Telcos have some of the largest datasets in the world. AT&T’s Data Science Team will pull back the curtain on a series of use cases that have been accelerated using GPUs and NVIDIA AI tools/frameworks. They'll talk through their analysis and use of NVIDIA capabilities across different …

Telcos will deploy 17 million 5G microcells and towers over the next five years. Optimizing deployment and operations of new and existing cells and towers can save billions for the 2 trillion dollar telecom industry. This demo shows how HEAVY.AI built an AI-accelerated application framework on NVIDIA …

Speech-to-text is often regarded as a “solved problem,” but out-of-the-box solutions are rarely useful in real life and they're typically without meaningful customization. Every contact center ever created for a business is composed of enterprise situations where the topics and vocabulary differ from general …

The telecommunications industry pioneered much of the 'big data' industry, with massive volumes of structured data building over time, and allowing telecommunication companies (telcos) to build deep models of customer and network behavior. As that has evolved, customer behavioral modeling has …

Data-driven personalization is an insurmountable challenge for AT&T’s data science team because of the size of datasets and complexity of data engineering. Usually, these data preparation tasks not only take several hours or days to complete, but some of them fail to complete, affecting productivity. …

Automatic speech recognition technology (ASR) is transforming the broad technology landscape and the past year saw adoption skyrocket, with the pandemic putting AI and analytics at the center of business operations. PwC found that 52% of companies accelerated their AI adoption plans because …

Conversational AI technologies are becoming ubiquitous, with countless products taking advantage of automatic speech recognition, natural language understanding, and speech synthesis coming to market. Thanks to new tools and technologies, developing conversational AI applications is easier …

We introduce KT’s large AI model development case that reflects the complex compound word combination of the Korean language, and improves the performance of natural language generation in encoder-decoder model. We'll also demonstrate some practical examples of reducing hallucination of …

Unlike mainstream language apps, we're seeing broader adoption of customized natural language processing (NLP) that’s tailored to understand an enterprise's unique vocabulary, their customer relationships, and the datasets on which their business runs. These demands are driving the creation…

In the past year we've seen unprecedented growth of models and datasets that deal with natural language processing (NLP). Models such as GPT-3 or Megatron Turing are now two orders of magnitude larger than models that just recently were state of the art (like BERT, RoBerta). What drives the …

Transformer neural networks are modern algorithms for basic language and speech processing tasks. While they are generally recognized in public conversational agents, their application to domain-specific chatbots presents an interesting challenge from both a research and production standpoint. …

Forrester Research noted recently, “Breakthroughs in deep learning around 2012 brought AI into focus, but only NVIDIA had the strategy, vision, and roadmap to invest in supporting these now-mainstream AI workloads.” Leveraging this deep AI experience that spans more than 10 years, NVIDIA has built a …

After a reality check by surveying 800 companies in July 2021, it's clear that data itself has only limited significance for companies. Only the insights gained from evaluating data (by AI, for example) lead to business benefits in various forms and gains in value. We'll show the phases in which companies find…

We'll bring together AI implementers who've deployed AI at scale using NVIDIA DGX systems. Discover what these companies are doing to achieve the highest bottom-line impact from AI. Walk away with their learnings and best practices, so you can uncover insights faster and ensure higher returns on …

The impact of AI can be seen across industries. Learn how AI is disrupting business and the opportunities that it creates. This panel of experts will discuss how AI impacts their business, and its increasingly prominent role. Learn from key innovators how they're making the most of the …

This year brings innovations in AI infrastructure design that will transform enterprise and enable unprecedented levels of scale, simplified manageability, and new consumption models for how business and IT leaders can procure and deliver AI development resources to their data science and …

While enterprise use of AI has grown by 270% over the past several years, many still struggle to make their AI initiatives successful with almost half never making it to production, according to recent Gartner research. For many, the complexity of AI infrastructure is one of the most frequently named …