Jonathan Cohen, Vice Preside of Applied Research by Nvidia, believes that in the field of artificial ielligence research, the main restrictive factor, the amou of computational resources is available.
“In the prese age, the most valuable asset for any artificial ielligence researcher is his access to graphic processing units (GPUs), and this is as importa as any other organization in Nvidia,” said Cohen in an ierview with Nvidia Developer.
Cohen was in charge of a group responsible for the developme of the family of Nvidia’s large language models (LLM). These models, iroduced in March of this year, indicate the company’s ery io the field of ielligence artificial ielligence systems.
Cohen said that the speed of forming these models was remarkable and surprising, and the process did not last more than one to two mohs. “Many scholars have agreed to provide our own computational resources so that we can teach and move Llama and Nemotron models as fast as you saw,” he said.
Cohen also attributed the high speed of the developme of these models to the domina and domina culture of Nvidia, which prioritizes large and large projects, regardless of the curre and curre goals of differe teams.
“How do you form a team to do something that has never been experienced before?” Part of our organizational culture has been something that we call “congestion” and is recognized in a matter of importance. In this situation, all managers are thinking about whether this new job is more importa than the thing that all the teams are doing now? “
If a manager recognizes that this new project has a higher priority, it can discharge employees from their previous tasks and assign them to a new priority. “Finally, the Llama Nemotron project was a very widespread ier -team effort,” Cohen said. “We had people from all over the organization who worked together without any formal and defined organizational structure.”
According to Cohen, the developme of Llama Nemotron required a set of sacrifices, both in terms of the necessary computational capabilities and in terms of specialist human resources, and the company’s staff was able to abandon their personal ierests and individual goals in line with the overall ierest and purpose of the organization.
“Seeing this amou of cooperation and sacrifice was really great and admirable,” he said. There was an extraordinary leadership. “Many sacrifices were made by people, and many sacrificial decisions were made that eveually led to the formation of the project, which is really amazing.”
