NVIDIA Launches Jarvis and Merlin  in Open Beta

NVIDIA has released Jarvis for conversational artificial intelligence and Merlin for recommender systems in open beta.

NVIDIA Jarvis and NVIDIA Merlin allow companies to explore larger deep learning models and develop more nuanced and intelligent recommendation systems.

Some companies in the NVIDIA Developer program have already begun work on conversational AI with NVIDIA Jarvis. Early adopters included Voca, an AI agent for call center support; Kensho, for automatic voice transcriptions for finance and business; and Square, offering a virtual assistant for scheduling appointments.

"Jarvis takes a multimodal approach that fuses key elements of automatic speech recognition with entity and intent matching to address new use cases where high-throughput and low latency are required," said Nigel Cannings, chief technology officer at Intelligent Voice, in a statement. "The Jarvis API is very easy to use, integrate, and customize to our customers' workflows for optimized performance."

Jarvis includes Megatron-BERT models, the largest today, for accuracy and low latency, and sensor fusion (the integration of video cameras and microphones). It can handle multiple data streams in real time and includes software libraries for building conversational AI applications and including GPU-optimized services for speech recognition, natural language understanding, text-to-speech, and computer vision that use the latest deep learning models.

The NVIDIA Merlin application framework, meanwhile, allows businesses to build recommenders accelerated by NVIDIA GPUs. Merlin's collection of libraries includes tools for building deep learning-based systems that provide predictions . Each stage of the pipeline is optimized to support hundreds of terabytes of data, all accessible through APIs.

At Tencent, recommender systems support videos, news, music and apps. Using NVIDIA Merlin, the company reduced its recommender training time from 20 hours to three.

"With the use of the Merlin HugeCTR advertising recommendation acceleration framework, our advertising business model can be trained faster and more accurately, which is expected to improve the effect of online advertising," said Ivan Kong, AI technical leader at Tencent, in a statement.

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