This project was my entry to Brown University (US) Admission Application where students had to upload a video showing their personal projects.
It showcases the current features and possibilities of the project.
It is a personal project so I am unable to share the source code. But I will drop some resources where you can learn and start working on your program. You can get a basic understanding of Chatbots and Speech Recognition through courses offered by ‘Stanford’ and ‘DeepLearning’ on Coursera and get started. I might upload a tutorial of some kind in the future showing the basic code to get started. Thank you for understanding!
This is not an AI. For now, the commands are mostly pre-determined with a pinch of chatbot but it still gets the job done. As mentioned at the end of the video, I want to incorporate AI, ML, and NLP in the future. Please read the full description.
The program can
– control appliances (non-smart too) without WiFi
– recognize English and Hindi language
– gives back witty replies
– control the computer functions
I invited an uneducated person nearby neighborhood to try my program to use the computer. He was reluctant at first but as soon as he said “Open Google Chrome” and the computer opened google chrome, he had a huge smile on his face. He looked at me and said “I have never used a computer in my life, until now and I am thankful to you.”
Those words really hit me.
My goal is to make the Program a complete A.I. that can also understand Natural Language and has Machine Language too. I have many ideas but I am limited by my knowledge.
I hope to join college next year and learn about these concepts in the college and then implement these concepts in my program!
Check more info on my website –
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AI powered analytics platform for water companies to prevent water wastage, predict asset failures, and minimize operating costs.
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Komatsu demonstrating their intelligent machine control system, two Komatsu PC210LCi-10 excavators, side by side working with and with out machine control, at the Bauma 2016 expo in Germany.
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In this segment, you will learn the basics of Natural Language Generation and the Integration between TIBCO Spotfire and Automated Insights’s Natural Language Generation Software Wordsmith.
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A spot showing what voice recognition is capable of these days
NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet aims to provide many of the tools, functionality and implementations that are essential for medical image analysis but missing from standard general purpose toolkits. Due to its modular structure, NiftyNet makes it easier to share networks and pre-trained models, adapt existing networks to new imaging data, and quickly build solutions to your own image analysis problems. This talk will explore the whys, the whats and the hows of this open source framework.
I have a BSc in Biomedical Engineering (2006) and an MSc in Medical Electronics and Signal Processing for Biomedical Engineering (2008) from the Universidade do Minho, Portugal, followed by a PhD (2008-2012) and PostDoc (2012-2015) in medical image analysis, machine learning and biomarker development between CMIC and the Dementia Research Centre at UCL. In June 2015 I have been appointed Lecturer in Quantitative Neuroradiology at the Translational Imaging Group, part of CMIC, in collaboration with the National Hospital for Neurology and Neurosurgery, working on developing, translating and integrating artificial intelligence-based quantitative imaging biomarkers into the clinical environment.
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chat bot for airlines based on ThatNeedle.com natural language processing stack. Solid NLP capabilities for automating processes.
These are intelligent chatbots for conversation. (conversational interfaces). It will give you better performance than many other bot frameworks like microsoft luis, wit.ai etc. This bot shows deep understanding of the domain and can answer questions that are indirect also. ThatNeedle has its own chatbot builder / chatbot maker to create custom chatbot behaviour. It performs accurate entity recognition and can be used to do other intelligent data processing.
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The HealthClinic.biz demo used in the video can be found in the repo at https://github.com/Microsoft/HealthClinic.biz/. The samples in the repo are used to present an end-to-end demo scenario based on a fictitious B2B and multitenant system, named “HealthClinic.biz” that provides different websites, mobile apps, wearable apps, and services running on the latest Microsoft and open technologies.