Liverpool vs. Villareal: Livestream Champions League Soccer From Anywhere

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Latest Tech News

• A draft of Russia's national AI plan proposed using AI to analyze 70% of blocked VPN services and lift blocking effectiveness to 95%
• The Digital Development Ministry says the measure is absent from the current draft, but Roskomnadzor's separately budgeted and arguably crucial ML filtering project remains
• The 95% is an effectiveness target, not accuracy, and sources expect AI to raise false positives, with corporate VPN, cloud and voice traffic most exposed

Russia's Digital Development Ministry considered using artificial intelligence to push the effectiveness of its VPN blocking to 95%, according to a front-page report in Kommersant.

The measure appeared in a draft of the country's national plan for implementing AI through 2030; the ministry now says it is not in the current version.

This isn't the first time such a move has been reported, but some earlier coverage might have been overzealous, to say the least, when it reported that "Russia Eyes AI-Powered VPN Crackdown With 95% Blocking Accuracy." The problem with that headline is that not only was that proposal dropped, but the 95% accuracy figure was never actually in play.

A draft that proposed AI use

None of the above reporting should reassure an estimated 57 million Russians who rely on circumvention tools.

Roskomnadzor (the Federal agency tasked with "Supervision of Communications, Information Technology and Mass Media") has its own machine-learning filtering project budgeted outside the national AI plan, and the money for Russia's blocking infrastructure is set to double next year.

Kommersant, which reviewed the draft, reports that the ministry wanted AI to analyze the characteristics of 70% of all the VPN services Russia blocks. The drafters reckoned that would lift blocking effectiveness to 95%.

Asked about it, the ministry said the current draft of the plan "contains no such information," in Meduza's translation. A source familiar with the discussions told Kommersant that agencies had pitched a range of measures for the plan, some of which may never be implemented, and that the traffic-analysis algorithms already in service are a form of intelligent analysis but do not count as AI.

An AI layer would behave fundamentally differently; rather than matching known signatures, models would weigh packet sizes and timing, session length, and the balance of inbound to outbound traffic, then flag likely VPN servers from indirect clues: how a node behaves, which host it sits on, and what its neighboring IP addresses look like. The payoff is speed, catching new servers before they reach any blocklist.

Kommersant uses the word effectiveness, and the distinction matters: a blocking-effectiveness figure describes how much targeted traffic it stops. It says nothing about how much legitimate traffic gets stopped with it, and that is what the catch is; the solution proposed does not account for any mistakes, just how effective it would be at its job of blocking out VPN traffic.

The 95% target is also less of a leap than some headlines suggest, because Russia already has 92% on paper, at least by its own estimates. A Roskomnadzor subsidy decision for its Main Radio Frequency Center (GRChTs), dated January 2025 and surfaced in May 2026 by journalist Maria Kolomychenko, sets an "average level of effectiveness" of 92% for restricting VPNs via signatures by the end of 2030. Verstka reports that the AI proposal was meant to lift that same indicator to 95%.

The more consequential point is that striking a line from a draft strategy does not strike the capability. Forbes Russia reported in January 2026 that Roskomnadzor planned to spend 2.27 billion rubles (around $29 million) in 2026 on a machine-learning-based traffic-filtering mechanism, a project we flagged when Windscribe saw a roughly 90% drop in its Russian traffic that same month.

The false-positive risk is not hypothetical in Russia, because the government has already learned how hard it is to separate good VPNs from bad ones. When the ministry ordered major platforms in April to block users with VPNs switched on, its guidance promised a whitelist for corporate VPNs.

Telegram founder Pavel Durov claimed the crackdown had "triggered a massive banking failure," and outage-tracking data showed bank disruptions on April 3 2026. A source told RBC at the time that no reliable technical method existed to tell permitted corporate VPN traffic from the rest.

For now the picture on the ground is unchanged: blocking is intensifying with or without an AI mandate. At least 10 VPN providers reported tighter restrictions in the week after September's State Duma elections, and VPN Guild chairman Alexey Kozlyuk described it to Meduza as "a continuation and gradual intensification" of a campaign that began in August.

The Kommersant report also landed a day after RBC revealed a draft ministry order requiring phones on Russia's 5G networks to support the FSB-developed Kuznyechik cipher from March 1, 2032.

Providers keep adapting. "In Russia, VPNs face pressure almost every month; it is a new norm," an Amnezia VPN spokeswoman told TechRadar Pro. But Sarkis Darbinyan of RKS Global and the VPN Guild warned TechRadar that for users, the end result is "an ever-shrinking number of services that actually work."

The 95% target may be gone from one document. The infrastructure, the money, and the intent behind it are not.

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You Have Just Hours Left to Grab an M4 Apple Mac Mini for a Massive $150 Off

This M4 Mac Mini is an excellent upgrade if you need a new desktop. Just be aware that this deal is only available for a few more hours.

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Latest Tech News

• Ukraine's CCD says suspected Russian bot posts in its sample fell 83.6% on October 8 after a strike shut Yandex's Sasovo data center
• The same data shows volume back above pre-strike levels by October 10, with a smaller 42.6% dip after the Vladimir shutdown
• Cloudflare and Graphika found no comparable drop in Western political communities, though Russian-language Telegram output fell 5% to 15%

Ukraine's Center for Countering Disinformation (CCD) says suspected Russian bot accounts went almost silent after drones knocked out Yandex data centers earlier this month, with message volume across a monitored network falling 83.6% in a single day.

The findings come from an analytical report the CCD dated October 15 2026. Using Osavul monitoring software, analysts tracked 22,664 messages from 5,201 accounts showing signs of inauthentic behavior across 26 topics in Ukraine's Facebook and Telegram space between October 6 and 12.

The 83.6% figure is real, but the same report shows those accounts posting more than before within 48 hours, and independent data from Cloudflare shows that at least some of the malicious automation running on Yandex's cloud did not die so much as move house.

A collapse in automated traffic after the Yandex Cloud took a beating

The first collapse came on October 8, hours after a drone strike and fire shut down Yandex's Sasovo data center in Ryazan region, home to two of the company's three supercomputers.

Daily messages fell from 4,032 to 660, and active accounts dropped from 1,526 to 258. Telegram took the harder hit, down 90%, while Facebook fell 79.5%. A second, shallower dip followed the October 11 strike that Yandex said had completely halted its Vladimir site, with messages falling 42.6% on October 12, from 4,711 to 2,704. A subgroup of 98 accounts the CCD flagged for justifying the invasion or inciting hatred followed the same curve, down 77.8% on October 8 and 49.2% on October 12.

The most telling detail sits in the middle. The October 9 strike at Yandex's Kaluga campus, which the company describes as its largest, only partially took the site offline, and the CCD recorded no fall in activity that day. The two dips line up with the two complete shutdowns, as one would expect if these accounts depended on that infrastructure, though that's not proof on its own.

A surprisingly fast turnaround time?

What the 84% figure that the CCD touts leaves out is how briefly the silence held. Message volume recovered to 2,231 on October 9, then reached 4,585 on October 10 and 4,711 on October 11, both above the pre-strike level. The monitoring window in the report closes on October 12, so it cannot show whether the second dip recovered the same way.

The agency has also been downplaying the event on other forums; two days before the report, the CCD said posting in some clusters of the Pravda, InfoDefense and Nod of Time networks roughly halved for about 12 hours, and stressed that it had not recorded a significant overall decline across Russian bot farms.

On October 16, the CCD's summary of remarks by media literacy head Ivan Slychko described the effect as "a disruption of automation, not the complete disappearance of bots."

It also makes no mention of a similar comparison for ordinary accounts. On the afternoon of October 8, banks, retailers, mobile operators and news sites across Russia suffered outages. Without said information, it is hard to separate bot farms losing their servers from operators inside Russia simply losing connectivity.

The CCD is hardly an impartial player here; it is a body attached to Ukraine's National Security and Defense Council, and it has an incentive to exaggerate victories even when the data doesn't always support them.

President Volodymyr Zelenskyy had already jumped the gun, telling the Warsaw Security Forum that after the strikes "it suddenly became a little easier to breathe on many social media platforms" and that might have been a deciding factor for how the CCD built its narrative.

Beyond Ukraine, the "bots went silent" story mostly rested on a Cloudflare Radar chart showing automated traffic from Yandex's AS13238 network falling to well under 1% of its recent peak on October 11. As we noted at the time, that traffic was far more likely to be crawlers than fake social media accounts, and "bot" is a loose word when automated requests make up around half of all web traffic.

Cloudflare's own post-mortem confirms it. Marina Elmore and Lai Yi Ohlsen found 99.5% of requests from AS13238 were automated, mostly verified Yandex search crawlers, and that the network supplied only about 7% of Russia-origin bot requests. Bot traffic from Russian IP addresses hitting the post, reply, and like endpoints of one social platform dipped just 5.7% across the event period.

Graphika reached a similar verdict from the other direction. Founder John Kelly's analysis of the AfD, MAGA and Reform UK communities that viral posts claimed had gone quiet found none lost their active accounts or heaviest posters.

AfD-linked accounts posted 40,365 times on October 11, 4% below the week before and well within normal swings, while MAGA mentions on X rose 25% in the eight hours after the Vladimir strike. Georgetown's Renée DiResta, writing in Lawfare, was blunt about the viral version: "It's a great story. But it looks like fiction rather than fact."

For now, the most defensible reading of the CCD's numbers is narrower than its headline. Knocking out the right data center can briefly cut the output of Russia-based accounts aimed at Ukraine. Keeping them quiet would mean hitting the servers they move to next, and on the evidence so far, that move takes a day or two.

As one analysis of battlefield computing puts it particularly well, resilience comes from designing for disconnection, and the bot operators appear to have learned that lesson faster than Yandex did.

Via UNITED24 Media

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Today’s NYT Wordle Hints, Answer and Help for Monday, Oct. 19, #1948

Need a Wordle hint today? Get spoiler-free hints for NYT Wordle No. 1,948 on Monday, Oct. 19, then the answer, plus yesterday’s word.

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Latest Tech News

• Intel's GPU D-series sets a new GPU memory record with 480GB of LPDDR5X
• Intel chose LPDDR5X instead of GDDR7 for its high-capacity AI accelerator
• The D-series supports models containing up to 300 billion parameters

At the recent Open Compute Project Global Summit, Intel unveiled a graphics processor with up to 480GB of memory, an unusually large capacity designed for demanding AI inference workloads.

The GPU, called Intel GPU D-series and previously known by its Crescent Island codename, also hosts specialized computing hardware.

The Intel D-series has now dethroned Nvidia's Blackwell Ultra B300, which offers 288GB of HBM3e memory, as the data center GPU with the highest memory capacity.

Intel prioritizes memory capacity

Rather than using GDDR7 memory associated with modern graphics cards, Intel has chosen LPDDR5X, a memory technology commonly found in laptops and other power-conscious devices.

The configuration suggests that Intel is prioritizing memory capacity and power efficiency for AI inference instead of designing a conventional gaming graphics card.

Intel says the accelerator can support large language models containing up to 300 billion parameters on one card, while an eight-GPU system can accommodate models exceeding one trillion parameters.

These capabilities are intended for lengthy prompts, simultaneous inference requests, enterprise AI services, and robotics applications requiring responsive processing.

“Inference is becoming the defining AI workload, and enterprises need infrastructure that delivers the right performance at the right cost,” said Anil Nanduri, vice president, AI Products & GTM, Intel Data Center Group.

“With Intel GPU D-series, we're focused on making high-capacity inference practical to deploy and economical to scale.”

The 480GB capacity is particularly relevant when AI systems must keep substantial model weights and associated data accessible during inference.

However, memory capacity alone does not establish how quickly a GPU will serve requests, since performance also depends on bandwidth, computing resources, software, and workload characteristics.

Intel rates the D-series at 1.3 petaflops for FP8 computation, a numerical format commonly used to accelerate AI operations while reducing memory requirements compared with higher-precision formats.

Its 1.5TB/s memory bandwidth provides a separate measure of how quickly data can move between memory and the processor.

Intel wants the accelerator to fit existing data centers

The company specifies a 350W power envelope and a standard PCIe form factor, alongside air cooling and software compatibility across its GPU platforms.

These characteristics are intended to simplify deployment in existing data centers without requiring specialized cooling arrangements or entirely new rack infrastructure.

Intel also plans to connect the accelerator with its Xeon processors, allowing CPUs to coordinate tasks, manage data movement, and handle workloads that do not require GPU acceleration.

This approach addresses AI systems increasingly built around multiple stages, including retrieval, reasoning, orchestration, external tools, and execution.

“Open models are expanding the options enterprises have for deploying AI,” said Nicolas Dubé, corporate vice president, Data Center Systems and Solutions Group, Intel.

“To realize their full potential, organizations need infrastructure that can match different workloads with the right intelligence, right compute resources and right economics. That's what we mean by 'put every prompt in its place.”

As of the time of writing, Intel has not revealed the public retail price or a specific general-availability date for the GPU D-series.

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Today’s NYT Strands Hints, Spangram and Answers for Sunday, Oct. 18, #959

Need a Strands hint today? Get the theme hint, the spangram and every answer for NYT Strands No. 959 on Sunday, Oct. 18 plus yesterday’s answers.

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Latest Tech News

• Microsoft will make Maia its main inference engine at multi-gigawatt scale, following Google and Amazon into in-house silicon
• Microsoft's upcoming Maia 300 trades a modest 36% compute gain for 2.5x Maia 200's memory bandwidth, betting on memory-bound decode, with production in 2027
• Hyperscalers supply just over half of Nvidia's data center revenue at a 75% gross margin, so each move to in-house chips affects not only its pricing power but the chip industry's sustainability as a whole

In 2024, Microsoft told the European Commission that Google was the only company vertically integrated at every AI layer, from chips to a mobile app store, and that "everybody else must rely on partnerships to innovate and compete."

Now, it has revealed plans to follow the same route without breaking a sweat.

In an Official Microsoft Blog post, Scott Guthrie, executive vice president of Cloud + AI, said Microsoft will scale its Azure Maia accelerators to multi-gigawatt deployments starting in 2027 and make Maia the primary inference system for Microsoft's products and services.

The vehicle of its choice is Maia 300, which Rani Borkar, president of Azure Hardware Systems and Infrastructure, and Saurabh Dighe, corporate vice president of systems planning and architecture, detail in an architecture deep dive.

Feeding the beast, not growing it, as it takes the Google route

The move is a pointed statement from one of Nvidia's biggest customers, and it lands as bubble worries grow louder. Gartner forecast this week that AI providers will spend nearly $1 trillion on infrastructure in 2026 alone, and that AI revenue won't cover the build-out profitably until at least 2032.

If the largest buyers of AI hardware stop paying Nvidia's margins for the work they do most, the most richly valued part of that build-out starts to look exposed. Whether Maia 300 is the final catalyst for such a move, though, is a harder case to make.

Maia 300 moves from Maia 200's single die to a multi-chiplet package, with compute on TSMC's N2P process and memory-controller and I/O functions split onto separate dies. Eight HBM4 stacks deliver 288GB at 18TB/s per accelerator, against 216GB at 7.1TB/s for Maia 200, according to StorageReview's breakdown of Microsoft's spec sheet.

Microsoft hasn't abandoned compute so much as rebalanced around memory. In decode, the token-by-token phase that dominates long reasoning chains and agent loops, accelerators spend much of their time waiting on data rather than doing arithmetic.

The Maia 300 tries to close that gap by keeping data near the compute that uses it, through a non-uniform memory layout across chiplets, software-managed on-die SRAM, and narrower number formats, including an enhanced MXFP4 and sub-3-bit storage formats, with hardware conversion between them. The Maia 300 announces something the rest of the industry already knew, albeit more subtly: Custom silicon is no longer a side project for hyperscalers.

Google, the company Microsoft singled out two years ago, began recognizing revenue from TPU system sales delivered to customer data centers in the second quarter, CFO Anat Ashkenazi said on Alphabet's July earnings call, while CEO Sundar Pichai said the company is "seeing strong demand for TPUs as standalone systems from other customers."

It isn't the only one either; Anthropic has lined up 3.5GW of TPU capacity through Broadcom for 2027, on top of an earlier deal for up to a million TPUs, and Meta was reported in 2025 to be in talks to rent-cum-purchase them. Amazon has gone the same way. CEO Andy Jassy said in April 2026 that Amazon's chip business, spanning Trainium, Graviton and Nitro, had passed a $20 billion annual revenue run rate and was now "one of the top three data center chip businesses in the world." OpenAI, meanwhile, has lifted the lid on its own Jalapeño accelerator.

Nvidia's margins: the AI holy grail?

The incentive is plain from Nvidia's own results. In the quarter to July 2026, the company reported $96.2 billion in revenue, $89 billion of it from data centers, at a 75% gross margin. CFO Colette Kress put hyperscale revenue at $49 billion on the earnings call, meaning a little over half of Nvidia's data center business comes from a small group of buyers, the biggest of which now design their own accelerators.

Every inference workload that moves in-house is one where that buyer pays closer to manufacturing cost instead of Nvidia's margin. Microsoft told investors in July that Maia 200 was up to 40% cheaper to operate than Nvidia's latest chips on OpenAI and Microsoft models.

It did, however, fail to name a particular GPU it called a "leading GPU-based system," an important distinction given Nvidia's focus on efficiency via Vera Rubin, which OpenAI even refused to compare against outright.

The reveal didn't move stocks much; on Monday, Nvidia shares closed down 1.29% after the reveal, while Microsoft's rose 1.14%, and Microsoft's opaqueness about efficiency gains may be one reason.

The other reason is equally important: Evercore ISI analysts estimate Maia will account for only about 10% of Microsoft's AI chip spending by the first quarter of 2027, CNBC reported, and Nvidia has guided to $108 billion in revenue for the current quarter.

Scale is arguably an ongoing constraint, however; at 167 kW per rack, a gigawatt of rack power is roughly 6,000 Maia 300 racks, or about 575,000 accelerators, before cooling and facility overheads.

Going the Google route hasn't stopped anyone buying from Nvidia either. Amazon, with its "top three" chip business, is still set to take more than 3 million Nvidia GPUs by mid-2028.

Alphabet, which now sells its own TPUs, raised its 2026 capex guidance to between $195 billion and $205 billion in July, lists Vera Rubin alongside its own TPUs, and Ashkenazi said it is "still in a supply constraint environment."

Microsoft keeps Nvidia and AMD for training, and Satya Nadella said earlier in 2026 that "because we can vertically integrate doesn't mean we just only vertically integrate."

Jensen Huang's answer to the custom silicon question on Nvidia's August call could have been written about Maia: "Whereas many of these XPUs are inference-specific chips for one cloud or one service, NVIDIA is a platform." Microsoft's counter-bet is somewhat different: one cloud is big enough.

The deeper problem for the pin theory is that custom silicon changes who collects the margin, not how much gets spent. Gartner warns that the industry needs about $8.5 trillion in revenue between 2026 and 2030 to earn a reasonable return on its build-out, versus no more than $3.6 trillion it expects AI to generate. Microsoft isn't responding by building less; it is planning gigawatts more, and cheaper tokens arguably help close that revenue gap rather than widen it.

Some of what Microsoft saves will also flow elsewhere in the supply chain. Maia 300's pitch rests on HBM4, the same constrained memory Nvidia's Rubin uses at the same 288GB per package, and its compute dies come from TSMC, which supplies everyone.

Google's TPUs are developed and supplied under a long-term agreement with Broadcom, whose CEO Hock Tan said that "many investors in AI don't understand what they're putting their money into," and who expects chip shortages to ease only around 2028 or 2029. Nvidia isn't sitting idle either; it already paid $20 billion to license Groq's SRAM decode technology, a sign it sees the same inference threat coming.

Until production silicon ships and someone outside Microsoft can measure it, Maia 300 is a well-argued design whose most important numbers are ones that only Microsoft has seen, and a reminder that the biggest threat to Nvidia's margins may be its best customers rather than its rivals.

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• Oxylabs, Decodo, Webshare, ScrapingBee, and Honeygain now formally sit under one Vilnius-based umbrella called Source
• Source claims AI agents drove a fourfold increase in demand for services across its organizations
• The brands, previously reviewed as rivals, including three of TechRadar's nine best-proxy picks, now officially share common oversight

Oxylabs, Decodo, Webshare, ScrapingBee, and Honeygain have formally come together under a single name, Source, and the Lithuanian group behind them says AI agents are why it needed one.

The Vilnius-based ecosystem claims demand across its companies has risen fourfold in a year as AI agents, next-generation search tools, and frontier AI products pull live data from the web.

Its systems now process 1.5 million requests per second, and that it is expanding into web search APIs built specifically for AI agents.

One umbrella with five different, competing shopfronts?

Source presents itself as a backbone rather than a business. Its launch post says it has no customers or products of its own; instead, it handles patents, procurement, hiring, and compliance, while each brand keeps its own team, product strategy, and customer base.

The brands are split by customer type. Oxylabs serves enterprises and AI labs; Decodo (formerly Smartproxy) targets the mid-market; ScrapingBee sells developer APIs; Webshare serves professional consumers and solo builders; and Honeygain pays ordinary people for their spare bandwidth.

For anyone shopping for a proxy service, this is the most practical takeaway. Oxylabs bought Webshare in 2022 and ScrapingBee in 2025, and Honeygain became its main residential proxy sourcing partner in 2021.

Decodo's ties were less clear-cut until now, and trade site Proxyway notes that the launch officially links Oxylabs and Decodo under one organization. Source CEO Vytautas Savickas ran Decodo until March 2026, when he moved across to lead the Oxylabs group and founder Julius Černiauskas became chairman.

All of this points to a marriage of convenience rather than a merger by organizations that are already very closely interlinked. This is interesting because some of these brands have been sold and reviewed as alternatives to one another.

The best example of this is that three of the nine picks in TechRadar's own best proxy sites guide now belong to Source: Decodo as best overall, Oxylabs as best for business, and Webshare as best for privacy.

For context on the overlap, our residential proxy roundup described Oxylabs as one of Decodo's toughest competitors. Source says the companies remain fully independent in strategy, customers, and market presence, and that may well hold commercially, but common oversight is now a matter of record.

The release provided to TechRadar says Source gives the group "a unified voice in defending responsible access to public web data," and its legal history explains the appetite.

Reddit sued Oxylabs alongside Perplexity, SerpApi and AWMProxy in October 2025, alleging they evaded its anti-scraping measures by lifting Reddit content from Google search results. Oxylabs said it was "shocked and disappointed" and would defend itself.

It was still listed as a defendant in filings this spring, and in late July a federal judge allowed Reddit's core claims against SerpApi and Perplexity to proceed. Further back, a Texas jury awarded rival Bright Data nearly $7.5 million against Oxylabs in a 2021 patent case.

Source's own essay on AI agents and the open web argues that if access is negotiated one licensing deal at a time, only the biggest companies will be able to afford it. This makes a convenient argument for a large web scraping group, but the gatekeeping fears are real.

The most concrete product promised here is AI search, and it is older than the umbrella itself: Oxylabs already offers a Web API that pairs a search endpoint with a scraping endpoint for agents, so the "dedicated AI Search APIs" promised look more like an expansion of existing work than a new product line.

For customers, the questions to watch are whether the brands keep competing on price, how clearly each one discloses their newfound relationship, and how the Reddit case plays out for Oxylabs.

For everyone else, Source is a bet that AI agents will keep needing the live web, and that the companies supplying the pipes deserve a seat at the table when the rules for that access get written, aiming to negotiate from a clustered position of strength.

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The Celebrity Traitors is back with episode 5 tonight, and it can't come quick enough. 6 days is far too long to be left wondering whats happening to what's left of this year's cohort of Celebs in The Traitors' castle.

When we left them, Rob, Romesh, Ross and Leigh-Anne were running to the crypts for a deadly game of hide and seek. In a moment of chivalry, which Romesh disagreed with steadfastly, but begrudgingly accepted in the end, the three men agreed to give Leigh-Anne a key which guarantees her safety.

Episode 5 airs tonight, October 15 at 8pm BST, and you can watch The Celebrity Traitors online from anywhere with a VPN (75% off) and potentially for free.

Next episode: Thurs, 15 Oct (Ep.5)

Watch LIVE: BBC iPlayer

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*SPOILERS*

In case you missed the first four episodes, here's a quick rundown to get you up to date.

The two original Traitors were Richard E. Grant and Maya Jama. they decided to go with two very different styles of game play... Maya Jama played the game as you're meant to, while Richard E. Grant immediately told everyone he was a traitor. Unsurprisingly, he was voted out at the first Round Table.

The Traitors have since been recruiting, meaning that the line-up of backstabbers now includes James Acaster and Prof. Hannah Fry.

Those among the dead include Bella Ramsey, of The Last Of Us fame and Amol Rajan, of Amal Rajan fame.

After successfully voting out a traitor in the first round table, the faithfuls banished two of their own; Julie Hesmondhalgh and Myha'la.

Who will be next to be murdered, and will the faithfuls manage to sniff out a traitor?

Read on as we explain how to watch episode 5 of The Celebrity Traitors 2026 from anywhere – including the spinoff Celebrity Traitors: Uncloaked and the final on Friday, October 30.

Can I watch The Celebrity Traitors for free?

Yes. Faithfuls (and everybody else) in the UK can watch The Celebrity Traitors FREE of charge on BBC One and the channel's BBC iPlayer streaming platform and app. Episode 1, Episode 2, Episode 3, Episode 4 are streaming now; Episode 5 airs on Thurs, Oct 15.

Watch The Celebrity Traitors S2 for FREE on iPlayer

Season 2 of Celebrity Traitors streams for free in UK on BBC iPlayer. The streaming service doesn’t require an account or subscription – merely a TV licence. Stream and watch away.

Going abroad during season 2? Unlock iPlayer with NordVPN – our No.1 streaming VPN – details below.View Deal

How to watch The Celebrity Traitors from anywhere

If you're keen to watch The Celebrity Traitors S2 but you're away from home and access to the show is geo-blocked, you can always use a VPN to access it (assuming you're not breaching any broadcaster T&Cs, of course). You may be surprised by how simple it is to do.

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Using a VPN is incredibly simple:

1. Install the VPN of your choice. As we've said, NordVPN is our favorite.

2. Choose the location you wish to connect to in the VPN app. For instance, if you're visiting the US and want to view your usual UK service, you'd select a UK-based server from the list.

3. Binge the backstabbing. Head to your usual local streaming service and watch Traitors.

Can I watch The Celebrity Traitors UK in the US?

The Celebrity Traitors (2026) will arrive on Peacock in "Q4 2026", which is not a surprise – NBC/Peacock is home to all things The Traitors. The US release date is due to be announced shortly.

If you're a UK resident who is currently across the pond, a VPN will help you tune in to your BBC. NordVPN is our recommended provider, and you can find out why with our in-depth NordVPN review.

Can I watch The Celebrity Traitors 2 in Canada?

In Canada, subscription service Crave is streaming all 4 episodes of The Celebrity Traitors season 2. Viewers can also chose between French and English.

Crave plans start from CA$11.99 a month and offers classic HBO series, on-demand movies and Crave originals alongside TV shows such as The Traitors.

Visiting Canada from the UK? Use a VPN to watch The Celebrity Traitors season 2 online – plus all the other content you'd normally stream at home.

Can I watch The Celebrity Traitors season 2 in the UK?

The Celebrity Traitors continues tonight, Thursday, 15 October 2026 at 8pm on BBC One and BBC iPlayer.

The series airs two nights a week on Thursday and Friday evenings at 8pm.

Visiting the UK? from Ireland Use a VPN to access your usual The Celebrity Traitors on iPlayer.

Can I watch The Celebrity Traitors 2 in Australia?

The Celebrity Traitors season two is available in Australia for free on 10.

Fans can catch up on the first 4 episodes, as well as watch new episodes at exactly the same time as they air in the UK. All you need is a 10 account, and they're completely free.

Episodes are also available on Paramount Plus.

Outside Australia? NordVPN will help you gain access to free 10 streams while you're out of the country.

Can I watch The Celebrity Traitors 2 in New Zealand?

For Kiwi viewers, The Celebrity Traitors UK season 2 will stream on ThreeNow starting October 4 – three days after it starts in the UK on BBC iPlayer.

Visiting New Zealand? Grab this VPN (75% off) now to watch all your usual British streaming services when traveling.

Missed the first 4 episodes?

First of all, sorry for the spoilers. However, there's good news! You can catch up with the first 4 episodes of The Celebrity Traitors for free via BBC iPlayer (as long as you've been faithful and paid your license fee).

Not in the UK? Have no fear. You can access your iPlayer from anywhere in the world with a VPN.

The Celebrity Traitors series 2 (2026) – Need to Know

Who is in The Celebrity Traitors 2 cast?

Amol Rajan — journalist and broadcaster

Bella Ramsey — actor (The Last of Us, Game of Thrones)

James Acaster — comedian and podcaster

James Blunt — singer-songwriter

Jerry Hall — model and actor

Joanne McNally — comedian

Joe Lycett — comedian

Julie Hesmondhalgh — actor (Coronation Street)

King Kenny — YouTuber/content creator

Leigh-Anne Pinnock — singer, formerly of Little Mix

Maya Jama — presenter

Michael Sheen — actor

Miranda Hart — comedian, actor and author

Myha’la — actor (Industry)

Professor Hannah Fry — mathematician and broadcaster

Richard E. Grant — actor

Rob Beckett — comedian

Romesh Ranganathan — comedian

Ross Kemp — actor and presenter

Sebastian Croft — actor (Heartstopper)

Sharon Rooney — actor (My Mad Fat Diary)

The Celebrity Traitors 2 trailer

How many episodes of The Celebrity Traitors season 2 are there?

There are 10 episodes in The Celebrity Traitors series 2 – one more than season one, which had nine.

It continues Thursday, 15 October 2026 at 8pm BST on BBC One and BBC iPlayer, with episodes airing Thursday and Friday evenings in Great Britain.

Episodes 1-4 are available now on BBC iPlayer, with Episode 6 out at 8pm on Friday, Oct 2.

Episodes 7 and 8 are available next week, on October 22 and 23, respectively.

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Latest Tech News

• Nvidia claims that for each gigawatt an AI data center uses, only 70% is used for AI work
• Inefficiencies include cooling and power distribution, failures, and restarts
• While a chip shortage was considered to be the main bottleneck to AI data center capacity, it is now a facility’s connection to the grid

AI data centers are inefficient, says Nvidia, with various physical and systems issues contributing to power use beyond AI processing. This opinion, shared by data center builder Vertiv at its recent annual EMEA event, underpins future development steps, in which it plans to assemble sustainable facilities.

Vertiv and Nvidia have been collaborating since early 2026 on co-designing the next generation of data centers, with Vertiv providing power and infrastructure management for Nvidia’s GPUs.

With a maximum of 70% of electricity drawn from the grid used for AI processing, the remaining 30% represents inefficiencies that optimized data center designs for the future should reduce.

That's not efficient

Although the various inefficiencies affecting AI data centers may not come as a surprise, the scale of them might. According to Nvidia – via its Vice President of Supercomputing, AI Cloud Infrastructure, and AI/HPC for EMEA Rod Evans – that 30% consists of infrastructure and system issues.

For a one-gigawatt data center, 20% is lost through cooling, power distribution, and conversion. A further 10% is lost to incorrectly configured racks, as well as failures and restarts.

Evans says that “You sign a contract for 100 megawatts, but you never actually get that. With a bit of luck, you’ll get 93 megawatts, and at certain times of the day, even less.”

Nvidia believes some of the 30% (which can be as high as 40%) can be recovered. Evans notes that “A data center is actually designed for peak load and outages, not for what it typically uses.” This means that unused capacity can be tapped, and power and cooling can be revised to find the optimum configurations.

Bottlenecks of power

Rod Evans states that Nvidia and Vertiv are planning data centers that are more efficient and sustainable. “Together, we want to build sustainable AI data centers where the focus isn’t on using as much power as possible, but on getting the most out of every watt.”

One of the most significant details from the press conference is the challenge posed to AI data centers not by a shortage of chips, but by a lack of power. Bottlenecks are resulting in underpowered data centers, with some waiting for several years to receive the power to match their capacity.

This can be impacted by location. Vertiv’s EMEA president Paul Ryan explained that while you can get power in some locations but no permit. “In another, the permit is granted quickly, but there’s no power. And sometimes you have both, but the location is so remote that you can barely get the equipment there.”

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Harry Kane and crew take on the Eliteserien champions.

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