Nvidia chips give graphics-hungry gamers the tools they need to play games in higher resolution, with higher quality and higher frame rates.
Anyone who came to the keynote expecting him to pull a Tim Cook, with a slick, audience-focused keynote, was bound to be disappointed.
The company also introduced Nvidia NIM, a software platform aimed at simplifying the deployment of AI models.
“Anything you can digitize: So long as there is some structure where we can apply some patterns, means we can learn the patterns,” Huang said.
And here we are, in the generative AI revolution.”Catch up on Nvidia’s GTC 2024:Update: This post was updated to include new information and a video of the keynote.
Nvidia chips give graphics-hungry gamers the tools they needed to play games in higher resolution, with higher quality and higher frame rates.
Anyone who had come to the keynote expecting him to pull a Tim Cook, with a slick, audience-focused keynote, was bound to be disappointed.
The company also introduced Nvidia NIM, a software platform aimed at simplifying the deployment of AI models.
NIM leverages Nvidia’s hardware as a foundation and aims to accelerate companies’ AI initiatives by providing an ecosystem of AI-ready containers.
“Anything you can digitize: So long as there is some structure where we can apply some patterns, means we can learn the patterns,” Huang said.
Simulations are an essential step in physical product engineering.
“Luminary’s real-time engineering approach empowers engineering teams to perform product simulation and analysis cycles in minutes, rather than weeks,” Lango said.
[This] results in improved time to market, faster insights, better design outcomes, increased team productivity and better use of valuable physical prototyping dollars.”AI-leaningLuminary isn’t exactly first-to-market with a cloud-based engineering simulation tool.
Lango met Alonso during summer 2019 through Sutter Hill Ventures, the private equity firm, where Lango was an entrepreneur in residence.
Sutter Hill sees a lucrative future in Luminary, evidently, as the startup’s customer base eclipses 33 organizations across the automotive, aerospace and defense and industrial equipment sectors.
Like most other code generators, StarCoder 2 can suggest ways to complete unfinished lines of code as well as summarize and retrieve snippets of code when asked in natural language.
Trained with 4x more data than the original StarCoder, StarCoder 2 delivers what Hugging Face, ServiceNow and Nvidia characterize as “significantly” improved performance at lower costs to operate.
Setting all this aside for a moment, is StarCoder 2 really superior to the other code generators out there — free or paid?
As with the original StarCoder, StarCoder 2’s training data is available for developers to fork, reproduce or audit as they please.
Hugging Face, which offers model implementation consulting plans, is providing hosted versions of the StarCoder 2 models on its platform.
