The US Department of Justice has sent subpoenas to Nvidia and other companies seeking evidence that the chipmaker violated antitrust laws. Antitrust officials are concerned that Nvidia is making it harder to switch to other suppliers and penalizing buyers that don't exclusively use its artificial intelligence chips. Nvidia claims that its market dominance stems from the quality of its products. The company prioritizes customers who can make use of its products in ready-to-go data centers as soon as they're provided to prevent stockpiling and to speed up the broader adoption of AI.

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.

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'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.

Nvidia's dominance in AI chips has propelled it to immense market value, largely thanks to its GPU capabilities and CUDA software ecosystem. However, competitors like AMD, Intel, Cerebras, and SambaNova are developing innovative solutions to challenge Nvidia's supremacy in AI hardware. While Nvidia's lead remains secure for now, the landscape is dynamic, with multiple players striving to carve out their own niches in the AI market.

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 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.

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.

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.

The Department of Justice is considering breaking up Alphabet following a ruling that found the company monopolized the online search market. The most likely units for divestment are the Android operating system and Chrome web browser. Less severe options include forcing Google to share more data with competitors and measures to prevent it from gaining an unfair advantage in AI products. The government will likely see a ban on the type of exclusive contracts that were at the center of the case.

The US Department of Justice's next monopoly trial against Google started on Monday. The trial challenges the tech giant's ad tech dominance. The DOJ is arguing that Google broke competition in the ad tech space by engaging in a systematic campaign to seize control of the tools used by publishers, advertisers, and brokers to facilitate digital advertising. Google profits from both advertisers and publishers, pocketing at least 30 cents of each advertising dollar flowing from advertisers to website publishers through its ad tech tools. The trial is expected to last four to six weeks and may be the most consequential of the monopoly trials Google has recently faced.

NVIDIA's dominance in the AI space continues to be secured not just by hardware, but by its CUDA software ecosystem and proprietary interconnects. Alternatives like AMD's ROCM struggle to match CUDA's ease of use and performance optimization, ensuring NVIDIA's GPUs remain the preferred choice for AI workloads. Investments in the CUDA ecosystem and community education solidify NVIDIA's stronghold in AI compute.

VC firm Andreessen Horowitz has secured thousands of AI chips, including Nvidia H100 GPUs, to dole out to its AI portfolio companies in exchange for equity.

The Department of Justice (DOJ) recently concluded a three-week trial focused on allegations that Google has established illegal monopolies within the ad tech market. Central to Google's defense is the assertion that the DOJ's understanding of the online advertising landscape is flawed. Google contends that the government is mischaracterizing the market by failing to recognize the significant competition it faces from social media platforms. The DOJ has defined the relevant market as comprising open web display ads, which include the ad boxes and banners seen on various websites. It identifies three key components: publisher ad servers, advertiser ad networks, and ad exchanges. According to the DOJ, Google holds a dominant position in this market, particularly through its publisher ad server, DoubleClick For Publishers (DFP), which it claims has a 90% market share in the U.S. The DOJ argues that Google's dominance is partly due to its practice of tying its products together, compelling publishers to use DFP to access Google's extensive advertiser base. In contrast, Google argues that the market should be viewed as a single entity where both buyers and sellers of digital advertising interact. The company claims that its integrated ad tech solutions provide benefits to customers, making it more efficient and cost-effective compared to using multiple separate products. Google’s expert witness, economist Mark Israel, emphasized that the digital ad industry is fundamentally about making connections between buyers and sellers, and that Google's offerings enhance this process rather than create monopolistic harm. A significant aspect of Google's defense hinges on the Supreme Court case Ohio v. American Express, which dealt with two-sided markets. Google aims to demonstrate that the ad tech market operates similarly, suggesting that the DOJ must prove that Google's actions harm both publishers and advertisers. This presents a challenge for the DOJ, as actions that benefit one side may not necessarily be detrimental to the other. The DOJ has also attempted to delineate the market by asserting that open web display ads are distinct from other forms of advertising, such as those on social media or video platforms. Google counters this by arguing that advertisers prioritize return on investment and will shift their budgets to platforms that yield better results, regardless of the specific format of the ads. Internal documents from Google reveal that the company closely monitors competitors that the DOJ has excluded from its market definition, including social media giants like TikTok and Facebook, which Google views as significant threats. Google argues that the presence of these competitors serves as a check on its market power. The trial has seen intense cross-examination, with DOJ counsel challenging the credibility of Google's expert witnesses and their claims about competition. The DOJ has illustrated that even as advertisers may diversify their spending, publishers still rely heavily on display ads, which creates a complex dynamic in the market. Judge Leonie Brinkema has presided over the trial, maintaining a focused approach while seeking clarity on the market definitions at play. As the trial progresses, the judge has indicated that the definition of the market is crucial to the case, and she will consider the entirety of the evidence presented before making her ruling. The closing arguments are set for November 25th, where both sides will have the opportunity to further articulate their positions on the market definitions and the implications for competition in the ad tech industry.

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 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 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.

AMD has agreed to buy ZT Systems, an artificial intelligence infrastructure group, for $4.9 billion in cash and stocks. The acquisition will help AMD accelerate the adoption of its AI data center chips, which compete with Nvidia's popular GPUs. The transaction is subject to regulatory approval. It is expected to close in the first half of 2025.

Reddit was one of the reasons Y Combinator was started. This post tells the story of how the site came to be. Despite being rejected in the first round for their food delivery app idea, Reddit's founders were offered funding after agreeing to work on a project that would eventually become Reddit. The project was launched on a quick schedule. It had a core set of real users after just a few weeks. Reddit is now a fundamentally useful tool that seems almost unkillable.

Doctors have performed a pig-to-human kidney transplant for the first time at Massachusetts General Hospital, the first hospital to perform a kidney transplant. The genetically modified kidney was implanted into a 62-year-old patient who had been diagnosed with end-stage kidney disease. They are recovering well and are expected to be discharged from the hospital soon. It is unknown how long the kidney will last for. This was the third transplant of a pig organ into a living human. The first two patients, who received heart transplants, died weeks after receiving their organs.

This article discusses things to consider when thinking about joining a startup. A job may provide higher salaries, more perks, security, less stress, and other benefits, but working in a startup can result in huge payoffs. Startups require a ton of challenging work to be successful, they have minimal infrastructure in place, and startup employees have lower salaries. However, startup employees own a portion of the company, and this could be worth a lot in the future.

Tortoise is an automated solution designed to meet all Kubernetes resource optimization needs. It shifts optimization responsibility from service owners to platform teams, requiring service owners to configure only a minimal amount of parameters to initiate autoscaling. Tortoise allows for comprehensive tuning by platform teams. It currently only supports deployment - support for all resources supporting scale subresources is in development.

Unnamed sources say that Microsoft is paying approximately $650 million in its deal with Inflection AI. $620 million was paid for non-exclusive licensing fees for Inflection's technology and $30 million was paid to get Inflection to agree not to sue over Microsoft's poaching. Inflection will pivot away from building a personalized AI chatbot to becoming an AI studio that helps other companies work with large language model AI. Microsoft has several reasons for needing a backup for OpenAI - for one, its deal with OpenAI is being scrutinized by the FTC.

Apple is being sued by the US for employing a strategy that relies on exclusionary anticompetitive conduct that hurts both consumers and developers. The 88-page lawsuit says that the company violated antitrust laws with practices that were intended to keep customers reliant on their iPhones and make them less likely to switch to competing devices. It seeks to put an end to those practices and possibly a breakup of the company. The lawsuit is likely to drag out for years before any type of resolution.

Dropflow is a CSS layout engine with a high-quality text layout implementation capable of displaying many languages. It can generate PDFs or images and render rich wrapped text to a canvas in the browser. Dropflow supports bidirectional and RTL text, font fallbacks at the grapheme level, colored diacritics, optimized shaping, and much more.

The US Justice Department is suing Adobe for allegedly hiding expensive fees, enrolling consumers in its most lucrative subscription plan without clear disclosure, and making cancellations difficult. The lawsuit also targets Adobe executives Maninder Sawhney and David Wadhwani. It follows continued regulatory scrutiny after Adobe's abandoned acquisition of Figma in 2022.

Building leading AI models is extremely costly - raising $400 million isn't even enough to compete these days. Big Tech has the cash, but it isn't allowed to buy companies like it once did due to antitrust enforcement. It has turned to aquihiring - hiring most of a company's employees and acquiring everything in a company but its name. While the current antitrust enforcement regime will likely try to block these types of acquisitions, it may not have a strong legal argument for doing so.

Building leading AI models is extremely costly - raising $400 million isn't even enough to compete these days. Big Tech has the cash, but it isn't allowed to buy companies like it once did due to antitrust enforcement. It has turned to aquihiring - hiring most of a company's employees and acquiring everything in a company but its name. While the current antitrust enforcement regime will likely try to block these types of acquisitions, it may not have a strong legal argument for doing so.

A US judge ruled that Google illegally monopolized the search market by paying billions to make its search engine the default on smartphones and web browsers, effectively blocking competitors. This decision is the US government's first major antitrust case win against a US tech giant in over two decades. Judge Amit Mehta found that Google's exclusive deals with companies like Apple and Samsung foreclosed competition and enabled the company to raise advertising prices without consequence.

Nvidia is addressing a significant challenge in telecommunications: the strain that artificial intelligence (AI) places on wireless networks. The company believes that AI can also provide solutions to these issues through its new AI-RAN platform, which aims to enhance the efficiency and performance of mobile networks. Collaborating with partners such as T-Mobile, Ericsson, and Nokia, Nvidia is set to test this innovative approach, with T-Mobile being the first to implement AI-RAN. The AI-RAN platform is designed to utilize vast amounts of data to create algorithms that optimize network adjustments and predict real-time capacity needs. This integration of AI into the radio access network is expected to make mobile networks smarter and faster, allowing telecommunications companies to run third-party AI applications at the network's edge. T-Mobile's CEO, Mike Sievert, highlighted the transformative potential of AI-RAN, while acknowledging the challenges involved in its implementation. As AI applications, particularly those related to augmented reality and AI-powered assistants, continue to grow, there is a pressing need to manage the increasing mobile data traffic that may exceed the capabilities of current 5G networks. Traditional networks were primarily designed for voice and basic data services, but the modern landscape demands more advanced solutions to support technologies like autonomous vehicles and smart factories. Nvidia's strategy involves positioning AI-RAN as a foundational element for future advancements, including the anticipated rollout of 6G technology. The AI-RAN Alliance, which includes Nvidia, T-Mobile, Nokia, and Ericsson, is actively working to harness the potential of AI in network operations. The alliance aims to tackle the challenges posed by the massive volume of data generated by AI-driven applications. Experts emphasize that network optimization will be crucial, as machine learning algorithms will need to dynamically adjust configurations to enhance performance and manage resources effectively. This collaborative effort seeks to ensure that telecommunications infrastructure can keep pace with the evolving demands of AI and emerging technologies.