Today’s consumers have the world at their fingertips. The boom in online users has made the consumer internet industry one of the largest users of machine learning, deep learning, and data science. From recommenders to smart chatbots to AI-enhanced video conferencing, these capabilities rely on fast, intelligent tools and infrastructure. That’s why leading companies are using NVIDIA solutions to harness their wealth of data to pioneer products that shape the online experience.
Don't miss these three upcoming consumer internet sessions at GTC.
In this talk, I will drive you through the Roblox ML Platform inference service. You will learn how we integrate Triton inference service with Kubeflow and Kserve. I will describe how we simplify the deployment for our end users to serve models on both CPU and GPUs.
Empowered by GPUs, LinkedIn developed a large graph neural network model to learn users’ professional network information on LinkedIn platform. We use this GNN model in the feed candidate selection and recommendation system to improve the quality of our feed recommendations.
Today's virtual production (VP) stages surround actors with the light of millions of LEDs, creating real-world image-based lighting in addition to in-camera backgrounds. But these stages often fall short of lighting the actors the same way they would appear if they were actually in the intended environments.
Conference & Training September 19 - 22 | Keynote September 20
In response to the explosion of different AI models and the resulting network complexity, NVIDIA’s GPU-based SDKs centralize deep learning and machine learning modeling, training, and inference.
Datasets aren’t just increasing at a massive pace. They’re also evolving into different formats with varying quality, making GPU-accelerated data science platforms critical to tackling modern processing workloads.
Scaling infrastructure monitoring, management, and software deployments can be challenging. With NVIDIA GPUs, engineers can build technical infrastructure and pipelines to support data.
From customized user interfaces to expertly recommended content and automated video production, NVIDIA GPU platforms help elevate the audience experience. Data scientists and engineers can better understand viewer behavior and predict success through GPU-powered, real-time data analysis.
Social media platforms allow for personalization and sharing at a large scale. Advanced machine learning serves targeted advertising, job, and product recommendations, suggests people you might like to connect with, and curates specific posts in your feed.
From AI chatbots to smart assistants, NVIDIA GPU platform power natural language processing and conversational AI for a seamless and tailor-made shopping experience. And cybersecurity analysts can use GPU technology to predict and prevent fraudulent online transactions.
With the help of GPU-powered AI and robotics, delivery services can leverage algorithms and collect and analyze mapping and geolocation data to provide the most efficient and automated transport.
Video conference providers can vastly improve streaming quality and offer enhanced AI features, such as super resolution, gaze correction, and live captions, using a suite of GPU AI-powered tools.
NVIDIA Riva is a GPU-accelerated application framework for building multimodal conversational AI services that deliver real-time performance. Riva includes pre-trained conversational AI models, tools in the NVIDIA AI Toolkit, and optimized end-to-end services like messaging apps, speech-based assistants, and chatbots for automating communication and creating personalized customer experiences at scale.
It combines vision, audio, and other sensory capabilities to power call center assistants and other virtual assistants.
NVIDIA Merlin is a framework for building high-performance, deep learning-based recommender systems. From personalized media thumbnails to tailored movie and TV show recommendations optimized end-to-end services like messaging apps,, Merlin includes tools that provide better predictions of user preference and behavior than traditional methods to increase engagement rates.
Data science can deliver faster time to business insight, including in areas like consumer behavior and predictive analytics. NVIDIA-accelerated data science, built on NVIDIA® CUDA-X AI™ and featuring NVIDIA RAPIDS™ data processing and machine learning libraries, provides GPU-accelerated software for data science workflows that maximize productivity, performance, and ROI.
The NVIDIA Maxine™ AI platform SDK enables video-conference providers to vastly improve streaming quality in the cloud with super resolution, gaze correction, live captions, and more. In addition to reducing video bandwidth, Maxine’s fully accelerated platform includes innovative capabilities such as face alignment, noise removal, and virtual assistants.
The NGC catalog is a registry of GPU-optimized software for AI and HPC applications, pre-trained models, AI application frameworks, and helm charts. The enterprise-ready software from the NGC catalog helps data engineers, data scientists, researchers, developers, DevOps, and system admins shorten time to solution and bring solutions faster to market.
The growth of AI-assisted services within the consumer internet industry is impeded by an explosion of complex AI models, increased datasets, and cumbersome deployment and management workflows. These challenges result in slow computing architectures and high costs. NVIDIA DGX™ A100 provides IT directors, data scientists, and data engineers a platform that can unify all AI workloads, simplify infrastructure, and accelerate ROI.
Consumer internet services are leveraged across the world and on multiple platforms. NVIDIA’s GPU-accelerated solutions are available through all top cloud platforms, empowering companies to scale and access massive computing power on demand and with ease. The NVIDIA T4 Tensor Core GPU speeds up cloud workloads, including high-performance computing, deep learning training and inference, machine learning, data analytics, and graphics. It enables businesses to create new customer experiences that help make services more accessible and scalable.