Elon Musk’s claim that he was mistreated by his OpenAI co-founders failed after nine California jurors returned a unanimous verdict that his lawsuits had been filed too late.

Musk accused Sam Altman, Greg Brockman, OpenAI, and Microsoft of “stealing a charity” by creating a for-profit affiliate of the frontier AI lab. Jurors, however, found that any harms that Musk may have suffered came before the deadline for filing his claims under the law.

While the trial delved deeply into the melodramatic history of OpenAI and featured testimony from leading figures in Silicon Valley, it ultimately turned on fairly narrow questions of the law. The trial focused on whether and when Altman and the other defendants had made and broken promises to Musk, but his case failed to convince jurors that he had a valid claim.

In particular, OpenAI had advanced a statute of limitations defense, which sought to prove that any harms Musk sought to litigate had taken place before 2021. (The specific date varied by the charge: before August 5, 2021, for the first count; August 5, 2022, for the second count; and November 14, 2021, for the third count.) Ultimately, the jury found that argument persuasive, which made for a short deliberation period.

“There was a substantial amount of evidence to support the jury’s finding, which is why I was prepared to dismiss on the spot,” Judge Yvonne Gonzalez Rogers said after the verdict was delivered.

The end of the case means that one major threat to OpenAI — a possible restructuring — is now off the table ahead of its reported IPO.

“It did not take [the jury] two hours to conclude … that Mr. Musk’s lawsuit is nothing more than an after-the-fact contrivance that bears no relationship to reality,” OpenAI’s lead attorney, Bill Savitt, said after the verdict. “They kicked it exactly where it belongs — just to the side. This lawsuit is a hypocritical attempt to sabotage a competitor.”

Microsoft, which Musk sued for aiding and abetting OpenAI’s alleged breach of charitable trust, welcomed the verdict. A spokesperson for the company said it “remained committed to our work with OpenAI to advance and scale AI for people and organizations around the world.”

The verdict came in the middle of a hearing to determine the potential damages to Musk if the verdict had gone the other way. While that discussion is moot for now, the judge appeared unconvinced by the analogy Musk’s lawyers drew between his charitable contributions and investments in a for-profit startup.

“Your analysis seems to be devoid of connection to the underlying facts,” she told Dr. C. Paul Wazzan, the expert who came up with Musk’s estimate of OpenAI and Microsoft’s wrongful gains at his expense — some $78.8 billion to $135 billion.

In a tweet after the ruling, Musk appeared to take the procedural grounds of the dismissal as a moral victory. “There is no question to anyone following the case in detail that Altman & Brockman did in fact enrich themselves by stealing a charity. The only question is WHEN they did it!” Musk wrote. “I will be filing an appeal with the Ninth Circuit, because creating a precedent to loot charities is incredibly destructive to charitable giving in America.”

Reached for comment by TechCrunch, Musk’s lead counsel, Marc Toberoff, said, “One word: Appeal.”

Stress on organisations to patch vulnerabilities a ‘major concern’ for NCSC’s Joseph Stephens.

The European Commission and several EU member states, including Ireland, are in talks with Anthropic over Mythos, as countries worldwide scramble to protect their vulnerable critical infrastructure from cyber risks.

“We’ve had direct contact with them,” the National Cyber Security Centre (NCSC)’s director of resilience Joseph Stephens told SiliconRepublic.com, referring to Anthropic, whose European headquarters is based in Ireland.

“But we’re working through the European system because there’s more strength in having a coordinated approach.” Stephens was speaking to SiliconRepublic.com during the recent ZeroDayCon event in Dublin.

Mythos sent shockwaves through the industry following its limited launch to select big businesses more than a month ago. Anthropic’s move received much praise from experts, including from Stephens, who called on other frontier AI model providers to do the same.

Is control out of bounds?

Mythos’s development, Anthropic claims, was not intentional, but merely the result of a “downstream consequence of general improvements in code, reasoning and autonomy”.

And undoubtedly, states don’t wield much power when it comes to controlling technological advancements or managing how it is disseminated – at least initially.

The growing concern around AI-induced cybersecurity risks is by no means restricted to Mythos. Put together, these factors create a difficult environment for legislators as they attempt to catch up to new innovations in this space cropping up faster than ever before.

“We have to recognise what the Irish state can and cannot do,” Stephens said. “We can’t stop a company like Anthropic based in the US from releasing or not releasing a model.”

Mythos’s launch created such a ripple that the NCSC – for the first ever time – released a statement on a specific product release.

Meanwhile, nations worldwide, including the US, UK, Canada and Japan, were quick to invite Anthropic to discussions to potentially employ the model to bolster their critical infrastructure security.

However, governments and big businesses aside, start-ups and SMEs with limited resources to bolster their cybersecurity are particularly at risk.

“The major concern here right now is the stress that [Mythos] may place on organisations who are now going to have to patch all of their digital products and services,” Stephens said.

But ironic as it is, AI might come in handy for situations such as these.

Will the EU AI Act help?

Stephens called for a joint effort between states to come up with a common regulatory approach around such models.

“The AI Act allows us to ensure that products that come onto our marketplace are done in a secure and a safe way,” he said. “Europe has really pushed forward with the AI Act … [but] we can’t regulate our way out of it.”

The line between regulating and stifling innovation is one that the EU is arguably still in search of.

It is attempting to remedy some of this over-regulation by way of a simplified and consolidated set of rules. Earlier this month, the bloc adopted new provisional rules on the AI Act.

The AI Act applies to businesses that sell into the EU, or if the AI output is used in the EU. The landmark regulation attempts to balance managing the risks of this technology while letting the EU benefit from its potential.

According to law expert Dr TJ McIntyre, it is possible to regulate models such as Mythos with extraterritorial effect, but only if they are sold into the EU or if their outputs are sold into the region.

McIntyre is an associate professor in the Sutherland School of Law at University College Dublin.

“It’s not clear that the AI Act would apply if Mythos is geo-restricted for use outside the EU,” he explained.

However, the Act is “designed to address ‘offensive cyber capabilities, such as the ways in which vulnerability discovery, exploitation or operational use can be enabled’ as a type of systemic risk,” he said – so, “in theory”, the EU could take action under the AI Act.

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At an event in New York this week, Volvo’s upcoming EX60 midsize electric SUV finally made its North American debut, opening US orders for the 2027 model at a starting price of $59,795 ($58,400 plus the requisite $1,395 destination fee) with up to 400 miles of range, depending on trim. 

At first blush, those numbers look pretty good for an EV positioned at the premium end of its highly competitive class. Yet recent events have left the automaker in an unenviable underdog position for its most important new launch.

When Volvo pulled the wraps off the EX60 at the global debut earlier this year, I called it “the most important model in [the brand’s] growing family of electric vehicles.” The EX60 slots into the midsize premium SUV segment — the single largest automotive battleground in America, EV or otherwise — and follows in the footsteps of the combustion-powered XC60, which has long been the brand’s volume backbone. 

Volvo’s EV rollout has been rougher than the brand would like to admit: The EX30 was discontinued in March after market headwinds and shifting political conditions made its US viability untenable, and the flagship EX90’s inaugural year was plagued with issues. 

I noted in January: “This feels like a make-or-break moment for the brand’s EV ambitions.” That assessment hasn’t changed. What has changed is that we now have the numbers, and they’re promising.

Up to 400 miles of range

The EX60 rides on Volvo’s new SPA3 platform, a dedicated electric architecture that introduces cell-to-body integration, next-generation in-house e-motors, megacasting and an 800-volt electrical system. That last point matters most at the charging station: The EX60 P6 rear-drive variant can add up to 155 miles in 10 minutes at a peak rate of 320 kilowatts, going from 10% to 80% in just 16 minutes. The AWD P10 and the P12 push that peak charging rate to 370 kilowatts. 

With the longest legs of the bunch, the P12 promises up to 400 miles of range — enough to drive from New York to Montreal without touching a charger, according to Volvo. The base P6 manages 307 miles, while the P10 AWD cruises for 322 miles. (Keep in mind, however, that all range and charging figures are estimates pending final EPA certification.)

Crucially, the EX60 is the first Volvo to ship with a native North American Charging Standard port, meaning that Tesla’s Supercharger network — with over 29,000 stations in North America — is accessible without an adapter. EX60 owners will still need a dongle to charge at roughly 13,000 to 17,000 public Combined Charging System ports across the US, but this remains a meaningful real-world advantage as the industry and infrastructure shift to NACS over the next few years.

Competitively priced

At launch, US buyers will have their choice of two powertrain options (P6 and P10 AWD) and two trim levels (Plus and Ultra) that dictate how well-equipped their EX60 will be. The entry P6 Plus comes in at $59,795 comes with Volvo’s Pilot Assist safety suite and a 21-speaker Bose system as standard. 

The P6 Ultra ($66,395) steps up to add ventilated Nappa leather seats and upholstery, a 28-speaker Bowers & Wilkins audio setup, an electrochromic panoramic roof and heated second-row booster seats integrated into the seat backs. Similarly equipped, but with more power and range, the P10 AWD Plus and Ultra open at $62,145 and $68,745, respectively. (All prices include the compulsory $1,395 destination fee.)

Pricing hasn’t been announced for the 670-horsepower EX60 P12 AWD — the most powerful variant and the range-leader — which will be configurable at a later date.

The sticker price is competitive. The BMW iX3 starts at $62,850, Audi’s Q6 e-tron at $65,795 and the upcoming electric Mercedes-Benz GLC is expected to start in the same ballpark. Volvo undercuts the competition meaningfully and goes toe-to-toe on range and charging speed. Whether that’s enough to claw back momentum after a stumbling start for the brand’s EV program is the real question.

The EX60 can be configured now at volvocars.com. First deliveries are expected later this year.

Redis built its name as the caching layer that kept web applications from collapsing under load. The problem it is targeting now has the same structure but is harder to solve: production AI agents failing not because the models are wrong, but because the data underneath them is scattered, stale and structured for humans rather than machines. Retrieval pipelines built for single queries cannot absorb the volume agents generate.

The gap Redis is targeting is structural: agents make orders of magnitude more data requests than human users, but most retrieval layers were built for the human-scale problem. Redis Iris, launched Monday, is the company’s answer: a context and memory platform that sits between an agent and the data it needs to act. The platform combines real-time data ingestion, a semantic interface that auto-generates MCP tools from business data models, and an agent memory server built on Redis Flex, a rewritten storage engine that runs 99% of data on flash at a tenth of the cost of in-memory storage alone.

The announcement lands as enterprise RAG infrastructure is in active transition. VentureBeat’s Q1 2026 VB Pulse RAG Infrastructure Market Tracker found buyer intent to adopt hybrid retrieval tripling from 10.3% to 33.3% between January and March. Retrieval optimization surpassed evaluation as the top enterprise investment priority for the first time. Custom in-house retrieval stacks rose from 24.1% to 35.6% as enterprises outgrew off-the-shelf options. Redis is not the only infrastructure vendor reading those signals — several data platform providers have repositioned around agent context layers in recent weeks.

The scale mismatch is the structural argument behind the launch.

“Companies will have orders of magnitude more agents than human beings,” Rowan Trollope, CEO of Redis, told VentureBeat. “Orders of magnitude more agents than human beings means orders of magnitude more load on back end systems.”

From cache to context

Trollope traces the parallel back to the mobile era: When legacy backends built for branch tellers suddenly had to serve a million smartphone users, Redis became the caching layer that absorbed the load without a full rebuild.

What is different this time is that agents cannot write their own middleware. In the mobile era, a developer would sit with a database administrator, identify the queries an application needed and hard-code the caching logic into a middleware layer. Agents cannot do that. They need to find the right data at runtime, through interfaces built for them in advance, or they stall.

“This is like the analogy of the grocery store in the fridge,” he said. “If every time you have to go make your sandwich, you have to run to the grocery store to get the food, that’s not very efficient. You put a fridge in every house, you store a little bit of food there. And that’s kind of where we still tend to exist in the infrastructure stack.”

What Redis Iris includes

Iris ships five components that together cover data ingestion, semantic access, memory and caching.

Redis Data Integration. Now in general availability. RDI uses change data capture pipelines to sync data from relational databases, warehouses and document stores into Redis continuously, with connectors for Oracle, Snowflake, Databricks and Postgres.

Context Retriever. Now in preview. Developers define a semantic model of business data using pydantic models and Redis auto-generates MCP tools agents use to query it directly, with row-level access controls enforced server-side. Trollope describes the shift from classic RAG as a directional inversion. “It’s just a flip to let the agent pull the data instead of presupposing and stuffing it into the pipeline,” he said.

Agent Memory. Now in preview. Stores short and long-term state across sessions so agents carry context without re-deriving it on each turn.

Redis Flex. A rewritten storage engine that runs 99% of data on SSDs and 1% in RAM, delivering petabyte-scale retrieval at sub-millisecond latencies.

Redis Search and LangCache. The retrieval and semantic caching backbone underneath the platform. LangCache reduces redundant model calls by caching prompt responses.

What analysts say

The data industry is generally heading in the same direction now. Every major database vendor is making a context layer argument. 

Traditional database vendors including Oracle are integrating context and memory layers to bring relational databases into the agentic AI era. Purpose-built vector database vendors including Pinecone are doing the same, building out a new knowledge layer for agentic AI context. Standalone context layers like Hindsight are also part of the emerging landscape.

Trollope frames Redis’s position as structurally different from that competition.

“For us to win, no one else has to lose,” he said. Many Redis deployments already run MongoDB or Oracle as the backend system of record. Iris reflects and caches from those systems rather than displacing them. Redis is launching Iris in the Snowflake marketplace with native connectors.

Stephanie Walter, Practice Leader for AI Stack at HyperFRAME Research, puts the market context plainly. “The market is converging on the same conclusion: agents don’t just need more tokens or better models. They need governed, current, low-latency context,” Walter said.

Her read on Redis’s differentiation focuses on where Redis already sits in the stack, which is close to runtime, latency-sensitive operational state, and real-time data., 

“The pitch is not ‘better RAG’ as much as ‘agents need live context, memory, and fast retrieval while they are actually working,” she said.

Whether it’s Redis or another vendor, every context layer technology will face a governance challenge to be successful.

“Agentic AI will not scale in the enterprise if every agent becomes a new cost center, a new data access risk, and a new governance exception,” she said. “The winning context layers will be the ones that make agents faster, cheaper, and safer to run.”

For real-time clinical AI, getting context wrong is not an option

Mangoes.ai is one company that has already had to answer those questions in production, under conditions where the cost of getting context wrong is measured in patient outcomes.

Amit Lamba, founder and CEO of Mangoes.ai, runs a real-time voice AI platform deployed across large healthcare facilities where patients and clinicians ask live questions about treatment, scheduling and case history. Mangoes.ai built its stack natively on Redis from the start. 

“Retrieval, memory, and session state all run through Redis, so we’re not stitching together separate tools and hoping they talk to each other,” Lamba said.

The problem Iris’s dynamic memory capability addresses is what happens across a complex session.

 “Think about a one-hour group therapy session,” Lamba said. “You need to know who said what, when, and be able to surface the right information to the therapist in the moment. That’s not a simple retrieval problem.”

The platform runs multiple specialized agents in parallel, one for entity identification, one for relationship reasoning and one for integrating case history.

“The dynamic memory capability maps almost perfectly to the problem we’re solving,” Lamba said.

What this means for enterprises

For enterprises that built their AI stack around RAG, the retrieval layer that got them to production is no longer enough to keep them there

The RAG era is giving way to context architecture. The classic RAG model pushed data into the agent before the model was called. Production deployments are flipping that: agents pull what they need at runtime through tool calls, treating the data layer as a live resource rather than a pre-loaded payload. Teams still optimizing RAG pipelines are solving last year’s problem.

The semantic layer is now production infrastructure. The model that defines business entities, their relationships and the access rules between them needs to be built, versioned and maintained with the same discipline as a data pipeline. Most organizations have not staffed or structured for that work. The enterprises that define their context architecture now are the ones that will not have to rebuild it when agent workloads scale.

Budget is already moving. VB Pulse Q1 2026 data shows retrieval optimization investment rising from 19% to 28.9% across the quarter, overtaking evaluation spending for the first time. Organizations that spent the previous year measuring their retrieval quality are now spending to fix it. The context layer is an active procurement decision, not a roadmap item.

“The first buyer question should not be ‘Do I need a vector database, long context, memory, or a context engine?’ It should be ‘What does this agent need to know, how fresh must that knowledge be, who is allowed to access it, and what does every retrieval cost?’” Walter said.

VIrtualization

Supports Nvidia Grace and Ampere processors

VMware has quietly debuted a technology preview of its flagship ESX hypervisor that is capable of running on Arm processors and servers.

The virtualization giant teased its new tech in a Xeet which piqued our interest and led to the discovery of this document [PDF] on the public internet that explains the hypervisor supports guests running RHEL, Ubuntu, and SUSE, on servers from HPE and Gigabyte powered by Ampere processors, or Supermicro’s ARS-221GL model with an Nvidia Grace processor.

The document offers slightly contradictory advice to the effect that “Arm host clusters must be managed by a separate, standalone vCenter running on x86. We do not recommend managing x86 installations and Arm installations from the same vCenter.”

The tech preview appears to be a very basic affair, as it lacks support for vSAN hyperconverged storage, NSX virtual networking, and plenty of other features VMware offers in its x86 hypervisor and Cloud Foundation (VCF) private cloud suite.

VMware has also made it possible to access Arm guests from its desktop hypervisors. As disclosed last week in release notes for new versions of the Workstation and Fusion products that add “the ability to connect to remote ARM-based ESXi, allowing users to manage VMs on remote ARM servers directly from VMware Workstation or Fusion on any supported platform.”

Virtzilla is therefore making good on its promise to bring its hypervisor and VCF to the Arm architecture.

The Broadcom business unit is porting its products because it thinks customers will increasingly turn to Arm servers on the network edge, perhaps for AI workloads. VMware is also aware that Arm processors can be more energy-efficient than x86 CPUs, and must also know that its hyperscale partners AWS, Microsoft, and Google aggressively promote their home-brew Arm processors as delivering superior performance-per-watt.

In its announcement of its new desktop hypervisors, VMware offers another reason: “As development environments diversify, cross-architecture connectivity is essential.”

VMware hasn’t offered a timeline to get ESX on Arm ready for a full release, but the company has previously told us it’s in no rush because customers are currently Arm-curious rather than in a rush to shift workloads onto the architecture.

While VMware explores a new architecture, its rivals continue to prepare products they hope will prize away some users who feel Broadcom’s licensing regime isn’t to their liking.

Platform9 last week debuted “Platform9 OS”, a cut of Linux that encapsulates its Private Cloud Director in an appliance-like format so that users don’t need Linux administration skills to adopt its stack. Platform9 is going after VMware’s top 10,000 customers with a promise it won’t try to lock them in with licensing or restrictive hardware compatibility lists.

Australian outfit Netframe takes a similar approach with its wares and has chosen to walk down a well-worn path by creating a free version of its eponymous product that allows users to run up to three hosts. The company thinks that offering will attract home lab operators and small shops who will be sufficiently impressed by the product to upgrade and sign up for support. ®

All eyes are on South Korea today as officials bid to avert a strike by more than 45,000 Samsung workers that could impact global semiconductor supply chains.

With a planned walkout set to begin on 21 May, Samsung Electronics and its workers’ unions began what could be a final round of talks today (18 May), following the collapse last week of a first round of South Korean government-mediated negotiations, according to Reuters.

The threatened 18-day strike comes amid an already severe global shortage in memory chips – essential components in AI data centres, smartphones and laptops – that has fuelled massive profits at Samsung and its peers in recent months.

The dispute centres on Samsung’s performance-based bonus system. According to CNBC, the union is seeking bonuses equivalent to 15pc of Samsung’s operating profit, plus other measures, while Samsung’s management has countered with an offer of 10pc of operating profit.

The economic stakes could hardly be higher. CNBC quotes prime minister Kim Min-seok, who estimates direct strike losses at 1trn won ($664.7m), potentially rising to 100trn won if chip production disruptions force Samsung to scrap wafers already in production.

The company accounts for 22.8pc of South Korea’s exports and revenue equivalent to 12.5pc of GDP, according to CNBC. Kim described Monday’s talks as the last opportunity to avert the strike, warning that “the economic losses we will face will be beyond imagination”.

Pressure on the unions mounted further today when the Suwon District Court partially granted Samsung’s injunction request against two unions, ordering that staffing levels required for safety, facility protection and product quality must remain at normal levels during any industrial action.

The Financial Times cited corporate lawyer Hyeseop Sim, who said the ruling “will significantly weaken the scope of the strike and the negotiating power of the unions”, adding that chip production was therefore unlikely to be significantly disrupted.

Samsung chip division executives have also warned that key customers including Nvidia indicated they might temporarily halt shipments during a strike over product quality concerns, according to Reuters. President Lee Jae-myung called for balance on Monday, posting on X that “labour must be respected as much as corporations, and corporate management rights must be respected as much as labour rights”.

“Workers must be able to receive fair compensation for the labour they provide, and shareholders who have invested while bearing risks and losses have a share in corporate profits,” he continued.

Samsung chairperson Lee Jae-yong issued a rare public apology to customers worldwide on Saturday for causing “concern and anxiety”, according to local Korean media.

All eyes will be on the talks that are reportedly due to finish tomorrow, as the industry fears yet another hit to the global chip supply chain.

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Catch the Canadian Grand Prix live on a service that isn’t Apple.

Valve, the team behind Steam and the much loved Steam Deck, has recently unveiled three new additions to its hardware lineup.

Alongside the Steam Controller and Steam Frame headset, Valve has introduced the Steam Machine, a PC optimised for gaming on the big screen.

While the Steam Machine hasn’t officially launched yet, we’ve rounded up everything you need to know about the upcoming gaming PC. Read on to see what you should expect from the Steam Machine.

Otherwise, make sure you visit our list of the best game consoles and best gaming laptops too. 

Last updated: 18th May to include rumours for gaming titles

Steam Machine at a glance

• According to Valve, the Steam Machine is set to launch within the first half of 2026, although exact date and pricing is still unconfirmed
• Delayed announcements blamed on RAM prices and shortages crisis
• Available in two sizes: 512GB and 2TB
• Leaks suggest the Steam Machine will start at around $950/£710 for the smaller model while the 2TB size may be $1070/£800
• Six-inch cube-shaped PC
• Customisable LED strip at its front
• Powered by SteamOS, potentially SteamOS 3.8.1 which is the first to offer initial support for the Steam Machine
• AMD desktop class CPU and GPU for 4K gaming at 60 fps

What are the Steam Machine specs?

When is the Steam Machine release date?

Although Valve announced the Steam Machine, alongside the Steam Frame and Steam Controller, back in November 2025 and promised all devices would launch in “early 2026”, the exact launch date is still currently unknown. Not only that but, at the time of writing, the pricing is still unconfirmed too.

However, in a statement published back in February, Valve promised that although it has needed to “revisit” its shipping schedule for the hardware, the “goal of shipping all three products in the first half of the year has not changed”. With this in mind, we can reasonably hope to see a launch by July 2026 latest. 

Why has the Steam Machine been delayed?

So, what has actually happened for Valve to need to reassess its launch date? Perhaps unsurprisingly, Valve has revealed that the ongoing RAM crisis is to partly to blame.

Essentially, the fact that there’s limited RAM availability and prices are continuing to rise, Valve has reported that it’s needed to reassess its initial shipping and pricing strategy. 

In a recent interview with PC Gamer, Valve’s Lawrence Yang addressed the obstacles including “RAM shortages, memory shortages, price hikes” which have gotten in the way of the launch. Despite those unavoidable issues, Valve has confirmed the team are “doing [their] best” to ensure the product will still be available at “as good and competitive a price” as possible.

How much will the Steam Machine cost?

But what does this mean for pricing? Although Valve hasn’t revealed any clues as to how much the Steam Machine will likely cost, internet sleuths did apparently manage to track down a listing for the console online. Although the listing, which was found on Czech retailer Smarty’s website back in January, didn’t publicly show a price, internet detectives worked out that if you inspect the site via the browser developer console then the hidden price is there.

Seriously, there’s no hiding anything from internet sleuths.

For the 512GB model the price is listed as 19,826 CZK which is roughly $950, while the larger 2TB model is listed for 22,305 CZK, which is around $1070.

The OP on Reddit disclaims that you should keep in mind that this pricing is from an external retailer, so the “final price directly from Steam could be lower”. 

However, do keep in mind that this so-called discovery was found before Valve gave its statement addressing the ongoing RAM prices issue. With this in mind, it’s not unreasonable to assume the cost of the Steam Machine might end up being higher, as Valve is still discussing the best possible pricing strategy.

Fans have also found evidence that could point to the hardware costing upwards of €1000. As shared on Reddit, an update in the source code chunk containing the hardware reservation system indicates that they have prepared the system for hardware that requires over €1000. However, we should note that it’s unclear whether or not this price refers to the Steam Machine or Steam Frame, and whether this is a bundle or not. 

While there’s plenty of rumours and supposed leaks circulating the internet, at the time of writing we simply don’t know how much the Steam Machine will cost.

Steam Machine design

Although Valve hasn’t confirmed neither the release date nor price of the Steam Machine, the company has certainly managed to build intrigue by revealing its design and specifications. 

At its surface, the Steam Machine looks like a neat, fuss-free console thanks to its roughly six-inch cube design. It doesn’t look dissimilar to the Fire TV Cube, and is designed to blend into your home entertainment or desk set-up.

Despite its compact size, the Steam Machine is impressively well equipped with plenty of ports. There’s a total of four USB-A ports available, plus a USB-C, HDMI, Ethernet and a DisplayPort. Not only that but regardless of whether you opt for the 512GB or larger 2TB version, you’ll benefit from expandable storage thanks to the microSD card slot too. 

There’s also a customisable LED strip at its front, which is fitted with 17 individually addressable LEDs. This, Valve explains, can be customised to suit your preferences, used as a visual indicator to determine a download’s progress, or turned off altogether. 

At the rear is a nifty fan that promises to ensure the Steam Machine stays cool and runs quietly, even during the “most demanding games”. 

Steam Machine performance

Before we dive into the Steam Machine’s specs, it’s worth noting that they might look a bit different after launch. According to PC’s official listing, some of the specifications are “subject to change ahead of availability”. 

Otherwise, considering that it’s promised to be up to six times more powerful than the Steam Deck, these initial specs undoubtedly sound promising.

As is to be expected, the Steam Machine is optimised for gaming and promises up to 4K gaming at 60fps with FSR. However, Valve has disclaimed that there are some titles that require more upscaling than others, and advises that “it may be preferable to play at a lower framerate with VRR to maintain a 1080p internal resolution”. 

Valve continues that it’s working on HDMI VRR, investigating improved upscaling and optimising ray tracing performance in the driver.

Otherwise, although the Steam Machine is a gaming device, thanks to its semi-custom AMD desktop class Zen 4 CPU and RDNA 3 GPU, it lends itself to be a pretty decent PC too – allowing you to install your own apps or even another operating system if you like. Plus, the Steam Machine’s NVMe 2230 or 2280 SSD and memory are both accessible and upgradeable too. 

Finally, although it is hailed as being “made for Steam Controller”, as the Steam Machine comes with a built-in wireless adapter specifically for pairing with the Controller, you can also pair other PC and gaming accessories to the Machine too.

Steam Machine software rumours

Unsurprisingly, the Steam Machine will come equipped with SteamOS. There’s much to love about SteamOS as it’s designed to offer a plug-and-play experience without a needlessly complicated set-up. Valve also states that it’s expanding the Verified program to include ratings for Steam Machine, which means you’ll be able to see how well a game will run on before committing. 

We actually have a bit more detail on what SteamOS version the Steam Machine will likely come running on. On April 10th, Steam released SteamOS 3.8.1 in beta, which is currently available for those who have opted in via their device’s Settings. The OS update includes general fixes and improvements to features, such as better support for screencasts in Game Mode and resolved issues in certain titles where the game window would have an incorrect position or could crash. However, what’s really caught our attention is the addition of “Initial support for upcoming Steam Machine hardware” listed in its feature updates.

With this in mind, it certainly seems as if we’re edging closer to the launch of Steam Machine, as Steam’s latest OS offers support for the hardware. However, remember this software update is still in beta and we don’t know when it’ll become readily available.

Will Half-Life 3 be a Steam Machine launch title?

While Valve has stated that it’s expanding the Verified program to include ratings for Steam Machine, we don’t have a direct list of titles. However, one title that has particularly drummed up attention is the possibility of the long-awaited sequel to 2004’s Half-Life 2: Half-Life 3.

Although former Valve writer Chet Faliszek stated he had “no interest” in working on Half-Life 3, there are still plenty of rumours surrounding the possibility that the title will launch for Steam Machine. As exciting as this rumour is, we should disclaim that this is pure speculation at this point.