TECH

EA Sports FC 27 launches this September 2026

EA Sports FC 27 launches globally on September 25 across consoles and PC. Explore The Grounds open world, Career Mode overhauls, and full FC 27 Lite details surrounding the launch.

Electronic Arts is rolling out EA Sports FC 27 worldwide on September 25, 2026, following early access for Ultimate and Ultimate Plus Edition players that opened on September 18. The football title arrives on PlayStation 5, PlayStation 4, Xbox Series X|S, Xbox One, PC, Nintendo Switch, and Nintendo Switch 2.

The headline addition is The Grounds, an open-world space for Clubs and street football sessions built around three districts inspired by different football cultures. It is restricted to current-generation hardware: PS5, Xbox Series X|S, PC, and Switch 2. Players on PS4 and Xbox One miss out on the mode entirely.

Manager Career sees its biggest update in years. EA has partnered with Transfer Room to fold its Expected Transfer Value system into scouting, giving managers a realistic price anchor before negotiations begin. Deals now unfold in multiple stages, with room for rival bids and last-minute demands even after an initial agreement. Player ratings are no longer static either: a new Dynamic OVR system adjusts overalls based on form, morale, fitness, and playing time throughout the season.

Football Ultimate Team introduces the FUT Gallery, a hub for tracking and grading sets of player items collected across the season. Squad building challenges move to a simplified, score-based system rather than strict rating and position requirements. Icons also shift to a two-stage structure, launching as Debut cards rated 85 to 86 before upgrading to Champion versions rated 89 to 91 later in the cycle.

EA is also launching FC 27 Lite on September 25, a free download offering a limited slice of the game, including the Kick-Off mode, across console and PC storefronts. Progression modes such as Ultimate Team, Manager Career, and The Grounds remain locked to the full release, with players able to upgrade at any time.

A new football season starts before the first whistle: the group chat wakes up, someone proposes a Career save, and somebody else is already planning their opening squad. EA SPORTS FC 27 arrives worldwide on September 25, 2026, with eligible early access beginning on 18 September. That gives you two useful dates to plan around, not one universal moment when every version unlocks. 

The smartest preparation is not buying the biggest bundle in a hurry. It is deciding where you will play, who you will play with, and whether an extra week actually fits your schedule. Use this launch guide to turn the build-up into a simple plan, so your first evening is spent playing football rather than sorting out an avoidable purchase or installation mistake.

Watch the time zone as well as the date. SteamDB currently lists the standard Steam unlock at 23:00 UTC on 24 September. Steam's own terms put the start of its seven-day early-access period at 23:00 UTC on 17 September. In Central Europe, those times fall on the following calendar day. Check your own storefront instead of applying the Steam timetable to every console.

Pick the platform before the edition...EA lists Standard and Ultimate editions for PS5, PS4, Xbox Series X|S, Xbox One, Nintendo Switch, Nintendo Switch 2 and PC through the EA app, Steam and Epic Games Store. Availability does not mean every version has identical features: The Grounds, including Clubs, is restricted to PS5, Xbox Series X|S, PC and Switch 2.

Start with the mode you care about most. A friend buying the same title is not enough information for a multiplayer plan: agree on the platform, the installed game version and the mode before anyone checks out. For a solo player, that same conversation becomes a personal question: which device will you genuinely use during a normal week?

Treat early access as a calendar decision. Count the evenings you can actually use between the two launch windows. Paying extra for seven advertised days is a different proposition when work, travel or your friends' schedules leave you with only one available session.

Give your PC a pre-match check...EA's PC requirements list 100 GB of storage. Its minimum specification includes 8 GB RAM and a GTX 1050 Ti or RX 570; the recommended tier lists 12 GB RAM and a GTX 1660 or RX 5600 XT. Steam also requires the EA app and a linked EA account. Treat those as installation requirements, not a promise of a particular frame rate.

Before launch, check your account access, clear adequate space and test the controller you intend to use. Leave room for updates rather than filling the drive to its last gigabyte. These are deliberately unglamorous jobs, but they are easier to finish on a quiet evening than when your friends are waiting for you.

Still undecided? Know what Lite offers...EA SPORTS FC 27 Lite is a free, limited preview scheduled for 25 September at 16:00 UTC. EA names selected modes such as Kick-Off, not unrestricted access to the full game. Its announced platform list covers PlayStation, Xbox and PC storefronts, but does not include Nintendo Switch or Switch 2.

That makes Lite a useful option for sampling the basics before committing, rather than a substitute for every mode discussed in a trailer. Decide what you need to learn from a preview: whether the controls suit you, whether football gaming fits your routine, or whether you would rather wait for more extensive impressions.

Make the first session a useful one...Keep the opening evening manageable. Set your camera and controls, play a low-pressure match, and then spend time in the mode that motivated your purchase. Resist the temptation to judge the whole game while switching settings after every misplaced pass. A consistent setup gives you a clearer sense of what to change next.

Choose the right offer for your season...When comparing FC 27 listings, match the edition, activation platform, region and delivery format. An account listing, a gift and an activation key are different purchase types; the G2A comparison page separates those options. Do not assume that the lowest headline amount describes the same offer you have been comparing elsewhere. 

Pick the version that matches your device, preferred modes and launch plans. The best start to the season is the one you can actually enjoy.

 

mundophone

 

TECH

Qualcomm intros Snapdragon 8 Elite Extreme Gen 6 and Snapdragon 8 Elite Gen 6: World's first 2 nm chips that break the 5 GHz barrier

Qualcomm has unveiled the 2 nm Snapdragon 8 Elite Extreme Gen 6 and Snapdragon 8 Elite Gen 6 SoCs, promising 5 GHz Oryon Prime Core CPU speeds alongside major gains in graphics, AI, imaging, efficiency, and connectivity. The Extreme model adds enhanced on-device AI, dedicated Adreno High Performance Memory, Neural Fusion, and advanced 8K 60 video capture. Devices featuring these chips are expected to arrive in the coming weeks.

It's Snapdragon Summit time and once again, Qualcomm is back with two flagship SoCs. While last year saw the launch of the Snapdragon 8 Elite Gen 5 and the Snapdragon 8 Gen 5, Qualcomm's top tier now has two Snapdragon 8 Elite chips — the Snapdragon 8 Elite Extreme Gen 6 and the Snapdragon 8 Elite Gen 6 — built on an advanced 2 nm process.

Breaking the 5 GHz barrier for the first time...In both the Snapdragon 8 Elite Extreme Gen 6 and the 8 Elite Gen 6, the Oryon CPU cluster features two Prime cores clocked at up to 5.0 GHz alongside six Performance cores running up to 4.0 GHz, backed by a 16 MB Oryon Flex Cache. Qualcomm says this is the world’s first mobile CPU to reach the 5 GHz threshold.

According to the company, the 8 Elite Extreme Gen 6 posts a 13% uplift in raw CPU performance while cutting CPU power consumption by 37% compared to the 8 Elite Gen 5. The standard 8 Elite Gen 6 shares the same 2 nm architecture, custom Oryon CPU design, and 5.0 GHz peak capabilities, and this will be SoC making up the bulk of top-tier offerings from various OEMs.

The new SoCs support LP-DDR5x/6-5300 memory up to 24 GB and UFS 5.0 storage.

Adreno with neural fusion...Like the Apple A19 Pro and now the A20 Pro, Qualcomm’s Adreno GPU now integrates dedicated AI matrix cores capable of handling machine learning workloads alongside traditional rasterization. Tied directly into these matrix cores is Adreno Neural Fusion, Qualcomm’s proprietary answer to AI-driven super resolution and frame generation. 

Qualcomm claims Neural Fusion delivers high frame rates without visual artifacts or smearing while reducing rendering power draws by up to 40% based on an internal Dragon Alley demo.

Overall, the GPU on the Extreme variant yields 44% higher graphics performance and 40% better power efficiency compared to the one in the 8 Elite Gen 5, aided by 18 MB of dedicated Adreno High Performance Memory (HPM).

Engine-level integration is already in place for Unreal Engine (including support for Lumen Global Illumination, MegaLights, and Nanite Virtualized Geometry), Unity, and NetEase's Messiah engine. Major mobile titles slated to support the platform’s graphics pipeline include Honkai: Star Rail, Monster Hunter Outlanders, Neverness to Everness, and more.

AI, imaging, and connectivity...The reengineered Qualcomm Hexagon NPU delivers a 35% jump in performance and a 33% improvement in power efficiency over its predecessor. It incorporates a new Element Accelerator, micro-tile inferencing, and a 50% increase in shared memory. 

Notably, the Extreme tier can run Mixture of Experts (MoE) models exceeding 30 billion parameters directly on device with support for up to 32K context windows. The NPU supports INT2, INT4, INT8, INT16, FP8, and FP16 precisions including mixed precisions.

Complementing the new Hexagon NPU is an overhauled Qualcomm Sensing Hub featuring dual micro-NPUs (delivering an 85% boost in compute and 20% better efficiency) and dual always-sensing ISPs. This hub, which supports up to 200M parameter models, powers Personal Scribe, an on-device utility that ingests messages, emails, and conversations to assemble a private local knowledge graph.

On the imaging side, we have a new triple 20-bit Spectra AI-ISP that Qualcomm says is capable of crunching 256x more granular AI data per pixel (up to 16 bits of AI data per pixel).

The Extreme tier expands mobile video capture to 8K at 60 fps and super slow-motion 4K at 240 fps. For mobile filmmakers, Qualcomm has integrated native hardware support for the Advanced Professional Video (APV) codec, alongside the Elite Color Engine with real-time 3D LUT support and hardware decoding for Versatile Video Coding (VVC/H.266).

Connectivity gets a future-proofing overhaul via the Qualcomm X105 5G Modem-RF system. As an early 3GPP Release 19-ready design, the X105 modem tops out at theoretical download speeds of up to 14.8 Gbps and uplinks of 4.2 Gbps. 

The Snapdragon 8 Elite Extreme Gen 6 and 8 Elite Gen 6 offer 6-antenna support for smartphones along with integrated quad-band (L1, L2, L5, and L6) GNSS, and built-in satellite communication supporting both NB-NTN for messaging and high-bandwidth NR-NTN for voice, data, and video.

Local networking is handled by Qualcomm FastConnect 8800, which delivers peak speeds up to 11.6 Gbps. Qualcomm touts it as the first mobile connectivity system to achieve a 4x4 Wi-Fi configuration with hardware ready for future Wi-Fi 8 (802.11bn) standards, alongside support for Bluetooth 6.0 with High Data Throughput (HDT), Ultra-Wideband (UWB), and Thread.

Snapdragon 8 Elite Extreme Gen 6 vs. 8 Elite Gen 6...While both processors share the same 2 nm foundation, Oryon CPU architecture, and baseline AI engine, Qualcomm has carved out several distinctions for the Extreme variant:

AI capabilities: Both chipsets run local agentic tasks, but the 8 Elite Extreme Gen 6 is equipped with a 50% larger shared NPU memory footprint to host massive 30B+ parameter MoE models and long-context documents.

Gaming: The Extreme variant exclusively features 18 MB of dedicated Adreno High-Performance Memory and the full hardware implementation of Adreno Matrix Cores to run advanced AI models and Neural Fusion for super resolution, and frame generation.

Video capture: While both chips feature intelligent pixel control and 3D LUT support, 8K60 capture, 4K240 slow-motion video, and native APV recording are reserved for the Extreme tier.

Qualcomm confirmed that devices powered by both the Snapdragon 8 Elite Extreme Gen 6 and Snapdragon 8 Elite Gen 6 will begin launching globally from key smartphone manufacturers in the coming weeks.

mundophone

TECH

HP reveals pricing for new 16-inch laptop with AMD Gorgon Halo and 160 GB VRAM

HP has revealed pricing for one of its latest 16-inch laptops. A powerful workstation, the ZBook Ultra G3a combines AMD's Gorgon Halo platform with up to 192 GB RAM, of which 160 GB can be assigned as VRAM. Versions with 192 GB RAM will cost considerably more than those with 64 GB or 128 GB of RAM, though.

HP has shed new light on its latest ZBook Ultra laptop. To recap, the company unveiled the ZBook Ultra G3a last week with AMD's new Gorgon Halo platform. While its US product listing revealed key hardware specifications, it did not indicate when the 16-inch workstation would be available, let alone for how much.

Nonetheless, VideoCardz has stumbled upon pricing for three SKUs. For the time being, this information is readily available on HP's 'Local AI Value Calculator'. Specifically, HP describes the following three SKUs for light, medium and heavy users, respectively:

AMD Ryzen AI Max+ PRO 490, 64 GB RAM, 512 GB SSD, FHD display - $3,899

AMD Ryzen AI Max+ PRO 495, 128 GB RAM, 512 GB SSD, FHD display - $5,999

AMD Ryzen AI Max+ PRO 495, 192 GB RAM, 512 GB SSD, FHD display - $7,449

Other configurations will be available, though. For instance, none of these SKUs include 4K IPS or 2.8K OLED displays, both with 120 Hz refresh rates. Meanwhile, StorageReview reports that the ZBook Ultra G3a delivers up to a 100 W thermal design thanks to a redesigned cooling system, up from 55 W in older models like the ZBook Ultra G1a we reviewed last year (curr. $1,999 on Amazon).

Moreover, StorageReview confirms that the ZBook Ultra G3a contains a 96 Wh battery within its 356 x 240 x 17.9 mm and 1.9 kg housing. The battery can be recharged at 180 W using its Thunderbolt 4 ports, too. Please see our launch article for more details about HP's latest ZBook Ultra.

HP has unveiled the 16-inch ZBook Ultra G3a, the brand's latest mobile workstation built around the new AMD Ryzen AI Max PRO 400 series processor, designed for on-device AI workflows and 3D creation.

AMD's new SoC features up to 16 desktop-class cores and integrated Radeon graphics; it can be configured with up to 192 GB of unified memory, with up to 160 GB allocatable as dedicated VRAM via the BIOS or AMD's application. According to HP, this enables the local execution of large language models—with up to 300 billion parameters—without cloud dependency, powered by an NPU capable of reaching up to 55 TOPS.

On the software front, the ZBook Ultra G3a integrates Perplexity, featuring custom connectors and exclusive HP capabilities designed to accelerate workflows in tools like Autodesk Revit, alongside support for running AI agents locally in the background. The laptop also comes with Windows 11 Pro and Microsoft Copilot.

HP states it has redesigned the device's thermal architecture, featuring center-mounted fans and a fin surface area four times larger than the previous generation; the company claims this delivers 81% higher performance than the ZBook Ultra G1a under heavy workloads.

At just 17.9 mm thick, the ZBook Ultra G3a is described by HP as the thinnest ZBook ever to feature a 16-inch screen. The external casings utilize at least 80% post-industrial recycled plastic, and the keyboard is designed for easy replacement in international deployments, with an internal layout engineered to facilitate repairs. The laptop also features a large haptic trackpad and optional 5G connectivity via the HP Go service.

For video calls, the ZBook Ultra G3a includes a 5MP infrared camera with temporal noise reduction, as well as a physical shutter to block the lens. Audio is handled by Poly Camera Pro and Poly Studio, featuring real-time noise cancellation, dynamic voice leveling, and capabilities such as auto-framing and background blur—all processed on the NPU to save power. The battery promises all-day life, with HP citing up to 16.5 hours in MobileMark 30 tests—a figure the company itself classifies as a preliminary engineering estimate.

mundophone

 

TECH

Reliable leaker contradicts Moore's Law Is Dead's Nvidia RTX 6090 release date

We have seen conflicting rumors regarding the release date of the Nvidia GeForce RTX 6090 based on the Nvidia Rubin architecture. Serial leaker kopite7kimi, who is generally quite reliable, has now provided some clarification on the RTX 6090 release date.

A few days ago, Moore’s Law Is Dead leaked that Nvidia was planning to kickstart the launch of the next-gen GeForce RTX 60 series GPUs in H1 2027. Utilizing the Rubin GPU architecture, MLID claimed that “milestones leading up to a 2027 launch” were put in place months ago. So, the leaker alleged that the RTX 6090 release date could fall sometime in H1 2027. This rumor caused quite a stir online, and kopite7kimi has now sounded off on the subject.

kopite7kimi reports on X that, while they hope “Jensen can see everyone's passion and launch new products for gaming as soon as possible”, the GR20X Rubin gaming GPUs won’t be here until 2028. The GR20X is a “2028 product” as Nvidia has delayed the launch once again, per kopite7kimi.

This directly contradicts MLID’s report which alleged that people assuming a 2028 RTX 60 series launch are “just WRONG”. MLID’s Nvidia source claimed that the RTX 6090 was originally targeting 2026 but was delayed to allow Nvidia to use as much TSMC capacity as possible for AI chips.

Many leakers opposed MLID’s RTX 6090 release date leak, including Jukan who calls the rumor ridiculous and suggests that there is “no way Rubin gaming GPUs are coming out that soon”.

Looking at the current state of the consumer tech market, we don’t see much hope of an H1 2027 RTX 60 series launch. DRAM and storage price are still sky high and the situation is unlikely to resolve in the near term. We don’t think Nvidia is stupid enough to launch new GPUs in a market where gamers can’t upgrade within a reasonable budget. We could be wrong though. So, all we can do is wait and watch.

Kepler_L2 refutes recent RTX 6090 rumours...KeplerL2, a prominent PC hardware leaker, has refuted recent claims that Nvidia’s RTX 60 series would arrive in 2027. A recent report from Moore’s Law is Dead, citing an unnamed Nvidia source, claimed Nvidia was “aiming for H1 2027” for its “Gaming Rubin” (RTX 60 series) GPUs. KeplerL2 wasn’t the first to call out this report, with MEGAsizeGPU also calling it “Fake-as-hell”.

If KeplerL2 is right, Nvidia won’t release its RTX 60 series graphics cards before 2028. This lines up with prior expectations for Nvidia’s next-generation graphics cards. Until very recently, Nvidia were reportedly working on RTX 50 SUPER series graphics cards, upgraded RTX 50 series GPU models with refreshed specifications. Typically, Nvidia waits at least a year between major gaming product launches, which would place their RTX 60 series launch in 2028.

Supply chain concerns ultimately scuppered Nvidia’s RTX 50 SUPER series gaming ambitions. High memory demand makes it hard to launch any new product that requires lots of memory. These same concerns would make launching RTX 60 series GPUs a challenge. If anything, the RTX 60 series would be even more challenging, given the heightened demand seen for next-generation gaming products.

And there are already conflicting reports about when the RTX 60 series will actually arrive.

Earlier rumours suggested Nvidia could launch the RTX 60 series in the second half of 2027, while other reports have pointed towards an even later release.

Adding even more uncertainty to the story, well-known GPU leaker MEGAsizeGPU has pushed back against the latest report, calling it a fake rumour and pointing towards Nvidia’s ongoing supply-chain problems. That makes the alleged first-half 2027 launch far from certain.

Nvidia itself has also yet to announce anything regarding the RTX 60 series or an RTX 6090, so for now, everything surrounding the next generation remains firmly in rumour territory.

If Nvidia really is targeting the first half of 2027, we could potentially hear more about the RTX 60 series at an event such as GTC or Computex next year. But until Nvidia actually confirms its plans, I’d take this particular rumour with a very large pinch of salt.

For now, the RTX 6090 isn’t official, and there is no confirmed release date, pricing or specifications.

Considering how much the GPU market has changed over the past year, Nvidia’s next-generation cards could be very interesting. The bigger question is whether Nvidia can actually produce enough of them at a price that makes sense for gamers.

mundophone

DIGITAL LIFE

Sánchez: AI companies "will never align with the public interest"

Spanish Prime Minister Pedro Sánchez used a meeting with his ministers to comment on Artificial Intelligence—specifically regarding recent developments in the tech world and statements made by leaders of companies in this sector.

At issue are calls from these leaders for greater regulation, which Sánchez interpreted as a possible tactic to secure funding. In the Spanish leader's view, stories about AI models acting on their own initiative might simply be intended to showcase just how advanced the technology has become.

"I believe the risks of uncontrolled Artificial Intelligence are becoming increasingly evident. We see this in numerous news reports about cybersecurity issues stemming from certain applications or models compared to others," Sánchez stated. "But what may also be at play is a strategy by some of these major companies to seek out and attract funding. In short, whatever the case, what is clear is that safety must be an absolute priority in this regard as well."

Regarding safety, Sánchez emphasized the need to "strengthen cyber protection" and to "increase oversight of the most aggressive models."

Sánchez also addressed the topic of regulation, stating that "self-regulation does not work"—a lesson taught by history.

The Spanish head of government recalled William Vanderbilt, a key figure in the expansion of US railways in the late 19th century, who famously declared: "The public be damned. I work only for my shareholders." “I think that phrase symbolizes many things, but what I would like to highlight is that it exemplifies, perhaps better than almost any other, the spirit of that era: the arrogance of a class that believed itself to be above everything and everyone. The only regulation it accepted was that which might originate from within itself—never from public authorities, whom, incidentally, this statement made clear they held in contempt,” noted Sánchez.

Drawing a parallel with the present day, Sánchez argued that such regulation must come from the state itself; one cannot expect companies to act against their own interests.

“The incentives of the few who control cutting-edge industries will never align with the public interest, no matter how much they try to convince us otherwise,” declared Sánchez.

What is the IA360 Plan...The IA360 Plan seeks to address artificial intelligence from all its angles: economic, labor, educational, technological, and regulatory. Hence the reference to the “360 degrees” of its name.

The strategy is structured around four major objectives: to reach a national agreement on the implementation of artificial intelligence, to strengthen Spain's own technological capacity, to make AI an economic engine and a talent creator, as well as to improve regulation, supervision, and cybersecurity.

The central idea is that Spain should not be limited to consuming tools developed by large foreign companies, but should have infrastructure, its own models, trained workers, and rules to control how this technology is used.

A “new social contract” for artificial intelligence...Sánchez has announced that the Government will summon social agents next month —mainly business organizations and unions— to advance in a “major national agreement” on artificial intelligence. The objective is to anticipate the changes that AI will cause in the labor market. Technology can automate tasks, modify professions, increase productivity, and create new jobs, but it can also displace workers, increase surveillance in companies, or introduce algorithms in decisions such as hiring, performance evaluation, or layoffs.

The agreement aims to provide security to workers and establish shared rules on issues such as: the adaptation of jobs, the training and reskilling of employees, the use of algorithms within companies, the protection of labor rights, the distribution of productivity gains, and the transition of the most exposed sectors and professions.

It is not, for now, a closed labor reform nor a new concrete law. The Government proposes to open a dialogue process with employers and unions to build what Sánchez has defined as a “new social contract” for artificial intelligence.

The president has defended that this consensus must also incorporate workers, political parties, public administrations, and other sectors of society.

An observatory will study the impact of AI on employment...The IA360 Plan includes the creation of a permanent observatory on artificial intelligence and the labor market. Its function will be to analyze how the implementation of this technology evolves and what effects it produces on employment.

This body must help determine what tasks are being automated, what professions are changing, where jobs are being destroyed or created, and what new skills workers need. The purpose is to have updated information to adopt measures before technological changes generate imbalances that are difficult to correct.

Sectoral tables will also be established to study the necessary transitions in areas such as education, the financial system, the labor market, or culture.

In this last case, the Government foresees a specific table with representatives from the cultural sector to analyze the effect of artificial intelligence on creation, authors' rights, and the economic value of content.

A gigafactory to reinforce technological autonomy...The second axis of the IA360 Plan consists of reinforcing Spain's “technological muscle.” One of its main projects will be the candidacy to host one of the seven gigafactories of artificial intelligence planned by the European Union.

An AI gigafactory is a large infrastructure equipped with thousands of advanced processors, enormous storage capacities, and high-speed networks. It allows training and executing large-scale artificial intelligence models without completely relying on the technological centers of the United States or China.

The plan also includes the development, together with the Barcelona Supercomputing Center, of models intended for specific applications in areas such as health, energy, the fight against the climate emergency, and the improvement of public services.

Sánchez has added that the new data centers must meet demanding environmental and energy standards, respect natural resources, protect data autonomy, and generate benefits for the territories where they are installed.

The goal: for half of SMEs to use generative AI by 2030...The third axis aims to extend the use of artificial intelligence beyond large companies. The goal set by the Government is that half of the small and medium-sized Spanish enterprises integrate generative AI into their processes before 2030.

In practice, this may mean using it to automate administrative tasks, serve customers, analyze information, prepare budgets, optimize production, or design new products. The challenge is to avoid a gap between large companies, which have the resources to adopt these technologies, and small businesses, which may face more economic and technical difficulties.

The Government links this objective to training. The IA360 Plan foresees adapting the curricula of Secondary Education and Vocational Training so that young people learn to use AI responsibly and productively, without these tools harming their learning.

More control over the most advanced artificial intelligence models...The fourth block of the plan focuses on governance and security. Sánchez has announced the strengthening of the Spanish “cybersecurity shield” and greater oversight of the so-called frontier models.

These are the most powerful and advanced artificial intelligence systems, capable of performing complex tasks and which, precisely because of their capability, may present greater risks if used to launch cyberattacks, spread misinformation, or make decisions without sufficient controls.

The president has called for artificial intelligence with oversight and traceability. That is, systems whose operation can be monitored and whose decisions can be reconstructed or explained, especially when used in areas where public interest is at stake.

AI companies may never fully align with the public interest primarily because their core financial incentives conflict with societal well-being. While public interest prioritizes safety, equity, job stability, and truth, commercial AI development is driven by a market structure that rewards speed, data collection, and profit maximization.This inherent tension is often described by tech critics, economists, and ethics researchers through several key arguments:

1. The profit incentive vs. public good:

Shareholder Primacy: As heavily funded corporations or venture-backed startups, AI companies have a legal and financial duty to maximize returns for investors. When safety testing or ethical guardrails slow down product launches, profit incentives usually win.

The "Move Fast and Break Things" Culture: Silicon Valley relies on being first to market to capture monopoly-like market share. This race discourages the slow, deliberate auditing required to ensure a technology does not harm the public.

2. Data and privacy exploitation:

Surveillance Capitalism: The business model of modern AI relies on scraping massive amounts of data, often without explicit consent, compensation, or regard for individual privacy.

Value Extraction: AI systems train on the collective knowledge, art, and writing of the public to create commercial products that could ultimately automate away the very livelihoods of the people who created that data.

3. Asymmetry of power and accountability:

Regulatory Capture: Tech giants have massive lobbying budgets. They often influence legislation to protect their own market positions rather than to protect consumers, effectively writing the rules of their own oversight

Lack of Democratic Input: Decisions about what AI models are built, what biases they contain, and how they deploy automated systems are made behind closed doors by a small group of tech executives, rather than through democratic or public processes

4. Externalization of costs:

AI companies capture the massive financial profits of automation while shifting the negative consequences onto society:

Misinformation: Maximizing user engagement often means algorithmic feeds promote sensationalist, AI-generated disinformation, damaging democratic discourse.

Environmental Impact: Running massive data centers requires immense amounts of water and energy, contributing heavily to carbon emissions while the public bears the climate costs.

Economic Disruption: Rapid job displacement affects workers and state social safety nets, while the wealth generated by AI concentrates into fewer hands.

Miguel Dias

TECH

AMD report says Zen 6 EPYC Venice smokes NVIDIA Vera in revised agentic AI benchmarks

AMD has updated its performance estimates for its upcoming 6th Gen EPYC 9006 "Venice" server CPUs, and the latest numbers make an aggressive case against Intel and NVIDIA in high-density data center workloads. A new AMD white paper, titled "AMD EPYC Server CPU Architecture And Performance Overview" revises the company's modeling for Venice and compares the 256-core EPYC 9996 against Intel's 128-core Xeon 6980P and NVIDIA's 88-core Vera CPU.

The updated analysis places particular priority on agentic AI infrastructure, where CPUs handle tasks such as orchestration, databases, web services, caching, APIs, retrieval, and other work surrounding accelerator-based AI inference. This work is now comprising a larger and larger percentage of the actual workload of Agentic AI, reinforcing the role of CPUs in the datacenter, once thought to merely be orchestration for GPUs that do all the 'real' work.

AMD expects that the EPYC 9996 will deliver 2.4× the performance of Xeon 6980P in server-side Java, 2.5× in OpenSSL, 3.5× in MongoDB with YCSB, 2.9× in Redis Benchmark, 3.7× in NGINX with WRK, and 2.6× in transaction processing based on TPC-C. Those results are normalized to a 128-core Xeon 6980P system and represent the CPU-heavy enterprise and cloud-native portions of an agentic AI infrastructure stack. Notably, Vera was not included in this modeling, but not because AMD didn't have numbers to compare against.

Besides, the more eye-catching update comes at the rack level. AMD has revisited its earlier 100-kW rack-capacity model from June, which estimated how much aggregate workload throughput each platform could deliver within a fixed rack-level power envelope. The company says the previous analysis put 5th Gen EPYC 9965 at 2.37× the rack-level throughput of its NVIDIA Vera baseline. The revised study now models the 6th Gen EPYC 9996 at 3.4× Vera's rack-level performance.

This is partially because the underlying methodology has changed. AMD's earlier rack estimate was based on a six-workload geometric mean that included SPECrate 2017 Int, while the updated model incorporates SPECrate 2026 Int, server-side Java, NGINX, Redis, Memcached, and TPROC-C. That makes the latest figure a refreshed model rather than simply adding Venice to the old chart. There's also a small but interesting change for AMD's previous-generation part. The earlier 9965 estimate was 2.37× Vera, while the new chart shows the 9965 at about 2.3× in the revised model. In other words, AMD appears to have rerun the calculations rather than simply carrying its previous numbers forward.

However, it's critical to keep in mind with these rack-scale comparisons that AMD is modeling performance rather than publishing results from physical 100-kW racks containing both Venice and Vera hardware. The company describes the figures as estimates based on a combination of benchmark data and system-level assumptions, so they absolutely should not be treated as apples-to-apples measurements of shipping systems.

But AMD's also making a broader argument about the role of CPUs in agentic AI. Rather than treating the CPU as merely a host for an accelerator, the company says increasingly complex AI workflows require substantial CPU resources for orchestration, retrieval, database access, tool execution, networking, and response generation. The latest EPYC 9996 figures reinforce AMD's pitch for Venice as a high-core-count CPU designed to maximize useful work under real-world rack constraints rather than simply chasing peak processor performance.

Still, Vera is a more specialized CPU than Venice, and it has a very different architecture at the platform level. While these simulations put NVIDIA's new chip behind AMD's finest, NVIDIA claims the win in its own testing using different benchmarks and constraints. It's entirely possible that Vera may end up being a better choice for some workloads. We'll just have to wait for independent benchmarks on real hardware to know for sure.

AMD EPYC Venice is expected to outsell NVIDIA Vera by 2027... To make things even more exciting, a Morgan Stanley report predicts that AMD's EPYC Venice CPUs will reach 6.75 million units sold by next year—17% more than NVIDIA's Vera (and 5.4 times the volume compared to 2026).

According to reports, NVIDIA will remain TSMC's primary customer for CoWoS packaging capacity, with the Taiwanese company expected to reach a capacity of 200,000 wafers per month by 2027.

"Team Green" utilizes TSMC's CoWoS packaging solution for two main products: CoWoS-L for AI GPUs (such as Blackwell and Rubin) and CoWoS-R for Vera CPUs.

CoWoS-L production capacity is expected to reach approximately 910,000 units—a 40% year-over-year increase—while Vera shipments are projected to double. This would drive a 52% increase in revenue for NVIDIA compared to the previous year.

Finally, the report projects that NVIDIA's Vera CPUs will reach 5.75 million units by 2027. This is a significant figure for a new CPU launch, especially given NVIDIA's stated goal of becoming the leading CPU supplier by 2026.

Great news (for AMD)...The key takeaway is that NVIDIA is currently facing stiff competition. While its Vera processors are already in mass production at TSMC, the same applies to AMD's next-generation EPYC platform, codenamed Venice.

It is worth noting that Venice is based on the upcoming Zen 6 architecture, which is expected to deliver significant gains in performance and efficiency. As previously highlighted, the report projects that EPYC Venice CPUs will reach a volume of 6.75 million units—17% more than NVIDIA’s Vera (and 5.4 times the volume compared to 2026).

AMD is also utilizing TSMC’s advanced 2nm manufacturing process, whereas Vera is based on 3nm process technology. Furthermore, Vera is designed for agentic AI, while AMD’s EPYC Venice addresses both AI and HPC workloads.

The challenge at hand is not simply AMD versus NVIDIA or NVIDIA versus AMD, but rather the rise of custom silicon, as many AI companies are now venturing into that field.

Just this week, we reported that Google and MediaTek are collaborating on a chip that integrates CPU and AI capabilities into a single package for the next generation of intelligent agents. OpenAI and Amazon are also either in talks to produce or are already manufacturing custom chips, a trend that will intensify the debate between in-house development and external sourcing.

In short, with the growing popularity of custom chip manufacturing, NVIDIA, AMD, and other manufacturers may be facing a critical situation. While the demand for computing power remains high, AI companies producing their own chips will further exacerbate the supply-demand imbalance.

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TECH

What led two security researchers to leave Google DeepMind

There is a difference between an industry outsider warning that artificial intelligence could become dangerous and hearing the same concern from researchers hired to prevent that from happening. That is exactly what happened at Google DeepMind. Two experts focused on the safety of advanced systems left the company within a few months of each other. And the reasons they cited point to a problem that is far from being resolved.

Bilal Chughtai left Google DeepMind in July 2026. His work was directly related to the interpretability and safety of artificial general intelligence (AGI) systems, seeking to understand what occurs inside increasingly complex models.

After leaving, Chughtai began leading an AI safety program at the organization BlueDot Impact.

His concern is particularly serious, yet it must be understood as a personal risk assessment rather than a proven prediction. Chughtai stated his belief that AI systems could pose an existential risk and that the time available to avert extreme scenarios may be running out.

The core of his argument, however, lies elsewhere.

To him, the alignment problem—ensuring that highly capable systems remain consistent with the goals and boundaries set by their developers—remains unsolved.

At the same time, model capabilities continue to advance rapidly.

For this reason, Chughtai advocates for measures such as greater transparency and a more controlled pace of development, rather than a race to build increasingly powerful systems before sufficiently understanding how they work.

This is not a demonstration that AI will inevitably spiral out of control; rather, it is the assessment of someone who worked specifically on trying to figure out how to prevent such a scenario.

The second researcher chose to observe from the outside... A few weeks later, Josh Engels also left Google DeepMind’s AGI safety team.

His decision had a unique aspect: Engels stated that he had turned down offers from OpenAI and Anthropic to work at METR, an independent organization that evaluates advanced models, investigates incidents, and analyzes safety mechanisms. This choice reveals another concern.

Engels is particularly interested in so-called recursive self-improvement: the possibility of AI systems helping to develop even more capable versions of themselves, creating potentially ever-faster cycles of refinement.

The problem, according to him, is that there is currently no guarantee that sufficiently powerful systems would be safe before initiating such a process.

His estimate also drew attention due to its timeframe. Engels considers the possibility of AI systems causing “immense harm” within the next five years to be concerning, though he makes it clear that he cannot assign a precise probability to this scenario.

Once again, this is an individual assessment of a future risk, not a scientific conclusion establishing that this will necessarily happen.

Concern has mounted following incidents involving AI agents with greater autonomy.

In July, during internal cybersecurity evaluations, OpenAI reported that some models managed to bypass certain restrictions, access the internet, exploit vulnerabilities, and reach systems on the Hugging Face platform. The model involved was being used in internal research and was operating under specific evaluation conditions.

The episode does not demonstrate that an AI spontaneously developed its own intentions, nor does it confirm the extreme scenarios described by Chughtai and Engels.

But it does change the nature of certain questions.

Questions regarding autonomy, oversight, and the ability to keep a model within established limits cease to be merely theoretical exercises when experimental systems manage to bypass mechanisms designed to restrict their behavior.

And the departures of researchers concerned about this issue are not limited to Google DeepMind. Jacob Coxon, who also worked at OpenAI and Anthropic, has expressed similar concerns regarding the race to create systems capable of contributing to their own development.

The most curious detail lies in where they worked...The most significant aspect of this story is not simply that some researchers made pessimistic predictions about the future of artificial intelligence.

It is that they were part of the very teams responsible for studying these risks.

Chughtai worked on interpretability and safety. Engels was part of a team dedicated to AGI safety. Both left major labs and went on to advocate—in different ways—for a more cautious approach.

This does not prove that current systems are out of control, nor does it establish that catastrophic predictions will come to pass.

A second departure...Josh Engels worked alongside Chughtai on DeepMind's AGI safety team. He's an MIT graduate. He resigned on September 13, 2026, and turned down job offers from both OpenAI and Anthropic - two of the companies he'd be most likely to warn about. Instead he's joining METR, the independent nonprofit that evaluates whether frontier AI systems are dangerous before they ship. That's a deliberate choice. Engels told reporters he sees a "terrifying chance" that AI systems cause "immense harm" within the next five years, according to Business Standard. His fear is specific: capability gains outpacing anyone's ability to align or evaluate the systems producing them.

At METR, Engels says he'll trace where alignment failures actually originate in training, and test whether the safety mitigations labs already claim to have would hold up if something went wrong. That's not abstract. It's the difference between a company saying it has guardrails and someone independently checking whether those guardrails work.

More than boardroom talk...It's worth being precise about what this is and isn't. Earlier this month, Anthropic chief executive Dario Amodei publicly called for the AI industry to slow its pace, part of a broader run of leadership-level statements urging coordination among labs. Chughtai and Engels are a different animal entirely. Neither is a CEO making a strategic argument from the top. Both are individual researchers, inside Google's own frontier lab, walking out the door and saying, on the record, that they don't trust where the company they worked for is headed.

They're not alone, either. Jacob Coxon left OpenAI for Anthropic, then quit that job too, on September 9. He told colleagues the major labs are "racing to self-improving superintelligence and gambling with our lives," according to TheNextWeb. Three departures, three different companies, the same complaint: the pace of capability gains is outrunning anyone's ability to keep the systems controllable.

Chughtai's own ask is fairly specific. He wants AI companies to slow their competitive race, submit to real transparency, and coordinate on a pace "that society can handle," rather than one set by whichever lab is most afraid of falling behind. That's a harder sell than it sounds. Slow down unilaterally, and you've just handed the frontier to whichever rival didn't.

Google hasn't said much. A DeepMind spokesperson wasn't available to comment outside business hours when Chughtai's post went viral, according to TheNextWeb. That silence is its own kind of answer. Frankly, when two safety researchers from the same team leave within months of each other and neither departure gets a real public response, it says something about how the company is managing the story, whatever it's doing about the underlying concern.

None of this means DeepMind's alignment work has stalled, and neither Chughtai nor Engels claimed it had. What they're both saying, in slightly different words, is that the gap between what AI systems can do and what anyone can verify about their behavior is widening, not closing. Engels put a number on it: five years, "terrifying chance." Chughtai's timeline was vaguer. His verdict was blunter.

Not every departing employee gets this kind of hearing. These two did, because they left the inside of one of the world's most closely watched AI labs and said, in public, exactly what they were afraid of.

However, it reveals an increasingly significant tension in AI development: the capabilities of these models may advance at a different pace than our ability to fully understand, test, and control them.

It is precisely this disparity that turns artificial intelligence safety into a race against the technology's own pace of evolution.

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