- June 2019
- May 2019
- April 2019
- March 2019
- February 2019
- January 2019
- December 2018
- November 2018
- October 2018
- September 2018
- August 2018
- July 2018
- June 2018
- May 2018
- April 2018
- March 2018
- February 2018
- January 2018
- December 2017
- November 2017
- October 2017
- September 2017
- August 2017
- July 2017
- June 2017
- May 2017
- April 2017
- March 2017
- February 2017
- January 2017
- December 2016
- November 2016
- October 2016
- September 2016
Category Archives: neural network
Eyes are windows into the soul, the old saying goes. They are also pathways into the mind, as much of our brain is involved in processing visual input. This dedication to vision is partly why much of AI research is likewise focused on machine vision. But do artificial neural networks …read more
One of the things that makes us human is our ability to communicate. However, a stroke or other medical impairment can take that ability away without warning. Although Stephen Hawking managed to do great things with a computer-aided voice, it took a lot of patience and technology to get there. …read more
Neural networks are computer systems that are vaguely inspired by the construction of animal brains, and much like human brains, can be trained to obey the whims of the almighty domestic cat. [EdjeElectronics] has built just such a system, and his cat is better off for it.
The build uses a Raspberry Pi, fitted with the Pi Camera board, to image the area around the back door of the house. A Python script regularly captures images and passes them to a TensorFlow neural network for object recognition. The TensorFlow network returns object type and positions to the Python script. This …read more
Neural networks are a key technology in the field of machine learning. A common technique is training them with sample data, and then asking them to create something new in the same vein. AI researcher [Janelle Shane] decided to task a neural network with a fun task – inventing new kinds of pie.
Using the char-rnn library, the network was initially trained on a sample of 2237 pie recipe titles, sourced from around the internet. Early iterations struggled to even spell “pie”, but as the network improved, so did the results. Where we can’t imagine how one would even make …read more
Artificial intelligence (AI) is undergoing somewhat of a renaissance in the last few years. There’s been plenty of research into neural networks and other technologies, often based around teaching an AI system to achieve certain goals or targets. However, this method of training is fraught with danger, because just like in the movies – the computer doesn’t always play fair.
It’s often very much a case of the AI doing exactly what it’s told, rather than exactly what you intended. Like a devious child who will gladly go to bed in the literal sense, but will not actually sleep, …read more
Neural networks use electronic analogs of the neurons in our brains. But it doesn’t seem likely that just making enough electronic neurons would create a human-brain-like thinking machine. Consider that animal brains are sometimes larger than ours — a sperm whale’s brain weighs 17 pounds — yet we don’t think they are as smart as humans or even dogs who have a much smaller brain. MIT researchers have discovered differences between human brain cells and animal ones that might help clear up some of that mystery. You can see a video about the work they’ve done below.
Neurons have long …read more
Want to sound great on a Piano using only your coding skills? Enter Piano Genie, the result of a research project from Google AI and DeepMind. You press any of eight buttons while a neural network makes sure the piano plays something cool — compensating in real time for what’s already been played.
Almost anyone new to playing music who sits down at a piano will produce a sound similar to that of a cat chasing a mouse through a tangle of kitchen pots. Who can blame them, given the sea of 88 inexplicable keys sitting before them? But they’ll …read more
One of the difficulties in learning about neural networks is finding a problem that is complex enough to be instructive but not so complex as to impede learning. [ThomasNield] had an idea: Create a neural network to learn if you should put a light or dark font on a particular colored background. He has a great video explaining it all (see below) and code in Kotlin.
[Thomas] is very interested in optimization, so his approach is very much based on mathematics and algorithms of optimization. One thing that’s handy is that there is already an algorithm for making this determination. …read more
Ever since Google’s Deep Dream results were made public several years ago, there has been major interest in the application of AI and neural network technologies to artistic endeavors. [Helena Sarin] has been experimenting in just this field, exploring the possibilities of collaborating with the ghost in the machine.
The work is centered around the use of Generative Adversarial Networks, or GANs. [Helena] describes using a GAN to create artworks as a sort of game. An apprentice attempts to create new works in the style of their established master, while a critic attempts to determine whether the artworks are created …read more
Did you know that chocolate candy production and sorting LEGO bricks have something in common? They both use the same techniques for turning clumps of chocolates or bricks into individual ones moving down a conveyor belt. At least that’s what [Paco Garcia] found out when making his LEGO Sorter.
However, he didn’t find that out right away. He first experimented with his own techniques, learning that if he fed bricks to his conveyor belt by dropping a batch of them in a line perpendicular to the direction of belt travel then no subsequent separation attempt of his worked. He then …read more