The pre-trained models and Transfer Learning Toolkit help data scientists, computer vision developers and software partners accelerate AI training. Developers can build highly accurate AI for several popular use cases using purpose-built models.
Learn from AI experts and leaders across a wide variety of sectors — from city planning, retail and manufacturing, to industrial, logistics and healthcare — about how IVA is streamlining business processes and operations.
Continuum Analytics, H2O.ai, and MapD recently announced the formation of the GPU Open Analytics Initiative (GOAI) to create common data frameworks enabling developers and statistical researchers to accelerate data science on GPUs.
Late last year, the NVIDIA Inception Program hosted a “Cool Demo Contest” for GPU-accelerated startups that are applying deep learning to their innovations.
To make Siri great, Apple employed several artificial intelligence experts three years ago to apply deep learning to their intelligent mobile smart assistant. The team began training a neural net to replace the original Siri.
Leo Meyerovich, CEO of Graphistry Inc., shares how GPUs and machine learning are protecting the largest companies and organizations in the world by visually alerting them of attacks and big outages.
Hugo Latapie, principal engineer at Cisco shares how they are using NVIDIA GPUs and deep learning in their products for a variety of applications such as encrypted network traffic classification, video compression and state-of-the-art crowd analytics
Joshua Patterson, principal data scientist of Accenture Labs shares how his team is using NVIDIA GPUs and GPU-accelerated libraries to quickly detect security threats by analyzing anomalies in large-scale network graphs.
