Severance creator Dan Erickson says he already knows how the hit Apple TV Plus series will end.
Speaking to TechRadar ahead of Severance season 2's launch, Erickson also confirmed that he "had a sense" of what the highly-rated show's final scene will be. However, while Erickson also admitted that he'd talked to director/fellow producer Ben Stiller and Apple executives about what would be the "ideal" number of seasons needed to tell Severance's story, he wouldn't be drawn on how many it would need.
Erickson discussed the mystery thriller's future with me in the wake of Stiller's own comments on the matter. In November 2024, Stiller told Collider that work on a third season was already in its early stages – remarks that all but confirm that another installment is on the way, even if Apple hasn't officially announced it yet.
Armed with that information, I asked Erickson if Severance season 3 might be the show's final entry. And, if he couldn't say that, whether he knew how many seasons it would take to wrap up its story and/or if he'd already planned the Apple TV Original's final scene.
"Yeah," he replied. "I have a sense of what the final scene will be and, in terms of a number of seasons, kind of where I see it all landing on a character level.
I won't say how many seasons we're thinking we'll last for
Dan Erickson, Severance creator"We've certainly talked about what we see as the ideal run of the show, Erickson continued. "But, from the beginning, we also wanted to be flexible enough that, if something came along that surprised us [narratively], and we fell in love with a certain storytelling element or a character, we'd want to spend more time with these things or these people. So, we wanted to create a flexible plan that we could turn to if we had any ideas [of where we could take these things].
"I won't say how many seasons we're thinking we'll last for," he added, "But we have that idea in mind, and we're also down to roll with the punches a little bit."
We don't have much longer to wait for one of the best Apple TV Plus shows' long-awaited second seasons to drop. Severance's sophomore outing will make its worldwide debut on one of the world's best streaming services on Friday, January 17. Before it premieres, read my Severance season 2 review to get the spoiler-light lowdown on its first four episodes – and check back in with me in the run-up to release for more exclusive coverage from my chats with Erickson and the show's cast.
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I’m a big fan of Xreal’s AR smart glasses – that’s why they feature on TechRadar’s picks of the best smart glasses overall – thanks to their ability to give you a wearable home cinema experience using just the specs and a compatible USB-C device. And now that experience is about to get even better thanks to two new innovations the company has showcased at CES 2025.
The first is new AR glasses in the form of the Xreal One Pro. A follow-up to the Xreal One, these smart glasses pack a 57-degree field-of-view, 700 nits of brightness, Bose sound, adjustable interpupillary distance, a vibrant Full-HD picture, and Xreal’s own X1 spatial computing chip. All in a package that weighs just 87g
They're impressive-looking glasses based on my hands-on experience with them so far – so impressive that we’ve awarded them a best of CES 2025 award – and we’re excited to test them out further ahead of their March launch. The Xreal One Pro are up for preorder now at $599 / £549.
Let there be sight I also tried Xreal's Air 2 Ultra glasses. (Image credit: Future)Even more impressive than the glasses themselves, however, is the new 12MP camera module that Xreal is launching for both the Xreal One and new One Pro: the Xreal Eye.
This optional attachment gives Xreal’s specs vision capabilities that right now allow for first-person photo and video capture. “Later this year” though, the camera will also offer image-based multimodal AI capabilities – which should be similar to the AI features we’ve seen in the popular Ray-Ban Meta smart glasses, including its 'Look and ask' feature.
The Xreal Eye is up for preorder at $99 / £99, and it looks like a solid update to Xreal’s existing specs, and offers a future-forward modular approach which is something I’ve been a fan of in XR for a while, as it gives users the freedom to construct the headset or glasses that best suits their needs and wants.
We’ll have to wait and see how the Eye perform in our full-review when they're released, as while I was able to wear specs with the camera module attached, I wasn’t able to snap a picture with them or see the AI in action during my hands-on time.
We’re covering all of the latest CES news from the show as it happens. Stick with us for the big stories on everything from 8K TVs and foldable displays to new phones, laptops, smart home gadgets, and the latest in AI.
And don’t forget to follow us on TikTok for the latest from the CES show floor!
You might also likeAs the adoption of AI tools continues to grow, so does the possibility of making major leaps in healthcare delivery. Artificial intelligence is already having significant clinical impacts, notably in cancer detection, and we are just beginning to tap its transformative potential.
The current landscape is marked by an overwhelming array of disconnected AI-enabled point solutions that operate within silos. In radiology, for instance, imaging systems are separated from the radiologist informatics layer, and each have their own separate workflows. Lack of integration limits the potential for data utilization and creates interoperability challenges, which lead to operational inefficiencies and added pressure on care teams.
Better integration is needed, not only to address workflow and data challenges, but also to drive adoption and harness new care delivery opportunities. To realize this vision requires both an end-to-end approach that embeds AI throughout the entire care journey and cloud-native solutions that integrate AI deep with the modality. The way to do this is through connected AI-powered informatics and smart technologies.
Integrated AI-powered informatics to connect care teamsAn integrated, cloud-native informatics layer across the care continuum is step one. In radiology, this unifying layer would connect the entire clinical and operational workflow – from patient registration through image acquisition to reporting, including collaboration with other physicians. End-to-end AI-powered informatics ensure ‘right place, right user, right time.
First, the ‘right place’ means deeply embedded within the technologies and settings where most needed. The ‘right users’ means customized workspaces for everyone in the workflow, with targeted views to support them in their individual roles and a single patient view – accessible to all in a connected and secure environment. Lastly, ‘at the right time’ means bringing AI in to help when needed – for example, with workflow automation or clinical assistance.
Smart technologies to enhance clinical and operational efficiencyEmbedding AI-powered informatics across workflows and with modalities like mammography or MRI systems gives both patients and care teams better experiences. This is the definition of smart technologies.
Smart technologies are ‘disruptive’ only in the sense that they make major care breakthroughs possible. Because smart technologies integrate seamlessly with existing workflows and healthcare IT systems, they are not disruptive for the people delivering care. Rather, they relieve pressure by enabling more streamlined and efficient workflows.
There are no extra clicks or added complexity for radiologists and care teams. Instead, integrated smart technologies would help create a more seamless clinical and operational environment, with AI assisting along the way to enable a better experience for everyone – those delivering care and those receiving it.
Better care experiences for patientsPatients can expect better care experiences with smart technologies. In radiology, by integrating the acquisition workflow – the imaging – with the interpretation workflow, patients would receive a faster readout and potentially a same-day diagnosis. Acquisition time is shortened because the informatics layer postprocesses the imaging in real time, rather than having to postprocess later.
Take breast cancer detection, for example. Integrating AI deeply with the mammography system can not only speed up and improve the process but create new possibilities. This represents a huge leap forward in cancer detection. Imagine getting a complete AI-powered readout from a breast exam in minutes. Patients would no longer have to deal with the stress of waiting for results. Those with no diagnostic findings could leave their appointment with peace of mind, knowing they are cancer-free. And for patients with screening findings, they could know right away and could begin their diagnosis and treatment journey.
Partnering to leverage smart technologiesBy embedding AI with medical devices and the equipment used in clinical settings, smart technologies remove the need for care providers to struggle with integration. This accelerates AI adoption and presents great potential to transform healthcare. However, it requires strategic collaboration between health technology companies and medical device manufacturers that focus on integrating AI deep into modalities. These collaborations can unlock the full potential of AI, transforming traditional medical technology into intelligent tools that enhance patient outcomes and improve care delivery. Moreover, as these partnerships evolve, they pave the way for a future where AI-driven innovations become the standard of care in the medical field.
The future of smart technologies is nowSmart technologies show great promise in bringing AI-powered clinical imaging support to breast cancer screening by embedding imaging informatics into advanced mammography systems. But what if we bring the AI-powered informatics layer closer in ultrasound? Or in x-ray, where smart technologies open the possibility of autonomous x-ray.
We already see the incredible potential of AI in real-world clinical settings. To make good on this promise will mean doubling down and partnering on AI-powered informatics and smart technologies to drive industry-wide adoption and, ultimately, revolutionize healthcare.
We've compiled a list of the best medical practice management software.
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
Stanford University and Google's DeepMind have released a new research paper showing how they taught an AI model to imitate how people behave. The Generative Agent Simulations of 1,000 People research created digital replicas of real people that can imitate their personalities with 85% accuracy after just a two-hour interview. A couple of hours of chat with an AI, and it’ll learn to simulate your reactions well enough to seem like it's thinking like you.
The slightly more than a thousand participants in the study started by reading the opening lines of The Great Gatsby to the AI. Apparently, this was the AI equivalent of stretching before a workout. After that, a 2D character asked them questions about their lives, beliefs, jobs, families, and more. With about two hours and an average of 6,491 words, the AI had all it needed to build a digital clone.
The clones seemed to know what they were doing, too. When asked to answer questions from personality tests or general surveys, the AI agents gave answers that matched their real-world counterparts about 85% of the time. Close enough to order for you at a restaurant, with maybe the wrong side dish.
The researchers put these AI clones to the test with economic games like the Prisoner’s Dilemma and the Dictator Game, where participants make choices about cooperation, trust, and sharing resources. While the AI only matched the real person's decisions around 60% of the time, that's still more than could be attributed to chance.
The AI might not fool your spouse or closest friend, but from just that short interview, it's pretty impressive. The AI could imitate decision-making patterns, opinions, and even personality quirks. Think about it: you spend years figuring out who you are, and this AI figures it out in an afternoon. It’s astounding and just a little bit creepy, like all good AI demonstrations.
Human behaviorStanford and DeepMind see this AI as a way to advance human behavior studies. It’s also a glimpse into how AI can simulate collective human behavior. Want to know how a community might react to a new health policy? Spin up some generative agents. Curious how customers might respond to a bold product redesign? Ask the AI clones. Essentially, it could be an eternal focus group.
Of course, if an AI can learn to mimic you this well after a single interview, what happens when it has access to years’ worth of data? Social media posts, online shopping habits, and even your Spotify playlists could all help teach the AI to be you or at least cater to your preferences, even the ones you didn't know you had.
There's plenty of potnetila for misuse by scammers and other malicious actors, but for now, this technology is in the hands of researchers, and the focus is on learning how to make it useful for fields like sociology, psychology, and economics. And it is somewhat inevitable that the technology would move in this direction. There's nothing more human than creating something that tries so hard to be just like us.
You might also likeOnce seen as energy-hungry liabilities, data centers are now emerging as critical assets in addressing urban energy challenges.
As the energy crisis deepens and cities grow, these facilities have the potential to transform from passive consumers to active contributors within their communities. The challenge of reusing waste heat from data centers has been examined for years. While low-grade heat is produced by these facilities, which are typically built in industrial estates, new solutions are being developed as locations move closer to residential areas.
Progress is steadily being made across the sector; waste heat is already being repurposed to warm public swimming pools and support district heating networks for housing developments, demonstrating how IT infrastructure can be woven into community energy strategies.
From digital waste to community resourceThe potential of data center heat reuse is already being realized through innovative projects across Europe. For instance, local swimming pools in England are benefiting from arrangements where waste heat is provided at no cost. Data center operators deliver IT services, while the pools receive free heating, significantly reducing operational costs—a crucial advantage during the ongoing energy crisis.
In the Nordics, excess heat is being channeled into industrial processes such as wood drying, a vital service for local industries. Other facilities are using waste heat to power greenhouses, fostering sustainable food production for nearby communities.
The main technical hurdle lies in the quality of heat produced by data centers. Low-grade heat must first be upgraded using heat pump systems to make it suitable for district heating networks. This challenge is being addressed through strategic design, such as in Manchester, where a new data center includes connection points for a future district heating network to support a nearby housing estate. These initiatives show how data centers are being moved closer to residential areas, enabling their waste heat to serve local community needs rather than being limited to industrial estates.
The investment case for integrationInvestment in data center heat reuse is increasingly driven by funds with green and sustainability mandates, requiring new approaches to reduce carbon intensity and enhance efficiency.
While integrating heat reuse systems raises upfront costs, support schemes like UK tax incentives for energy-efficient infrastructure can help offset these expenses. The business model is also evolving, with operators exploring diverse revenue streams. For instance, in the swimming pool example, free heat is supplied in exchange for revenue from IT services.
In district heating projects, roles are clearly defined between data center operators, heat network managers, and end users to ensure smooth operations. Future-proofing is becoming standard, with new developments incorporating infrastructure for potential heat network connections. However, long-term heat supply reliability remains a critical factor in planning.
Measuring environmental impact through heat reuseEnvironmental considerations are influencing design from the outset. Embodied carbon in construction materials, renewable energy integration, and total carbon reduction are being prioritized. For example, previously unused roof spaces are now equipped with PV panels, generating renewable energy for on-site operations.
The environmental benefits of data center heat reuse are becoming a key focus, building on the shift from isolated facilities to integrated community assets. Metrics like the Energy Reuse Factor and Energy Reuse Effectiveness now quantify how much of a facility’s energy consumption is repurposed for productive use.
These efforts are aligning with urban planning priorities, as local authorities assess data center proposals through the lens of community sustainability. Beyond energy efficiency, there is growing emphasis on how these facilities can support regeneration projects, contributing to local heating and power solutions while minimizing their overall environmental impact.
Creating successful partnershipsUltimately, the successful implementation of data center heat reuse projects hinges on stakeholder collaboration. Clear operational boundaries are essential: data center operators provide waste heat via heat exchangers, while other parties manage heat pumps, network infrastructure, and end-user services. This clear division of responsibilities ensures long-term reliability and efficiency.
Key factors include maintaining a consistent heat supply, integrating with existing infrastructure and engaging diverse stakeholders such as property developers and local businesses. However, with heat reuse still in its early stages, these ecosystems often need to be built from the ground up, requiring meticulous coordination and planning.
As the sector shifts its focus towards reducing carbon intensity, collaboration remains critical. While challenges remain in aligning interests and operations, the drive to create sustainable energy ecosystems is accelerating innovation, redefining the role of data centers in urban environments.
We've compiled a list of the best green web hosting services.
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