Artificial Intelligence. A hefty topic that has dominated the field since computers were first conceived. What if I told you that you could put an artificial intelligence service on your own $30 computer?! That’s right! In this tutorial I will show you how to create your own artificially intelligent personal assistant, using Amazon’s Alexa voice recognition and information service! Just like with Siri, OK Google and others, you will be able to speak to your Pi and have it answer you: “What is the square root of 25?”, “What won best movie in 1995?”, “Add tomatoes to my shopping list” – and much much more! Watch this episode to unleash the AI capability of your Raspberry Pi!
INFORMATION & LINKS:
Raspberry Pi information: https://www.raspberrypi.org/
Artificial Intelligence Pi – the GitHub repository that has all of my code and FAQs in: https://github.com/the-raspberry-pi-guy/Artificial-Intelligence-Pi
SenseHAT purchase link: https://shop.pimoroni.com/products/raspberry-pi-sense-hat?utm_medium=cpc&utm_source=googlepla&variant=6019555009&gclid=CjwKEAjwsr-6BRCLvrj785rbhTsSJADjUxakzNiVT9brFvOjVUhqtwFGDWyjtz_1w-Iaf2M9yXx-xhoCAHrw_wcB
Microphone purchase link (the one I used in this video!) (Amazon UK): https://www.amazon.co.uk/gp/product/B01142EPO4/ref=oh_aui_detailpage_o00_s00?ie=UTF8&psc=1
3.5mm loud speaker: https://www.amazon.co.uk/gp/product/B001UEBN42/ref=s9_simh_gw_g23_i1_r?pf_rd_m=A3P5ROKL5A1OLE&pf_rd_s=desktop-1&pf_rd_r=E1T6CTCGPQYMJ17E7QDY&pf_rd_t=36701&pf_rd_p=867551827&pf_rd_i=desktop
Amazon’s Developer Console: http://developer.amazon.com/
Amazon Echo??? http://www.amazon.com/gp/product/B00X4WHP5E
Display your Raspberry Pi’s IP address: ifconfig
Download the code: git clone https://github.com/the-raspberry-pi-guy/Artificial-Intelligence-Pi
Change into the new directory: cd Artificial-Intelligence-Pi
Run the setup script: sudo ./setup.sh
Run Alexa: python main.py
Thanks for watching! This video took me a *long* time – why not give it a like? Don’t forget to subscribe and share too! More great videos soon 😉
The Raspberry Pi Guy
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Thanks to Sam Machin and Simon Beal!
Music: Valesco – All I Need: https://soundcloud.com/argofox/valesco-all-i-need
Facebook’s Caffe2 AI tools reach out to iPhone, Android, plus Raspberry Pi
Your cell phone may soon have the ability to figure out items in photos with no need of accessing the cloud
New intelligence can be added onto mobile phones similar to the iPhone, Android OS devices, and low-power computers including Raspberry Pi with Facebook’s new open-source Caffe2 deep-learning framework.
Caffe2 enables you to program artificial intelligence features into smartphones and tablets, allowing them to identify pictures, movie, text, and speech and be more situationally aware.
You should be aware that Caffe2 isn’t an AI program, but a tool enabling AI to be programmed into phones. It takes just a few lines of code to write learning models, which can then be included into applications.
The release of Caffe2 is important. It means people will be in a position to get image identification, natural language processing, and computer vision directly on their smartphone. That job is typically offloaded to remote servers in the cloud, with phones then connecting to it.
Mobile gadgets are having more and more artificial intelligence abilities. More mobiles are being bundled with Amazon’s Alexa and Google Assistant, while Apple’s Siri has been a staple in the iPhone for many years. Samsung’s Galaxy S8 phones are set to get the Bixby voice assistant, which will make using the devices easier.
Caffe2 can work within the power constraints of mobile gadgets. It works with mobile hardware to accelerate AI apps and create neural networks.
Caffe2 uses the computing power of cutting edge mobile hardware to accelerate deep-learning jobs. For example, in phones, Caffe2 will take advantage of the computing power of Adreno GPUs and Hexagon DSPs on Qualcomm’s Snapdragon mobile chips.
Continue reading at http://pcworld.com/article/3190759/artificial-intelligence/facebooks-caffe2-ai-tools-come-to-iphone-android-and-raspberry-pi.html