformation provider and Microsoft’s UK Services Partner of the Year 2024. Headquartered in Manchester, it offers public and private cloud, security, business applications, low code, and data services to thousands of customers, from enterprise to SMB and public sector organisations.

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Intel Battlemage GPUs could hit shelves on December 12 – but price rumors are worrying some PC gamers

  • Intel’s B580 and B570 GPUs are rumored for a December 12 launch
  • Team Blue will supposedly reveal them next week on December 3
  • Price rumors hint at $250 MSRP, but don’t get carried away with that idea

Intel’s next-gen Battlemage GPUs are going to be out next month, according to the latest rumor, which gives us a specific release date for the first time – December 12.

VideoCardz claims that the Arc B580 (which has been widely leaked) and B570 desktop graphics cards are in the pipeline, and will be on sale at the same time reviews will apparently be aired, on the mentioned December 12 date.

We will get an announcement from Intel before that, on December 3, according to information VideoCardz has obtained – take all this with a teaspoon of seasoning, naturally.

Intel will supposedly have its own reference boards (or limited edition Arc products, as it calls them) for these GPUs, which will emerge first, and custom graphics cards from third-party partners are going to launch the day after (December 13). This slightly staggered approach to launch is not uncommon these days in the graphics card world.

Meanwhile, fresh buzz on the pricing of the Arc B580 has also emerged, with the usual early retailer listings popping up – some of which are around the $250 mark from US outlets.

Acer Predator BiFrost Arc A770 GPU, pictured against a bright blue and green background.

(Image credit: Acer, Intel)

Analysis: Maintain a keen sense of skepticism

Regarding the price leaks, these are notoriously flaky – and probably placeholder prices – so that part of the latest rumor dump must be regarded with even more caution than the release date-related spillage.

Assuming that the $250 rumor is close to ballpark for a moment, though, it’s coming in on the heavy side compared to the A580, which kicked off with an MSRP of $180 – and this has caused some fretting among some PC gamers out there.

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However, what we have to remember is that the B580 is a beefier model, at least if the rumored spec is right, particularly as it’ll purportedly come with 12GB of VRAM (up from 8GB with its predecessor), and seemingly a much faster boost clock. So, in that light, a price increase doesn’t look quite so bad – but with the specs and pricing being just speculation at this point, we’ll reserve judgement for now.

What we really want from Intel, though, is for Battlemage to bring in some truly affordable (sub-$200) GPUs. Although of course they should be coming down the line (fingers crossed).

There’s certainly a whole pile of evidence suggesting there’ll be a December launch for next-gen Battlemage desktop graphics cards, mind you, and it’s looking more and more likely that we could witness a new generation of Arc GPUs as soon as next week.

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Justifying ECC upgrade: A Computer Weekly Downtime Upload podcast

“We all want to do this,” says Conor Riordan, chair of the UK and Ireland SAP User Group (UKISUG),” describing the transition to cloud-based ERP with SAP Rise. “We all want to get to the end point. We just can’t get there as fast as SAP wants us to go.”

Computer Weekly met up with Riordan during the user group’s annual Connect 2024 event, which took place in Birmingham at the start of December.

Upgrading and moving to the SAP cloud has been a hot topic for UKISUG for a number of years.

Mainstream support for SAP Enterprise Core Components (ECC), officially ends in 2027. Moving to SAP Rise is regarded by many as too big a step to take in one go and instead, as Riordan explains, users need financial support to make the transition from ECC to S4/Hana, which is a stepping stone towards Rise. But for Riordan, many SAP customers will not find this step easy. However, he says: “SAP responded and it has come up with a modernisation programme,  which was well received by customers and our members.” 

He is confident the newly appointed UK and Ireland managing director for SAP, Leila Romane, has recognised this challenge and the move to SAP Rise is more of a marathon than a sprint. “User group members aren’t convinced about SAP’s strategy, but we need to manage risk,” he says, adding: “We probably need to do the migrations in multiple steps rather than one big step.”

Riordan believes that for SAP customers the move to Rise is inevitable. “The majority of customers will go to Rise at some stage, whenever it’s right for them. That might be next year. That could be 20-30 years. Who knows. It’s about doing the upgrade when it’s right for the customers rather than doing it when it’s right for SAP.”

Although upgrading SAP will offer new functionality like a more modern user experience through Fiori, for Riordan the most important consideration is “Going live with no business impact”. For a lot of companies, success is when a project goes live without business disruption.

Discussing what can seem like a push from the IT industry to make sure businesses spend a lot of money upgrading, Riordan notes that there is a constant need to be more efficient in business and drive better earnings per share to get better margins. This, in turn, means the business is rated as a growth company by the financial markets. “People are under more pressure to drive more innovation and in order to deliver more innovation, you need a more modern platform,” he says.

As Riordan points out most companies that are still on ECC tend to be running manufacturing, procurement, sales and finance business processes. “You’re doing these in the same way you have done over the last 20 years,” he says. “But now in this new digital world, you’ve got access to an infinite amount of data that can help drive better decision-making. If you want to innovate and have smarter ways of running your business, you need to be on a better platform.”

An example of this is forecasting, as Riordan explains. “In the past you’d have planners that would try and figure out a forecast and put the forecast into SAP. Now you can get artificial intelligence (AI) to do that and figure out what your demand plans are and it can probably do it better than the planners because an AI forecast can bring in many different sources of information.”

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Desperate to see Nvidia’s RTX 5090? A graphics card maker rep just accidentally revealed that next-gen flagship GPU will be unveiled at CES 2025

  • A rep from Inno3D Brazil let slip info about the next-gen flagship
  • On a YouTube livestream they initially said it’d be available in a few weeks
  • They then backtracked and said the reveal is set for CES 2025

Nvidia’s RTX 5090 is widely expected to be revealed at CES 2025, and here’s another leak to add to the growing pile of speculation suggesting that this is indeed the case for the next-gen flagship GPU.

VideoCardz spotted that a representative from the Brazilian arm of Inno3D, a graphics card maker, accidentally let this nugget of info slip in a livestreamed interview on YouTube with Brazil-based retailer Pichau. (The video has just been taken down, we should note – it was live when we started writing this story, but is now marked as unavailable).

The Inno3D rep was responding to questions from viewers about the next-gen Blackwell GPUs, and there were mentions of the RTX 5090, whereupon the representative said that the graphics card would be ‘available’ in just three weeks.

You can imagine the reaction to that from viewers, which led to the representative backpedaling and saying that the RTX 5090 will “only be announced at CES 2025 in January.”

A mockup of the Gigabyte RTX 4090 Windforce graphics card

(Image credit: Gigabyte)

Analysis: CES 2025 looks a pretty sure bet now – as does a price hike

As VideoCardz theorizes, what’s probably happened here (grab your saltshaker now) is that the rep was referring to Inno3D receiving its first RTX 5090 cards in a few weeks – so it’s probably prelaunch samples that’ll be ‘available’ to the board maker (not the public, of course).

However, this does indicate that Nvidia is readying everything for the big launch early next year, and that as many previous rumors have now insisted, the RTX 5090 is set to be revealed at CES 2025. (To be fair, there was some buzz about a late 2024 launch in recent times, but we think that idea has pretty much been sidelined again).

When the RTX 5090 does turn up, if the rumors are right, it’ll be very powerful – a big step on from the RTX 4090 – but also very power-hungry. And perhaps most worryingly, very expensive too, possibly to the point that Nvidia is pitching it as a GPU targeted at professionals, rather than PC gamers, to justify the price. Although GeForce is a gaming brand, so as we’ve discussed in the past, that doesn’t really make a lot of sense.

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Whatever the case, the RTX 5090 is likely to see a price hike of some variety, the rumor mill is pretty certain about that – and possibly the RTX 5080 as well, the other Blackwell GPU supposedly set to be sprung on the world at CES 2025.

If you want an affordable high-end card – and affordable is a heavily relative term these days at the top of the graphics card spectrum – your soundest bet might be to check out some of the best GPU deals for Black Friday currently in play, with some tempting offers to be had (which is true at the mid-range, too).

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Intel confirms Arc desktop GPU launch on December 3, while Battlemage B570 leak hints that it could be a dream budget graphics card

  • Intel has announced an Arc launch event on December 3
  • Teaser video clearly shows a desktop GPU which must be Battlemage
  • B570 GPU spec leak suggests what to expect from the sibling of the B580

Intel has officially confirmed that there’s a big Arc GPU announcement tomorrow, on December 3, which surely must be Battlemage, as rumors have already suggested – and we’ve caught some leaked specs for the purported Arc B570 graphics card, too.

First off, let’s consider that revelation from Intel which arrived on X, with Team Blue noting that it has some “big graphics news” while providing a video giving us more clues as to what this is.

In the video clip, Intel doesn’t directly mention Battlemage, but rather this is a teaser which tells us that an Intel Arc-related announcement is coming on December 3. Given that we see a desktop graphics card from various angles in the video, clearly the revelation is for a desktop product – which can only be Battlemage.

There’s no way a new Alchemist board could be in the works, and anyway, as mentioned, this lines up with the many rumors that a Battlemage unveiling is coming on December 3. Indeed, given the weight of that speculation, perhaps Intel felt at this point it might as well (almost) confirm what’s happening this week.

The rumor mill reckons that we’ll see new Battlemage B580 and B570 graphics cards, and we’ve seen the leaked spec for the B580 already. The B570 remained a mystery, spec-wise, up until now, but as ever, treat this fresh leak with plenty of skepticism.

The leak comes via a tip from a reader of VideoCardz (which also spotted the Intel tweet above) and if correct, the B570 will run with 18 Xe2 cores and 10GB of VRAM (GDDR6) along with a 160-bit memory bus. The boost clock will hit 2.6GHz.

That’s according to a leaked product brief for ASRock’s Arc B570 Challenger OC which looks authentic enough, but as mentioned, season liberally here.

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Intel Arc A7 graphics card

(Image credit: Intel)

Analysis: B500 series spec shootout – with caveats

So, how does that B570 spec compare to the B580, bearing all the usual caveats in mind about both of these being rumored specifications at this point.

In theory, the B580 is going to run with 20 Xe2 cores, so the B570 will drop a pair of cores, and the B580 supposedly has 12GB of VRAM, so the B570 will drop 2GB. Sticking with that theme, the B570 will also be 200MHz slower for its boost clock, and it will have a lesser amount of memory bandwidth to the tune of a near 17% drop.

That will, of course, make for a somewhat less powerful GPU, but the lower-tier B500 series model shouldn’t be too far off the performance of the B580.

What we’re hoping the B570 will provide is a considerably more affordable alternative, if the price rumors about the B580 are correct – namely that it could arrive at around $250 in the US (and proportionate to that elsewhere, of course). If the B570 can sneak under $200, though, with 10GB of VRAM – when Nvidia still insists on 8GB with rival models in this bracket – Intel could have a budget winner on its hands.

And more importantly, PC gamers could have a budget GPU winner on their hands, too – but there’s some road to cover yet, in terms of the accuracy of these leaks, and that big price tag reveal.

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AMD RX 8800 XT could match RTX 4080’s performance – and easily outgun Nvidia’s GPU for ray tracing

  • RX 8800 XT is rumored to equal RTX 4080 for non-ray tracing performance
  • The RDNA 4 graphics card could match the RTX 4080 Super for ray tracing
  • The GPU is about to enter mass production, hinting at an early 2025 launch

AMD’s rumored Radeon RX 8800 XT could pack a real punch – especially for ray tracing – if a fresh leak about the next-gen GPU turns out to be true.

In theory, this will be the top-tier RDNA 4 graphics card – although it’ll be a mid-range GPU, as AMD isn’t doing the high-end this time around, going by the rumor mill – and the new info on performance and a possible release date comes from Zhangzhonghao, a leaker over at the Chiphell forums (in China).

Add plenty of seasoning, but the claim (as highlighted by Wccftech) is that the RX 8800 XT is a huge improvement in ray tracing performance, and a good step up for rasterization performance (no ray tracing) too.

Zhangzhonghao believes that rasterization performance will equal Nvidia’s RTX 4080 GPU, and that the 8800 XT will be more in the ballpark of the RTX 4080 Super when it comes to ray tracing.

The leaker also claims that the RX 8800 XT is 45% faster in ray tracing compared to the current flagship, the RX 7900 XTX, with the Resident Evil 4 Remake. And that in other popular games, the 8800 XT’s generational ray tracing boost is ‘epic’ albeit partly because the performance levels seen with RDNA 3 were pretty shoddy.

Another point to note is that power consumption for the 8800 XT should be 25% less than the 7900 XTX, although we aren’t provided with any specific metric here, just a vague assertion.

Regarding the release date, we’re told that the RX 8800 XT is about to start mass production in the middle of December. In theory, then, it could emerge late in January 2025, or perhaps February, which fits with current rumors of a Q1 launch for RDNA 4 graphics cards.

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An AMD Radeon RX 7700 XT on a table

(Image credit: Future / John Loeffler)

Analysis: Reasons to be hopeful

Interestingly, most of the recent buzz is about the RX 8800 XT, and we’re not hearing anything much on the 8700 XT which would, in theory, be the likely partner GPU (based on guesswork and past rumors).

Considering that the unveiling of AMD’s RDNA 4 desktop GPUs is apparently planned for CES 2025, in just over a month, we’d expect more spillage about a sibling GPU to come through soon – unless Team Red is kicking off with a solo launch here before other RDNA 4 cards arrive further down the line, but we’d be very surprised if that was the case.

With the performance leaks, previous speculation has suggested that the top RDNA 4 GPU (in theory this 8800 XT) could be a bit faster than the 7900 XT, and equating the 8800 XT with the RTX 4080 here indicates that is indeed the case (though other rumors have suggested it’ll be level with the 7900 XT, so a touch slower than the 4080).

That’s for rasterization, but the leap with ray tracing looks to be a huge one – and that makes sense in terms of AMD wanting to fix that weakness with its next-gen desktop graphics cards. Fingers crossed on that front, as often the arguments in favor of Nvidia being the superior choice revolve around ray tracing (and DLSS too).

On the topic of power usage, with the current 7900 XTX flagship having a TDP of 355W, based on the above info, we could be looking at 265W or so for the 8800 XT, which would put it in much the same bracket as the 7800 XT. That suggests AMD is concentrating on driving performance with RDNA 4, rather than efficiency (but not performance at the cost of efficiency, crucially).

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Podcast: Storage and AI training, inference, and agentic AI

In this podcast, we look at storage and artificial intelligence (AI) with Jason Hardy, chief technology officer for AI with Hitachi Vantara.

He talks about the performance demands on storage that AI processing brings, but also highlights the extreme context switching it can result in as enterprises are forced to pivot between training and inferencing workloads in AI.

Hardy also talks about a future that potentially includes agentic AI – AI that designs its own workflow and takes decisions for itself – that will likely result in an even greater increase in workload context switching.

Antony Adshead: What demands do AI workloads place on data storage?

Jason Hardy: It’s a two-dimensional problem. Obviously, there is that AI needs speed, speed, speed, speed and more speed. Having that level of processing, especially when talking about building LLMs and doing foundational model training, it [AI] needs extremely high performance capabilities.

That is still the case and will always be the case, especially as we start doing a lot of this stuff in volume, as we start to trend into inferencing, and RAG, and all of these other paradigms that are starting to be introduced to it. But, the other demand that I think is – I don’t want to say overlooked, but is under-emphasised – the data management side of it.

For example, how do I know what data I need to bring and introduce into my AI outcome without understanding what data I actually have? And one could say, that’s what the data lake is for, and really, the data lake’s just a big dumping ground in a lot of cases.

So, yes, we need extremely high performance, but also we need to know what data we have. I need to know what data is applicable for the use case I’m starting to target, and then how I can appropriately use it, even from a compliance requirement, or a regulatory requirement, or anything like that from those themes.

It’s really this two-headed dragon, almost, of needing to be extremely performant, but also to know exactly what data I have out there, and then having proper data management practices and tools and the like all wrapped around that.

And a lot of that burden, especially as we look at the unstructured data side, is very critical and embedded into some of these technologies like object storage, where you have these metadata functions and things like that, where it gives you a little bit more of that descriptive layer.

But when it comes to traditional NAS, that’s a lot more of a challenge, but also a lot more of where the data’s coming from. So, it’s, again, this double-sided thing of, “I need to be extremely fast, but I also need to have proper data management tools wrapped around it.”

Features for AI use cases

That leads me nicely to my next question, which is, what features do enterprise data storage arrays need for AI use cases?

Hardy: You’re absolutely right. One is leading into the other, where, just like we said, we need to be extremely performant, but what we also need to be is performant at scale.

If you look at it from, for example … if we talk about model training, model training was always about, “I need a massive amount of volume and a huge amount of throughput so I can just crunch and learn from this data and go from there.”

Now what we’re seeing is [that] we’re starting to operationalise and bring a level of enterprise-ness into these AI outcomes that requires a lot more of the compliance side of it and the data visibility side of it, while also being very performant.

But the performance side is also changing a bit, too. It’s saying, yes, I need high throughput and I need to be able to constantly improve on or fine-tune these models … But then it’s also [that] I now have an indescribable workload that my end users or my applications or my business processes are starting to integrate into and creating this inferencing-level workload.

And the inferencing-level workload is a little bit more unpredictable, especially as we start to step into context switching. Like, “Hey, I always need to be fine-tuning and improving on my models by injecting the latest data, but I also need to introduce retrieval augmentation into this, and so I now have the RAG workload associated with it.”

So, I need to be able to do this high-throughput, high-IOPS context switching back and forth, and be able to support this at enterprise scale.

But also, as new data is introduced into the ecosystem – generated through applications and normal business processes – I need to understand, not necessarily in real time, but almost in real time, what new data is made available so I can incorporate that.

[That’s] as long as it’s the right data and it has the right wrapper and controls and everything around it. Depending again on the data type, to allow for me to embed or improve on my RAG processes or whatever, but [also] how I can incorporate a lot of that data into it.

And then at the same time, too, is the source systems that we’re pulling this information from. Whether it’s an OLTP environment like an SQL or some sort of structured environment, or if it’s an unstructured environment, those source systems also need to be equipped to be able to support this additional workload as well.

I need to have this data awareness, but I need to have performance even outside of just what’s generally made available to the GPU directly from the high performance file system that’s supporting directly against the GPU workload. So, one is really the other, and it’s not a mystery, this major epiphany or anything. These are common data practices that we at Vantara have always been practicing and preaching for a long time, [that] data has value.

You need to understand that data is [using] proper indexing, proper tagging – again, all of those data processes – and proper data hygiene. But also now, how do you do that at scale and do that very performantly?

Training and inference needs

How do the needs of training and inference in AI differ when it comes to storage?

Hardy: That’s a great question. And like I said, we’ve been focused so heavily on – “we” being the market – I’ve been so focused on how to build models and how to integrate in and create these foundational models that can start to really revolutionise how we do business. That was all well and good; massive amounts of volume. Hitachi ourselves are creating these for a lot of the markets that we work inside of from the big Hitachi perspective.

But now what’s happening is we’re shifting from – and we’re going to start to see this trend in 2025 and 2026 … just [being] exclusively about building models into how we integrate in and we do inferencing at scale.

Inferencing at scale, like I said, is very random because it’s driven by end users or applications or processes, not in a predictable fashion like, “Hey, I’m going to start a training process, and I’m going to evaluate it and do another training process where it’s very regimented and scheduled in a way.”

This is kind of at the whim of how the business operates and almost at the whim of, “I have a question that I want to ask the system” … and then it now spins up all these resources and processes to be able to support that workload.

So, this becomes a lot more random. Additionally, it’s not just one use case. We’re going to see many use cases where the infrastructure needs to support this all simultaneously.

It’s loading the proper model up, it’s tokenising, it’s then being able to get the output from what’s being interfaced into, and then being able to portray that back to the customer or the consumer, and then the back and forth nature of that. So, from our perspective, what you’re going to see here is inferencing is going to drive a huge level of random workload that is also going to be more impactful to the source data sides as well, not just the model.

So, again, like I mentioned earlier, retrieval augmentation, agentic AI, things like that.

These are spinning up all sorts of different levels of consumption against the storage platform that is specifically being driven by inferencing.

Agentic AI, this new trend that’s starting to appear, is going to make this more of an exponential problem as well, because now, instead of traditionally, if I’m going to interface with a system, I ask it a question, a model gets loaded, it does its tokenisation, I get the result back, etc, etc. That whole process.

Well, now what’s happening is that same level of communication of working with the system is turning into not just one model, but many different models, many different queries or the same queries being done against many different models to try to get to the best outcome or the best answer for that specific question.

Now what’s happening is this is spinning up that exponential level of more workload. And then, once that’s done, you need to spin that down and shift back over to doing your fine-tuning or your training or whatever other workload, because you don’t just have an idle set of resources there that are just going to wait. It’s going to be constantly used for both sides now, the inferencing and the training workloads.

This context switching is going to put a big burden on the storage platform to be able to support really high-speed checkpointing so that I can stop my tuning or stop my model training and then shift into using those resources to fulfil the end user or the process demand as quickly as possible, because that is a real-time interface.

Then that gets spun down because the inferencing is done, and then I spin back up and I continue with where I left off on the training and tuning side. So, you’re going to see now this really weird, random level of workload that both of these types of demands are going to place onto the storage systems.

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What do the Home Secretary’s policing reforms mean for the future of the Police Digital Service?

The Department for Science, Innovation and Technology (DSIT) has become a landing zone for Whitehall’s various digital functions since the new government came to power in July 2024.

Responsibility for running the Government Digital Service (GDS) and the Central Digital and Data Office (CDDO) has transferred from the Cabinet Office to DSIT, but it seems the government’s digital reshuffle might not be over yet.

On 19 November 2024, home secretary Yvette Cooper released a statement about the government’s plans to take a more “active leadership role” to restore the public’s waning confidence in UK policing.

“Confidence in policing has fallen in recent years,” she said. “Visible neighbourhood policing has been decimated. At the same time, crime has become more complex, and policing lacks the systems and technology to respond. Police, and the public they serve, need a system that is fit for purpose and fit for the future.”

The policing sector needs to be reformed, she continued, to ensure it can operate effectively and efficiently – and so that local forces can improve the level of service they provide to the public.

The statement outlines the various actions the Home Office will take to achieve its goals, including the creation of a National Centre of Policing (NCoP) that will have IT in its purview.

“We are determined to work with policing to consult on the creation of a new National Centre of Policing to bring together crucial support services, such as IT and forensics, that local police forces can draw upon, to raise standards and improve efficiency,” it said.

The Home Office’s involvement in UK police IT

What is notable about this is that the Home Office already has a hand in directing the UK’s policing sector’s technology use, through its funding of the privately owned Police Digital Service (PDS).

According to the most recent set of accounts, filed with Companies House on 28 November 2024, the Home Office National Police Capabilities Unit provided PDS with a £32m grant during the financial year ending 31 March 2024.

Previous accounts from PDS have neglected to provide details of the exact size of the grants or funding the Home Office has provided the organisation with.

However, Computer Weekly understands the department defines the £32m grant as being a single-year funding stream, issued on the “basis of need”. As such, there are no guarantees PDS will receive a Home Office grant from one financial year to the next.

For context, during the financial period this grant was issued, PDS made a loss of just over £1m in 2024, having posted a profit of £2.4m in 2023. Its staffing costs also increased from £11.9m to £20.4m during the same 12-month period.

The organisation is tasked with the development and delivery of the National Policing Digital Strategy, which is focused on enabling forces through technology to tackle increasingly complex crimes and, in turn, improve public safety.

With the Home Secretary emphasising the need for more efficiency in policing, does it make sense for two organisations with similar-sounding responsibilities to exist when there is a risk that they could be duplicating efforts?

PDS reform

Owen Sayers, an independent security consultant and enterprise architect with over 20 years’ experience in delivering national policing systems, told Computer Weekly back in mid-July 2024 that he expected the new Labour government would seek to reform PDS when they came to power.

Several months on and it appears his prediction could be coming true, with Sayers now of the view that PDS, or at least its responsibilities, will most likely end up getting folded into NCoP. “I do not doubt the Home Office will seek to build on the work that PDS has done thus far, just as the new administration has lifted the entirety of the CDDO and GDS and placed them into DSIT to ‘continue their good work’ and ‘rely on their expertise’,” he said.

That said, PDS does “carry significant baggage”, he continued, which might make it difficult for the government to “base any new central service upon them”.

To this point, two individuals working for PDS were arrested and bailed in July 2024 on suspicion of bribery, fraud and misconduct in public office – and within two weeks of this news being made public, the organisation’s CEO – Ian Bell – resigned.

The organisation has also been heavily and repeatedly criticised in the past for championing the use of US-based hyperscale cloud services by the policing sector, despite there being a persistent misalignment between how these platforms operate and the policing sector’s own data protection laws.

“PDS, in particular, has overseen and promoted adoption of technologies that breach UK data laws, and that’s not a great CV,” said Sayers. “In addition, there remains serious questions as to whether a body packaged as a profit-making limited company, operating in the heart of government, is an acceptable model to build upon.”

Particularly one that is losing money and receiving multimillion-pound grants from the government. “Making a loss for a public body is nearly as bad as making a profit,” he added.

Invoice data

Invoice data from public sector market watcher Tussell shows that – despite reporting a loss of over £1m for the 12 months to 31 March 2024 – PDS brought in £29.6m of business.  

Computer Weekly contacted the Home Office for clarification on what the creation of NCoP means for the future of PDS, but the department did not directly answer the question.

Computer Weekly also contacted PDS to see if it had received any indication from the Home Office about what the creation of the NCoP means for its future, and received a statement in response from its interim CEO, Tony Eastaugh.

There is no detail in the statement about how PDS and the NCoP will be expected to coexist, but Eastaugh said his organisation “hugely welcomes” the prospect of the NCoP’s creation, describing it as a “once-in-a-generation opportunity” for the policing sector to “design, build and deliver a new construct” that will make communities safer.

“PDS exists solely to support our policing colleagues in that mission – and so we welcome the prospect of being asked to bring our skills, experience and expertise to the discussions on how digital, data and technology in law enforcement needs to look over the coming years,” he said.

“It’s genuinely an exciting opportunity for all of us to deliver tangible change – and PDS is fully committed to doing everything it can to help build that new body with colleagues from across the sector.”

The need for reform

On the same day Cooper’s statement about the need for policing reform went public, she gave a speech at the National Police Chiefs’ Council and Association of Police and Crime Commissioners annual conference, where she shared a few more details about the NCoP’s remit.

“As a starting point, I see this body [NCoP] taking on responsibility for existing shared services [and] national IT capabilities,” she said, having talked about “outdated technology holding policing back” earlier on in her speech.

As an example of this, she pointed to the 50-year-old Police National Computer (PNC). “It was cutting-edge when I was five,” said Cooper.

The government is already working with the sector to create a “collaboration and efficiencies” programme that will seek to cut the costs of IT contracts, among other things, in the interests of saving “hundreds of millions of pounds over the next few years” that can be reinvested in frontline policing, she continued.

“[We’re also] working with you on tackling the bureaucracy that drags policing down – including reforms on redaction, and use of new technology – to free up more time for officers to get back on the frontline,” said Cooper.

Expanding on this point, she said technology procurement is an area that every force wrestles with repeatedly, “with the same questions about new software, IT changes or records management – wasting time, pushing up costs and creating news systems that aren’t even interoperable”.

“Instead of technology driving great leaps forward in policing, too often it is holding policing back,” said Cooper.

Technological changes

Calum Baird is a digital forensics incident response consultant at managed security services provider Systal Technology Solutions, who previously served as a detective constable specialising in cyber investigations for Police Scotland. Speaking to Computer Weekly, he said there are myriad ways that forces are hampered in their ability to fight crime and protect the public because of IT limitations, but also because of how quickly changes to the technological landscape occur.

“Legislative change can take time, and often technology advances at a faster pace, [and] this means that police and legal professionals have to identify how potentially criminal acts fit into existing legislation,” said Baird.

“[Also] think about recent advancements, such as generative AI, cryptocurrency and cloud computing – many of which lack explicit mentions in existing legislation,” he said.

At the same time, forces are often on the back foot when it comes to tackling online forms of crime, because officers need a mix of both investigative and technical skillsets to do so effectively.

“These can be a challenge to develop individually, and even more challenging to develop continually,” said Baird. “Investigative skills take time to develop in law enforcement, and whilst they can be taught, much is learned through practical experience.”

“Cyber security technical skills [as an example] can be developed, but require considerable dedication and often funding to do so,” he said.

What the future holds

For the time being, it remains to be seen how PDS will fit in with the Home Office’s vision of what the future of policing should look like.

However, Secon Solutions’ Sayers said the Home Office would be wise to “turn back the clock” and seek inspiration from how IT was delivered across the policing and criminal justice sector during the latter stages of the last Labour government. “[Back then] the UK had services that were internationally considered to be at the leading edge – both in terms of their technology adoption and exemplars of good governance,” he said.

Sayers cited the Labour government’s early 2000s “Joined-Up Justice” Criminal Justice IT (CJIT) programme that sought to link up the IT systems used by the police and court system. The National Policing Improvement Agency (NPIA) was another example called out by Sayers.

The latter was a non-departmental public body created in 2007 that was set up to support police by providing expertise in IT and data-sharing, among other areas. It closed down during the 2012–2013 financial year.

“During NPIA and CJIT’s tenure, they introduced over 30 national systems, and a host of lesser-known, but still critical, public safety systems,” he said.  

“They worked hand-in-hand to deliver on the joined-up justice agenda, reflecting the reality that criminal justice has many participants, but that for the bulk of cases, the data journey begins in policing,” said Sayers. “This means if the integrity of the data or IT is compromised there, it will never regain good provenance, and the justice process suffers accordingly.

“Rebuilding police technology has to be recognised as foundational to rebuilding all justice IT, and requires organisations to be modelled more on NPIA and CJIT models than police-centric structures like PDS,” he added.

More specifically, Sayers said he would like to see the NCoP change the direction of travel for policing IT, which has seen the sector develop a growing reliance on the US-based cloud hyperscalers, despite their services being “wholly unsuitable” for police and justice use.

“Those technologies are familiar, popular and helped the UK to manage Covid, but the pandemic is behind us now, and we need to build technology platforms suitable for a more diverse operating future,” he said. “Tactical decisions hastily made to address times of urgent need are rarely the right fit for strategic use and growth.

“That is, however, exactly where we are today in policing – where systems born out of our need to react to Covid are being increasingly built upon to form, and constrain, our future thinking,” said Sayers. “We need to be brighter than that.”

We also need the policing sector to start adopting technology offerings that are “optimised for UK laws” because they are built by homegrown providers.

“This does not mean we revert to monolithic and non-interoperable systems … nor should we continue to invest in single-provider technology stacks that lock UK criminal justice into generic commercial services requiring us to compromise on the UK’s mandatory security and vetting requirements – or require UK laws to be changed for use,” said Sayers.

“Whatever the NCoP’s form, it should be tasked to include delivery of a future technology landscape that is based on open standards and federated services, and can provide services at a national scale independent of a reliance on a primary supplier,” he said.

“The next five years can see a renaissance of UK-bred justice technology innovation, but only if the government are brave enough to choose to do so.”

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How AI can help you attract, engage and retain the best talent in 2025

As we move into 2025, the landscape of human resources (HR) is heading for a significant transformation. Artificial intelligence (AI) is set to revolutionise workforce collaboration, efficiency, and talent management.

For HR leaders, harnessing the power of AI will be essential to attract, engage, and retain top talent in an increasingly competitive market.

Enhancing HR performance

AI is reshaping and revamping HR by automating routine and mundane tasks such as interview scheduling, data entry, and CV screenings. This automation allows HR teams to focus on strategic initiatives that add real value to employees, such as developing diverse cultures, offering tailored development programmes, and increasing engagement.

AI-powered analytics can identify workforce trends, predict employee turnover, and suggest to retain top talent. These insights enable HR leaders to make data-driven decisions to support a high-performance culture, ultimately improving employee engagement and organisational performance.

Just look at Unilever, which uses AI to streamline its recruitment process. By using AI-driven assessments and video interview analytics, Unilever has significantly reduced time-to-hire while enhancing the candidate experience. Additionally, AI can streamline performance management by providing continuous feedback and personalised development plans. This shift towards real-time performance management fosters a culture of continuous improvement, where the team receives timely feedback and support to achieve their goals, leading to higher engagement levels and better retention rates.

Talent attraction and retention

As the demand on sourcing talent with scarce skills continues in 2025, attracting top talent needs innovative strategies. AI can play a pivotal role in enhancing the candidate experience. Imagine AI-driven chatbots engaging with candidates in real-time, answering their questions and providing personalised information about the company and the role. This immediate engagement can significantly improve the candidate experience, making the organisation more attractive.

AI can also help create a more inclusive hiring processes by eliminating unconscious biases from recruitment. AI algorithms can analyse job descriptions to ensure they are free from biased language and assess candidates based on objective criteria. This is an incredibly important step to support organisations in attracting and growing a more diverse and inclusive workforce, which is crucial for driving innovation and business success.

Retaining your team is equally important as attracting it. AI can help HR leaders identify early signs of people’s disengagement or dissatisfaction. For instance, AI-powered sentiment analysis can monitor employee communications and flag any negative sentiments, allowing HR and managers to intervene proactively. By addressing issues before they escalate, organisations can improve the satisfaction, happiness and ultimately retention of the team.  

AI can also facilitate personalised employee development. By analysing skills, performance data, and career aspirations, AI can recommend tailored development programmes and career paths for each individual. This personalised approach to development can help people feel valued and supported.

Upskilling your team in the New Year

24% of all workers are worried that AI will soon make their job obsolete. HR leaders have a crucial role in addressing these concerns and ensuring their teams are ready for AI integration. Providing training and the right tools to integrate AI smoothly is essential. By fostering a culture of continuous improvement and responsible AI use, HR can drive greater efficiency and empower the entire workforce.

AI is more likely to enhance roles rather than replace them, and HR leaders should embrace AI ethically and transparently. This involves being clear about how AI is used, ensuring data privacy, and maintaining a human touch in all interactions. By doing so, HR can build trust and create a positive environment where AI is seen as a tool for empowerment rather than a threat.

2025 – the future of AI in HR

As we approach 2025 and beyond, the integration of AI in HR will continue to evolve. Future trends may include more sophisticated AI-driven talent management systems, enhanced predictive analytics for workforce planning, and even more personalised employee experiences powered by AI. HR leaders who stay ahead of these trends and continually innovate will be well-positioned to lead their organisations into the future.

Looking to the New Year, AI will play a pivotal role in enhancing HR functions, making them more efficient, strategic, and employee centric. By leveraging AI to attract, engage, and retain top talent, organisations can stay competitive in a rapidly evolving job market. HR leaders who embrace AI responsibly and proactively will be well-positioned to drive their organisations forward, creating workplaces that are both productive and fulfilling for their team.

Toria Walters is chief people officer at ANS, a digital transformation provider and Microsoft’s UK Services Partner of the Year 2024. Headquartered in Manchester, it offers public and private cloud, security, business applications, low code, and data services to thousands of customers, from enterprise to SMB and public sector organisations.

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New iPad Pro won’t be Apple’s first product with an M5 chip

Apple won’t follow the trend of introducing a brand new chip with its best new iPad models, as it did with the M4 iPad Pro. According to the latest reports, the M5 iPad Pro won’t arrive before late 2025 or even early 2026.

Top insider Ming-Chi Kuo wrote a blog post on Medium saying the M5 iPad Pro is expected to enter mass production in the second half of 2025. “The iPad Pro equipped with the M5 processor is expected to enter mass production in 2H25,” he wrote. “The company’s business momentum in 2H25 is anticipated to benefit significantly from Apple’s new product launches.”

While this might not mean much, Kuo is likely talking about the significant refreshes expected by this time of the year, such as the iPhone, Apple Watch, and possibly a new version of the Apple Vision Pro. That said, users shouldn’t be that worried about their M4 iPad Pro becoming an obsolete product in the near future.

If rumors are accurate, the iPad Pro with the M4 processor could be almost two years old before Apple introduces a new variant. Even when that happens, we don’t expect significant changes. Based on what we’ve heard so far, it seems that the iPad Pro will only get a specs bump with the M5 processor, and the next-generation chip won’t even be such a big deal.

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While the M4 greatly improves over the M3, Apple has apparently canceled the M5 with the newer 2nm process developed by TSMC due to cost concerns. According to The Elec, the M5 chip will adopt a new System On Integrated Chip technology, which enhances thermal management and reduces electrical leakage.

With that, we could see enhancements in performance and efficiency and a broader focus on Neural Engine tasks for AI and Apple Intelligence. While knowing that Apple has moved on to producing its newer processors, we still have several months with M4 products, including some new ones that need to be unveiled.

When will Apple start introducing new M5 products?

If the company follows the schedule analysts predict, the M5 family won’t be available before the end of next year. Here’s what we expect:

  • Late 2025: Apple should unveil at least new M5 MacBook Pro models with the M5 Pro and M5 Max options; the company could also update the Mac mini and iMac, although it’s unclear at this moment;
  • Late 2025/Early 2026: Apple introduces the M5 iPad Pro;
  • Early 2026/Mid 2026: Cupertino unveils new MacBook Air models with the M5 processor;
  • Mid 2026/Late 2026: Apple expands the M5 chips for the Mac Studio and potentially to Mac Pro, depending on the upgrades expected for this processor.

It’s important to note that bigger changes are expected to start appearing by 2026 or 2027, when Apple will unveil a new OLED display technology for the MacBook Pro, followed by an improved display on the iPad Pro. In the next couple of years, we could also see Apple unveiling its first foldable products as well.

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