Nvidia announced a new generation of artificial intelligence chips and software for running AI models during its developer's conference on Monday. The new Blackwell AI graphics processors are expected to ship later this year. NIM is a software that makes it easier to deploy AI. Nvidia aims to make all models runnable with all of its GPUs through NIM. NIM will make it easier to use older Nvidia GPUs for inference, allowing companies to continue using the GPUs they already own.

Nvidia is discontinuing its Turing-based GTX GPUs, moving towards exclusively branding its gaming graphics cards under the "RTX" lineup. The transition signifies a shift away from the GTX series in favor of cards that support advanced features like ray tracing. The GT series may persist, but the GTX line is on its last legs as stocks deplete.

A new toolkit from Nvidia that allows checkpointing the CUDA state for transfer and restarting. It is useful for distributed training of very large AI models.

The Jensen special grant will vest over four years, with the first portion coming in September.

Google's new AI chip, Cloud TPU v5p, is now available. It boasts nearly triple the training speed for large language models compared to its predecessor, TPU v4. This release underscores Google's position in the AI hardware race alongside competitors like Nvidia. Google has also introduced the Google Axion CPU, based on Arm's chip infrastructure, promising better performance and energy efficiency.

Nvidia is acquiring AI infrastructure optimization firm Run:ai for approximately $700 million to enhance its DGX Cloud AI platform, allowing customers improved management of their AI workloads. The acquisition will support complex AI deployments across multiple data center locations. Run:ai had previous VC investments and a broad customer base, including Fortune 500 companies.

Nvidia has released a dataset and recipe along with a high quality paper about training reward models to align model output to human preferences.

Nvidia has unveiled a new generation of artificial intelligence chip architecture called Rubin. The company only just announced its upcoming Blackwell model in March - those chips are still in production and expected to ship to customers later in 2024. Nvidia has pledged to release new AI chip models on a one-year rhythm. The less-than-three-month turnaround from Blackwell to Rubin underscores the competitive frenzy in the AI chip market.

Nvidia is reportedly preparing a system-on-chip that pairs Arm's Cortex-X5 core design with GPUs based on Nvidia's Blackwell architecture.

AMD unveiled its latest AI processors, including the MI325X accelerator due in Q4 2024, at the Computex trade show. It also detailed plans to compete with Nvidia by releasing new AI chips annually. The MI350 series, expected in 2025, promises a 35-fold performance increase in inference compared to the MI300 series. The MI400 series is set for a 2026 release.

Nvidia became the second most valuable company in the world on Wednesday afternoon as its market capitalization hit $3.01 trillion. It became a $1 trillion company in May 2023, hitting $2 trillion in February this year. The company reported $14 billion in profit in May. Its AI accelerators make up between 70% and 95% of the market share for AI chips. Nvidia has plans to launch a new AI chip every year.

The Justice Department and the Federal Trade Commission have reached a deal that allows them to proceed with antitrust investigations into the dominant roles that Microsoft, OpenAI, and Nvidia play in the artificial intelligence industry. The Justice Department will take the lead in investigating Nvidia, while the FTC will examine the conduct of OpenAI and Microsoft. A similar deal in 2019 resulted in Google, Apple, Amazon, and Meta being sued on claims that they violated anti-monopoly laws.

Nvidia became the second most valuable company in the world on Wednesday afternoon as its market capitalization hit $3.01 trillion.

Nvidia is now the most valuable public company in the world. Its market cap surpassed Microsoft's $3.32 trillion on Tuesday, reaching a high of $3.34 trillion. Nvidia's shares are up more than 170% so far this year. Its market cap hit $3 trillion for the first time earlier this month. Nvidia's rise has been so rapid the company has yet to be added to the Dow Jones Industrial Average, the stock benchmark of the 30 most valuable US companies.

Systems powered by Nvidia's Hopper architecture dominated the results of two new tests from MLPerf, an AI benchmarking suite that compares the fine-tuning of large language models and training of graph neural networks.

Nvidia is now the most valuable public company in the world. Its market cap surpassed Microsoft's $3.32 trillion on Tuesday, reaching a high of $3.34 trillion. Nvidia's shares are up more than 170% so far this year. Its market cap hit $3 trillion for the first time earlier this month. Nvidia's rise has been so rapid the company has yet to be added to the Dow Jones Industrial Average, the stock benchmark of the 30 most valuable US companies.

Nvidia's CEO Jensen Huang attributes the company's AI chip market dominance, maintaining an over 80% market share despite rising competition, to a decade-old strategic investment. Advocating for Nvidia's AI chips' cost-effectiveness and performance, Huang highlights the firm's transformation into a data center-focused entity and expansion into new markets.

For content creators, Nvidia's Broadcast app offers AI-powered tools that elevate any room to studio quality. Features like virtual backgrounds, noise reduction, and auto framing enhance streaming and video conferencing. It is compatible with any RTX-powered device and provides studio-quality effects for popular apps like Zoom, Google Meet, and Microsoft Teams.

Several major AI companies, including Anthropic, Nvidia, Apple, and Salesforce, used subtitles from 173,536 YouTube videos across 48,000 channels to train AI models, despite YouTube's rules against unauthorized data harvesting. This has sparked backlash from content creators, who argue that their work has been exploited without consent or compensation, raising concerns about AI's impact on the creative industry and the ethics of using such training data.

Mistral Nemo 12B is a multilingual model trained with a new tokenizer that shows powerful multilingual and English performance. It supports 128k contexts too.

Nvidia is developing a new AI chip, the B20, tailored to comply with U.S. export controls for the Chinese market, leveraging its partnership with distributor Inspur. Its advanced H20 chip has reportedly seen a rapid growth in sales in China, with projections of selling over 1 million units worth $12 billion this year. U.S. pressure on semiconductor exports continues, with possible further restrictions and control measures on AI model development.

Nvidia's Blackwell B200 chips will take at least three months longer to produce than was planned. The delay is due to a design flaw that was discovered unusually late in the production process. Nvidia is now working through a fresh set of test runs and won't ship large numbers of the chips until the first quarter. Microsoft, Google, and Meta have already ordered tens of billions of dollars worth of the chips.

Nvidia is facing increased government scrutiny from the EU, UK, China, and the US Justice Department over its dominant market share in AI chips and sales practices. The company is rapidly building its legal and policy teams to address antitrust concerns amid profitable growth, as it commands 90 percent of the GPU market essential for AI systems. Nvidia is also adapting to increased competition oversight, with recent attention turning to its planned acquisition of Run.ai and impact on the AI supply chain.

Nvidia's upcoming GB200 server racks will be mainly cooled with liquid circulated in tubes. The company is also working on other cooling technologies, including one that involves dunking entire computers in a non-conductive liquid that absorbs and dissipates heat. Cooling accounts for a significant amount of power consumption in data centers. Liquid-cooled data centers would be able to pack much more computing power in the same space.

Nvidia has released its Llama 3.1 minitron 4B model. The model scored 16% better on MMLU compared with training from scratch by using knowledge distillation and pruning and required 40x fewer tokens.

Nvidia's AI system ACE will power in-game character interactions in Mecha Break, a mech battle game launching in 2025. It uses GPT-4o and a mix of on-device and cloud-based AI for natural language processing and vocal generation. Initial demonstrations reveal lackluster NPC engagement, with concerns over response delays and uninspiring dialogue.

Many of Nvidia's employees are millionaires because of the company's growth. Despite this, the company still has a 'pressure cooker' culture with long working hours, yelling and fighting at meetings, and company politics. Some employees work every day, including weekends, late into the night. Employees who work less than the norm are called out at company-wide meetings. The company maintains a low turnover rate, likely due to the way it gives its employees access to stock grants and its 'flat' hierarchy, which could make the company an appealing choice.

Apple and Nvidia are in talks to invest in OpenAI as part of a fundraising round that would value OpenAI at above $100 billion. It is an unusual move for Apple, as the company doesn't usually invest in startups. Nvidia has stepped up its investment activity in the past two years, putting its money into AI-related companies. OpenAI is one of the largest users of Nvidia's AI chips.

Nvidia's Blackwell chips are about twice as big as its predecessors, housing 2.6 times the number of transistors. Instead of one big piece of silicon, Blackwell consists of two advanced processors and numerous memory components joined in a single, delicate mesh of silicon, metal, and plastic. The manufacturing of each chip has to be close to perfect, presenting engineering challenges that have a sizable impact on the bottom line, with each defect rendering a $40,000 chip useless. This article looks at some of the challenges Nvidia had to overcome to produce the chip.

Nvidia CEO Jensen Huang is trying to build Nvidia into a one-stop shop for all of the key elements in a data center. The strategy is designed to make the company's offerings stickier for customers. Nvidia is also building a business that supplies AI-optimized Ethernet, a business that is expected to generate billions of dollars in revenue within a year. The competition in the space is growing, with companies like AMD bolstering their data-center offerings and chip suppliers like Intel offering services and systems to help customers build and operate AI tools.