Massive models exceeded server memory. An AI factory now powers agents that write code and turn design flowcharts into specs.
A global semiconductor leader enabling nearly two billion connected devices annually with systems-on-chips for mobile, home, and IoT markets.
Developing large language models required processing billions of tokens monthly, but models with hundreds of billions of parameters exceeded the...
“Our AI factory, powered by DGX SuperPOD, processes approximately 60 billion tokens per month for inference and completes thousands of model-training iterations every month.”
Fabless semiconductor designer of chipsets for mobile, home, and automotive devices.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
MediaTek's Chip design automation is part of this use case:
Related implementations across industries and use cases
Tax teams spent weeks sifting through thousands of pages. GenAI now summarizes the technical notes in hours.
Developers waited 15 minutes for routine fixes. Now, they run parallel agents to finish tasks in 30 seconds.
Sensor data overwhelmed local servers. Engineers now run natural language queries 5x faster via AI, cutting PoC timelines by 80%.
Sensor data overwhelmed local servers. Engineers now run natural language queries 5x faster via AI, cutting PoC timelines by 80%.
Processing 2T tokens on CPUs took days. GPU acceleration cut prep to hours, unlocking a 5% accuracy gain.
Manual workflows delayed global campaigns for weeks. Now, local teams use GenAI to instantly draft localized, regulatory-compliant copy.
Fragmented legacy platforms took weeks to scale. Now, AI routes emails by intent while unified desktops let agents resolve issues faster.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Massive models exceeded server memory. An AI factory now powers agents that write code and turn design flowcharts into specs.
A global semiconductor leader enabling nearly two billion connected devices annually with systems-on-chips for mobile, home, and IoT markets.
Developing large language models required processing billions of tokens monthly, but models with hundreds of billions of parameters exceeded the...
“Our AI factory, powered by DGX SuperPOD, processes approximately 60 billion tokens per month for inference and completes thousands of model-training iterations every month.”
Fabless semiconductor designer of chipsets for mobile, home, and automotive devices.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
MediaTek's Chip design automation is part of this use case:
Related implementations across industries and use cases
Tax teams spent weeks sifting through thousands of pages. GenAI now summarizes the technical notes in hours.
Developers waited 15 minutes for routine fixes. Now, they run parallel agents to finish tasks in 30 seconds.
Sensor data overwhelmed local servers. Engineers now run natural language queries 5x faster via AI, cutting PoC timelines by 80%.
Sensor data overwhelmed local servers. Engineers now run natural language queries 5x faster via AI, cutting PoC timelines by 80%.
Processing 2T tokens on CPUs took days. GPU acceleration cut prep to hours, unlocking a 5% accuracy gain.
Manual workflows delayed global campaigns for weeks. Now, local teams use GenAI to instantly draft localized, regulatory-compliant copy.
Fragmented legacy platforms took weeks to scale. Now, AI routes emails by intent while unified desktops let agents resolve issues faster.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.