Creating any type of company takes enormous amounts of effort, hard work, and persistence. Let alone an Artificial Intelligence company. As we can assure you, it will take a lot more than the above and adding just a team of brilliant AI scientists to build complex real-world AI solutions. In this talk, we will show you the crucial roles of development teams in a high-performing Artificial Intelligence company.
6. Behind the scenes development
• Development that is not necessarily visible to the outside
• Can drastically vary in size between seemingly similar companies
• Requires more resources and more expertise to scale
• Gives more room for engineers to push the limits of a complex system
21. Garbage in, garbage out
DATA ANNOTATION ACCURACY
RANDOM 50%
CROWSOURCED 95%
THIRD PARTY SERVICE 98%
PROPRIETARY SYSTEM 99,9%
22. Data management system
• Used by our team of domain experts and data annotators
• Enables maximum annotation efficiency with its custom UI
• Runs several quality assurance mechanisms to ensure data quality
• Performs preannotation with our currently best AI models
• Custom built annotation workflow for each product
23. Development
• Software and UI developers
• DevOps, Data and QA engineers
• Internal clients: domain experts and data annotators
• .NET Core microservices using Docker and Kubernetes
• MongoDB, SQL Server on Linux and ElasticSearch
• Figma, ReactJS and enterprise-class UI library
26. Machine learning engine
• Enables our AI development process
• Optimizes the data management process with AI model serving
• Repository of proprietary neural network layers, architectures and training
procedures
• Production-scale model training and evaluation with deployment
27. Development
• Software and DevOps engineers
• Experienced with software architecture and microservice development
• Python with emphasis on internal Tensorflow integration
• Microservices using Docker and Kubernetes
• Pipeline definition and execution with Argo
• Metadata storage with MongoDB and PostreSQL
30. AI inference engine
• Optimizing our needs while open source engines are optimizing
everyone’s needs
• Implemented in C++, completely cross-platform
• Maximum control over privacy of the models
• Multi-model support optimized in both speed and memory footprint
• Our playground for innovation and new products
31. Development
• C++ developers
• Highly optimized neural network inference
• Latest C++ standards
• Conan C/C++ Package Manager
• Build system with Cmake and Jenkins
• WebAssembly
33. Complex AI system
• It’s design determines which AI models are needed and how they will
interact to solve the problem
• Additional processing units are implemented by product developers
• Allows control over the parts of the system where crucial or sensitive
decisions are made
• Implemented and exported as a static C++ library
34. Development
• C++ developers
• Experience in Computer vision
• Product development with AI models
• Compile-time and meta programming
• Latest C++ standard packaged with Conan
36. Mobile deployment
• Custom Camera management
• SDKs developed for iOS and Android
• Cross-platform auto generated using proprietary code generation tools
• Emphasis on simple UX and use of platform specific features
• Always exploring new features on platforms
37. Web deployment
• Custom Web API
• AI system static C++ library wrapped in a Docker container
• Software as a Service (SaaS)
• In-Browser scanning with our AI inference engine powered by
WebAssembly