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Category Archives: machine learning
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
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
If you were a youth in the 90s, odds are good that you were a part of the virtual pet fad and had your very own beeping Tamagotchi to take care of, much to the chagrin of your parents. Without the appropriate amout of attention each day, the pets could become sick or die, and the only way to prevent this was to sneak the toy into class and hope it didn’t make too much noise. A more responsible solution to this problem would have been to build something to take care of your virtual pet for you.
An art …read more
Scientists don’t know exactly what fast radio bursts (FRBs) are. What they do know is that they come from a long way away. In fact, one that occurs regularly comes from a galaxy 3 billion light years away. They could form from neutron stars or they could be extraterrestrials phoning home. The other thing is — thanks to machine learning — we now know about a lot more of them. You can see a video from Berkeley, below. and find more technical information, raw data, and [Danielle Futselaar’s] killer project graphic seen above from at their site.
The first FRB …read more
Setting camera traps in your garden to see what local wildlife is around is quite popular. But [Chris Lam] has just one subject in mind: the hummingbird. He devised a custom setup to capture the footage he wanted using some neat tech.
To attract the hummingbirds, [Chris] used an off-the-shelf feeder — no need to re-invent the wheel there. To obtain the closeup footage required, a 4K action cam was used. This was attached to the feeder with a 3D-printed mount that [Chris] designed.
When it came to detecting the presence of a hummingbird in the video, there were various …read more
When you think of technical education about machine learning, Facebook might not be the company that pops into your head. However, the company uses machine learning, and they’ve rolled out a six-part video series that they say “shares best real-world practices and provides practical tips about how to apply machine-learning capabilities to real-world problems.”
The videos correspond to what they say are the six aspects of machine learning development:
- Problem definition
None of the videos are longer than 10 minutes, so you’ll invest less than an hour. The videos focus less on a specific product …read more
Disney is working on modular, intelligent robot limbs that snap into place with magnets. The intelligence comes from a reasonable sized neural network that also incorporates some modularity. The robot is their Snapbot whose base unit can fit up to eight of limbs, and so far they’ve trained with up to three together.
The modularity further extends to a choice of three types of limb. One with roll and pitch, another with yaw and pitch, and a third with roll, yaw, and pitch. Interestingly, of the three types, the yaw-pitch one seems most effective.
In this age of massive, deep …read more