The evolution of hardware for Artificial Intelligence: the success story of NVIDIA

Nvidia - Raptech

The evolution of hardware for Artificial Intelligence: the success story of NVIDIA

Artificial Intelligence (AI) is revolutionizing the world we live in and hardware is playing a crucial role in this process. The evolution of AI is closely linked to the progress of the hardware that supports it, opening up new possibilities and challenges. In this new blog post from Raptech we will explore the success story of NVIDIA, a leader in generative AI, which recently presented its new Blackwell chips in California. We will analyze the importance of hardware in the evolution of Artificial Intelligence and NVIDIA’s role as a pioneer in this sector.

The importance of hardware in the evolution of Artificial Intelligence

The evolution of Artificial Intelligence is closely linked to the development of hardware. Without the right hardware, AI could not reach its potential. As the years have passed, there have been notable advances in technology, allowing for the creation of increasingly advanced chips to support Artificial Intelligence.

Through its hardware solutions, such as graphics processors (GPUs), NVIDIA has helped advance Artificial Intelligence in several fields, including data analysis, computer vision, speech recognition and much more. NVIDIA’s hardware was able to handle large amounts of data and perform complex calculations efficiently, leading to significant achievements in AI.

As a leader in AI, it has always invested in research and development to improve the hardware to support Artificial Intelligence. Its new Blackwell chips are a clear example of this commitment, with cutting-edge features that improve the efficiency and effectiveness of generative AI.

Importantly, companies like NVIDIA are critical to hardware innovation in Artificial Intelligence. With their commitment and resources, they can advance the research and development of new technologies that contribute to the evolution of AI.

NVIDIA has been able to support and improve the performance of Artificial Intelligence applications also through collaboration between humans and AI. This has led to success for both NVIDIA and its customers, who have been able to make the most of the potential of NVIDIA’s hardware and the capabilities of Artificial Intelligence.

An example of this success is the collaboration with industrial robotics company KUKA, which used NVIDIA technologies to develop an advanced robotic system capable of learning and adapting to production situations in real time. Thanks to the collaboration between humans and Artificial Intelligence, this system achieved a 30% increase in performance compared to previous solutions.

Additionally, NVIDIA worked with automation company Siemens to develop an AI-based control system for industrial machines that reduced production times and improved accuracy by 25%. These are just some of the many success stories in which the collaboration between humans and AI has led to exceptional results thanks to NVIDIA hardware.


NVIDIA: a leader in AI

NVIDIA is undoubtedly one of the leaders in the Artificial Intelligence market. Founded in 1993, the company has established itself as a leading provider of AI hardware, offering innovative, cutting-edge solutions to support the evolution of this technology. Nvidia Blackwell chips are an example of this ongoing commitment to innovating and improving the performance of Artificial Intelligence devices.

With their high computing power and machine learning capability, these chips were designed to support and optimize generative AI applications. Their launch was announced in California a few weeks ago, during the NVIDIA event, where other company news and projects in the field of Artificial Intelligence were also presented.

NVIDIA’s goal is to consolidate its leadership position in the generative AI market, exploiting the potential of the new Blackwell chips and offering increasingly advanced and high-performance solutions to meet the needs of a constantly evolving sector.

Thanks to its leadership in innovation and the development of cutting-edge technologies, NVIDIA has received numerous recognitions and awards, confirming its success in the field of Artificial Intelligence. The company continues to invest in research and development to constantly improve its solutions and support the evolution of Artificial Intelligence.


Nvidia Blackwell is the most powerful AI chip in the world

The Nvidia GTC 2024 conference opened with the official announcement of the next generation Blackwell GPU architecture: the manufacturer calls it the most powerful chip in the world.

The company will offer three GPUs for data centers and AI tasks: B100, B200, and GB200. The latter, the most powerful, will be composed of two GPUs and a Grace central processor.

To some extent, the new architecture, like AMD’s GPU, involves the use of blocks (“chiplets”): the processors consist of two large crystals connected by a 10 TB/s interface.

Nvidia says the GB200 will have seven times faster inference performance, four times faster training performance, and 25 times better power efficiency than its predecessor, the GH200, which is based on the Hopper architecture. As calculated by the company, thanks to the high energy efficiency characteristics, the scope of artificial intelligence systems in data centers can be easily increased by equipping them with more than 100 thousand GPUs.

The GB200 Grace Blackwell Superchip motherboard supports two new GPUs and the Grace ARM processor, which has 72 Neoverse V2 cores and delivers 40 petaflops of FP4 computing performance. Nvidia said it created a new type of conversion algorithm for this high level of performance.

The main users of the new Blackwell chips are expected to be the world’s large technology companies, such as Amazon, Dell, Google, Microsoft, Tesla and others. The sales start date for Nvidia Blackwell GPUs has not been announced during GTC 2024.

At the moment not even the cost of Nvidia Blackwell has been announced. The previous generation H100 is sold on the market at prices ranging from 25 thousand to 40 thousand dollars per unit; the cost of server systems is several hundred thousand dollars.


Artificial intelligence and renewable energy

Artificial intelligence and renewable energy are two elements that can collaborate synergistically to achieve sustainability goals. AI can be used to optimize the use of renewable energy resources, thanks to its ability to analyze and manage large amounts of data efficiently.

Furthermore, the collaboration between artificial intelligence and renewable energy can lead to more precise and reliable results, as AI can provide useful information and suggestions for making strategic decisions in the management of renewable energy sources. An example of this is using AI algorithms to predict wind or solar energy production, thus improving renewable energy planning and efficiency.

It is important to continue to develop and deepen this collaboration, as it can lead to greater sustainability and a better future for our planet.


Generative AI: the future of Artificial Intelligence

Artificial Intelligence technology is advancing rapidly, and one of the most promising areas is generative AI. This field focuses on creating algorithms capable of generating new ideas and solutions, rather than simply repeating existing information. In this context, the new Nvidia Blackwell chips are attracting attention thanks to their potential in generative AI.

These chips offer greater computing power and greater versatility than previous AI hardware solutions. This means they can be used for a wide range of applications, from financial market forecasting to creating art and music. Furthermore, generative AI can also be used to improve user experience in areas such as video games or augmented reality.

Nvidia Blackwell chips are therefore an important resource for the future of Artificial Intelligence, capable of broadening the horizons of this technology and leading to new and innovative applications. Thanks to their power and versatility, they represent the next evolutionary step in AI hardware and open up new avenues for collaboration between humans and machines.