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BONSAI
Bonsai requires a Microsoft account and runs on Azure cloud services, which requires an Azure subscription.BONSAI
Bonsai
BONSAI
The world's first programming platform for capturing, sharing and reusing artificial intelligence. PYTHON LIBRARY REFERENCE Library Overview. The Bonsai libraries known as libbonsai (C++) and bonsai_ai (Python) wrap the Bonsai API to simplify the process of building simulators in C++ and Python programming languages. This Python library is compatible with Python 2.7+ and Python 3+ on Windows 7/10, macOS, and Linux. MACHINE TEACHING PLAYBOOKS Current playbooks. Device Calibration Playbook: using Machine Teaching and RL to automate calibration of device controllers. Continuous Manufacturing Playbook: using Machine Teaching and RL to automate and optimize continuous manufacturing processes. Watch this space forfuture playbooks!
BONSAI
Bonsai requires a Microsoft account and runs on Azure cloud services, which requires an Azure subscription.BONSAI
Bonsai
BONSAI
The world's first programming platform for capturing, sharing and reusing artificial intelligence. PYTHON LIBRARY REFERENCE Library Overview. The Bonsai libraries known as libbonsai (C++) and bonsai_ai (Python) wrap the Bonsai API to simplify the process of building simulators in C++ and Python programming languages. This Python library is compatible with Python 2.7+ and Python 3+ on Windows 7/10, macOS, and Linux. MACHINE TEACHING PLAYBOOKS Current playbooks. Device Calibration Playbook: using Machine Teaching and RL to automate calibration of device controllers. Continuous Manufacturing Playbook: using Machine Teaching and RL to automate and optimize continuous manufacturing processes. Watch this space forfuture playbooks!
BONSAI
Bonsai requires a Microsoft account and runs on Azure cloud services, which requires an Azure subscription.BONSAI
Bonsai
PYTHON LIBRARY REFERENCE Library Overview. The Bonsai libraries known as libbonsai (C++) and bonsai_ai (Python) wrap the Bonsai API to simplify the process of building simulators in C++ and Python programming languages. This Python library is compatible with Python 2.7+ and Python 3+ on Windows 7/10, macOS, and Linux.BONSAI
The world's first programming platform for capturing, sharing and reusing artificial intelligence. MACHINE TEACHING PLAYBOOKS Current playbooks. Device Calibration Playbook: using Machine Teaching and RL to automate calibration of device controllers. Continuous Manufacturing Playbook: using Machine Teaching and RL to automate and optimize continuous manufacturing processes. Watch this space forfuture playbooks!
UNDERSTAND BRAIN GRAPHS Introduction. This guide will familiarize you with the two training graphs displayed on every BRAIN’s Details Page on The Bonsai Platform. These graphs can be used to monitor training, troubleshoot your BRAIN, and decide when your BRAIN has been sufficiently trained and is ready for predictions.BONSAI
Bonsai requires a Microsoft account and runs on Azure cloud services, which requires an Azure subscription.BONSAI
Bonsai
PYTHON LIBRARY REFERENCE Library Overview. The Bonsai libraries known as libbonsai (C++) and bonsai_ai (Python) wrap the Bonsai API to simplify the process of building simulators in C++ and Python programming languages. This Python library is compatible with Python 2.7+ and Python 3+ on Windows 7/10, macOS, and Linux.BONSAI
The world's first programming platform for capturing, sharing and reusing artificial intelligence. MACHINE TEACHING PLAYBOOKS Current playbooks. Device Calibration Playbook: using Machine Teaching and RL to automate calibration of device controllers. Continuous Manufacturing Playbook: using Machine Teaching and RL to automate and optimize continuous manufacturing processes. Watch this space forfuture playbooks!
UNDERSTAND BRAIN GRAPHS Introduction. This guide will familiarize you with the two training graphs displayed on every BRAIN’s Details Page on The Bonsai Platform. These graphs can be used to monitor training, troubleshoot your BRAIN, and decide when your BRAIN has been sufficiently trained and is ready for predictions. UNDERSTAND BRAIN GRAPHS Introduction. This guide will familiarize you with the two training graphs displayed on every BRAIN’s Details Page on The Bonsai Platform. These graphs can be used to monitor training, troubleshoot your BRAIN, and decide when your BRAIN has been sufficiently trained and is ready for predictions. Skip to main contentMicrosoft
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Search Search Microsoft.com Cancel 0 Cart 0 items in shopping cart Sign in to your account PROJECT BONSAI FOR AUTONOMOUS SYSTEMS Explore our low-code AI development platform for building autonomous solutions for industrial control systems. Now available in preview.Watch how it works
BUILD AI WITHOUT DATA SCIENTISTS Project Bonsai speeds the creation of AI-powered automation to help improve product quality and efficiency while reducing downtime. Now available in preview.BUILT BY ENGINEERS
Create AI with minimal coding and data scienceTRAINED BY HUMANS
Teach AI with instructions and guidancePRACTICES SAFELY
Use simulation to train AI for real environmentsWORKS FOR YOU
Deploy AI to work independently or with people ENABLE ENGINEERS TO BUILD AI-POWERED AUTOMATION Start with an intuitive experience that helps your engineers create AI with minimal data science and coding. Choose to optimize a process variable or add intelligence to an entire process. Safely and quickly validate your AI in a simulated environment before deploying it in thereal world.
IMPROVE OPERATOR DECISION-MAKING Your engineers’ expertise is directly infused into your AI solution through lessons, goal setting, and rewards. Build once and then reuse your AI in multiple projects to save time and money. Add safety policies to help meet safety and compliance regulations. DEPLOY AI THAT YOU FULLY CONTROL You decide how to implement your AI solution: Use it alongside people for decision support or create a system that works independently. Design a solution suited to your infrastructure by deploying AI on-premises, in the cloud, to the IoT Edge, or inembedded devices.
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> "Project Bonsai allows us to utilize technology for the things it > does best and our employees for the things they do best." Kevin Lin, Associate Principal Engineer | PepsiCoRead about PepsiCo
Watch the PepsiCo video > "Project Bonsai was unique because the engineers are the ones > building the AI, they train it from their own expertise, and we get > total control over how it gets deployed – either to give our > operators advice on what to do or to work on its own." Yanon Lorpatarapong, AI Lead Engineer for Chemicals, Business | SCGRead the SCG story
> "With Project Bonsai, we uncovered recommended optimizations that we > never could have come to on our own. Using this AI, we were able to > uncover a new plan for optimization in about 2 weeks, with an > expected reducing in energy of about 15%." Brendan Bryant, Mechanical Engineer at DB Engineering | Microsoft Read the Microsoft story > "At the end of the day, this is about shortening supply chains and > growing and improving our own workforce." Ashe Menon, Former Senior Vice President of Global Manufacturing | NOV, Grant Prideco DivisionRead the NOV story
> "We’re using Project Bonsai because it allows us to quickly create > and teach an AI just like if we were training a pilot on what to> look for."
Matthew Holvey, Senior Manager, Intelligent Systems | BellRead the Bell story
Watch the Bell video USE CASES AND SOLUTIONS Start with a single process or add autonomy to a whole system. Popular use cases span from manufacturing to climate management systems. Read the manufacturing guide*
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