With a market capitalization of USD $3.34 trillion, NVIDIA has beaten Microsoft to become the world's most valuable company. The company's valuation doubled year-over-year, thanks to its meteoric rise as the preeminent manufacturer of AI accelerator chips that's in a dominant position to support the productization and mainstreaming of generative AI, and the company only expects further growth of the AI acceleration industry. Chris Penrose, global head of business development for telecom at NVIDIA, speaking at an event in Copenhagen, said "The generative AI journey is really transforming businesses and telcos around the world," he said. "We're just at the beginning." BBC notes that eight years ago, NVIDIA was worth less than 1% of its current valuation.

In the most recent quarterly result, Q1 fiscal 2025, NVIDIA posted a revenue of $26 billion, with the Data Center business handling the company's AI GPUs making up the lion's share of it, at $22.6 billion. The Gaming and AI PC segment, which handles the GeForce GPU product line that used to be NVIDIA's main breadwinner until a few years ago, made just $2.6 billion, in stark contrast. This highlights that NVIDIA is now mainly a data center acceleration hardware company that happens to sell visual compute products on the side, along with a constellation of smaller product lines such as robotics and automobile self-driving hardware. With NVIDIA at the number-1 spot, the top-5 most valuable companies in the world are all American tech giants—NVIDIA, Microsoft, Apple, Alphabet (Google), and Amazon. The other companies in the top-10 list include Meta and Broadcom.

NVIDIA's CEO Jensen Huang said on June 5th that TSMC's stock price is too low, and he agrees with new TSMC chairman C. C. Wei's idea about TSMC's value. Jensen promised to support TSMC in charging more for their wafers and a type of packaging called CoWoS. An article from TrendForce says that NVIDIA and TSMC will talk about chip prices for next year, which could help TSMC make more money. Jensen also said he's not too worried about problems between countries because Taiwan has a strong supply chain; TSMC is doing more than just making chips, they're handling many supply chain issues too.

Last year, many companies were waiting for TSMC's products, ever-increasing demand and production issues causing delays. Even though things got a bit better this year, there's still not enough supply. TSMC says that even making three times more 3-nanometer chips isn't enough, so they need to make even more. NVIDIA's profits are very high, much higher than other companies like AMD and even TSMC. If TSMC raises prices for these advanced processes, it won't hurt NVIDIA's profits much, but it might lower profits for other companies like Apple, AMD, and Qualcomm. It will also have an impact on end-users.

Arm CEO Rene Haas predicts that SoCs based on the Arm CPU machine architecture will beat x86 in the Windows PC space in the next 5 years (by 2029). Haas is bullish about the current crop of Arm SoCs striking the right balance of performance and power efficiency, along with just the right blend of on-chip acceleration for AI and graphics, to make serious gains in this market, which has traditionally been dominated by the x86 machine architecture, with chips from just two manufacturers—Intel and AMD. On the other hand, Arm has a vibrant ecosystem of SoC vendors. "Arm's market share in Windows - I think, truly, in the next five years, it could be better than 50%." Haas said, in an interview with Reuters.

Currently, Microsoft has an exclusive deal with Qualcomm to power Windows-on-Arm (WoA) Copilot+ AI PCs. Qualcomm's chip lineup spans the Snapdragon Elite X and Snapdragon Elite Plus. This exclusivity, however, could change, with a recent interview of Michael Dell and Jensen Huang hinting at NVIDIA working on a chip for the AI PC market. The writing is on the wall for Intel and AMD—they need to compete with Arm on its terms: to make leaner PC processors with the kinds of performance/Watt and chip costs that Arm SoCs offer to PC OEMs. Intel has taken a big step in this direction with its "Lunar Lake" processor, you can read all about the architecture here.

Palit sprung an unexpected surprise at the 2024 Computex. Normally, graphics card partners announce their new custom-design brands alongside new GPU generation launches. Palit took a different path, it rehashed its usual GameRock, JetStream, and Dual OC brands with the RTX 40-series "Ada," back in 2022, but showcased all new custom graphics card designs at Computex 2024, with an expected 5-6 months left for NVIDIA's next-gen GeForce "Blackwell" to hit the scene. The RTX 4090 Neptunus is a variation of the GameRock OC, except it is an air+liquid hybrid cooling solution. The card doesn't include a liquid cooling loop, and out of the box, the air-cooling performance of this card should resemble that of the GameRock, but it has a liquid cooling channel, you use your own G 1/4" fittings, and connect the card to a DIY loop for a transformative upgrade in cooling performance.

Next up, is the RTX 4080 SUPER Beyond Limits. This is Palit being flamboyant with its design, similar to the ASUS ROG Strix or the MSI Gaming X. The card features a very capable 3.5-slot air cooling design with high static-pressure fans, but the star attraction is a large acrylic RGB LED diffuser that runs along the length of the card, which has the Beyond Limits logo, and an infinite-reflection mirror. There is a variant of this card called the Beyond Limits Crystal, which has an "infinity reflection pyramid." The screaming "Beyond Limits" lettering makes way for some abstract shapes.

We visited the PNY booth at the 2024 Computex and found something interesting, an air-cooled GeForce RTX 4070 SUPER graphics card, and a pre-built, which was custom-made by PNY for their booth. Jensen Huang of NVIDIA visited this booth, and signed the card. It's now quite the attraction. It's a simple lateral blower card that's meant to be bought in numbers, and crammed into workstation cases, where the lateral blower design allows neighboring cards to breathe better. Typically, such cards tend to have boring, unremarkable black designs, with plastic cooler shrouds, but PNY managed to make their card stand out with a die-cast metal shroud finished in NVIDIA's favorite shade of green. As of now, this card isn't a real product, but we've been told that the company is considering a small production run, without Jensen's signature, of course.

NVIDIA today announced widespread adoption of the NVIDIA Spectrum -X Ethernet networking platform as well as an accelerated product release schedule. CoreWeave, GMO Internet Group, Lambda, Scaleway, STPX Global and Yotta are among the first AI cloud service providers embracing NVIDIA Spectrum-X to bring extreme networking performance to their AI infrastructures. Additionally, several NVIDIA partners have announced Spectrum-based products, including ASRock Rack, ASUS, GIGABYTE, Ingrasys, Inventec, Pegatron, QCT, Wistron and Wiwynn, which join Dell Technologies, Hewlett Packard Enterprise, Lenovo and Supermicro in incorporating the platform into their offerings.

"Rapid advancements in groundbreaking technologies like generative AI underscore the necessity for every business to prioritize networking innovation to gain a competitive edge," said Gilad Shainer, senior vice president of networking at NVIDIA. "NVIDIA Spectrum-X revolutionizes Ethernet networking to let businesses fully harness the power of their AI infrastructures to transform their operations and their industries."

NVIDIA is eying a comeback to the client processor business, reveals a Bloomberg interview with the CEOs of NVIDIA and Dell. For NVIDIA, all it takes is a simple driver update that exposes every GeForce GPU with tensor cores as an NPU to Windows 11, with translation layers to get popular client AI apps to work with TensorRT. But that would need you to have a discrete NVIDIA GPU. What about the vast market of Windows AI PCs powered by the likes of Qualcomm, Intel, and AMD, who each sell 15 W-class processors with integrated NPUs capable of 50 AI TOPS, which is all that Copilot+ needs? NVIDIA held an Arm license for decades now, and makes Arm-based CPUs to this day, with the NVIDIA Grace, however, that is a large server processor meant for its AI GPU servers.

NVIDIA already made client processors under the Tegra brand targeting smartphones, which it winded down last decade. It's since been making Drive PX processors for its automotive self-driving hardware division; and of course there's Grace. NVIDIA hinted that it might have a client CPU for the AI PC market in 2025. In the interview Bloomberg asked NVIDIA CEO Jensen Huang a pointed question on whether NVIDIA has a place in the AI PC market. Dell CEO Michael Dell, who was also in the interview, interjected "come back next year," to which Jensen affirmed "exactly." Dell would be in a front-and-center position to know if NVIDIA is working on a new PC processor for launch in 2025, and Jensen's nod almost confirms this

Amid an AI revolution sweeping through trillion-dollar industries worldwide, NVIDIA founder and CEO Jensen Huang will deliver a keynote address ahead of COMPUTEX 2024, in Taipei, outlining what's next for the AI ecosystem. Slated for June 2 at the National Taiwan University Sports Center, the address kicks off before the COMPUTEX trade show scheduled to run from June 3-6 at the Taipei Nangang Exhibition Center. The keynote will be livestreamed at 7 p.m. Taiwan time (4 a.m. PT) on Sunday, June 2, with a replay available at NVIDIA.com.

With over 1,500 exhibitors from 26 countries and an expected crowd of 50,000 attendees, COMPUTEX is one of the world's premier technology events. It has long showcased the vibrant technology ecosystem anchored by Taiwan and has become a launching pad for the cutting-edge systems required to scale AI globally. As a leader in AI, NVIDIA continues to nurture and expand the AI ecosystem. Last year, Huang's keynote and appearances in partner press conferences exemplified NVIDIA's role in helping advance partners across the technology industry.

It's official: NVIDIA delivered the world's fastest platform in industry-standard tests for inference on generative AI. In the latest MLPerf benchmarks, NVIDIA TensorRT-LLM—software that speeds and simplifies the complex job of inference on large language models—boosted the performance of NVIDIA Hopper architecture GPUs on the GPT-J LLM nearly 3x over their results just six months ago. The dramatic speedup demonstrates the power of NVIDIA's full-stack platform of chips, systems and software to handle the demanding requirements of running generative AI. Leading companies are using TensorRT-LLM to optimize their models. And NVIDIA NIM—a set of inference microservices that includes inferencing engines like TensorRT-LLM—makes it easier than ever for businesses to deploy NVIDIA's inference platform.

Raising the Bar in Generative AI
TensorRT-LLM running on NVIDIA H200 Tensor Core GPUs—the latest, memory-enhanced Hopper GPUs—delivered the fastest performance running inference in MLPerf's biggest test of generative AI to date. The new benchmark uses the largest version of Llama 2, a state-of-the-art large language model packing 70 billion parameters. The model is more than 10x larger than the GPT-J LLM first used in the September benchmarks. The memory-enhanced H200 GPUs, in their MLPerf debut, used TensorRT-LLM to produce up to 31,000 tokens/second, a record on MLPerf's Llama 2 benchmark. The H200 GPU results include up to 14% gains from a custom thermal solution. It's one example of innovations beyond standard air cooling that systems builders are applying to their NVIDIA MGX designs to take the performance of Hopper GPUs to new heights.

After giving a vivid GTC talk, NVIDIA's CEO Jensen Huang took on a Q&A session with many interesting ideas for debate. One of them is addressing the pressing concerns surrounding AI hallucinations and the future of Artificial General Intelligence (AGI). With a tone of confidence, Huang reassured the tech community that the phenomenon of AI hallucinations—where AI systems generate plausible yet unfounded answers—is a solvable issue. His solution emphasizes the importance of well-researched and accurate data feeding into AI systems to mitigate these occurrences. "The AI shouldn't just answer; it should do research first to determine which of the answers are the best," noted Mr. Huang as he added that for every single question, there should be a rule that makes AI research the answer. This also refers to Retrieval-Augmented Generation (RAG), where LLMs fetch data from external sources, like additional databases, for fact-checking.

Another interesting comment made by the CEO is that the pinnacle of AI evolution—Artificial General Intelligence—is just five years away. Many people working in AI are divided between the AGI timeline. While Mr. Huang predicted five years, some leading researchers like Meta's Yann LeCunn think we are far from the AGI singularity threshold and will be stuck with dog/cat-level AI systems first. AGI has long been a topic of both fascination and apprehension, with debates often revolving around its potential to exceed human intelligence and the ethical implications of such a development. Critics worry about the unpredictability and uncontrollability of AGI once it reaches a certain level of autonomy, raising questions about aligning its objectives with human values and priorities. Timeline-wise, no one knows, and everyone makes their prediction, so time will tell who was right.

Jensen Huang has been talking to media outlets following the conclusion of his keynote presentation at NVIDIA's GTC 2024 conference—an NBC TV "exclusive" interview with the Team Green boss has caused a stir in tech circles. Jim Cramer's long-running "Squawk on the Street" trade segment hosted Huang for just under five minutes—NBC's presenter labelled the latest edition of GTC the "Woodstock of AI." NVIDIA's leader reckoned that around $1 trillion of industry was in attendance at this year's event—folks turned up to witness the unveiling of "Blackwell" B200 and GB200 AI GPUs. In the interview, Huang estimated that his company had invested around $10 billion into the research and development of its latest architecture: "we had to invent some new technology to make it possible."

Industry watchdogs have seized on a major revelation—as disclosed during the televised NBC report—Huang revealed that his next-gen AI GPUs "will cost between $30,000 and $40,000 per unit." NVIDIA (and its rivals) are not known to publicly announce price ranges for AI and HPC chips—leaks from hardware partners and individuals within industry supply chains are the "usual" sources. An investment banking company has already delved into alleged Blackwell production costs—as shared by Tae Kim/firstadopter: "Raymond James estimates it will cost NVIDIA more than $6000 to make a B200 and they will price the GPU at a 50-60% premium to H100...(the bank) estimates it costs NVIDIA $3320 to make the H100, which is then sold to customers for $25,000 to $30,000." Huang's disclosure should be treated as an approximation, since his company (normally) deals with the supply of basic building blocks.

At GTC on Monday, Microsoft Corp. and NVIDIA expanded their longstanding collaboration with powerful new integrations that leverage the latest NVIDIA generative AI and Omniverse technologies across Microsoft Azure, Azure AI services, Microsoft Fabric and Microsoft 365.

"Together with NVIDIA, we are making the promise of AI real, helping to drive new benefits and productivity gains for people and organizations everywhere," said Satya Nadella, Chairman and CEO, Microsoft. "From bringing the GB200 Grace Blackwell processor to Azure, to new integrations between DGX Cloud and Microsoft Fabric, the announcements we are making today will ensure customers have the most comprehensive platforms and tools across every layer of the Copilot stack, from silicon to software, to build their own breakthrough AI capability."

"AI is transforming our daily lives - opening up a world of new opportunities," said Jensen Huang, founder and CEO of NVIDIA. "Through our collaboration with Microsoft, we're building a future that unlocks the promise of AI for customers, helping them deliver innovative solutions to the world."

NVIDIA today announced its next-generation AI supercomputer—the NVIDIA DGX SuperPOD powered by NVIDIA GB200 Grace Blackwell Superchips—for processing trillion-parameter models with constant uptime for superscale generative AI training and inference workloads.

Featuring a new, highly efficient, liquid-cooled rack-scale architecture, the new DGX SuperPOD is built with NVIDIA DGX GB200 systems and provides 11.5 exaflops of AI supercomputing at FP4 precision and 240 terabytes of fast memory—scaling to more with additional racks.

Powering a new era of computing, NVIDIA today announced that the NVIDIA Blackwell platform has arrived—enabling organizations everywhere to build and run real-time generative AI on trillion-parameter large language models at up to 25x less cost and energy consumption than its predecessor.

The Blackwell GPU architecture features six transformative technologies for accelerated computing, which will help unlock breakthroughs in data processing, engineering simulation, electronic design automation, computer-aided drug design, quantum computing and generative AI—all emerging industry opportunities for NVIDIA.

NVIDIA today announced that TSMC and Synopsys are going into production with NVIDIA's computational lithography platform to accelerate manufacturing and push the limits of physics for the next generation of advanced semiconductor chips. TSMC, the world's leading foundry, and Synopsys, the leader in silicon to systems design solutions, have integrated NVIDIA cuLitho with their software, manufacturing processes and systems to speed chip fabrication, and in the future support the latest-generation NVIDIA Blackwell architecture GPUs.

"Computational lithography is a cornerstone of chip manufacturing," said Jensen Huang, founder and CEO of NVIDIA. "Our work on cuLitho, in partnership with TSMC and Synopsys, applies accelerated computing and generative AI to open new frontiers for semiconductor scaling." NVIDIA also introduced new generative AI algorithms that enhance cuLitho, a library for GPU-accelerated computational lithography, dramatically improving the semiconductor manufacturing process over current CPU-based methods.

Jensen Huang's opening GTC 2024 keynote is scheduled to happen tomorrow afternoon (13:00 Pacific time)—many industry experts believe that the NVIDIA boss will take the stage and formally introduce his company's B100 "Blackwell" GPU architecture. An enlightened few have been treated to preview (AI and HPC) units—including Dell's CEO, Jeff Clarke—but pre-introduction leaks have not flowed out. Team Green is likely enforcing strict conditions upon a fortunate selection of trusted evaluators, within a pool of ecosystem partners and customers.

Today, a brave soul has broken that silence—tech tipster, AGF/XpeaGPU, fears repercussions from the leather-jacketed one. They revealed a handful of technical details, a day prior to Team Green's highly anticipated unveiling: "I don't want to spoil NVIDIA B100 launch tomorrow, but this thing is a monster. 2 dies on (TSMC) CoWoS-L, 8x8-Hi HBM3E stacks for 192 GB of memory." They also crystal balled an inevitable follow-up card: "one year later, B200 goes with 12-Hi stacks and will offer a beefy 288 GB. And the performance! It's... oh no Jensen is there... me run away!" Reuters has also joined in on the fun, with some predictions and insider information: "NVIDIA is unlikely to give specific pricing, but the B100 is likely to cost more than its predecessor, which sells for upwards of $20,000." Enterprise products are expected to arrive first—possibly later this year—followed by gaming variants, maybe months later.

Samsung Electronics is all set to discuss the future of AI, alongside Jensen Huang, at NVIDIA's upcoming GTC 2024 conference. South Korean insiders have leaked the company's intentions, only days before the event's March 18 kickoff time. Their recently unveiled 36 GB HBM3E 12H DRAM product is expected to be the main focus of official presentations—additionally, a new storage subscription service is marked down for a possible live introduction. An overall "Redefining AI Infrastructure" presentation could include—according to BusinessKorea—a planned launch of: "petabyte (PB)-level SSD solution, dubbed 'PBSSD,' along with a subscription service in the US market within the second quarter (of 2024) to address the era of ultra-high-capacity data."

A Samsung statement—likely sourced from leaked material—summarized this business model: "the subscription service will help reduce initial investment costs in storage infrastructure for our customers and cut down on maintenance expenses." Under agreed upon conditions, customers are not required to purchasing ultra-high-capacity SSD solutions outright: "enterprises using the service can flexibly utilize SSD storage without the need to build separate infrastructure, while simultaneously receiving various services from Samsung Electronics related to storage management, security, and upgrades." A special session—"The Value of Storage as a Service for AI/ML and Data Analysis"—is alleged to be on the company's GTC schedule.

NVIDIA's GTC 2024 AI conference will set the stage for another leap forward in AI. At the heart of this highly anticipated event: the opening keynote by Jensen Huang, NVIDIA's visionary founder and CEO, who speaks on Monday, March 18, at 1 p.m. Pacific, at the SAP Center in San Jose, California.

Planning Your GTC Experience
There are two ways to watch. Register to attend GTC in person to secure a spot for an immersive experience at the SAP Center. The center is a short walk from the San Jose Convention Center, where the rest of the conference takes place. Doors open at 11 a.m., and badge pickup starts at 10:30 a.m. The keynote will also be livestreamed at www.nvidia.com/gtc/keynote/.

During the 2024 SIEPR Economic Summit, NVIDIA CEO Jensen Huang acknowledged that the company's next-generation DGX systems, designed for AI and high-performance computing workloads, will require liquid cooling due to their immense power consumption. Huang also hinted that these new systems are set to be released in the near future. The revelation comes as no surprise, given the increasing power of GPUs needed to satisfy AI and machine learning applications. As computational requirements continue to grow, so does the need for more powerful hardware. However, with great power comes great heat generation, necessitating advanced cooling solutions to maintain optimal performance and system stability. Liquid cooling has long been a staple in high-end computing systems, offering superior thermal management compared to traditional air cooling methods.

By implementing liquid cooling in the upcoming DGX systems, NVIDIA aims to push the boundaries of performance while ensuring the hardware remains reliable and efficient. Although Huang did not provide a specific release date for the new DGX systems, his statement suggests that they are on the horizon. Whether the next generation of DGX systems uses the current NVIDIA H200 or the upcoming Blackwell B100 GPU as their primary accelerator, the performance will undoubtedly be delivered. As the AI and high-performance computing landscape continues to evolve, NVIDIA's position continues to strengthen, and liquid-cooled systems will certainly play a crucial role in shaping the future of these industries.

Nations have long invested in domestic infrastructure to advance their economies, control their own data and take advantage of technology opportunities in areas such as transportation, communications, commerce, entertainment and healthcare. AI, the most important technology of our time, is turbocharging innovation across every facet of society. It's expected to generate trillions of dollars in economic dividends and productivity gains. Countries are investing in sovereign AI to develop and harness such benefits on their own. Sovereign AI refers to a nation's capabilities to produce artificial intelligence using its own infrastructure, data, workforce and business networks.

Why Sovereign AI Is Important
The global imperative for nations to invest in sovereign AI capabilities has grown since the rise of generative AI, which is reshaping markets, challenging governance models, inspiring new industries and transforming others—from gaming to biopharma. It's also rewriting the nature of work, as people in many fields start using AI-powered "copilots." Sovereign AI encompasses both physical and data infrastructures. The latter includes sovereign foundation models, such as large language models, developed by local teams and trained on local datasets to promote inclusiveness with specific dialects, cultures and practices. For example, speech AI models can help preserve, promote and revitalize indigenous languages. And LLMs aren't just for teaching AIs human languages, but for writing software code, protecting consumers from financial fraud, teaching robots physical skills and much more.

2024 will be the year generative AI gets personal, the CEOs of NVIDIA and HP said today in a fireside chat, unveiling new laptops that can build, test and run large language models. "This is a renaissance of the personal computer," said NVIDIA founder and CEO Jensen Huang at HP Amplify, a gathering in Las Vegas of about 1,500 resellers and distributors. "The work of creators, designers and data scientists is going to be revolutionized by these new workstations."

Greater Speed and Security
"AI is the biggest thing to come to the PC in decades," said HP's Enrique Lores, in the runup to the announcement of what his company billed as "the industry's largest portfolio of AI PCs and workstations." Compared to running their AI work in the cloud, the new systems will provide increased speed and security while reducing costs and energy, Lores said in a keynote at the event. New HP ZBooks provide a portfolio of mobile AI workstations powered by a full range of NVIDIA RTX Ada Generation GPUs. Entry-level systems with the NVIDIA RTX 500 Ada Generation Laptop GPU let users run generative AI apps and tools wherever they go. High-end models pack the RTX 5000 to deliver up to 682 TOPS, so they can create and run LLMs locally, using retrieval-augmented generation (RAG) to connect to their content for results that are both personalized and private.

NVIDIA is offering a new professional certification in generative AI to enable developers to establish technical credibility in this important domain. Generative AI is revolutionizing industries worldwide, yet there's a critical skills gap and need to uplevel employees to more fully harness the technology. Available for the first time from NVIDIA, this new professional certification enables developers, career professionals, and others to validate and showcase their generative AI skills and expertise. Our new professional certification program introduces two associate-level generative AI certifications, focusing on proficiency in large language models and multimodal workflow skills.

"Generative AI has moved to center stage as governments, industries and organizations everywhere look to harness its transformative capabilities," NVIDIA founder and CEO Jensen Huang recently said. The certification will become available starting at GTC, where in-person attendees can also access recommended training to prepare for a certification exam. "Organizations in every industry need to increase their expertise in this transformative technology," said Greg Estes, VP of developer programs at NVIDIA. "Our goals are to assist in upskilling workforces, sharpen the skills of qualified professionals, and enable individuals to demonstrate their proficiency in order to gain a competitive advantage in the job market."

NVIDIA is reported to be setting up an AI-focused semi-custom chip design business unit, according to inside sources known to Reuters—it is believed that Team Green leadership is adapting to demands leveraged by key data-center customers. Many companies are seeking cheaper alternatives, or have devised their own designs (budget/war chest permitting)—NVIDIA's current range of AI GPUs are simply off-the-shelf solutions. OpenAI has generated the most industry noise—their alleged early 2024 fund-raising pursuits have attracted plenty of speculative/kind-of-serious interest from notable semiconductor personalities.

Team Green is seemingly reacting to emerging market trends—Jensen Huang (CEO, president and co-founder) has hinted that NVIDIA custom chip designing services are on the cusp. Stephen Nellis—a Reuters reporter specializing in tech industry developments—has highlighted select NVIDIA boss quotes from an incoming interview piece: "We're always open to do that. Usually, the customization, after some discussion, could fall into system reconfigurations or recompositions of systems." The Team Green chief teased that his engineering team is prepared to take on the challenge meeting exact requests: "But if it's not possible to do that, we're more than happy to do a custom chip. And the benefit to the customer, as you can imagine, is really quite terrific. It allows them to extend our architecture with their know-how and their proprietary information." The rumored NVIDIA semi-custom chip design business unit could be introduced in an official capacity at next month's GTC 2024 Conference.

NVIDIA (NASDAQ: NVDA) today reported revenue for the fourth quarter ended January 28, 2024, of $22.1 billion, up 22% from the previous quarter and up 265% from a year ago. For the quarter, GAAP earnings per diluted share was $4.93, up 33% from the previous quarter and up 765% from a year ago. Non-GAAP earnings per diluted share was $5.16, up 28% from the previous quarter and up 486% from a year ago.

For fiscal 2024, revenue was up 126% to $60.9 billion. GAAP earnings per diluted share was $11.93, up 586% from a year ago. Non-GAAP earnings per diluted share was $12.96, up 288% from a year ago. "Accelerated computing and generative AI have hit the tipping point. Demand is surging worldwide across companies, industries and nations," said Jensen Huang, founder and CEO of NVIDIA.

NVIDIA today announced it will host its flagship GTC 2024 conference at the San Jose Convention Center from March 18-21. More than 300,000 people are expected to register to attend in person or virtually. NVIDIA founder and CEO Jensen Huang will deliver the keynote from the SAP Center on Monday, March 18, at 1 p.m. Pacific time. It will be livestreamed and available on demand. Registration is not required to view the keynote online. Since Huang first highlighted machine learning in his 2014 GTC keynote, NVIDIA has been at the forefront of the AI revolution. The company's platforms have played a crucial role in enabling AI across numerous domains including large language models, biology, cybersecurity, data center and cloud computing, conversational AI, networking, physics, robotics, and quantum, scientific and edge computing.

The event's 900 sessions and over 300 exhibitors will showcase how organizations are deploying NVIDIA platforms to achieve remarkable breakthroughs across industries, including aerospace, agriculture, automotive and transportation, cloud services, financial services, healthcare and life sciences, manufacturing, retail and telecommunications. "Generative AI has moved to center stage as governments, industries and organizations everywhere look to harness its transformative capabilities," Huang said. "GTC has become the world's most important AI conference because the entire ecosystem is there to share knowledge and advance the state of the art. Come join us."