The Meteoric Rise of Nvidia [Fastest Growing Stock]

this video is presented by Aura Hello, welcome to another episode of Cold Fusion 220%, which is the surprising

rise

in the

stock

price of the California-based chipm giant. They have secured the position as the top-performing

stock

in the S&P 500 by 2023 traditionally. Nvidia is the company behind companies powering Netflix Adobe Airbnb NASA and even Kellogg's cloud services for those outside the tech space Nvidia is probably the biggest company you've never heard of according to Amazon, over 90% Of Fortune 100 companies use AWS or Amazon Web Services, which today runs on Nvidia hardware, Nvidia helps power AI systems like GPT chat and also partners with Google.

It is also used in Amazon's robot warehouses. In short, Nvidia is a much bigger business than most people realize, it's not just a company that makes gaming graphics cards even though that's what they've become known for, they're selling shovels in a gold rush providing the infrastructure for the digital age and that is why today Nvidia is worth more than $1 trillion while there are questions about whether a company with a market capitalization of $1.2 trillion is part of a bubble, there is no doubt the influence Nvidia has had on the industry as a whole since it almost went bankrupt in 1995.

It's been a notable turnaround. In this episode we explore Nvidia's extraordinary journey from technical feats to unraveling pricing controversies. the true size and history of the company the 1990s, a decade of fuzzy television, dial-up internet and beige boxes, those of us who grew up in this decade also witnessed the evolution of the personal computer in the early 1990s. 1990s, which featured a file explorer window or fragments of The text was about all the graphics you would need. CPUs were powerful enough for that, unless you were in the animation or engineering industry, there was no need for complicated graphics if you wanted video game consoles to be the answer, but what if there was separate hardware? processor that could easily bring graphics into the world of personal computing Hidden in sunny California, a trio of engineers Jensen Hang Chris Malachowski and Curtis Prum were thinking the same thing they'd find at a local Denny's where endless cups of coffee fueled their conversations in one of In these meetings the trio noticed something: a CPU that is the heart of the computer is designed as a general-purpose processor that can only tackle one task at a time, a method known as serial processing, when generating 3D graphics for video games included tremendously repetitive mathematics. intensive demands on CPUs, if there was a separate chip that could do parallel processing, it would be a game changer;

In other words, this chip would divide complex tasks into smaller ones and carry them out at the same time. This approach is much more efficient for tasks such as rendering 3D graphics where many calculations can be done at the same time. This new chip would not replace the CPU but would complement it for graphical tasks. This would later be known as the GPU and this idea was the beginning of Nvidia, It was a simple idea in modern retrospect, but it would revolutionize not only computing but also computer science in the next 20 years, but at this time Nvidia's focus was on the gaming experience on PCS in the 90s and that market.

It had great potential, so in 1993 in a condo in Fremont, California. Nvidia was founded with the idea of ​​applying the use of GPU parallel processing in home computers. Fun fact, the name Nvidia is actually the Mento port of nvy, short for the upcoming version and I

nvidia

, which means envy in Latin, you'll notice all the green in their logos. This represents the envy they hoped everyone would feel because of the computing power their chip would generate before we continue, let's hear a brief word from today's sponsor, Aura, every day, countless people are affected by data brokers and are winning a fortune selling your information.

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nvidia

were the best engineers.

Jensen Hang, a Taiwanese American electrical engineer, had a background as a Weare core director at LSI Logic and a microprocessor designer at AMD. Remember the name LSI Logic. This company would be essential for Nvidia to take off. the other two founders were also capable Chris Malachowski brought engineering experience from his time at HP and Sun Microsystems and Curtis Prim was a graphics chip designer at IBM and Sun Micro Systems, although being a qualified engineer is one thing, but launching a startup is another. and this is something the hateful founders learned firsthand; In fact, at first they weren't even sure what to do, so they hired a lawyer to attend one of their meetings in 1993.

The first step was to incorporate the company to get the ball rolling they needed. some initial capital to value the company's shares. Jensen Hang had $200 in his pocket which he handed to the lawyer. This modest sum not only got the company incorporated, but also gained a 20% stake in Nvidia. The next step was to finance the company. However, the process was not easy as Nvidia's founders soon learned that venture capitalists were not interested in polished business plans, but instead relied on their founders' reputation, past success, and a grand vision. big enough to make it worth the risk.

Nvidia would eventually get $20 million in financing from Sequoia. Capital and Suter Hill Ventures from the outside this seems absurd. How could a startup secure $20 million in funding like that? It was actually Jensen Hang's previous connection with LSI Logic, the company I mentioned earlier, that made the financing that Jensen would reach possible. Sequoia had previously invested in LSI Logic, which generated a record return of $150 million through its IPO with Hang's reputation within LS. Sequoya was ready to listen when he first knocked on the door. The founder of Sequoia was skeptical about investing in a graphics card company, but they finally took a chance and invested an initial sum of $2 million followed by another $18 million.

What I'm going to say next is key context. This was a very risky decision at the time. There were 89 other companies with similar ambitions as Nvidia, but the fact of the matter is that, with the exception of AMD and Nvidia, none of these other companies would survive when Nvidia went public in 1999. It was valued at 600 million, so that the risk of the initial investment was worth it. generously multiplied by 100 times, but we are getting ahead of ourselves at this stage in history. Nvidia was just a small group of engineers after receiving funding, it took Nvidia 2 years to form a team and create their first product, the nv1, which was officially launched in 1995 during the development of the nv1 chip, Nvidia got a deal with Sega to make nv1 chips for their game consoles, these chips were intended for games like Virtual Fighter and Daytona.

The nv1 chips were also available for computers, meaning you could play Sega Saturn games natively on your PC in 1995 for context, the first PlayStation only came out a year earlier until today. I don't think I've seen anything similar done, as it's like Sony built a graphics computer. card and you could insert it into your desktop and play PS5 games natively, but there was a problem, although Nvidia chose to use a quadrilateral-based image rendering architecture for its nv1 chips and Sega was not happy with this, regardless of the fact that the Nvidia leadership refused to change their decision, so the question is why they chose to render polygons in quadratics instead of triangles.

That choice is explained in this video through lazy game reviews. This uses quadrangles or squares instead of triangles to speed up rendering by reducing CPU workload, at least in theory. in fewer polygons and renders better rounded objects, so you could do things with squares instead of just a bunch of triangles everywhere and at the time with much lower CPU speeds and memory clocks and all that, it made sense to use squares in place. of triangles at least in some situations to get better rounded objects or models in your game because triangles required more processing power now that memory was getting better and better, this made little sense and it also made little sense at the time because this meant that there was no support for openg GL, they didn't even want to include it.

I read a statement from Nvidia and SGS Thompson saying that they didn't think consumers would need opengl at all so they just didn't bother with it and then when Direct 3D and Direct x came out uh this couldn't do that either because it didn't support rendering through quads, just through traditional triangles and those types of polygons, they released a driver or a patch to update it. run directex but only through software, so you are effectively running a hardware accelerator in software mode to run direct Designed to be a jack of all trades combining audio and video processing with 3D graphics and a host of other functions on a single chip, as Jensen Hang would later say, it was a complicated, multifaceted octopus and perhaps too ahead of its time. , the end result was a failure to capture the market's attention. what the market wanted was something much simpler, they wanted a dedicated 3D graphics chip, they didn't want an all in one solution like the nv1 chip, apart from it being too expensive compared to the competition, to make matters worse.

The industry in general was moving. In a different direction, Microsoft had recently introduced Direct X, a new API that favored a triangle-based standard for rendering 3D graphics. It made coding graphics easier for developers, so they naturally flocked to it. This change meant that the nv1 chip was incompatible with Direct The incompatibility was a significant blow to Nvidia. Their customer partner Diamond Multimedia returned the vast majority of the 250,000 nv1 units they had purchased, citing poor sales and lack of games. Supporting this comeback nearly bankrupted Nvidia, forcing them to lay off 40 of 80 employees and leaving them with a stockpile of chips that could not be sold;

In essence, it was a 10 million doll disaster in the midst of turmoil. Nvidia was in the process of developing the nv2 chip for Sega, but it was also based on the same outdated quadrilateral architecture. Nvidia now knew they had to pivot to survive. Jensen Hang had a major problem here. In a hail move, he approached the CEO of Sega to ask him to release us from the contract, but with full payment. Nvidia desperately needed this money to keep the company afloat in an act of extraordinary kindness. Sega's CEO accepted Hang's request. This act of generosity allowed Nvidia to redirect its focus and resources toward a path that aligned with the direction of the industry if Sega withdrew its investment in At that time, Nvidia would have generally ceased to exist.

The failure of the nvy 1 became a critical learning experience for NVIDIA. They realized the need to understand customer needs and market trends. This shaped Nvidia's strategy going forward. I think it's pretty surprising how close Nvidia came to failing and now. With a value of over a trillion dollars, making the decision to listen to the market and focus on PCS was the beginning of their success after their initial failure. Nvidia decided to jump into the PC industry this time with a simple product. The PC market was booming and everything they needed. What he had to do was lie about weight and pounds at the timeRight in 1999, Nvidia entered the PC graphics market with the GeForce 256 graphics card.

This card was not only a success, it transformed the landscape as the first programmable graphics card, it also popularized the The term GPU or graphics processing unit allowed It allowed both regular gamers and developers to explore new possibilities with shading and lighting effects, significantly improving the gaming experience as Nvidia rode this wave of success. The company went public in the same year. In 2000, Nvidia had landed a major deal to develop graphics hardware for Microsoft's Xbox game console, this deal gave Nvidia a substantial $200 million advance, a far cry from the game console's previous effort with Sega, The Xbox would launch in 2001 with a custom console-ready chip called nv2a with this success as Launchpad Nvidia thrived during the 2000s, they played a key role in creating Sony's Playstation 3 processors.

Massive brands in the computer industry like Apple. Dell and HP started using nvidia GPUs. The company continued to grow from strength to strength. Let's take a look at the strategies and technologies. What got them there, one of Nvidia's most important strategic decisions was to operate as a fabulous chip company, so what is a fabulous chip company? Well, the fabulous chip companies design the chips but don't physically manufacture them. Jensen Hang, the CEO of nvidia was very particular about this. decision a decision to keep costs drastically low in the case of nvidia tsmc or Taiwanese semiconductor manufacturing company has been its manufacturing partner for the past three decades tsmc is the world's largest and most advanced semiconductor foundry provides manufacturing services for other large chip design companies, including Apple, AMD, Qualcomm and others. tsmc played an important role in nvidia's continued success as they have the best manufacturing capabilities in the world.

Jensen Hang knows this well, in his own words, he quotes Nvidia wouldn't be here today, if it weren't for the pioneering work that tsmc did while outsourcing manufacturing to nvidia, the company could direct resources to innovation, they began to Shifting their focus beyond gaming chips and graphics, they realized that the GPUs and parallel processing power they possessed could be used for much more. Now it sought to give developers the tools and software to harness the full potential of the GPU. In 2006, Nvidia released a software toolkit called cuda. ​​Before programming Cuda, a GPU required a lot of tinkering and was a real headache for programmers as it involved complex low levels. -Machine language or API level, but with Cuda it became much easier to write programs that could run on GPU using standard languages ​​like C, C++ and Java.

The impact was that many more applications instead of just graphics were able to use parallel processing power, it opened up possibilities for all sectors. That required dealing with huge amounts of data, the trend began in 2008 when the Tokyo Institute of Technology used the Cuda GPU accelerator for its Bame 1.01 supercomputer. Since then, many other data centers, such as Amazon Web Services, Google Cloud Platform, and Netflix, have adopted GPUs for various applications. These applications include cloud computing, machine learning, video streaming, and web search, but the true acceleration It came with the

rise

of AI. 2012 is the year that many consider the Big Bang moment for AI.

This was also the year that nvidia's innovations would be involved in significant AI. This breakthrough came at Imet, an annual global competition where teams from around the world competed to see how well their software could recognize objects, scenes and images. Alex Keski, a PhD student at the University of Toronto at the time, entered the competition with a novel approach that harnessed the power of GPUs to improve the computing efficiency of his deep learning neural network Alexnet deep learning is a process in which that computers can learn on their own without the help of programmers by connecting two Nvidia GeForce GTX 580 game cards to your computer Compu kesy was able to process Alex Net's neural network with 1.2 million images, the result was notable in At the time, image recognition accuracy showed a 15% error rate, compared to 25% the year before, today it's ridiculous that tools like GPT chat, Google Gemini, and even Google Lens can do it now with much more precision, but at the time it was revolutionary.

It was this event that kicked off the AI ​​winter after decades of experts accepted that neural networks would never be practical. This proved them wrong. The Nvidia GeForce GTX 580 cards were important because they were optimized. for Cuda, which of course allows the implementation of parallel algorithms, were crucial for the deep learning tasks performed by alexnet AI now the door had been opened wide for many possibilities in deep learning applications and Nvidia was ready for it. The strategic time and investment in Cuda and the software ecosystem around it was paying off. Nvidia GPUs are now the deao standard for training and deploying generative AI and large language models, for example, open chat-aware AI.

GPT uses A100 series GPUs and this is for the rapid and widespread deployment of its AI models after the GPT chat burst onto the scene in November 2022, all the major technology companies hoping to cash in on the AI ​​hype rushed to To get your hands on Nvidia GPUs, the A100 GPUs, especially the A100 GPUs, were flying off the shelves. Microsoft alone was using a whopping 10,000 of For them, a single a100 unit would cost $110,000 and Nvidia was selling hundreds of thousands of units as a result of this frenzy. Nvidia's sales soared to $13.5 billion in the quarter ending July 2023, a staggering 101% increase from a year earlier on May 25. gained $184 billion in market value in just one day and finally, on May 30, 2023, Nvidia became the sixth company in the world to reach that magical $1 trillion market cap, joining companies like Apple, Microsoft, Amazon Alphabet and Tesla at the time of writing in December 2023. the company is worth $1.15 trillion Nvidia's impact on the healthcare industry is also notable in 2022 a genomic sequencing technique from Nvidia set a Guinness World Record for the

fastest

DNA sequencing, completing the feat in 5 hours and 2 minutes Nvidia's chip technology has further impacted the fields Tegra chips, once designed for mobile phones, power major mobile operations e-commerce and autonomous cars.

Tesla used those chips to power its Model 3S from 2016 to 2019. Tesla now uses its own chips, but Nvidia provides semi-autonomous driving technologies for other automakers like Mercedes. -Benz, then how is a company of this type managed? How did you pivot so quickly to serve so many industries with Microsoft's tenth employee? Let's take a quick detour into nvidia's management style. I think it's quite interesting. Jensen Hang, CEO, directly manages a team of 40 people. and believes in the power of a flat organizational structure - there are no exclusive meetings with only VPS or directors, anyone can join and participate in career coaching sessions because, as Hang says, his management team has already achieved great results, he also chooses to a more dynamic approach. by encouraging anyone in the company to send you their quote the five most important things on the go when it comes to information flow, everyone is informed at all times, this ensures that information is transmitted quickly, there is no Planning cycle like a large 5-year period or one-year plan is about being agile and adapting to ever-evolving business and market conditions, especially in the rapidly changing field of AI.

Jensen also has an eye for top-tier talent, keeping the team agile amid the post-major tech economic crisis. Companies like Facebook, Amazon and Google laid off thousands of workers, in contrast, Nvidia has pledged to avoid layoffs or pay cuts by promising raises for staff since its 1995 layoff disaster with the Sega chip. Nvidia's internal operations regarding this have changed drastically, an example of this was in 2008 when nvidia's Tegra chip failed, Nvidia hoped to enter the mobile industry and created the Tegra smartphone chip. Aside from that, there was actually a Tegra-powered Android tablet called the Asus Transformer. I had one of these in the past and found the performance to be excellent. be quite disappointing, many others must have also thought the same because the chip failed to gain traction and failed in a team of over a thousand engineers were responsible for the development of the Tegra series instead of getting rid of them after the failure of the chip.

Jensen retained the team. and encouraged them to explore new avenues, the team then collaborated with Nvidia's existing automotive unit and together they would create chips for self-driving cars, so we've touched a lot on what Nvidia is involved in and what they've been doing, but There is still a key sector that we should talk about their original Focus games, although Nvidia has diversified, they have not completely abandoned the gaming market. GPUs remain the core of its business in 2018, Nvidia launched the RTX series of graphics cards popularizing a technology called Ray. tracing Ray tracing is a demanding technique that simulates light paths, creating shadows, reflections and more realistic effects.

Previously, this was generally not a real-time effect, it was only common in the 3D art and animation sectors in the Jensen Hang view. It is only possible thanks to Nvidia's research in physics simulation and artificial intelligence. He explains that Nvidia uses AI to generate seven out of eight pixels in a scene based on one pixel with ray tracing. It's like a puzzle where AI fills in the missing pieces. Nvidia also popularized the Improving the AI ​​of video games in real time is a process called dlss that in theory allows for sharper, higher resolution games without the computational load, but in all of this there has been a problem with nvidia gpus and now we get into the controversies, the year is 2018 and the crypto mining boom is at its peak, miners rushed to buy as many GPUs as they could to earn some cash, as a result the demand for GPUs skyrocketed and the supply sold out for those who normally use them, meaning gamer prices skyrocketed. 71% in some cases Amid this increase, Nvidia's gaming revenue increased by 26% to 1.65 billion boost with this writing The investor's ability to accurately evaluate the company's performance was compromised, its investments risky unknowingly eventually collapsed along with the crash of cryptocurrencies, this incident attracted the attention of the US Securities and Exchange Commission and Nvidia was accused of illegally hiding information that Nvidia would liquidate in 2022. paying a fine of $5, 5 million and did not admit any fault or irregularity, but agreed to improve their income.

Disclosures from sources in response to this in 2021, Nvidia decided to introduce a dedicated crypto cryptocurrency mining processor or CMP line. This was supposedly to address the gaming card shortage, but at $4,300 per CMP, crypto miners would rather buy regular gaming graphics cards. Jensen Hang is the only CEO of a tech giant who has been at the helm since the company's inception. It has been 30 years and his long and successful leadership. He has also attracted some criticism over the years. One of the most controversial aspects of his management style is his relentless pursuit of profits that sometimes borders on greed after being fined by the SEC.

The lack of transparency left many investors feeling cheated and, apart from this, the gaming community in particular is not enthusiastic about spending so much money on their graphics cards; There is an unmissable chatter online conveying that Nvidia cards are too expensive, especially in the mid-range sector where AMD is more competitive, an incident that did not jeopardize Hang's business ethics. The question was Fallout 2022 with EVGA EVGA was a key partner in nvidia's GPU production. They chose to sever ties with Nvidia and withdraw from the GPU market. This decision, according to EVGA CEO Andrew Han, was initially based on nvidia's unsatisfactory communication about controversial pricing strategies.

Such controversies have cast a shadow on Hang's leadership, which questions the integrity of his profit-oriented approach, perhaps to emphasize the challenges. Hang recently stated in an interviewthat if he were allowed to go back in time, he would choose not to relive this career path he began. and running a company the size of Nvidia was a headache. He says he faced many struggles and difficulties as an entrepreneur, from laying off employees with the nv1 chip in 1995 to competing with larger rivals and dealing with the constant pressure of uncertainty in his opinion, no one in their right mind would want to endure that pressure if they magically You were 30 again today in 2023 and you went to Denny's with your two best friends, who are the two smartest people you know, and you're talking. about starting a business, what are you talking about?

I wouldn't do it, I know that and the reason is pretty simple, ignoring the company we would start in the first place, I'm not exactly sure why I wouldn't do it. Do it and it goes back to why it's so hard to build a company, and building Nvidia turned out to be a million times harder than I expected. Any of us expected it to be and at that moment, we do realize the pain and suffering. and how vulnerable you're going to feel and the challenges you're going to endure, the embarrassment and the embarrassment, and you know the list of all the things that go wrong.

I don't think anyone would start a company, no one in their right mind would and I think that's Nvidia has seen massive growth in the last 2 years. They were in the right place at the right time. The share price is up 220% in the last year and revenue growth. 26%, but the latest opinions are divided, there are two main views: one is that AI will remain a massive industry and is just getting started. This view believes that Nvidia will continue to ride this wave. They are currently betting on AI. The other opinion is that this growth is unsustainable, as it turns out Nvidia won't be the only player in the GPU/ai hardware space, both Amazon and Microsoft are looking to create their own custom item. desktop-based chips Computing space Microsoft has entered the arena with its Arc series AMD is also gaining ground, plus Nvidia's heavy reliance on Taiwan-based tsmc for its semiconductor chip production may prove problematic , this is due to China's increasing military pressure on Taiwan, but this is not just for NVIDIA, but for the entire global semiconductor supply chain.

There are more threats to Nvidia in this chip space today than there have been in many years, so we'll have to wait and see what happens, so there you have it. Nvidia's story so far has been quite a journey, so I hope you've enjoyed it and gained some new ideas. Nvidia is currently hitting an all-time high, but whether this is a fundamental trend or a bubble remains to be seen. I'm curious to hear your opinion. Do you have an Nvidia card? What is your opinion about the company, positive, neutral or negative? Were you surprised by the amount of things they're up to?

Feel free to comment on them in the comments section below. From me, thanks for watching, my name is toogo and you guys have been watching Cold Fusion and I'll see you soon for the next episode. Greetings guys, have a good time.fusion is a new thought