According to a recent investigative report, UK-based Imagination Technologies faces allegations of transferring sensitive GPU intellectual property to Chinese companies with potential military connections. The UK-China Transparency organization claims that following its 2020 acquisition by China-controlled investment firm Canyon Bridge, Imagination provided complete access to its GPU IP to Chinese entities with military connections. The report suggests this included sharing detailed architectural documentation typically reserved for premier clients like Apple. At the center of the controversy are Chinese firms Moore Threads and Biren Technology, which have emerged as significant players in China's AI and GPU sectors. The report indicates Moore Threads maintains connections with military GPU suppliers, while Biren Technology has received partial Russian investment.

The organization argues that Canyon Bridge, which has ties to the state-owned China Reform enterprise, helped these technological transfers to benefit China's military-industrial complex. Imagination Technologies has defended its actions, maintaining that all licensing agreements comply with industry standards. The allegations have sparked renewed debate about foreign ownership of strategic technology assets and the effectiveness of current export controls. When Canyon Bridge acquired Imagination in 2020, security experts raised concerns about potential military applications of the firm's technology. UKCT plans to release additional findings, including information from legal disputes involving Imagination's previous management. Rising concerns over technology transfers have prompted governments to reassess export controls and corporate oversight in the semiconductor industry, as nations struggle to balance international commerce with national security priorities. We are yet to see official government response to this situation.

GEEKOM, a Taiwanese tech company famous for making high quality mini PCs, is heading to CES for the second consecutive year in 2025 with an exciting lineup of new products. Known as the Green Mini PC Global Leader, GEEKOM always focuses on improving the quality and reliability of its products, and it also spares no effort in cutting down carbon emissions and making the world a greener place.

Among the many mini PCs that GEEKOM plans to put on show at CES 2025, there are many industry firsts. The GEEKOM QS1, for instance, is the world's first mini PC powered by a Qualcomm chipset. The tiny computer sports an Arm-based Qualcomm Snapdragon X1E-80-100 processor with twelve 4.0 GHz Oryon CPU cores, a 3.8 TFLOPS Adreno X1-85 GPU and a 45 TOPS Hexagon NPU. It is smart and fast enough to breeze through all of your daily home and office computing chores, yet energy-efficient enough to significantly cut down your electric bill.

VeriSilicon today announced the launch of its latest Vitality architecture Graphics Processing Unit (GPU) IP series, designed to deliver high-performance computing across a wide range of applications, including cloud gaming, AI PC, and both discrete and integrated graphics cards.

VeriSilicon's new generation Vitality GPU architecture delivers exceptional advancements in computational performance with scalability. It incorporates advanced features such as a configurable Tensor Core AI accelerator and a 32 MB to 64 MB Level 3 (L3) cache, offering both powerful processing power and superior energy efficiency. Additionally, the Vitality architecture supports up to 128 channels of cloud gaming per core, addressing the needs of high concurrency and high image quality cloud-based entertainment, while enabling large-scale desktop gaming and applications on Windows systems. With robust support for Microsoft DirectX 12 APIs and AI acceleration libraries, this architecture is ideally suited for a wide range of performance-intensive applications and complex computing workloads.

Microsoft is heavily investing in enabling its company and cloud infrastructure to support the massive AI expansion. The Redmond giant has acquired nearly half a million of the NVIDIA "Hopper" family of GPUs to support this effort. According to market research company Omdia, Microsoft was the biggest hyperscaler, with data center CapEx and GPU expenditure reaching a record high. The company acquired precisely 485,000 NVIDIA "Hopper" GPUs, including H100, H200, and H20, resulting in more than $30 billion spent on servers alone. To put things into perspective, this is about double that of the next-biggest GPU purchaser, Chinese ByteDance, who acquired about 230,000 sanction-abiding H800 GPUs and regular H100s sources from third parties.

Regarding US-based companies, the only ones that have come close to the GPU acquisition rate are Meta, Tesla/xAI, Amazon, and Google. They have acquired around 200,000 GPUs on average while significantly boosting their in-house chip design efforts. "NVIDIA GPUs claimed a tremendously high share of the server capex," Vlad Galabov, director of cloud and data center research at Omdia, noted, adding, "We're close to the peak." Hyperscalers like Amazon, Google, and Meta have been working on their custom solutions for AI training and inference. For example, Google has its TPU, Amazon has its Trainium and Inferentia chips, and Meta has its MTIA. Hyperscalers are eager to develop their in-house solutions, but NVIDIA's grip on the software stack paired with timely product updates seems hard to break. The latest "Blackwell" chips are projected to get even bigger orders, so only the sky (and the local power plant) is the limit.

Axelera AI - a leading edge-inference company - and Arduino, the global leader in open-source hardware and software, today announced a strategic partnership to make high-performance AI at the edge more accessible than ever, building advanced technology solutions based on inference and an open ecosystem. This furthers Axelera AI's strategy to democratize artificial intelligence everywhere.

The collaboration will combine the strengths of Axelera AI's Metis AI Platform with the powerful SOMs from the Arduino Pro range to provide customers with easy-to-use hardware and software to innovate around AI. Users will enjoy the freedom to dictate their own AI journey, thanks to tools that provide unique digital in-memory computing and RISC-V controlled dataflow technology, delivering high performance and usability at a fraction of the cost and power of other solutions available today.

SK hynix Inc. announced today that it has completed development of its high-capacity SSD product, PS1012 U.2, designed for AI data centers. As the era of AI accelerates, the demand for high-performance enterprise SSDs (eSSD) is rapidly increasing, and QLC technology, which enables high capacity, has become the industry standard. In line with this trend, SK hynix has developed a 61 TB product using this technology and introduced it to the market.

SK hynix has been leading the SSD market for AI data centers with Solidigm, a subsidiary which commercialized QLC-based eSSD for the first time in the world. With the development of PS1012, the company expects to build a balanced SSD portfolio, thereby maximizing synergy between the two companies. With the latest 5th generation (Gen 5) PCIe, PS1012 doubles its bandwidth compared to 4th generation based products. As a result, the data transfer speed reaches 32 GT/s (Gig-transfers per second), with the sequential read performance of 13 GB/s (Gigabyte per second), which is twice that of previous generation products.

NVIDIA's RTX 5000 series GPU hardware has been leaked repeatedly in the weeks and months leading up to CES 2025, with previous leaks tipping significant updates for the RTX 5070 Ti in the VRAM department. Now, Inno3D is apparently hinting that the RTX 5000 series will also introduce updated machine learning and AI tools to NVIDIA's GPU line-up. An official CES 2025 teaser published by Inno3D, titled "Inno3D At CES 2025, See You In Las Vegas!" makes mention of potential updates to NVIDIA's AI acceleration suite for both gaming and productivity.

The Inno3D teaser specifically points out "Advanced DLSS Technology," "Enhanced Ray Tracing" with new RT cores, "better integration of AI in gaming and content creation," "AI-Enhanced Power Efficiency," AI-powered upscaling tech for content creators, and optimizations for generative AI tasks. All of this sounds like it builds off of previous NVIDIA technology, like RTX Video Super Resolution, although the mention of content creation suggests that it will be more capable than previous efforts, which were seemingly mostly consumer-focussed. Of course, improved RT cores in the new RTX 5000 GPUs is also expected, although it will seemingly be the first time NVIDIA will use AI to enhance power draw, suggesting that the CES announcement will come with new features for the NVIDIA App. The real standout feature, though, are called "Neural Rendering" and "Advanced DLSS," both of which are new nomenclatures. Of course, Advanced DLSS may simply be Inno3D marketing copy, but Neural Rendering suggests that NVIDIA will "Revolutionize how graphics are processed and displayed," which is about as vague as one could be.

Databricks, the Data and AI company, today announced its Series J funding. The company is raising $10 billion of expected non-dilutive financing and has completed $8.6 billion to date. This funding values Databricks at $62 billion and is led by Thrive Capital. Along with Thrive, the round is co-led by Andreessen Horowitz, DST Global, GIC, Insight Partners and WCM Investment Management. Other significant participants include existing investor Ontario Teachers' Pension Plan and new investors ICONIQ Growth, MGX, Sands Capital and Wellington Management.

The company has seen increased momentum and accelerated growth (over 60% year-over-year) in recent quarters largely due to the unprecedented interest in artificial intelligence. To satisfy customer demand, Databricks intends to invest this capital towards new AI products, acquisitions, and significant expansion of its international go-to-market operations. In addition to fueling its growth, this capital is expected to be used towards providing liquidity for current and former employees, as well as pay related taxes. Finally, this quarter marks the first time the company is expected to achieve positive free cash flow.

NVIDIA is taking the wraps off a new compact generative AI supercomputer, offering increased performance at a lower price with a software upgrade. The new NVIDIA Jetson Orin Nano Super Developer Kit, which fits in the palm of a hand, provides everyone from commercial AI developers to hobbyists and students, gains in generative AI capabilities and performance. And the price is now $249, down from $499.

Available today, it delivers as much as a 1.7x leap in generative AI inference performance, a 70% increase in performance to 67 INT8 TOPS, and a 50% increase in memory bandwidth to 102 GB/s compared with its predecessor. Whether creating LLM chatbots based on retrieval-augmented generation, building a visual AI agent, or deploying AI-based robots, the Jetson Orin Nano Super is an ideal solution to fetch.

Intel's ambitious plan to challenge AMD and NVIDIA in the AI accelerator market may still be a little questionable, according to recent comments from interim co-CEO Michelle Johnston Holthaus at the Barclays 22nd Annual Global Technology Conference. The company's "Falcon Shores" project, which aims to merge Gaudi AI capabilities with Intel's data center GPU technology for HPC workloads, received surprising commentary from Holthaus. "We really need to think about how we go from Gaudi to our first generation of Falcon Shores, which is a GPU," she stated, before acknowledging potential limitations. "And I'll tell you right now, is it going to be wonderful? No, but it is a good first step."

Intel's pragmatic approach to AI hardware development was further highlighted when Holthaus addressed the company's product strategy. Rather than completely overhauling their development pipeline, she emphasized the value of iterative progress: "If you just stop everything and you go back to doing like all new product, products take a really long time to come to market. And so, you know, you're two years to three years out from having something." The co-CEO advocated for a more agile approach, stating, "I'd rather have something that I can do in smaller volume, learn, iterate, and get better so that we can get there." She acknowledged the enduring nature of AI market opportunities, particularly noting the current focus on training while highlighting the potential in other areas: "Obviously, AI is not going away. Obviously training is, you know, the focus today, but there's inference opportunities in other places where there will be different needs from a hardware perspective."

We started Android over a decade ago with a simple idea: transform computing for everyone. Android powers more than just phones—it's on tablets, watches, TVs, cars and more.

Now, we're taking the next step into the future. Advancements in AI are making interacting with computers more natural and conversational. This inflection point enables new extended reality (XR) devices, like headsets and glasses, to understand your intent and the world around you, helping you get things done in entirely new ways.

Imagine being able to step into any world in an instant—from the bustling streets of New York City to the snowy mountain tops of the Alps. These worlds are no longer merely places to observe from afar. They can now be explored and interacted with simply through a gaze, a gesture or your voice. What once seemed like science fiction has become a reality as eXtended reality (XR) transforms how we engage with the world around us.

XR is an umbrella term for technologies that use digital elements to extend or alter reality by merging the physical and digital worlds together. This includes virtual reality (VR), augmented reality (AR), mixed reality (MR) as well as other similar technologies yet to be developed. XR offers infinite possibilities, creating a dynamic spatial canvas where users' sight, sound and motion combine to interact with the outside world. A world that will unlock unprecedented experiences across core areas of life, from working and learning to entertainment, gaming and even health and wellness.

Advantech, a leading provider of AIoT platforms and services, proudly unveils its latest AI acceleration modules: the EAI-1200 and EAI-3300, powered by Hailo-8 AI processors. These modules deliver AI performance of up to 52 TOPS while achieving more than 12 times the power efficiency of comparable AI modules and GPU cards. Designed in standard M.2 and PCIe form factors, the EAI-1200 and EAI-3300 can be seamlessly integrated with diverse x86 and Arm-based platforms, enabling quick upgrades of existing systems and boards to incorporate AI capabilities. With these AI acceleration modules, developers can run inference efficiently on the Hailo-8 NPU while handling application processing primarily on the CPU, optimizing resource allocation. The modules are paired with user-friendly software toolkits, including the Edge AI SDK for seamless integration with HailoRT, the Dataflow Compiler for converting existing models, and TAPPAS, which offers pre-trained application examples. These features accelerate the development of edge-based vision AI applications.

EAI-1200 M.2 AI Module: Accelerating Development for Vision AI Security
The EAI-1200 is an M.2 AI module powered by a single Hailo-8 VPU, delivering up to 26 TOPS of computing performance while consuming approximately 5 watts of power. An optional heatsink supports operation in temperatures ranging from -40 to 65°C, ensuring easy integration. This cost-effective module is especially designed to bundle with Advantech's systems and boards, such as the ARK-1221L, AIR-150, and AFE-R770, enhancing AI applications including baggage screening, workforce safety, and autonomous mobile robots (AMR).

Marvell Technology, Inc. (NASDAQ: MRVL), a leader in data infrastructure semiconductor solutions, today announced that it has pioneered a new custom HBM compute architecture that enables XPUs to achieve greater compute and memory density. The new technology is available to all of its custom silicon customers to improve the performance, efficiency and TCO of their custom XPUs. Marvell is collaborating with its cloud customers and leading HBM manufacturers, Micron, Samsung Electronics, and SK hynix to define and develop custom HBM solutions for next-generation XPUs.

HBM is a critical component integrated within the XPU using advanced 2.5D packaging technology and high-speed industry-standard interfaces. However, the scaling of XPUs is limited by the current standard interface-based architecture. The new Marvell custom HBM compute architecture introduces tailored interfaces to optimize performance, power, die size, and cost for specific XPU designs. This approach considers the compute silicon, HBM stacks, and packaging. By customizing the HBM memory subsystem, including the stack itself, Marvell is advancing customization in cloud data center infrastructure. Marvell is collaborating with major HBM makers to implement this new architecture and meet cloud data center operators' needs.

Fujitsu has previewed its next-generation Monaka processor, a 144-core powerhouse for data center. Satoshi Matsuoka of the RIKEN Center for Computational Science showcased the mechanical sample on social media platform X. The Monaka processor is developed in collaboration with Broadcom and employs an innovative 3.5D eXtreme Dimension System-in-Package architecture featuring four 36-core chiplets manufactured using TSMC's N2 process. These chiplets are stacked face-to-face with SRAM tiles through hybrid copper bonding, utilizing TSMC's N5 process for the cache layer. A distinguishing feature of the Monaka design is its approach to memory architecture. Rather than incorporating HBM, Fujitsu has opted for pure cache dies below compute logic in combination with DDR5 DRAM compatibility, potentially leveraging advanced modules like MR-DIMM and MCR-DIMM.

The processor's I/O die supports cutting-edge interfaces, including DDR5 memory, PCIe 6.0, and CXL 3.0 for seamless integration with modern data center infrastructure. Security in the design is taken care of with the implementation of Armv9-A's Confidential Computing Architecture for enhanced workload isolation. Fujitsu has set ambitious goals for the Monaka processor. The company aims to achieve twice the energy efficiency of current x86 processors by 2027 while maintaining air cooling capabilities. The processor aims to do AI and HPC with the Arm SVE 2 support, which enables vector lengths up to 2048 bits. Scheduled for release during Fujitsu's fiscal year 2027 (April 2026 to March 2027), the Monaka processor is shaping up as a competitor to AMD's EPYC and Intel's Xeon processors.

Synopsys, Inc. today announced the industry's first Ultra Ethernet IP and UALink IP solutions, including controllers, PHYs, and verification IP, to meet the demand for standards-based, high-bandwidth, and low-latency HPC and AI accelerator interconnects. As hyperscale data center infrastructures evolve to support the processing of trillions of parameters in large language models, they must scale to hundreds of thousands of accelerators with highly efficient and fast connections. Synopsys Ultra Ethernet and UALink IP will provide a holistic, low-risk solution for high-speed and low-latency communication to scale-up and scale-out AI architectures.

"For more than 25 years, Synopsys has been at the forefront of providing best-in-class IP solutions that enable designers to accelerate the integration of standards-based functionality," said Neeraj Paliwal, senior vice president of IP product management at Synopsys. "With the industry's first Ultra Ethernet and UALink IP, companies can get a head start on developing a new generation of high-performance chips and systems with broad interoperability to scale future AI and HPC infrastructure."

Advantech, a leading global provider of industrial edge AI solutions, is excited to introduce its GPU server SKY-602E3 equipped with the NVIDIA H200 NVL platform. This powerful combination is set to accelerate the offline LLM for manufacturing, providing unprecedented levels of performance and efficiency. The NVIDIA H200 NVL, requiring 600 W passive cooling, is fully supported by the compact and efficient SKY-602E3 GPU server, making it an ideal solution for demanding edge AI applications.

Core of Factory LLM Deployment: AI Vision
The SKY-602E3 GPU server excels in supporting large language models (LLMs) for AI inference and training. It features four PCIe 5.0 x16 slots, delivering high bandwidth for intensive tasks, and four PCIe 5.0 x8 slots, providing enhanced flexibility for GPU and frame grabber card expansion. The half-width design of the SKY-602E3 makes it an excellent choice for workstation environments. Additionally, the server can be equipped with the NVIDIA H200 NVL platform, which offers 1.7x more performance than the NVIDIA H100 NVL, freeing up additional PCIe slots for other expansion needs.

TrendForce's latest investigations found that the enterprise SSD market experienced significant growth in 3Q24, driven by robust demand from AI-related applications. Prices surged as suppliers struggled to keep pace with market needs, pushing overall industry revenue up by an impressive 28.6% QoQ. Demand for high-capacity models was especially strong, fueled by the arrival of NVIDIA's H-series products and sustained orders for AI training servers. As a result, the total procurement volume for enterprise SSDs rose 15% compared to the previous quarter.

Looking ahead to 4Q24, TrendForce forecasts a slowdown in enterprise SSD revenue as procurement demand begins to cool. Total procurement volume is expected to dip, with the peak buying period behind and server OEM orders being slightly revised downward. As shipment volume declines, overall industry revenue is also projected to decrease in the fourth quarter.

Renowned for its groundbreaking innovations in computing technology, GIGABYTE Technology continues to spearhead advancements that redefine the industry. From January 7 to 10, 2025, GIGABYTE will participate in CES, showcasing its latest breakthroughs in high-performance computing and personal computing solutions. Under the theme "ACCEVOLUTION," GIGABYTE's booth will present a diverse range of cutting-edge technologies. Highlights include:

• Rack-scale cluster computing solution for large-scale data centers
• AI servers supporting next-generation "superchips"
• Advanced cooling technologies that optimize energy efficiency and performance
• Workstations tailored for smaller-scale workloads
• Mini-PCs, embedded systems, and in-vehicle platforms designed for endpoint deployment and commercial applications

Marvell Technology, Inc., a leader in data infrastructure semiconductor solutions, today announced that it has pioneered a new custom HBM compute architecture that enables XPUs to achieve greater compute and memory density. The new technology is available to all of its custom silicon customers to improve the performance, efficiency and TCO of their custom XPUs. Marvell is collaborating with its cloud customers and leading HBM manufacturers, Micron, Samsung Electronics, and SK hynix to define and develop custom HBM solutions for next-generation XPUs.

HBM is a critical component integrated within the XPU using advanced 2.5D packaging technology and high-speed industry-standard interfaces. However, the scaling of XPUs is limited by the current standard interface-based architecture. The new Marvell custom HBM compute architecture introduces tailored interfaces to optimize performance, power, die size, and cost for specific XPU designs. This approach considers the compute silicon, HBM stacks, and packaging. By customizing the HBM memory subsystem, including the stack itself, Marvell is advancing customization in cloud data center infrastructure. Marvell is collaborating with major HBM makers to implement this new architecture and meet cloud data center operators' needs.

Microsoft has finally opened the iron gate guarding the Windows 11 upgrade for systems running incompatible hardware, including systems lacking TPM 2.0. This is excellent news for users who are rocking older systems or have been without the TPM 2.0 module in their system but want to upgrade to the newer OS release. Microsoft opened an official support page, noting that "Installing Windows 11 on a device that doesn't meet Windows 11 minimum system requirements isn't recommended. If Windows 11 is installed on ineligible hardware, you should be comfortable assuming the risk of running into compatibility issues. A device might malfunction due to these compatibility or other issues. Devices that don't meet these system requirements aren't guaranteed to receive updates, including but not limited to security updates."

However, an interesting disclaimer appears once a user tries to install Windows 11 on a PC that doesn't meet minimum requirements:

MicrosoftThis PC doesn't meet the minimum system requirements for running Windows 11 - these requirements help ensure a more reliable and higher quality experience. Installing Windows 11 on this PC is not recommended and may result in compatibility issues. If you proceed with installing Windows 11, your PC will no longer be supported and won't be entitled to receive updates. Damages to your PC due to lack of compatibility aren't covered under the manufacturer warranty. By selecting Accept, you are acknowledging that you read and understand this statement.

Google Quantum AI lab has announced a huge advancement in quantum computing with its new Willow processor. The chip demonstrated remarkable error correction capabilities and computational power beyond traditional supercomputers, including ExaFLOP machines such as Frontier and El Capitan. In research published in Nature, Google's team showed that Willow can exponentially reduce error rates as more qubits are added to the system—a feat known as operating "below threshold" that has been a major challenge in quantum computing since 1995. Using arrays of quantum bits in increasingly larger grids, the team successfully cut error rates in half with each expansion. The chip's performance is particularly recorded in random circuit sampling (RCS), where Willow completed calculations in under five minutes. Something like that would take today's fastest supercomputer approximately ten septillion years to solve—a timespan far greater than the universe's age.

Manufactured at Google's specialized facility in Santa Barbara, the 105-qubit Willow chip also achieved impressive coherence times, with qubits maintaining their quantum states for up to 100 microseconds—five times longer than previous generations. Dr. Hartmut Neven, who founded Google Quantum AI in 2012, emphasized that the breakthrough brings quantum computing closer to scaling into more complex systems for data processing. Potential applications include discovering new medicines, designing more efficient batteries for electric vehicles, and accelerating fusion energy research. The next challenge for Google's quantum team is demonstrating a "useful, beyond-classical" computation that addresses practical applications. While Willow has shown superior performance in benchmark tests, researchers are now focused on developing algorithms that can tackle commercially relevant problems that are impossible for traditional computers to solve.

During the prestigious IEDM 2024 conference, NVIDIA presented its vision for the future AI accelerator design, which the company plans to chase after in future accelerator iterations. Currently, the limits of chip packaging and silicon innovation are being stretched. However, future AI accelerators might need some additional verticals to gain the required performance improvement. The proposed design at IEDM 24 introduces silicon photonics (SiPh) at the center stage. NVIDIA's architecture calls for 12 SiPh connections for intrachip and interchip connections, with three connections per GPU tile across four GPU tiles per tier. This marks a significant departure from traditional interconnect technologies, which in the past have been limited by the natural properties of copper.

Perhaps the most striking aspect of NVIDIA's vision is the introduction of so-called "GPU tiers"—a novel approach that appears to stack GPU components vertically. This is complemented by an advanced 3D stacked DRAM configuration featuring six memory units per tile, enabling fine-grained memory access and substantially improved bandwidth. This stacked DRAM would have a direct electrical connection to the GPU tiles, mimicking the AMD 3D V-Cache on a larger scale. However, the timeline for implementation reflects the significant technological hurdles that must be overcome. The scale-up of silicon photonics manufacturing presents a particular challenge, with NVIDIA requiring the capacity to produce over one million SiPh connections monthly to make the design commercially viable. NVIDIA has invested in Lightmatter, which builds photonic packages for scaling the compute, so some form of its technology could end up in future NVIDIA accelerators

TSMC is reportedly negotiating with NVIDIA to manufacture advanced "Blackwell" GPUs in its Arizona facility. First reported by Reuters, this partnership could mark another major shift in AI chip production toward US soil. The discussion centers around TSMC's Fab 21 in Phoenix, Arizona, specializing in 4 nm and 5 nm chip production. NVIDIA's Blackwell GPUs utilize TSMC's 4NP process technology, making the Arizona facility a technically viable production site. However, the proposed arrangement faces several logistical challenges. A key issue is the absence of advanced packaging facilities in the United States. There is Amkor that planned to do advanced packaging, but it's only scheduled to begin packaging in 2027. TSMC's sophisticated CoWoS packaging technology is currently available only in Taiwan. This means that chips manufactured in Arizona would need to be shipped back to Taiwan for final assembly, potentially increasing production costs.

While alternative solutions exist, such as redesigning the chips to use Intel's packaging technology or focusing on gaming GPU production in Arizona, these options present their own complications. Intel's packaging methods would likely increase costs, and the current absence of graphics card manufacturing infrastructure in the US makes domestic gaming GPU production less practical. Both TSMC and NVIDIA have declined to comment on the ongoing negotiations, as this is confidential information unknown to the public. Interestingly, TSMC's Arizona facility has already attracted a few more US firms for domestic manufacturing, like Apple, rumored to manufacture its A16 Bionic chip and AMD with high-performance designs, likely either EPYC or Instinct MI chips.

For better or worse, generative AI has been a disruptive force in many industries, although its reception in video games has been lukewarm at best, with attempts at integrating AI-powered NPCs into games failing to impress most gamers. Now, Google's DeepMind AI has a new model called Genie 2, which can supposedly be used to generate "action-controllable, playable, 3D environments for training and evaluating embodied agents." All the environments generated by Genie 2 can supposedly be interacted with, whether by a human piloting a character with a mouse and keyboard or an AI-controlled NPC, although it's unclear what the behind-the-scenes code and optimizations look like, both aspects of which will be key to any real-world applications of the tech. Google says worlds created by Genie 2 can simulate consequences of actions in addition to the world itself, all in real-time. This means that when a player interacts with a world generated by Genie 2, the AI will respond with what its model suggests is the result of that action (like stepping on a leaf resulting in the destruction of said leaf). This extends to things like lighting, reflections, and physics, with Google showing off some impressively accurate water, volumetric effects, and accurate gravity.

In a demo video, Google showed a number of different AI-generated worlds, each with their own interactive characters, from a spaceship interior being explored by an astronaut to a robot taking a stroll in a futuristic cyberpunk urban environment, and even a sailboat sailing over water and a cowboy riding through some grassy plains on horseback. What's perhaps most interesting about Genie 2's generated environments is that Genie has apparently given each world a different perspective and camera control scheme. Some of the examples shown are first-person, while others are third-person with the camera either locked to the character or free-floating around the character. Of course, being generative AI, there is some weirdness, and Google clearly chose its demo clips carefully to avoid graphical anomalies from taking center stage. What's more, at least a few clips seem to very strongly resemble worlds from popular video games, Assassin's Creed, Red Dead Redemption, Sony's Horizon franchise, and what appears to be a mix of various sci-fi games, including Warframe, Destiny, Mass Effect, and Subnautica. This isn't surprising, since the worlds Google used to showcase the AI are all generated with an image and text prompt as inputs, and, given what Google says it used as training data used, it seems likely that gaming clips from those games made it into the AI model's training data.