Artificial Intelligence

NVIDIA is reportedly cutting its B40 AI GPU production from an estimated 1.5-2M units to 900,000 units as Chinese AI companies are reportedly using RTX 5090 gaming graphics cards, as well as Hopper and locally-sourced AI chips instead.

In a new market report posted by insider @Jukan on X, we're hearing that NVIDIA's new B40 AI GPU, which complies with US export restrictions and is ready for China, is seeing its production cut, with an expected 1.5M to 2M units in 2H 2025, reduced to just 900,000 units.

The reason behind this is that the analysts' last "field trip" throughout Asia suggests that China's AI inference compute is still "largely dependent" on RTX 5090 gaming graphics cards (thanks to 32GB of speedy GDDR7 memory) and "previously improved" Hopper AI GPUs, and "some local chips".

NVIDIA will be the first customer for TSMC on its next-generation A16 process (1.6nm) with production taking off in 2027 at its Taiwan fab, while Apple will reportedly skip A16 and use the A4 (1.4nm) process.

We've been hearing rumors that NVIDIA would be the first customer for TSMC on its new A16 process node in 2026, but it looks like that will now take place in 2027, while other rumors said Apple was "not yet in talks" with TSMC to use its A16, with this new report suggesting the company is going directly to A14.

The new DigiTimes report also confirms that TSMC's plans to build 3 more 2nm semiconductor fabs in Taiwan in order to keep up with the ever-growing demand, with industry insiders saying TSMC's 2026 capex could reach $48-$50 billion, up from $40-42 billion this year. TSMC's advanced capacity at its Arizona fabs will also be going through some changes:

Microsoft has proclaimed on multiple occasions that Windows 11 and Windows in general are transforming into an 'Agentic OS,' and the latest 'Experimental Agentic Features' included in a recent Windows 11 preview build offer a first honest look at a Windows PC becoming an AI PC. The quick summary is that AI Agents will have their own accounts and privileges and run in the background while you're using your PC, leading to a situation where multiple users are logged in to your PC, with you being the only human.

Basically, you'll be able to interact with your PC using natural language. At the same time, these AI Agents will handle everything from launching office apps and creating charts to browsing, finding a deal, buying a new appliance, and searching through images to find something specific. These agents will run in the background, with Copilot as the primary interface.

Microsoft notes that you'll be able to monitor AI Agents like you can apps, while also confirming that these agents are prone to hallucinating and can even be tricked into installing malware or sending sensitive data and files to bad actors, which makes you wonder why anyone would enable these 'Experimental Agentic Features' when Microsoft is adamant that they pose a real security risk.

AMD is reportedly working on a couple of new Radeon AI PRO R9000 "RDNA 4" series consumer-grade AI cards, with a tease of the R9700S and R9600D leaking out.

AMD has officially listed its new consumer-grade Radeon AI PRO R9700S and Radeon AI PRO R9600D cards on its own support page, spotted by @KOMACHI_ENSAKA and @RubyRapids on X. We don't have any specifications on the new cards, and nothing official was posted on AMD's support page apart from the names of the two new Radeon AI PRO R9000 series "RDNA 4" cards.

Currently, AMD has its Radeon AI PRO R9700 workstation GPU on the market for $1299, featuring the full Navi 48 GPU core and up to 32GB of VRAM for the desktop. On the laptop side however, RDNA 4 hasn't graced any gaming laptops so far... so the new Radeon AI PRO R9700S could be a flagship RDNA 4-based offering for laptops, with the same Navi 48 GPU + 32GB of GDDR6 memory as the desktop R9700 variant.

The path towards combining both GPUs and HBM memory chips together is here, with NVIDIA and Meta "reviewing plans" to mount GPU cores on HBM.

The general concept is that placing GPU cores into the base die at the bottom of the HBM stack, with Meta and NVIDIA working with HBM leaders SK hynix and Samsung. In a new report from Korean outlet SEDaily and multiple industry insiders "familiar with the matter" that "next-generation 'custom HBM' architectures are being discussed, and among them, a structure that directly integrates GPU cores into the HBM base die is being pursued".

HBM (High Bandwidth Memory) is widely used on AI GPUs from both NVIDIA and AMD, with next-gen HBM4 right around the corner, and HBM4E not far behind it, and it's built perfectly for AI applications and mass amounts of data through its incredibly high memory bandwidth.

The IEEE ISSCC 2026 conference kicks off in February 2026, where SK hynix and Samsung will be showing off their very latest GDDR7, LPDDR6, and HBM4 memory products.

In the list of sessions at ISSCC 2026 is "DRAM, SRAM, and Non-Volatile Memories" and just that section alone -- outside of the hundreds of topics and sessions across the 5 days, we have SK hynix presenting its 1cnm SRAM 16Gb LPDDR6 memory with 14.4Gbps per pin of bandwidth, and its new 48Gbps 24Gb modules of GDDR7 memory for "mid-range" inference AI performance.

Samsung on the other hand will be showing off its new 36GB HBM4 modules with 3.3TB/sec of bandwidth per channel, and its new 16Gb LPDDR6 memory with 12.8Gbps of bandwidth.

NVIDIA is cooking up a new China-exclusive GPU with the new RTX 6000D Blackwell GPU, recently tested on Geekbench and teases what is happening under the hood.

The company has sliced the CUDA core count, VRAM capacity, and GPU clock speeds of its new RTX 6000D "Blackwell Pro for China" GPU. NVIDIA created the RTX 6000D after ever-increasing US export restrictions for AI hardware were imposed, with the RTX 6000D Blackwell GPU being a different SKU than the one available globally.

Inside, NVIDIA's new RTX 6000D GPU for China features 156 SMs or 19,968 CUDA cores, representing 17% less CUDA cores than the RTX PRO 6000, as well as less VRAM with 84GB of GDDR7 memory compared to 96GB GDDR7 on the full RTX PRO 6000. We should expect to see NVIDIA using 3GB GDDR7 memory modules on the RTX 6000D for China, indicating a 448-bit memory bus compared to the 512-bit memory bus on the RTX PRO 6000.

The unfortunate user with an expensive, dead NVIDIA RTX PRO 6000 card worth $10,000 has just had his card replaced by the company, as used PCIe boards enter the Chinese market.

Just a few days ago we reported that a user had sent NorthridgeFix a damaged NVIDIA RTX PRO 6000 card, which had been damaged during transport as the user kept the $10,000 card installed into the PCIe slot in his motherboard, and the PCIe board snapped. The board isn't replaceable by NVIDIA and the company doesn't sell any spare boards, so $10K was flushed down the drain... until now.

That was just a few days ago, with NVIDIA reaching out to Northridge Fix saying: "we recently saw your video featuring the NVIDIA RTX PRO 6000 GPU that a customer sent to you. We would like to provide a replacement unit to the customer. Also, if the original RTX PRO 6000 Blackwell Server Edition GPU can be returned to us, we'd like our technical team to help inspect and troubleshoot".

AMD has just unveiled one of the first models in its next-gen Instinct MI400 AI GPU family with the introduction of the Instinct MI430X, which was specifically created for HPC system buildouts, based on the new CDNA 5 architecture and using next-gen HBM4 memory.

In a new blog post, the company teased its new Instinct MI430X AI chip which was designed for large-scale AI environments, with some of the details unveiled on the new MI430X accelerator. AMD's new Instinct MI430X will feature the next-generation CDNA 5 architecture, and a huge 432GB of next-gen HBM4 memory with up to 19.6TB/sec of memory bandwidth.

AMD says its new MI430X is a "true successor" to the MI300A, with improvements on paper between both the chips -- the new CDNA 5 architecture, more VRAM and next-gen HBM4 with huge amounts more memory bandwidth -- making the MI430X ready for next-gen AI workloads.

Elon Musk has recently said that Tesla will need between 100 billion and 200 billion AI chips per year, and that both TSMC and Samsung can't meet that demand in the timeline he wants. Elon doubled-down on his plans for Tesla to build its own massive semiconductor fab.

The comments from the SpaceX and Tesla founder were made during the Baron Investment Conference, where he said that chip giant partners like TSMC and Samsung Foundry he has "tremendous respect for" but they need 5 years to get a new chip fab plant up and running, and he added that those 5 years are "an eternity".

Elon continued, explaining: "The production speed doesn't seem fast enough. When I asked them how long it would take from groundbreaking to completion of a new chip factory, they told me it would take five years to start production. I felt that five years was an endless wait for me".

Samsung has officially announced its mass production results for its new 2nm GAA process node, saying that it's 5% faster, 8% more efficient, and has 5% more area than its current 3nm GAA process.

Samsung Electronics announced the update on its new 2nm GAA process node mass production during its Q3 2025 earnings report, stating: "the 2nm first-generation gate-all-around (GAA) process has improved performance by 5%, power efficiency by 8%, and area by 5% compared to the 3nm second-generation process".

TSMC absolutely dominates semiconductor manufacturing, where according to its Q2 2025 sales, it owns 70.2% global market share, while Samsung Foundry only holds 7.3% of the global silicon manufacturing market. TSMC has enjoyed mega-success in the AI market, with big tech customers like Apple and NVIDIA using its 3nm process node for their latest silicon.

AMD confirms its next-gen Instinct MI400 AI accelerators for 2026 based on the new CDNA 5 architecture, with a huge 432GB of HBM4 memory, where it will compete against NVIDIA's next-gen Vera Rubin AI platform.

During its Financial Analysts Day event, the company confirmed its new MI400 series will come in multiple variants: MI455X is for training and inference, while the MI430X will be available in HPC variants.

AMD's new Instinct MI400 series feature the new CDNA 5 architecture, huge amounts of ultra-fast HBM4 memory, more AI formats and higher throughput, and standard-based rack-scale networking (UALoE, UAL, and UEC).

During a recent 'The Minds of Modern AI' roundtable discussion and interview with the Financial Times, editor Madhumita Murgia brought up the question or idea that we're currently living in an 'AI bubble' similar to the dotcom bubble of the 1990s, and that sooner or later it's going to burst and the market will "correct" itself.

For those who need a refresher or were too young to remember the 'dot-com bubble' of the late 1990s, this refers to a time when the stock market and investors saw the rise of the internet and the concept of the "World Wide Web" and decided to invest heavily in dot-com startups and companies. The bubble eventually burst, leaving only a few companies, such as Amazon, intact.

The reason people are comparing the AI boom to the dot-com boom is that they see parallels in the rapid growth and the lack of signs that AI investments are leading to actual profits. In response to the comparison and question posed to NVIDIA CEO Jensen Huang, his initial brief answer is 'no'; the AI boom is not like the dot-com boom because back then, the majority of the fiber was "dark," meaning unused.

NVIDIA's next-generation Rubin GPUs have reportedly entered production, with the company also having all major DRAM manufacturers provide it with HBM4 memory samples.

NVIDIA CEO Jensen Huang has been in Taiwan over the last few days, visiting TSMC and having extensive discussions with the semiconductor giant, with NVIDIA seeking more 3nm production capacity for its Blackwell and Rubin AI GPUs, seeing TSMC increase 3nm production by 50%. In even more recent news, UDN reports that NVIDIA's next-gen Rubin AI GPUs have now entered production, and that the company has received HBM4 memory samples, too.

NVIDIA only just received its first Rubin GPU at its labs a few days ago, and now we're at the production stage in just a few days, which is pretty crazy. UDN reports that regarding product and supply chain timing, Jensen said that demand for Blackwell is strong, and that it's not just for GPUs. Jensen explained: "NVIDIA is also manufacturing CPUs, network chips, switches, and many other chips related to Blackwell".

NVIDIA CEO Jensen Huang has asked TSMC to increase its 3nm production by 50% as demand for the company's Blackwell AI chips continues to swell, as the groundwork is being laid down for its next-gen Rubin AI GPUs.

Jensen is in Taiwan right now, where he was hanging out with TSMC founder Morris Chang, where he praised the country and TSMC, saying: "without TSMC, there would be no NVIDIA today". Jensen has visited TSMC's new Tainan 3nm semiconductor fab, while also visiting Hsinchu to participate in TSMC's annual sports day.

TSMC has fresh new additional orders for NVIDIA AI chips fabbed on its 3nm process, which will require TSMC to expand the production capacity of its 3nm process fabbed at its Southern Taiwan Science Park 18B fab, increasing from the current 100,000 to 110,000 wafers per month, to 160,000 wafers per month. This is a huge increase of 45% to 50%, with NVIDIA's additional monthly wafer requirements at around 35,000 wafers.

TSMC has reportedly started the foundation pile construction for its new 1.4nm process node semiconductor plant, with the new fab coming in at a cost of a whopping $48.5 billion.

In a new report from UDN, we're hearing that TSMC kicked off construction on its new 1.4nm semiconductor plant in the Central Taiwan Science Park yesterday, but didn't hold a public groundbreaking ceremony, and kept a rather low profile about it all. TSMC is expected to complete risk trial production before the end of 2027, with mass production kicking off in 2028.

TSMC said yesterday that the groundbreaking had started for the new fab in the Taichung Science Park, with the second phase of the expansion project to work on advanced 1.4nm (A14) processes. Construction was meant to start this year, but it is now planned to "proceed as planned" reports UDN.

AMD has its new Instinct MI308 AI GPU in the ovens and ready to deploy into the Chinese AI market, after the Trump administration approved some licenses for its new MI308 chip to be sold in China.

During the record Q3 2025 earnings call, AMD CEO Dr. Lisa Su said that the company had received approval for licenses to export its Instinct MI308 AI chips to China. We don't know the detailed specifications of the MI308 AI chip just yet, but it should be similar to NVIDIA's popular H20 AI GPU.

AMD CEO Lisa Su said: "So look, it's still a pretty dynamic situation with MI308. So that's the reason that we did not include any MI308 revenue in the Q4 guide. We have received some licenses for MI308, so we're appreciative of the administration supporting some licenses for MI308. We're still working with our customers on the demand environment and sort of what the overall opportunity is".

Google Maps is getting a Gemini and AI-powered upgrade with new features designed to simplify and enhance navigation and discovery. With the integrated AI assistant, you can communicate hands-free with Google Maps to discover specific points of interest on your journey or check for things like EV chargers. And if you're stuck in traffic or delayed, Google Maps can share your live ETA with friends.

With Google Calendar integration (an opt-in feature) and access to Gemini, you can also use natural language to add reminders, schedule appointments, and catch up on news. When it comes to specific Google Maps improvements and upgrades, the addition of Gemini will now use landmarks for guidance. So instead of saying "turn left in 300 feet," it will say "turn left at the BP gas station," restaurant, or clearly identifiable building, by name.

This is an impressive and welcome feature that adds a more human touch for navigation, which leverages Google Maps' updated and comprehensive information on 250 million places, as well as cross-referencing that data with Street View images to ensure that landmarks are visible from the street. This new landmark-based navigation is now rolling out in the U.S. on both Android and iOS.

AMD has just posted its Q3 2025 financial report and during the earnings call, AMD CEO Dr. Lisa Su, reaffirmed that the company's next-generation EPYC "Venice" CPUs fabbed on TSMC's new 2nm process node, will be launching in 2026.

AMD already has its next-gen EPYC Venice CPUs in the labs, promising big performance upgrades with up to 256 cores and 512 threads on a new EPYC Venice processor. We are to expect an impressive 70% performance boost with more memory bandwidth, too, with Lisa saying: "We remain on track to launch our next-generation 2-nanometer Venice processors in 2026. Venice silicon is in the labs and performing very well, delivering substantial gains in performance, efficiency and compute density".

Not only will AMD be launching its next-gen EPYC "Venice" CPUs, but it will simultaneously launch its next-gen Instinct MI400 AI accelerator series. During the earnings call, Lisa said that AMD's new MI400 series AI accelerators combine a new compute engine with industry-leading memory capacity -- 432GB of next-gen HBM4 memory and 19.6TB/sec bandwidth -- and advanced networking capabilities to "deliver a major leap in performance for the most demanding AI training and inference workloads".

Google is joining in on the recent push to get data centers off Earth and into orbit in an effort to harness the endless solar energy of the Sun.

It was only recently that NVIDIA announced that a company called Starcloud is sending NVIDIA's AI GPUs to space, marking a moment in history when it comes to space-based compute, as the Starcloud-1 satellite offers 100x more GPU compute than any previous space-based operation. Why are companies looking to space for data centers? There are a few simple reasons.

The vacuum of space acts as an infinite heatsink, and the solar energy produced by the Sun is endless and free. Just those two facts combined mean energy costs in space will be 10x cheaper than land-based operations, even when including the cost to launch the data center, according to Starcloud. Google has now recognized the potential of space-based data centers with its announcement of a "moonshot" research project called "Project Suncatcher".