Latest news with #SIGGRAPH2017
The Star
01-08-2025
- Business
- The Star
Exclusive-Alphabet's CapitalG, Nvidia in talks to fund Vast Data at up to $30 billion valuation, sources say
FILE PHOTO: An Nvidia logo is shown at SIGGRAPH 2017 in Los Angeles, California, U.S. July 31, 2017. REUTERS/Mike Blake/File Photo NEW YORK/SAN FRANCISCO (Reuters) -Alphabet's growth-stage venture arm CapitalGand Nvidia are in talks to invest in artificial intelligence infrastructure provider Vast Data in a new funding round that could value the startup as high as $30 billion, two sources said. The startup is raising severalbillion dollars from tech giants, private equity and venture capital investors, which could make it one of the most valuable AI startups, the two sources with knowledge of the matter said, as companies building the backbone for the AI boom come into sharper focus. CapitalG and existing backer Nvidia are in discussions to participate in the round, which could close in the next few weeks, according to the sources, who requested anonymity to speak on private matters. New York-headquartered Vast Data develops storage technology specifically designed for large AI data centers, enabling efficient data movement between graphics processors (GPUs) made by the likes of Nvidia. Its clients include companies such as Elon Musk's xAI and CoreWeave, and its value in the AI supply chain makes it an attractive acquisition target, bankers and analysts said. Nvidia declined to comment, while Vast Data and CapitalG did not respond to requests for comment. TechCrunch earlier reported Vast Data's fundraising efforts, but the valuation of up to $30 billion and the expected involvement of CapitalG and Nvidia have not been reported previously. Vast Data CEO Renen Halak has said the company is free cash flow positive. The company earned $200 million in annual recurring revenue (ARR) by January 2025, with a strong backlog of orders and projections to grow ARR to $600 million next year, according to a separate source familiar with its financials. The company has raised roughly $380 million to date, and its last funding round in 2023 valued it at $9.1 billion. Vast Data has said it would consider an initial public offering at the right time. While no listing is imminent, according to another source familiar with the matter, investors and bankers view the data infrastructure firm as a likely IPO candidate. Vast Data last year hired Amy Shapero, its first chief financial officer, who was previously in the same role at publicly listed e-commerce giant Shopify, in a move that could signal preparations for an IPO. Mergers and acquisitions activity has also been heating up in the sector, and Nvidia has been acquiring companies that add complementary software and hardware products beyond its flagship GPUs. In 2020, it bought networking chip and cable maker Mellanox, which has helped Nvidia build integrated systems featuring its latest Blackwell chips. Ithas also acquired software companies such as Run:ai, which helps engineers optimize data center AI hardware. Vast Data's storage architecture is based on a system of flash storage devices and other off-the-shelf hardware, combined with its specialized software for data access and movement. The company says adopting its technology can reduce the cost of building and running large AI models. Several early-stage companies, such as Weka and DDN, are pursuing similar efforts, but analysts and industry executives say Vast Data's technology is more mature than that of its rivals. (Reporting by Max A. Cherney in San Francisco and Krystal Hu and Milana Vinn in New York; Additional reporting by Kenrick Cai in San Francisco and Echo Wang in New York; Editing by Sayantani Ghosh and Jamie Freed)
Economic Times
31-07-2025
- Business
- Economic Times
Nvidia Executives Colette Kress and Jay Puri Join Billionaire Ranks Amid AI Stock Surge
Reuters A NVIDIA logo is shown at SIGGRAPH 2017 in Los Angeles, California, U.S. July 31, 2017. REUTERS/Mike Blake/File Photo Nvidia billionaires: The relentless rise of Nvidia has driven two of the company's top executives into the billionaire ranks, joining their boss, CEO Jensen Huang, as some of the most richly rewarded figures in tech, as per a Kress, Nvidia's Chief Financial Officer, and Jay Puri, Executive Vice President of Worldwide Field Operations, have both crossed into 10-figure territory in net worth, according to Bloomberg's Billionaires Index. Their fortunes come due to their massive holdings in Nvidia stock, which has surged nearly 70% over the past year and 27% in 2025 alone, pushing the chipmaker's market cap past $4 trillion, as reported by Fortune. For Kress, the path to billionaire status is paved with patience and stock. On July 15, Kress sold just over 27,000 shares for roughly $171 apiece, raking in $4.7 million, as reported by Fortune. Yet, even after that sale, SEC filings reveal she still holds nearly 3 million shares directly, as per the Fortune report. Along with that, Kress also holds hundreds of thousands of Nvidia shares that are indirectly retained through trusts or immediate family members, according to the report. ALSO READ: Asteroid 2024 YR4 may smash into moon, wipe out 10,000 satellites, and trigger meteor showers on earth Even Puri's fortune tells a similar story. Though he directly holds around 634,000 shares, worth over $108 million, he holds more wealth via indirect ownership, as per the Fortune report. Puri controls roughly 20 million shares through various trusts, plus another 46,000 held in a children's trust under his care, according to the report. Both executives sold their shares through pre-planned Rule 10b5-1 trading plans, which are designed to prevent accusations of insider trading, as per Fortune. These plans lock in trade dates, volumes, and prices based on formulas rather than discretion, and must be executed by independent third parties, according to the Nvidia founder and CEO Jensen Huang, whose own net worth has ballooned to $153 billion, surpassed even billionaire investor Warren Buffett, as per Fortune. Huang is famously known to be obsessed with work, he claims he can't even watch a movie without thinking about the company, but he's just as focused on rewarding those who help build it, according to the report. Huang said recently during a panel hosted by venture capitalists running the All-In podcast, saying, 'I've created more billionaires on my management team than any CEO in the world. They're doing just fine,' and added that, 'Don't feel sad for anybody at my layer. My layer is doing just fine,' quoted also revealed that he makes sure that his key personnel are being compensated appropriately and also look at all employees' pay, as reported by Fortune. Huang told the panel this month, 'I review everybody's compensation up to this day. I sort through all 42,000 employees, and 100% of the time I increase the company's spend on [operating expenses]. And the reason for that is because you take care of people, everything else takes care of itself,' as quoted in the Fortune are Nvidia's newest billionaires?Colette Kress (CFO) and Jay Puri (EVP of Worldwide Field Operations) have both become billionaires, largely due to their Nvidia stock holdings. What is Rule 10b5-1? It's a legal framework that allows executives to sell stock through pre-set plans to avoid insider trading accusations.
Economic Times
31-07-2025
- Business
- Economic Times
China's cyberspace regulator summons Nvidia over H20 chip risks
Reuters FILE PHOTO: An Nvidia logo is shown at SIGGRAPH 2017 in Los Angeles, California, U.S. July 31, 2017. REUTERS/Mike Blake/File Photo China's cyberspace regulator summoned Nvidia on Thursday over security risks related to its H20 chips, it said in a statement. Nvidia was required to provide explanation on "backdoor vulnerability security risks" of its H20 computing chips sold to China and submit relevant documents, the Cyberspace Administration of China said.
The Star
29-07-2025
- Business
- The Star
Nvidia-backed Enfabrica releases system aimed at easing memory costs
A NVIDIA logo is shown at SIGGRAPH 2017 in Los Angeles, California, U.S. July 31, 2017. REUTERS/Mike Blake SAN FRANCISCO (Reuters) -Enfabrica, a Silicon Valley-based chip startup working on solving bottlenecks in artificial intelligence data centers, on Tuesday released a chip-and-software system aimed at reining in the cost of memory chips in those centers. Enfabrica, which has raised $260 million in venture capital to date and is backed by Nvidia, released a system it calls EMFASYS, pronounced like "emphasis." The system aims to address the fact that a portion of the high cost of flagship AI chips from Nvidia or rivals such as Advanced Micro Devices is not the computing chips themselves, but the expensive high-bandwidth memory (HBM) attached to them that is required to keep those speedy computing chips supplied with data. Those HBM chips are supplied by makers such as SK Hynix and Micron Technology. The Enfabrica system uses a special networking chip that it has designed to hook the AI computing chips up directly to boxes filled with another kind of memory chip called DDR5 that is slower than its HBM counterpart but much cheaper. By using special software, also made by Enfabrica, to route data back and forth between AI chips and large amounts of lower-cost memory, Enfabrica is hoping its chip will keep data center speeds up but costs down as tech companies ramp up chatbots and AI agents, said Enfabrica Co-Founder and CEO Rochan Sankar. Rochan said Enfabrica has three "large AI cloud" customers using the chip but declined to disclose their names. "It's not replacing" HBM, Sankar told Reuters. "It is capping (costs) where those things would otherwise have to blow through the roof in order to scale to what people are expecting." (Reporting by Stephen Nellis in San Francisco; Editing by Jamie Freed)
The Star
18-06-2025
- Science
- The Star
Nvidia-backed AI startup SandboxAQ creates new data to speed up drug discovery
FILE PHOTO: A NVIDIA logo is shown at SIGGRAPH 2017 in Los Angeles, California, U.S. July 31, 2017. REUTERS/Mike Blake SAN FRANCISCO (Reuters) -SandboxAQ, an artificial intelligence startup spun out of Alphabet's Google and backed by Nvidia, on Wednesday released a trove of data it hopes will speed up the discovery of new medical treatments by helping scientists understand how drugs stick to proteins. The goal is to help scientists predict whether a drug will bind to its target in the human body. But while the data is backed up by real-world scientific experiments, it did not come from a lab. Instead, SandboxAQ, which has raised nearly $1 billion in venture capital, generated the data using Nvidia's chips and will feed it back into AI models that it hopes scientists can use to rapidly predict whether a small-molecule pharmaceutical will bind to the protein that researchers are targeting, a key question that must be answered before a drug candidate can move forward. For example, if a drug is meant to inhibit a biological process like the progression of a disease, scientists can use the tool to predict whether the drug molecule is likely to bind to the proteins involved in that process. The approach is an emerging field that combines traditional scientific computing techniques with advancements in AI. In many fields, scientists have long had equations that can precisely predict how atoms combine into molecules. But even for relatively small three-dimensional pharmaceutical molecules, the potential combinations become far too vast to calculate manually, even with today's fastest computers. So SandboxAQ's approach was to use existing experimental data to calculate about 5.2 million new, "synthetic" three-dimensional molecules - molecules that haven't been observed in the real world, but were calculated with equations based on real-world data. That synthetic data, which SandboxAQ is releasing publicly, can be used to train AI models that can predict whether a new drug molecule is likely to stick to the protein researchers are targeting in a fraction of the time it would take to calculate it manually, while retaining accuracy. SandboxAQ will charge money for its own AI models developed with the data, which it hopes will get results that rival running lab experiments, but virtually. "This is a long-standing problem in biology that we've all, as an industry, been trying to solve for," Nadia Harhen, general manager of AI simulation at SandboxAQ, told Reuters on Tuesday. "All of these computationally generated structures are tagged to a ground-truth experimental data, and so when you pick this data set and you train models, you can actually use the synthetic data in a way that's never been done before." (Reporting by Stephen Nellis; Editing by Leslie Adler)
