This hands-on workshop will help guide you through the process of voice-enabling using NVIDIA Riva, a GPU-accelerated speech AI—automatic speech recognition (ASR) and text-to-speech (TTS)—SDK for building fully customizable, real-time conversational AI pipelines.
Familiarize yourself with NVIDIA Riva
Evaluate the business value that can be derived from using NVIDIA Riva
Gain practical experience by working on various use cases to comprehend its functionality
Set realistic expectations for the project
Seek clarifications by asking questions
Plan the project structure in advance
Assess the costs and resources required for the project
Take measures to avoid any potential problems
Identify any potential risks associated with the project
Through out the workshop, you will be focusing on your individual case
Agenda and timing - 60 mins
10 mins
Introductions, goals, agenda
5 mins
NVIDIA Riva. Why do you need it?
10 mins
Interactive part 1
Use cases overview and exploring two use-cases
10 mins
Interactive part 2
Exploring two real use-cases of attendees
10 mins
Interactive part 3
Use-case presentation
5 mins
Riva implementation process
5 mins
Riva Workshop Feedback
5 mins
Wrapping up
Takeaways
Implementation process checklist
Two examples
Sample architectures
What else?
our Speakers
Julia Rubtsova
Data product manager / NLP solution architect
Ph.D. in Data Science. For the last four years with Data Monsters, I am responsible for launching, growing, and developing complex, knowledge-intensive IT products that use Data Science and Machine Learning technologies.
Max Pavlov
Head of Project Office
Building a bridge between AI technologies and business needs. Putting AI into production.
Dan Lesovodski
Partner, Data Monsters
Managed 46 AI projects for large companies, including GE, Intel, AB InBev, and Boston Scientific. Author of the course “AI for managers” on Coursera.
Tripti Singhal
Expert from NVIDIA
Tripti Singhal is a Senior Solutions Architect on the NVIDIA Partner Network team in the Worldwide Field Organization at NVIDIA focusing on Conversational AI. She has been at NVIDIA for six years and received her bachelor's degree in Computer Science at University of California, Santa Barbara.
WHY CHOOSE US?
NVIDIA
NVIDIA is the leading provider of GPUs for AI, and scientific research
Data Monsters
An NVIDIA Elite service delivery partner with a portfolio of 100+ AI projects.
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This hands-on workshop will help you procure and commission an AI system for industrial quality inspections:
Determine requirements
Ask the right questions
Estimate budgets and resources
Evaluate and secure business value
Select vendors
Identify risks
Build expectations
Structure the project
Avoid pitfalls
Commission the system to pilot and production
During this session, you will work on your own case. The workshop will be held by industrial AI experts from leading tech companies.
Agenda and timing - 60 mins
Introduction - 5 mins Use case estimations & budget and risk assessment - 15 mins Participants will use Data Monsters’ framework to structure their use cases and required resources. Data volume, throughput, and storage strategies (time to store & fast and long-term storage). Develop solution architecture and determine integration strategies. Business case evaluation. Relation of AI accuracy and business value - 10 mins We will use a spreadsheet to evaluate the business effect basing on a participant’s use cases. How to choose a system. Evaluation parameters - 15 mins Requirements, expectations, and the right questions to ask. Participants and experts will elaborate the key features that define success or failure.
Project structure. AI system commissioning - 5 mins Project structure framework: POC, Pilot, and Production phases. The ins and outs, what to expect, and how to avoid pitfalls. Common mistake at commissioning - overfitting, and train\test mismatches. Your expert team roles.
Next steps - 5 mins Q&A section - 5 mins
Takeaways
Framework
Checklists
Sample process
Sample architectures
This practical session will help you to:
• Establish and clarify your understanding of AI core concepts, • Learn about best AI use-cases in your industry, • Understand what 5 areas should be managed within an AI project, • Set up your next actions towards your goal.
During the session, we will cover 8 steps and topics:
• “What is AI?”, “How does AI work?, and “What can and can't AI do?” • The most popular AI use cases in manufacturing. • How to spot a feasible and valuable AI use-case that relates to your needs? • How to estimate AI projects and evaluate ROI? The cost structure. • Assessment, PoC, Pilot - The major phases of an AI project’s life cycle. • What can go wrong? The main risks in AI projects. • Success or failure? Terminate or continue? Setting the right acceptance criteria. • Scaling challenges. How to go beyond a PoC?
Who can benefit from this session?
If you're a manager or director striving to make the most out of AI, and you work in one of these industries: •Automotive Manufacturing •Food & Beverages •Electronics & Semiconductors •Logistics & Supply Chain
• Use cases • AI building blocks • Best practices in AI project managementand understanding of how to deal with: - Practical AI implementation - AI team roles & expectations - Investment in AI: risks, deliverables, expenses - How to measure success
• Use cases • AI building blocks • Best practices in AI project managementand understanding of how to deal with: - Practical AI implementation - AI team roles & expectations - Investment in AI: risks, deliverables, expenses - How to measure success
Speakers
Russ Sagert
Director Business Development - Industrial Manufacturing / IoT, NetApp
An expert in developing and bringing to market Digital Transformation solutions for manufacturing plant operators across the oil and gas, mining, power utilities, automotive, and high-tech fabrication industries.
DJ Bush
Global Client Executive - HPC/AI/ML, Sycomp
A global client executive working closely on integrating AI/ML solutions across different industries.
Piyush Modi
Business Development of Industrial Sector, NVIDIA
Responsible for global business development and strategy for the industrial sector at NVIDIA. Over the past 20 years, he has held the positions of CTO, Senior VP, and Head of Research Labs at various companies.
Dan Lesovodski
Partner, Data Monsters
Managed 46 AI projects for large companies, including GE, Intel, AB InBev, and Boston Scientific. Author of the course “AI for managers” on Coursera.
German Suvorov
Head of Industrial AI, Data Monsters
An expert in AI for industrial applications with over 20 years of experience in automotive manufacturing, advanced materials engineering, industrial automation, supply chain management, and information technologies.
PARTNERS
WHY CHOOSE US?
NetApp is a global leader in data management solutions, providing a common infrastructure for moving data from edge to core to cloud. They provide a simplified approach to managing data and accelerating applications whether on-premise, in the cloud, or both. Sycomp is a global system integrator, developing architectures that bring together data science, software and infrastructure to provide clients with a holistic approach to deploying AI/ML solutions. With their global footprint of over 40 countries, they bring a level of standardization to global technology deployments. Data Monsters. An NVIDIA Elite service delivery partner with a portfolio of 100+ AI projects.
