Artificial Intelligence - Page 8

TSMC is reportedly ahead of schedule with its next-gen 1.4nm process node, where it will break ground on the new semiconductor fab with an initial investment that could reach $49 billion.

In a new report from Economic Daily News, we're hearing that TSMC suppliers have been informed of the changed plans, just in case things need to be expedited in order to kick off 1.4nm production. TSMC's new "Fab 25" semiconductor facility will be built at the Central Taiwan Science Park which is located near Taichung City, with Fab 25 to comprise of four different plants, with the first plant undergoing trial production towards the tail end of 2027.

TSMC could move into full-scale production of its next-gen 1.4nm process node (A14) in the second half of 2028, with the new 1.4nm node promising a 15% improvement in performance, and a larger 30% in power efficiency. TSMC's other three plants will also be working on the new 1.4nm wafer production, with the report saying TSMC is looking at an even more advanced lithography of 1nm, which we've previously reported would be unleashed in 2029.

NVIDIA CEO Jensen Huang has confirmed that its next-generation Rubin AI GPUs are already in the fabs, and are aiming for volume production in the second half of 2026, after it posted another quarter of record revenue hitting $46.7 billion.

During its recent Q2 2026 earnings call, Jensen confirmed Rubin and its 5 other chips -- Vera CPU, CX9 SuperNIC, Spectrum-X, scale Silicon Photonics processor, and NVLINK 144 switch, are in the fabs at TSMC right now, and will launch in 2026. NVIDIA confirmed that all of these new chips will be ready for volume production in 2H 2026.

Jensen said: "The chips of the Rubin platform are in fab, the Vera CPU, Rubin GPU, CX9 SuperNIC, NVLink 144 scale up switch, Spectrum-X scale out and scale across switch, and the silicon photonics processor. Rubin remains on schedule for volume production next year. Rubin will be our third-generation NVLink rack scale AI supercomputer with a mature and full-scale supply chain. This keeps us on track with our pace of an annual product cadence and continuous innovation across compute, networking, systems and software".

NVIDIA has quite a lot of things to detail and announce at Hot Chips 2025, with one of them being more details on its new Blackwell Ultra GB300 GPU, the fastest AI chip the company has ever made, and it's 50% faster than GB200.

The new entry into the Blackwell AI GPU family before its next-gen Rubin AI chips debut in 2026, the new Blackwell Ultra GB300 features two Reticle-sized Blackwell GPU dies, connecting them through NVIDIA's in-house NV-HBI high-bandwidth interface, making them appear as a single GPU.

The Blackwell Ultra GPU is made on the TSMC N4P process node (which is an optimized 5nm node for NVIDIA) with 208 billion transistors in total, beating out the 185 billion transistors in AMD's new flagship Instinct MI355X AI accelerator. The NV-HBI interface on Blackwell Ultra GB300 has 10TB/sec of bandwidth for the two GPU dies, while functioning as a single chip.

NVIDIA has just unveiled more details on its new Spectrum-X Ethernet Photonics interconnect, using next-gen silicon photonics replacing the traditional optical interconnect, and it's a "game changer" for AI.

During the recent Hot Chips 2025 event, NVIDIA presented its next-gen Spectrum-X Ethernet Photonics interconnect, showing some rather huge improvements in scaling AI factories, and making sure the new interconnect will be an effective and powerful replacement of the traditional optical interconnect.

NVIDIA went into detail about the need of co-packaged photonics, and how massively it can scale AI factories, with the company noting that AI factories use around 17x more optics power compared to a traditional cloud data center, mostly because of the increased in GPU clusters that need dozens of optical transistors in order to talk to other GPUs.

AMD launched its new Instinct MI350 series AI accelerators two months ago, but the company has now detailed the MI350 chip at Hot Chips 2025, all fabbed on TSMC's bleeding-edge N3P process node.

AMD's new Instinct MI350 series AI accelerators feature the CDNA 4 architecture, bringing improved performance and efficiency for AI workloads, as well as support for larger capacities of VRAM and capacity at higher speeds, faster AI training and inference on large models with boosted link speed, and improved power efficiency and performance.

The new flagship Instinct MI355X AI accelerator is liquid-cooled with up to 1400W of power, with its GPU running at 2400MHz, with up to 288GB of HBM3E memory.

NVIDIA's impressive new Jetson Thor system is now out in the market, a tiny compact powerhouse AI system, that Boston Dynamics is integrating into its humanoid robot Atlas.

NVIDIA has published a new blog post on its website detailing the new Jetson Thor chip, which features 7.5x more AI compute power, 3.1x more CPU performance, and 2x more memory than its predecessor, the Jetson Orin. This huge performance leap enables roboticists to process high-speed sensor data and perform visual reasoning at the edge, these are workflows that were too slow to run in dynamic real-world environments.

NVIDIA's new Jetson Thor chip and its new powerful performance upgrades across the board open new possibilities for multimodal AI applications, such as humanoid robots. Jetson Thor modules will be used inside of new robotics computers that can "serve as the brains for robotic systems across research and industry", explains NVIDIA.

NVIDIA has provided more details on its new GB10 Superchip with a Blackwell GPU at the Hot Chips 2025 event, a new chip that will power multiple DGX AI Mini supercomputers.

The first system announced powered by the new NVIDIA GB10 Superchip is the DGX Spark, which is the first step from the company into the "AI PC" segment, with NVIDIA partners also announcing their own GB10-powered "AI PC" platforms. NVIDIA used the event to detail its GB10 Superchip, and how it scales the Blackwell GPU architecture down into small-sized developer and workstation systems.

The new GB10 Superchip has a large number of innovations from the datacenter mixed in with the Blackwell GPU architecture that is traditionally in gaming and AI GPU markets (GeForce RTX 50 series, GB100, GB200, GB300 AI GPUs). In order to create the GB10 Superchip, NVIDIA uses technologies from the datacenter like NVFP4, CUDA, SLANG, TensorRT, vLLM, CX-7 NIC, NVLINK C2C, TMEM, and more, crammed into a Mini-PC platform in a small form factor.

Elon Musk's artificial intelligence company xAI has sued Apple and ChatGPT creator OpenAI in US federal court in Texas on Monday, with xAI alleging Apple and OpenAI are illegally conspiring against the X, formerly Twitter, and Grok app.

The lawsuit claims that OpenAI and Apple have engaged in a deal that doesn't allow for competing AI-based apps, such as xAI's Grok, to reach #1 on Apple App Store rankings. OpenAI and Apple entered into a partnership to integrate ChatGPT into Apple's iOS operating system, which directly injects the power of ChatGPT into Apple's iPhones, iPads, and Macs. The lawsuit claims that part of this agreement between the two companies is to prevent other innovators, such as X and xAI, from competing in Apple App Store rankings.

xAI said it's seeking billions of dollars in damages. Musk wrote on X earlier this month that Apple's behavior "makes it impossible for any AI company besides OpenAI to reach #1 in the App Store," and in another X post on Monday the Tesla CEO wrote, "A million reviews with 4.9 average for @Grok and still Apple refuses to mention Grok on any lists."

Netflix views generative AI as a "valuable creative aid" and key part of the moviemaking or TV show production process in 2025, but only when used "transparently and responsibly." What does that mean? Well, Netflix has posted a new in-depth guideline for its partners and creators who are using generative AI for content production.

"This guidance helps filmmakers, production partners, and vendors understand when and how to use GenAI tools in production," the guideline says. "It also offers a practical tool for assessing and enabling confident GenAI use when producing content for Netflix."

Naturally, as generative AI tools cover a wide range of things and are continuously evolving, Netflix's guidelines were written to protect personal data and creative rights, and comply with laws and regulations such as copyright. There's also a note in there that states that any use of generative AI for content production "does not replace or materially impact work typically done by union-represented individuals, including actors, writers, or crew members, without proper approvals or agreements."

NVIDIA Spectrum-XGS Ethernet is a new technology built for the AI era, and a time where the limits of data centers are demanding scale that often exceeds the capabilities of a single building. With Spectrum-XGS Ethernet, NVIDIA's latest networking technology will help combine the power of multiple data centers into "unified, giga-scale AI super-factories."

The technology was also created due to the limitations of off-the-shelf Ethernet networking, which is prone to latency, jitter, and "unpredictable performance." How Spectrum-XGS Ethernet differs is that it includes NVIDIA Spectrum-X switches and NVIDIA ConnectX-8 SuperNICs to deliver greater bandwidth density with telemetry, latency management, and something called "auto-adjusted distance congestion control."

Spectrum-XGS Ethernet offers nearly double the performance to accelerate multi-GPU and multi-node communication across geographically distributed AI clusters. Designed for hyperscale, the first company that will deploy the technology in its data centers is CoreWeave.

NVIDIA has just unveiled what it says is the fastest mini PC it has ever released. Introducing the Jetson AGX Thor Developer Kit, a mini PC capable of 2070 TFLOPS.

Team Green has added one more model to its expanding Jetson lineup of consumer-facing AI PCs, with the new system, called the Jetson AGX Thor Developer kit, which comes with the Jetson T5000 system-on-module (SoM), which is built on NVIDIA's latest Blackwell architecture. NVIDIA is aiming the mini PC directly at developers working in robotics, engineering, and other various edge workloads.

As for the Jetson T5000 SoM, the 2070 TFLOPS of performance can be attributed to the 2560-core Blackwell-based GPU that features 96 fifth-generation Tensor Cores and Multi-Instance GPU features. Other specifications include the system coming with a 14-core Arm Neoverse-V3AE CPU, 128GB of LPDDR5X memory, four 25GbE network connectors, and support for NVMe storage through PCIe slots.

NVIDIA CEO Jensen Huang made a quick flight and visit to Taiwan yesterday, meeting with key executives at TSMC and announcing that its Blackwell Ultra GB300 is in "full production" and "successfully ramping up".

Jensen's visit to Taiwan also saw the NVIDIA CEO give deep gratitude to the US government for approving export licenses for its H20 AI GPUs to China, and teased that its next-generation Rubin AI GPU architecture is its "most advanced" AI architecture, cooking in TSMC's ovens as you read this.

NVIDIA's next-gen Rubin chips include a dedicated CPU, GPU, scale-up NVLink Switch, and a new silicon photonics processor, which means the entire stack is getting a huge Rubin-infused upgrade. Rubin is a different beast to Blackwell and Hopper, as the changes to Rubin are from the ground up: HBM, the process node, design, and more

NVIDIA CEO Jensen Huang has confirmed that his company has six different Rubin chips in the ovens at TSMC, gearing up for trial production right now.

Jensen is in Taiwan right now for important meetings with key executives at TSMC, with local Taiwanese media talking to Jensen who confirmed that NVIDIA has already taped out six different Rubin chips -- including new CPUs and GPUs -- and that they're at TSMC being prepared for trial production.

The NVIDIA CEO mentioned that the new Rubin chips include a dedicated CPU, GPU, scale-up NVLink Switch, and a new silicon photonics processor, which means the entire stack is getting a huge Rubin-infused upgrade. Rubin is a different beast to Blackwell and Hopper, as the changes to Rubin are from the ground up: HBM, the process node, design, and more.

NVIDIA CEO Jensen Huang has flown to Taiwan to meet with key TSMC executives, while also expressing deep gratitude to the US government for approving export licenses for its H20 AI GPUs to China.

Jensen noted that while China has recently raised concerns about potential security backdoors inside of NVIDIA chips, there are no such vulnerabilities in H20. The NVIDIA CEO added that the company has provided enough explanations to address any concerns that Beijing may have.

During his conversation with President Trump, Jensen underlined the importance of AI, linking it to US chip tariffs, stressing that AI will advance regardless of US participation, but supporting the American technology ecosystem is extremely important. Jensen described TSMC as "one of the greatest companies in human history" and called the Taiwanese contract semiconductor manufacturer a powerful investment destination.

Apple is long overdue to release its next-generation version of Siri, which the company used as marketing to sell its latest generation of iPhone. Unfortunately for consumers and Apple, that release never happened, and instead, consumers got only a few AI-powered upgrades in the form of image editors, custom emoji makers, and several other smaller quality-of-life features.

The big selling points of the latest generation of iPhone were an AI-powered upgrade was for Siri, which would enable deep Siri integration into all of Apple's homebrewed applications and settings. Essentially, Siri would become smart.

However, due to Siri's struggles to meet Apple's extremely high standard for public release, the assistant's level-up has been delayed indefinitely. We are now hearing that the assistant may be powered by a third-party vendor, such as OpenAI, Anthropic, or even Google.

It may sound unlikely, but it's possible that Microsoft could bring functionality to Edge so that users can let Copilot take control of their browser - a feature already available more broadly in the enterprise world.

Leopeva64, a regular leaker of browser-related bits and pieces, discovered a new flag in the Canary version of Edge which allows for enabling a WebUI overlay for a banner that reads: 'Copilot is in control right now'.

This appears to be the very first hint in test builds of Edge that the browser could get a feature whereby Copilot interacts with the web page currently displayed via simulated clicks or key presses.

China is reportedly pushing for the ban of foreign chips made by any company -- namely NVIDIA -- for use in inferencing, which accounts for the most AI demand, according to new reports.

In an article from the well-trusted outlet the Financial Times, it's being reported that according to someone who was "recently summoned" to meet with Beijing policymakers in China are pushing for a ban on foreign-made chips used for AI inferencing, but it won't happen any time soon.

There is a major shortage of domestic AI chip supplies in China, but Beijing hopes to "significantly improve" that in 2026 with multiple advanced production lines coming online. China's foreign ministry said: "As a matter of principle, science, technology, and economic and trade issues should not be politicized, instrumentalized, or weaponized. Containment and suppression will not hold back China's development".

Samsung has reportedly offered its HBM3E memory for NVIDIA's tweaked H20 AI GPU for China, at prices 20-30% lower than South Korean memory rival SK hynix according to new reports.

In a new report from South Korean outlet SEdaily picked up by @Jukanrosleve on X, it's reported that: "at the end of this month, Samsung's 12-layer HBM3E product is also expected to pass NVIDIA's quality test and begin delivery. Industry observers believe that ongoing deadlock in supply and price negotiations between NVIDIA and SK hynix is due to Samsung's imminent delivery".

The article continues: "recently, NVIDIA received approval to export its low-spec H20, developed for China, under the condition of paying 15% of sales to the US government. Samsung is reported to have proposed an HBM3E supply price for the H20 that is 20-30% lower than SK hynix. Accordingly, NVIDIA is insisting on confirming the quality of Samsung's HBM3E and HBM4 before finalizing price agreements with SK hynix".

Samsung Electronics has reportedly had its next-gen HBM4 memory samples have passed NVIDIA's qualification tests to be used inside of its AI GPUs.

In a new report from SEdaily picked up by insider @Jukanrosleve on X, we're hearing that the semiconductor industry said that Samsung's new HBM4 memory samples provided to NVIDIA in their initial prototype and quality tests, and will now enter the "Pre-Production (PP)" stage at the end of this month (August 2025).

A key industry insider said: "It received positive evaluations regarding quality, including yield, and has entered the PP stage for mass-production testing", adding "If it passes PP, mass production will be possible in November-December". This is the final stage before large-scale semiconductor production, with the HBM4 prototype that Samsung provided last month being an "engineering sample" for simple operational tests.

NVIDIA is reportedly cooking up the Blackwell B30A chip that will replace Hopper H20 in China, where the new B30A will beat the H20, but it will offer just half the performance of the Blackwell Ultra B300 AI GPU.

In a new report from Reuters, NVIDIA has reportedly finalized the new B30A chip design for China that is compliant with US regulations, with B30A being faster than H20, but much slower than higher-end AI chip offerings like B200 and the upcoming B300.

NVIDIA's purported B30A will feature a single-chip design, compared to the dual chiplets found on B200 and B300. NVIDIA's upcoming Blackwell Ultra B300 features 50% more performance than B200, with 50% more HBM3E memory, and twice the interconnect speeds. The highest-end B300 AI GPU will feature two reticle-sized GPUs with a total of 15 PetaFLOPS of FP4 compute performance, and up to 288GB of HBM3E memory.