Twenty-five years ago, Nvidia changed the world of computing forever, sparking a ripple effect that is reshaping technology all around us today.
On October 11, 1999, Nvidia released its first graphics processing unit (GPU), the GeForce 256. It revolutionized PC gaming, which was still in its infancy at the time. While Nvidia has had a massive impact on PC gaming in the decades since then, the GeForce 256 also set in motion Nvidia’s path toward tech supremacy, not just in gaming, but in artificial intelligence.
As of August 2024, Nvidia controls a staggering 80% of the AI chips market, and CEO Jensen Huang isn’t slowing down any time soon.
Huang made headlines in May when Nvidia announced during a quarterly earnings call that it will release a new AI chip every year, doubling its release speed from its previous two-year schedule.
This move is not only ambitious but a necessary response to the rapid growth of AI over the past year. 2024 saw an explosion in new AI apps and products, from AI dog collars to the jaw-dropping SORA video generator. For AI to advance and evolve even further in 2025, AI developers need ever-more powerful chips to train and run their algorithms.
That’s where Nvidia comes in. Behind every AI model you ask to write text for you or generate a meme, there’s probably an Nvidia chip hard at work.
At least, for now. Can Nvidia’s ambitious yearly release schedule keep it ahead in the competitive AI arms race?
How Nvidia became the hardware hub behind the AI boom
Nvidia was founded in Fremont, California in 1993 by then-30-year-old Jensen Huang and two friends, Chris Malachowsky and Curtis Priem. Huang remains at the helm of Nvidia over 30 years later. Malachowsky is also still at Nvidia as a member of its executive staff and a senior technology executive. Priem retired from the company in 2003.
The trio was inspired to found their own chip company after witnessing the amazing progress in 3D graphics that was starting to take shape in the early 90s. It only took six years for Nvidia to launch the world’s first GPU, the GeForce 256, which revolutionized PC gaming.
To this day, Nvidia remains one of the two main GPU brands dominating the PC gaming market. AMD is its main rival in the space, but Nvidia’s chips are widely considered the gold standard among gamers. That success has helped Nvidia earn a place among the most successful companies in the world, valued at over $3 trillion.
Nvidia isn’t settling for success in just gaming, though. GPUs are capable of more than rendering stunning graphics. They are also the perfect solution for the intense processing power needed to develop and run large language models (LLMs), like OpenAI’s ChatGPT.
You have probably used an AI model powered by one of Nvidia’s chips without even realizing it. OpenAI and Meta use Nvidia’s H100 GPU to train their AI models. The H100 chip has become one of the most sought-after GPUs in the world amidst the AI boom.
In fact, demand for Nvidia’s AI-capable GPUs has grown so much that its upcoming Blackwell chips are expected to cost upwards of $30,000. The skyrocketing clamor for GPUs capable of running AI leaves many analysts wondering if we could soon face another GPU shortage like the infamous 2020 drought, driven by a cryptocurrency boom.
While other companies are making GPUs, like AMD and Intel, there’s no denying Nvidia has a firm hold on the market, for both gamers and AI developers. The question is, how much longer can Nvidia remain at the top?
Jensen Huang’s fear and vision for Nvidia and the future of the chip market
Nvidia’s initial rise to success was driven by innovation in a budding market. In the early 90s, that was PC gaming and 3D graphics. For Nvidia to not only stay on top but to grow throughout the 2020s and beyond, it will have to innovate again, this time in the AI market.
Nvidia is already well on the way to accomplishing that, as its H100s chips prove. However, Jensen Huang knows countless competitors are hungering to take a slice of Nvidia’s market share.
At the 2023 New York Times DealBook Summit, Huang admitted a persistent fear of Nvidia going out of business, commenting in an interview, “I don’t wake up proud and confident. I wake up worried and concerned.”
Huang explained, “I don’t think people are trying to put me out of business — I probably know they’re trying to, so that’s different. I live in this condition where we’re partly desperate, partly aspirational.”
This awareness of Nvidia’s highly coveted, yet precarious spot at the top of the chip market explains Huang’s decision to move to a yearly release cadence. The decision isn’t just about self-preservation and market leadership, though. For Huang, it may also be about pursuing a vision for AI and the possibilities we have yet to achieve.
In the 2023 DealBook Summit interview, Huang said, “There’s a whole bunch of things that we can’t do [with AI] yet. We can’t reason yet, this multi-step reasoning that humans are very good at.”
Huang theorized that we could see early examples of Artificial General Intelligence (AGI) within the next five years. Interestingly, he also stressed that AI is part of the innovation powering its own evolution. The H100 chips were designed with assistance from AI and Huang has been adamant that AI will continue to play a major role in innovation at Nvidia.
Perhaps that alone is reason to be confident in Nvidia’s continued success. Nvidia is arguably one of the best examples of the power of human and AI collaboration, one that could soon lead to some of the most staggering advancements in the history of computing.
If you’re anything from an AI enthusiast to the average AI tinkerer (or simply seeking out some of the additional features offered through Windows Copilot+ PCs or Apple Intelligence on Macs), then you’ll need a powerful and performative laptop to keep up to speed with your needs.
At Laptop Mag, we review laptops year-round to ensure we’re giving you expert-backed and up-to-date recommendations on which notebook is right for you. When it comes to the best AI PC category, our top picks are the excellent Asus Zenbook S 14 (UX5406) for Windows users and the impressive Apple Macbook Air M3 for those running macOS.
So, if you’re shopping for a new laptop and looking to invest in an AI PC (or just a great laptop in general), check out our current top-tier picks below.
We love the MacBook Air 13 M3. Starting at just $1,099 (MSRP), with education pricing dropping to $999 (MSRP), the Air is a laptop we can recommend for just about any purpose. It’s affordable, especially by Apple standards, and it features an excellent keyboard, fantastic performance, and outstanding endurance (over 15 hours of battery life), which makes it a great laptop for just about anyone’s needs, especially those interested in getting to grips with all of the latest Apple Intelligence features.
The Asus Zenbook S 14 (UX5406) has quickly become our favorite AI PC laptop of the year, offering all the hallmarks of a great buy, including exceptional performance and battery life. This laptop is one of the first to feature an Intel Core Ultra 200V series processor and at just $1,499 (MSRP), you get a fantastic balance of power, a stunning 14-inch OLED display, effortless multitasking, NPU-enhanced performance for AI tasks, and all of the additional Copilot+ features available with Windows 11.
