Nvidia's New Super-Computer Has Released A Terrifying To Humanity...

Nvidia Nvidia Nvidia Nvidia was the bell of the ball today's gain was yet another record high the rate at which we're advancing Computing is insane over the course of the last 8 years we've increased computation by 1,000 times our TCO is so good that even when the competitor's chips are free it's not cheap enough and one of the greatest contributions we made was advancing Computing and advancing AI by 1 million times nvidia's new computer has issued a terrifying warning to all other computers this bold move pushes technology to its limits and even Beyond Nvidia which started in 1993 to improve video game Graphics has now become a major force in AI by late 2023 Nvidia had sold 500,000 Hopper based h100 accelerators proving its dominance in the AI Market why is Apple so terrified of going bankrupt after such massive projections from Nvidia let us reveal how these accelerators could leave the current computer power humiliated to its core nvidia's new era in generative AI this pioneering company is shaking up the tech world with its Advanced AI chip technology this Tech isn't just pushing the boundaries of what current devices can do it boldly claims to go even further by enhancing Graphics Nvidia helped make games more immersive significantly improving the gaming experience for users Around the World As Time passed Nvidia shifted its efforts and broadened its focus it ventured into artificial intelligence using its expertise in graphics processing to develop chips that do much more than just render game Graphics these chips are now leading the charge in technological advancements influencing developments in robotics self-driving cars and smart technology launched in March 2022 the hopper architecture was specifically designed for data centers to boost AI abilities its introduction sparked excitement among AI experts leading to a high demand during the AI surge in 2023 however this excitement was tempered by supply shortages and high demand making customers wait up to a year for H 100 based servers by the end of 2023 Nvidia had sold an impressive 500,000 Hopper based h100 accelerators showing its strong position in the AI Market h 100 has a Transformer engine designed to process models like the amazing chat GPT Nvidia named its next architecture Blackwell to honor David Blackwell a notable American mathematician whose work in Game Theory probability Theory information Theory and statistics significantly influenced AI model training algorithms Blackwell was the first African-American elected to the prestigious National Academy of Sciences and naming the architecture after him highlights the importance of his contributions the hopper architecture is a technical Marvel with 28 billion transistors its standout feature is the integration of two chip dies enabling incredibly fast communication speeds of 10 terabytes per second and removing performance delays due to memory or cash while nvidia's technological advances are impressive the excitement they generate often mixes real breakthroughs with hype despite nvidia's advancements it is vital to critically examine the technology and market dynamics driving strong public and investor interest keeping a critical perspective is crucial to distinguish between practical applications and Market excitement this balanced view is necessary to understand the long-term effects and sustainability of nvidia's technology in a rapidly changing industry despite skepticism about their High aims Nvidia has continued to push forward leading to the development of the Blackwell chip this is hopper Hopper changed the world this is Blackwell this Innovative chip integrates smoothly into two system types the first pairs easily with its predecessor Hopper making upgrades simple the second type shown on a prototype board showcases the potential power and future applicability of Blackwell Envision a setup that includes two Blackwell chips and four Blackwell dyes all connected to a Grace CPU through Ultra fast links this Arrangement promises to transform the Computing World nvidia's CEO states that this computer system is revolutionary packing immense computational power into a small size to advance technology further Nvidia introduced several new features designed to exceed traditional technological limits though it has a listed speed of 1.8 tbes per second its actual performance surpasses this making it much faster than Hopper in terms of training capabilities per chip it offers two and a half times the performance of Hopper thanks to its new fp6 format it also introduces the fp4 format which doubles the data processing speed for inference tasks these enhancements are crucial for saving energy reducing Network bandwidth and improving time efficiency all increasingly important in the field of generative AI Nvidia has termed this new phase the generative AI era reflecting a significant shift in how Computing is approached the processor Nvidia has developed for this era is specifically designed to excel in it with one of its main functions being the generation of content tokens enabled by The fp4 Format situated within the Nvidia Blackwell AI supercomputer this processor has five times the capability of hopper for generating tokens and handling inference tasks Nvidia has once again pushed the boundaries of Technology with its latest version of the dgx this new model is a massive step up from the first dgx-1 introduced 6 years ago with 170 Tera flops now considered a modest figure today the new dgx boasts an impressive 700 20 petaflops almost reaching the exaflop level a milestone in computing power that places it among the elite few systems worldwide capable of such Feats this isn't just any AI system it's a Powerhouse compressed into a single stylish rack nvidia's next big reveal is the MV link spine and the powerful dgx system the rise of autonomous robotics the core strength of this machine lies in its MV link spine which offers an extraordinary bandwidth of 130 terabyt per second this capacity exceeds the total bandwidth of the internet an achievement that Nvidia has managed without the expensive components typically required such as high-end Optics or transceivers this not only Cuts costs but also saves a significant amount of energy 20 kW to be exact in a system that uses a total of 120 KW every bit of energy saved is crucial in such a power hungry setup the gpus at the heart of the dgx are far from simple each GPU is a complex assembly of 600,000 parts and weighs about £3,000 putting together one of these gpus is akin to a assembling a small vehicle one capable of handling vast amounts of data rapidly the potential of these gpus is showcased in their ability to train extremely large AI models like a GPT model with 1.8 so trillion parameters previously such a task would have been a marathon taking several months and requiring a massive setup with the previous Hopper architecture the process would still take a significant toll in terms of energy and Hardware however with the new Blackwell gpus the same task can now be accomplished with far fewer gpus only 2,000 and much less power Just 4 megawatts showcasing a leap in efficiency and performance the anticipation around the Blackwell GPU is palpable as it is set to be perhaps nvidia's most successful product launch to date this excitement also marks nvidia's foray into the realm of physical AI with Nvidia robotics in this new Venture machines are designed to interact with the real world sensing moving and responding to their environment this move is a major step forward demonstrating nvidia's ambition to not just participate in the AI Revolution but to lead it as we discuss these technological advancements it's Essen IAL to consider their broader implications the specifications and capabilities of the new dgx are undoubtedly impressive and they represent a significant Leap Forward in computing power however they also raise questions about how these technologies will integrate into everyday life what does this mean for the typical user the broader environment or the structure of our workplaces these are the lingering questions as we continue to witness the rapid evolution of Technology the pace at which we are expected to adapt and integrate these advances into our lives is breathtaking and warrants a thoughtful examination of where we are heading AI has traditionally been limited to operating within the confines of computers like nvidia's dgx system but there's a growing vision that AI will soon Step Beyond these boundaries with robots becoming smart enough to operate independently in the real world this shift from virtual to tangible is driven by nvidia's intense development in robotics using their powerful systems like the dgx for training complex models in the agx designed specifically for robotics to handle rapid sensor processing with with minimal power use the bridge between the digital and the physical is represented by Omniverse nvidia's platform for creating detailed simulations of real world environments which runs on the Azia Cloud picture a warehouse that runs entirely autonomously where human workers and forklifts work together smoothly under the constant supervision of an AI system named the warehouse this system actually like a highly efficient traffic controller ensuring safety and guiding movements within the warehouse all happening in real time each robot in this Warehouse has its own built-in robotic system allowing it to operate efficiently without human intervention it seems that under Blackwell's leadership the future of effective and autonomous robotics is closer than we think as we look further ahead the idea that robotics will soon dominate various Industries seems almost certain presented as a safer and more efficient alternative these robots are set to transform the automotive industry in particular Nvidia has formed Partnerships with major car manufacturers like Mercedes and jlr and plans are underway for byd the leading Electric Vehicle Manufacturer to adopt nvidia's latest technological breakthrough Thor this advanced computer system designed for Transformer engines is expected to revolutionize the way Vehicles operate potentially leading to the development of humanoid robots Nvidia has also launched an ambitious project called project Groot which aims to revolutionize robot learning this project is not just about making small improvements it's about pushing the limits of current technology to develop a foundational model for robots that can understand and process complex instructions and learn from past interactions project Groot represents a significant advancement in the field of Robotics preparing the ground for a future where robots might not only perform tasks but also interact with humans in more meaningful ways with dgx systems transforming AI Nvidia steps into Robotics and autonomous machines the unsung heroes of 3D Graphics Revolution as these advancements unfold one might wonder whether we are moving towards a future where we celebrate our technological achievements or whether we might have to deal with unexpected consequences of opening new technological Frontiers will we look back with pride at the intelligent systems we've created or will we Face challenges that we hadn't anticipated as robots become more integrated into our daily lives and industries these are the questions we may need to consider alongside Isaac Labby Nvidia has introduced osmo a service that manages and coordinates the heavy Computing tasks across Nvidia systems like dgx and ovx while this sounds impressive it brings up issues about the impact on jobs and how much we should rely on robots project Groot is particularly notable for enabling robots to learn from watching just a few human actions allowing them to perform everyday tasks with surprising Precision these robots can even understand and follow spoken instructions making them even more humanlike this ability is powered by nvidia's latest chips called Jetson Thor designed specifically for robots these chips are crucial for project Groot giving robots the processing power they need to operate but as these robots become more common we have to consider what this means for human workers and the ethical lines of AI and automation going back to the early 1990s the scene was quite different most people were using simple computers good enough for basic tasks but anything that required better graphics like video games needed special consoles during this time three Engineers from California Jensen hang Chris malikasi and Kurt PR came up with the idea of Nvidia during their meetups at a local Denny's they realized that the standard CPUs in computers were good at doing tasks one at a time but struggled with the complex repetitive task tasks required for creating 3D Graphics their solution was a new kind of chip called a GPU which could handle multiple tasks at once making it perfect for graphic heavy applications this chip was meant to work alongside the CPU specifically to handle Graphics Paving the way for nvidia's future in changing not just gaming but the entire field of computing in interestingly nvidia's initial aim was quite focused on just improving how games looked on PCS targeting the growing number of people owning home computers the company started in a small condo in Fremont California in 1993 with a name that combined next version and Nvidia which means Envy in Latin a nod to the Envy they hoped their powerful chips would evoke the key figures in nvidia's early days were Jensen hang who had experience at AMD and LSI logic and his Partners Chris malikowski and Kurt PR who came from HP Sun Microsystems and IBM despite their skills starting Nvidia wasn't easy they faced challenges in setting up the company and convincing investors to fund their ideas they began with just $1200 enough to in corporate the company and secure a significant ownership stake for hang raising enough money to turn their Vision into reality was tough investors were initially hesitant to put their money into a company without a proven track record but eventually Nvidia caught the eye of Sequoia capital and Suter Hill Ventures who invested a substantial $20 million this funding was crucial especially considering the competitive landscape at the time with nearly 90 companies trying to make their Mark in the graphics card industry only Nvidia and another company AMD managed to stay relevant over time this initial support from investors was a gamble but it paid off significantly when Nvidia went public in 1999 its value skyrocketing to $600 million this early phase saw Nvidia as just a small team of Engineers with funding taking two years to assemble a team and develop their first product the nv1 launched in 1995 during its development Nvidia struck a deal with Sega to produce chips for their gaming consoles used in popular games like virtu fighter and Daytona this was an interesting move that helped Nvidia gain a foothold in the gaming indust industry setting the stage for its future successes nvidia's choice to employ quadrangles aimed to lighten the computational load the thinking was that using quadrangles would mean dealing with fewer polygons potentially allowing for smoother rendering of round shapes and more complex models given the slow CPU speeds and limited memory of computers in the mid90s this strategy of appeared to make sense at least on paper it promised to streamline rendering processes when Computing resources were limited offering a flexibility in shape creation that triangles simply could not match looking back at nvidia's early struggles we see the rise and fall of the nv1 chip how Nvidia overcame the nv1 disaster however the real world results of this decision were not very good as as the tech world started to support openg a new standard for creating Graphics that worked across different systems and programming languages nvidia's choice to use a system based on quadrangles seemed outdated this issue got worse because Nvidia was doubtful about the need for open myl in consumer Graphics this view looked more and more wrong as the industry moved toward more widely accepted standards the tech scene changed even more with the rise of direct X and direct 3D which made triangles the standard for creating 3D Graphics nvidia's stickiness with quadrangles made the nv1 chip increasingly incompatible with new technologies attempts to fix this like a software update that made the mv1 Run DirectX in a basic software mode just showed the Chip's weaknesses it basically took away the Chip's ability to speed up Graphics making it useless for its original purpose the MV 1's failure to become popular wasn't just a technical error it was a costly mistake for NVIDIA the nv1 was marketed as a chip that could do everything handle Graphics video and audio processing but it was this complexity that led to its failure the market was moving towards simpler more special specialized chips especially for 3D Graphics the nv1 with its high price and poor performance didn't meet these new market needs as the tech World moved to direct X which preferred triangles the m1's Reliance on quadrangles became a big problem this caused major compatibility issues and reduced performance in many games things got to a crisis point when diamond multimedia nvidia's retail partner sent back almost all of the 250,000 nv1 units they had bought due to bad sales this nearly made Nvidia go bankrupt forcing them to cut half of their staff and take a $10 million loss during this tough time Nvidia was also developing the mv2 for Sega which unfortunately still used the problem atic quadrangle architecture realizing they needed to change direction nvidia's CEO hang took a brave step by asking Sega to end their contract but still pay them in full surprisingly Sega agreed giving Nvidia the financial help they desperately needed this situation was a crucial lesson for NVIDIA highlighting the need to keep up with market trends and understand what customer want it was a close call with disaster showing how quickly technological bets can become outdated after this Nvidia refocused and came back to the PC market with a clearer vision in 1999 they released the GE Force 256 graphics card which not only sold well but also set new industry standards this marked the start of nvidia's climb to the top a big change from the tough times they had faced just a few years before while many praise Nvidia for leading the revolution in graphics processing units gpus it's interesting to think about how much of their success comes from Sir smart marketing and good timing when Nvidia introduced the world to programmable graphics cards they didn't just make games look better they changed what was expected in the gaming industry pushing developers to add more complex visual effects this shift set a new standard but also pushed developers to keep up with nvidia's next big thing in graphics Nvidia cleverly planned their initial public offering to match these big Tech advances ensuring a strong start in the market by 2000 their smart moves landed them a big deal with Microsoft to make the graphics hardware for the Xbox console this wasn't just a deal it was a $200 million advance that put Nvidia in a strong position in the growing console Market greatly improving their financial statements the launch of the Xbox in 2001 with nvidia's custommade nv2a chip was more than a tech Victory it strategically placed inidia products in many homes boosting their presence in the mainstream market over the 2000s nvidia's influence grew as they not only worked with Sony's Playstation 3 but also caught the attention of big computer makers like apple Dell and HP who started using nvidia's gpus in their devices cementing nvidia's dominance in the market after the nv1 challenges nvidia's come back with the GeForce 256 sets new standards nvidia's key role in the AI boom nvidia's CEO opted for a fabless operational model early in the company's history Nvidia designed the chips but outsourced their production mainly to thawan semiconductor Manufacturing Company the world's top semiconductor Foundry this strategy was seen as a way to cut costs and while it certainly reduced Financial outlays it also made Nvidia highly dependent on tsmc's success and stability this relationship while beneficial exposes Nvidia to risks if e any issues arise with tsmc's operations pointing to a potential weak spot in nvidia's business model expanding the use of gpus Beyond Graphics was a Visionary step by Nvidia in 2006 they launched chuda a toolkit that transformed the programming of G pus making it easier for developers to use familiar programming languages such as C C++ and Java this Innovation opened up new possibilities for gpus allowing them to be used in diverse Fields like data analysis scientific research and artificial intelligence far beyond traditional Graphics applications by 2008 institutions like the Tokyo Institute of technology were using cudai enhanced gpus to improve their supercomputers a practice soon adopted by major companies like Amazon web services Google Cloud platform and Netflix these firms use gpus for various tasks including cloud computing data processing and video streaming showcasing the versatility of nvidia's Technology a significant shift occurred in in 2012 with the development of alexnet by Alex kvki this deep Learning Network powered by Nvidia gForce GTX 580 gaming cards dramatically improved how computers recognized images this breakthrough not only proved the Practical value of a neural networks but also revitalized interest in AI research although the improvement from from a 25% to a 15% error rate might seem small today at the time it represented a Monumental Advance Paving the way for the sophisticated AI systems we now rely on daily nvidia's narrative is often portrayed as a series of deliberate and strategic successes but it's essential to question this portrayal was there a result of foresight and planning or were they simply capitalizing on the right opportunities at the right time as we celebrate the successes of tech giants like Nvidia it's important to recognize that their paths are often a mix of strategic planning opportunism and fortunate timing many initially doubted the Practical use of neural networks seeing them more as academic experiments than anything else yet events that demonstrated their real world applications Chang changed that perspective dramatically among the key players in this shift were the Nvidia GE Force GTX 580 graphics cards designed specifically to handle QA technology this specialization made them critical for running parallel algorithms essential for early deep learning efforts like those seen in alexnet this development was pivotal ushering in New Age of deep learning applications with Nvidia at the helm nvidia's early bets on cou day and their development of a comprehensive software ecosystem began to yield significant turns their Graphics processing units gpus quickly became the go-to choice for developers working on complex AI projects including generative Ai and massive language models open AI known for its development of chat GPT utilized nvidia's a100 series gpus extensively leveraging their Advanced capabilities to roll out AI models efficiently and on a large scale the release of chat GPT in November 2022 set off a rush for nvidia's gpus particularly the a100 series which soon became a sort-after resource big tech companies including including Microsoft were among those eager to get their hands on these gpus with Microsoft alone purchasing 10,000 units despite each GPU costing $110,000 Nvidia sold hundreds of thousands leading to a significant boost in their sales figures by the quarter ending in July 2023 nvidia's sales had doubled year-over-year to 13.4 5 billion on May 25th 2023 there was a huge increase in interest and sales that boosted nvidia's stock market value by $184 billion in just one day a few days later on May 30th Nvidia hit another major achievement by reaching a market cap of $1 trillion this made Nvidia the sixth company in the world to reach this impressive Milestone as of today nvidia's market value has soared even higher hitting an astounding $2 trillion this incredible growth and nvidia's strong position in the tech Market highlights several key points first nvidia's success is a clear example of how creativity and smart planning in business can lead to remarkable outcomes it shows that being Forward Thinking and Innovative can Propel a company to the top of its industry however this success also brings up some concerns about the balance of power within the tech world with so much influence concentrated in just a few Tech Giants there are worries about the broader effects this could have on society the push to be the leader in technology might sometimes mean that we don't pay enough attention to how these advancements affect people's lives and the world as a whole as Nvidia continues to grow and shape the tech landscape it's important to think about these issues the company's Journey from a strong player to a market leader worth $2 trillion is not just about financial numbers it's also about understanding the responsibilities that come with such power and influence there's a need for a careful look at how the actions of big tech companies like Nvidia impact the broader Society from economic changes to social dynamics this conversation is essential as we navigate the complex relationship between technological progress and its effects on our daily lives and the global Community as Nvidia shapes our digital future should we worry about the power of tech giants like leave your comments and subscribe for more insights on this evolving landscape

Channel: Cosmos Lab

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Keywords: nvidia gtc 2024, nvidia keynote, jensen huang keynote, nvidia robots, jensen huang robots, nvidia blackwell gpu, blackwell, nvidia, nvda, nvidia stock, nvda stock, jensen huang, openai, chatgpt, gpt4, msft, microsoft stock, msft stock, googl, google stock, artificial intelligence stocks, nvidia stock news, semiconductor stocks, gpt-4, nvidia news, ai copilot, omniverse, ai stocks, best ai stocks

Id: NA46tMKVgh8

Length: 34min 37sec (2077 seconds)

Published: Wed May 29 2024