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Research Outline

Prepared for Julie R. | Delivered October 1, 2019

Tech Design Tools

Goals

To identify 5 easy-to-use tech design tools such as templates, canvases, card decks, guides, playbooks, toolkits, etc including pictures, why it’s easy to use, and the source. The purpose is to design a new tool kit.

Early Findings

The Intelligence Augmentation Design Toolkit By Futurice

 Why it's easy to use: the intelligence augmentation design toolkit and its workshop help non-tech experts learn about machine learning and develop smart service concepts. the toolkit creates the opportunity for shared understanding between users, working with analog tools on maps allow for tangible concepts, and the toolkit provides clear explations for users throughout the design process.
 Key features: the free version contains a handbook, canvases, cards, and maps.

Google AI Tools

 Why it's easy to use: Tensorflow is Google's open-source machine learning platform which provides a collaborative eco-system with tools, excersises, and open-source projects for students and developers. The machine learning toolkit brings Google's machine learning expertise to mobile developers in an easy-to-use package that is optimized for mobile, and tailored to each app.
 Key features: includes the machine learning toolkit, repository with sample code, Javascript library, and machine learning education/research resources.

Softrobotics Toolkit

 Why it''s easy to use: this toolkit includes shared resources to support the design, fabrication, modeling, characterization, and control of soft robotic devices. It allows designers and researchers to built upon others' work. The toolkit enables developers to produce soft robotics components easily and affordably.
 Key features: open source fluidic control board, detailed design documentation, and related files that can be used in the design, manufacture, and operation of soft robots.

Runaway Machine Learning

 Why it''s easy to use: this software enables users to utilize AI using a simple and intuitive visual interface. Users are able to find out about new machine learning models through the directory, experiment with new models without coding knowledge, integrate seamlessly with other applications, and train data using a few clicks.
 Key features: motion capture, image synthesis, object recognition, and more.

The Artificial Intelligence Toolkit

 Why it's easy to use: this toolkit enables users to apply machine learning without any programming using supervised, unsupervised, and reinforcement learning. The software toolkit can be used for easy training, testing, and inference of machine learning models and creating machine learning flow.
 Key features: AI professional toolkit, Voicedata toolkit, Document Summary, and training videos.