Applied AI News 1

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When it comes to applications of AI and Machine Learning these days, we are mostly limited by our imagination, which at its core is limited by our exposure to possibilities. The intention of this series of posts is to make the audience more aware of how AI and Machine Learning are leveraged by industries, exposing the reader to new applications, and extending the opportunities one could imagine in their daily business.

Summary of the week

How to deal with the shortage of data scientists and create your own fleet cost-effectively, recognizing everyone in the world, AI pollution debate, cancer and AI, new investments in AI in Queensland, Australia, and AI during the pandemic are the headlines for this week.

• Democratizing AI: There has been a shortage of data scientists and machine learning experts all around the world. To overcome this, many organizations try to democratize the knowledge, making citizen data scientists, so that they would train a fleet of data scientists. Here is how and why you should do it.
• Machine vision: Identifying everyone requires a photo of everyone, which can be rather easily collected by scraping the web. A company actually did this to build an AI that can identify everyone. Here is the news.
• AI emission: Training a certain neural network architecture involves the emissions of roughly 626,000 pounds of carbon dioxide. That’s equivalent to nearly five times the lifetime emissions of the average U.S. car, including its manufacturing. Here is what MIT is doing about this.
• Human-robot interface: Human-robot interaction is a field in robotics, activities range from brain-computer interface all the way to smart joysticks. There has been an attempt to interface with robots by muscle movements.
• Cancer: Diagnosing cancer has been active in medicine and computational fields. There have been significant recent movements on this.
• Collaborative robots: Collaboration among individuals is a sophisticated task. As being social is an essential characteristic of many natural organisms to enable faster improvements, bio-inspired algorithms are expected to perform well when such sophisticated task is required. This has been tested in robots.

Video of the week: What is AI?

• Programming: Great news for python developers, Python apps might soon be able to run on Android. This enables a huge potential, such as multi-platform MVPs. Of course, this could be achieved by writing browser-based apps, however, this is, by all means, a new functionality Python programers can enjoy.
• Failure prediction and scams: Predicting equipment failure and addressing voice and SMS scams are the ways Telstra is using deep learning in their business.
• Investments: Queensland, Australia, has been facing a shortage of talents in the area of AI, based on which Advance Queensland, the Queensland Government funding agency, has invested $5.5M to address the shortage. See also more details here.
• Recommender engines: Selecting the best embryo for an IVF volunteer has been shown pretty successful to boost IVF chances!
• Machine vision: Try a simple online machine vision for "object" detection (image/sound) tool to see if it works for your sample images for object detection, with absolutely no knowledge about machine learning or coding. Just a simple browser-based, 3 steps, tool.
• Behavior and AI: Many AI machines are analyzing our behaviors to extract insights for different purposes, including digital marketing. These AIs have been confused because of a different behavior people are showing these days due to the COVID19.
• Neuroscience and AI: A rather simple neural network translates brain waves to English text (paper in Nature, preprint).
• Machine vision: You can now detect objects, pose, and segment images in real-time using a library in Python. This is really great if interested in real-time vision:

• Startup ideas: More and more startups in the area of AI are coming to the world, and here is a list of some of the interesting ones.

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That is it for this week. There is a lot happening in the area of AI and Machine Learning, we just need to find the opportunity, the tool is there. Like always, comments are very welcome. 

Best wishes and have a great week/end.

Reza 

rezabny@gmail.com