Lifeboat Foundation

The data came from Common Crawl, a non-profit that scans the open web every month and downloads content from billions of HTML pages then makes it available in a special format for large-scale data mining. In 2017 the average monthly “crawl” yielded over three billion web pages. Common Crawl has been doing this since 2011, and has petabytes of data in over 40 different languages. The OpenAI team applied some filtering techniques to improve the overall quality of the data, including adding curated datasets like Wikipedia.

GPT stands for Generative Pretrained Transformer. The “transformer” part refers to a neural network architecture introduced by Google in 2017. Rather than looking at words in sequential order and making decisions based on a word’s positioning within a sentence, text or speech generators with this design model the relationships between all the words in a sentence at once. Each word gets an “attention score,” which is used as its weight and fed into the larger network. Essentially, this is a complex way of saying the model is weighing how likely it is that a given word will be preceded or followed by another word, and how much that likelihood changes based on the other words in the sentence.

Through finding the relationships and patterns between words in a giant dataset, the algorithm ultimately ends up learning from its own inferences, in what’s called unsupervised machine learning. And it doesn’t end with words—GPT-3 can also figure out how concepts relate to each other, and discern context.

Ultracold atoms trapped in appropriately prepared optical traps can arrange themselves in surprisingly complex, hitherto unobserved structures, according to scientists from the Institute of Nuclear Physics of the Polish Academy of Sciences in Cracow. In line with their most recent predictions, matter in optical lattices should form tensile and inhomogeneous quantum rings in a controlled manner.

An optical lattice is a structure built of light, i.e. electromagnetic waves. Lasers play a key role in the construction of such lattices. Each laser generates an electromagnetic wave with strictly defined, constant parameters which can be almost arbitrary modified. When the laser beams are matched properly, it is possible to create a lattice with well known properties. By overlapping of waves, the minima of potential can be obtained, whose arrangement enables simulation of the systems and models well-known from solid state physics. The advantage of such prepared systems is the relatively simple way to modify positions of these minima, what in practice means the possibility of preparing various type of lattices.

“If we introduce appropriately selected atoms into an area of space that has been prepared in this way, they will congregate in the locations of potential minima. However, there is an important condition: the atoms must be cooled to ultra-low temperatures. Only then will their energy be small enough not to break out of the subtle prepared trap,” explains Dr. Andrzej Ptok from the Institute of Nuclear Physics of the Polish Academy of Sciences (IFJ PAN) in Cracow.

NASA is eyeing up a nearby asteroid that contains enough gold to make everyone on Earth a billionaire.

A female National Guard soldier has successfully completed the final stage of the Army’s Special Forces Qualification Course (Q Course), but she’s not a Green Beret yet.

The soldier finished the grueling three-week evaluation known as Robin Sage this week, but she is still in the final counseling phase, in which she and other students receive evaluations from course staff, Lt. Col. Loren Bymer, spokesman for U.S. Army Special Operations Command, told Military.com on Thursday.

Read Next: Marine Raider Dies During Airborne Training at Fort Benning.

Artificial intelligence networks have learnt a new trick: being able to create photo-realistic faces from just a few pixelated dots, adding in features such as eyelashes and wrinkles that can’t even be found in the original.

Before you freak out, it’s good to note this is not some kind of creepy reverse pixelation that can undo blurring, because the faces the AI comes up with are artificial – they don’t belong to real people. But it’s a cool technological step forward from what such networks have been able to do before.

The PULSE (Photo Upsampling via Latent Space Exploration) system can produce photos with up to 64 times greater resolution than the source images, which is 8 times more detailed than earlier methods.

This electric hydrofoil boat from SeaBubbles is the aquatic equivalent of a Tesla!

In recent years, many research teams worldwide have been developing and evaluating techniques to enable different locomotion styles in legged robots. One way of training robots to walk like humans or animals is by having them analyze and emulate real-world demonstrations. This approach is known as imitation learning.

Researchers at the University of Edinburgh in Scotland have recently devised a framework for training humanoid robots to walk like humans using human demonstrations. This new framework, presented in a paper pre-published on arXiv, combines imitation learning and deep reinforcement learning techniques with theories of robotic control, in order to achieve natural and dynamic locomotion in humanoid robots.

“The key question we set out to investigate was how to incorporate useful human knowledge in robot locomotion and human motion capture data for imitation into deep reinforcement learning paradigm to advance the autonomous capabilities of legged robots more efficiently,” Chuanyu Yang, one of the researchers who carried out the study, told TechXplore. We proposed two methods of introducing human prior knowledge into a DRL framework.”

Back in the Sixties, one of the hottest toys in history swept America. It was called Etch-A-Sketch, and its popularity was based on a now-laughably simple feature. It was a handheld small-laptop-sized device that allowed users to create crude images by turning two control knobs that drew horizontal, vertical and diagonal lines composed of aluminum particles sealed in a plastic case. It allowed experienced artists to compose simple and sometimes recognizable portraits. And it allowed inexperienced wannabe artists who could barely draw stick-figure characters to feel like masters of the genre by generating what, frankly, still looked pretty much like mush. But Etch-A-Sketch was fun, and it went on to sell 100 million units to this day.

Six decades later, researchers at the Chinese Academy of Sciences and City University of Hong Kong have come up with an invention that actually does what so many wishful enthusiasts imagined Etch-A-Sketch did all those years ago.

Continue reading “AI creates realistic faces from crude sketches” »