In 1999, fans lined up at Blockbuster to rent thick VHS tapes of The Matrix. Y2K preparers stocked up on cash and cans of Spam, fearing a worldwide computer crash. Teens gleefully downloaded Britney Spears and Eminem on Napster.
But amidst the caffeinated fizz of early 2000s tech culture, something more transformative was unfolding.
25 years ago today, NVIDIA’s GeForce 256 was released, ignored by all but hardcore PC gamers and tech enthusiasts, and went on to lay the foundation for today’s generative AI. .
More than just a graphics card, the GeForce 256 was introduced as the world’s first GPU, setting the stage for future advances in both gaming and computing.
Hardware translation and lighting (T&L) reduced the load on the CPU and was a pivotal advancement. As Tom’s Hardware highlighted, “[GeForce 256]reduces CPU strain, prevents 3D pipeline stalls, and allows game developers to use more polygons, automatically increasing detail will improve.”
Where the game changed forever
For gamers, launching Quake III Arena on the GeForce 256 was a revelation. Enthusiasts at AnandTech say, “The moment you launch your favorite game, it’s like you’ve never even seen the title before.”
The GeForce 256 pairs beautifully with groundbreaking titles such as Unreal Championship, one of the first games with realistic reflections, which sold over 1 million copies in its first year.
Over the next quarter century, NVIDIA’s collaborations with game developers pushed the boundaries, driving advancements like increasingly realistic textures, dynamic lighting, and smoother frame rates, giving gamers far more than just immersive experiences. We will provide innovation that goes beyond.
NVIDIA GPUs have evolved into a platform that turns new silicon and software into powerful, intuitive innovations that reshape the world of gaming.
Over the next few decades, NVIDIA GPUs delivered higher frame rates and visual fidelity, enabling smoother, more responsive gameplay.
This breakthrough in performance allows gamers to stream content with incredible clarity and speed, and has been embraced by platforms like Twitch, YouTube Gaming, and Facebook.
These performance improvements have not only transformed the gaming experience, but also turned players into entertainers. This has helped fuel the global growth of esports.
Major events such as The International (Dota 2), League of Legends World Championship, and Fortnite World Cup attract millions of viewers, cementing esports as a global phenomenon and creating new opportunities for competitive gaming. has been created.
From games to AI: the next frontier for GPUs
As game worlds have become more complex, so have their computational demands.
The parallel power that has transformed game graphics has caught the attention of researchers, who realize that these GPUs have the potential to unlock vast computational power in AI and enable breakthroughs far beyond the world of gaming. I did.
Deep learning—software models that rely on billions of neurons and trillions of connections—requires enormous computational power.
Traditional CPUs designed for sequential tasks could not efficiently handle this workload. But GPUs, with their massively parallel architecture, were perfect for the job.
By 2011, AI researchers discovered NVIDIA GPUs and their ability to handle the massive processing needs of deep learning.
Researchers at Google, Stanford, and New York University have begun using NVIDIA GPUs to accelerate AI development, achieving performance that previously required supercomputers.
A breakthrough occurred in 2012 when Alex Krizhevsky of the University of Toronto won the ImageNet image recognition competition using NVIDIA GPUs. His neural network, AlexNet, was trained on 1 million images and beat out the competition, beating hand-crafted software created by vision experts.
This marked a dramatic change in technology. The raw power of GPUs has made computers learning and adapting from vast amounts of data, which once seemed like science fiction, a reality.
By 2015, AI had reached superhuman cognitive levels, with Google, Microsoft, and Baidu outperforming humans in tasks such as image recognition and speech understanding. All of this is made possible by deep neural networks running on GPUs.
In 2016, NVIDIA CEO Jensen Huang donated the first NVIDIA DGX-1 AI supercomputer, a system with eight cutting-edge GPUs, to OpenAI. OpenAI plans to use GPUs to train ChatGPT when it launches in November 2022.
In 2018, NVIDIA debuted GeForce RTX (20 Series) with RT Cores and Tensor Cores designed specifically for real-time ray tracing and AI workloads.
This innovation accelerates the adoption of ray-traced graphics in games, brings cinematic realism to game visuals, and leverages AI such as NVIDIA DLSS, which leverages deep learning to improve game performance. feature has been introduced.
Meanwhile, ChatGPT, launched in 2022, reached over 100 million users within months of launch, demonstrating how NVIDIA GPUs continue to drive the transformative power of generative AI.
Today, GPUs aren’t just celebrated in the gaming world. GPUs have become icons of tech culture, appearing on Reddit memes, Twitch streams, Comic-Con T-shirts, and immortalized in custom PC builds and digital fan art.
shape the future
The revolution that began with the GeForce 256 continues today in games and entertainment, personal computing where NVIDIA GPU-powered AI is a part of everyday life, and inside the multitrillion-dollar industry built around next-generation AI. continues to be expanded. business.
GPUs don’t just power games, they design the future of AI itself.
And now, with innovations like NVIDIA DLSS, which uses AI to improve game performance and provide sharper images, and NVIDIA ACE, designed to bring more realistic interactions to characters in games, AI We are rebuilding the game world again.
GeForce 256 laid the foundation for a future in which gaming, computing, and AI not only evolve, but work together to transform the world.
