With the introduction of ChatGPT, generative AI has completely taken over the globe. So even while everyone is now praising Satya Nadella for his wise investments and Sam Altman and his team at Open AI for their incredible successes, we frequently overlook one of the most essential elements. That is how NVIDIA’s hardware enabled these most recent advances in generative AI.
The turning point for AI
Accelerated computing and AI have come, claims Jensen. He identifies three underlying processes that are responsible for these advances in computing and serve as their triggers.
The ability to meet the world’s increasing demand for computing in a manner that is environmentally friendly is, according to Huang, “Number one and foremost is our ability to continue to grow computing demand in a way that’s sustainable for the planet is nearly impossible unless we accelerate every workload,”
“The second is, of course, ChatGPT’s phenomenal AI advancement, which has made headlines all over the world. The huge language model breakthrough was made possible by NVIDIA’s DGX AI supercomputer, the first of its kind in the world, which also sparked the emergence of AI “Huang added.
The advancement of Generative AI has led to a step-function improvement in AI training and inference.
Jensen Huang thinks that the inflection point in AI has finally been reached because of generative AI. He refers to the development of a new computer platform as the “iPhone moment for AI.” Every 15 years, according to historical trends, a new computing platform has emerged. With new businesses and applications, the PC, internet, and mobile cloud revolutions all helped to build a new computing paradigm and gave us new ways to “program” computers. The same holds true for generative AI built on a large language model foundation.
Huang explained, “This is a new computing model that you program in a new way, and this new approach uses human language. The first computer allows you to program in whatever language you choose, including English, Chinese, French, and Japanese, he continued.
Digitalization is the third fundamental cause, according to Jensen Huang, that is causing these changes in computing. “The majority of artificial intelligence (AI) development to date has been in the realm of software, visual recommender systems, web interaction, and now with Chat GPT, huge language models linked to office automation, office apps, and productivity applications. So far, everything is digital. Nonetheless, physical industries are the biggest in the world. They produce tangible items but would like to design them digitally “, Huang added.
“We developed a platform we call Omniverse that aids in the globalization of industries. Omniverse is a physical-digital operating system for the globalization of industry “Added he.
Impact of generative AI
Transformer model technology is a significant driving force behind the present advancement in Generative AI. A neural network called a transformer model follows relationships in sequential input, such as the words in this sentence, to learn context and subsequently meaning. Transformer models use an expanding collection of mathematical approaches known as attention or self-attention to find minute relationships between even far-flung data pieces in a series.
Jensen Huang asserts that these transformer models have potential that goes beyond that of language models.
“It is particularly efficient at processing, coding, and compressing a lot of data into neural networks. There are numerous languages you can learn using the transformer model because you can use it for language, images, proteins, chemicals, and movies.”
He went on to discuss the potential roles these models could have outside of chatGPT.
“When it comes to proteins, you can comprehend them and create them because you are aware of what they mean. This ability has thus proven to be of great value. And I predict that over the coming years, you will see one industry after another implement extensive language models.”
Also, he stressed the significance of the hardware in this change, particularly the capacity of NVIDIA’s Hopper GPU, which is built to comprehend these substantial language models.
The most potent driver for democracy is generative AI.
Despite receiving a lot of praise and excitement, generative AI tools like ChatGPT have also sparked numerous concerns about employment and career options, particularly in developing nations like India with a sizable youth population.
Jensen Huang believes that generative AI has the potential to have a positive impact on nations like India.
The potential now, according to Huang, “I believe this is the greatest opportunity that we have ever had to close and to bring together the social divide and the technology divide,”
“There has only been a limited number of people who can program computers throughout the past 30–40 years. There are not many people who are knowledgeable about how to use this amazing tool for the good of their country, their business, or themselves.”
“And yet, all of a sudden, there is a new sort of computer, this new type of computer does not require you to learn C, C++, Pascal, Fortran, or Java. Python is not even necessary. Simply use your native tongue. Also, if you tell this computer what you require, desire, and problems you wish to have resolved, it will create the necessary software on its own.”
According to his theory, nowadays everyone is a computer programmer.
For the first time ever, he added, “This is going to have the greatest opportunity for us to democratize this very powerful instrument we call the computer for the very first time in history,”
“I think it will benefit so many societal groups. It will provide excellent education to those without access to it. It is the most potent force for democratization I have ever witnessed “Finally, he said.
