One billion public Instagram photos were used to train an algorithm created by Facebook to learn to recognise images by itself.
The photos were used to help a Facebook algorithm learn to recognise images without supervision.
Category: robotics/AI – Page 1582
The legal rights of robots have expanded, at least in Pennsylvania. There, autonomous delivery drones will be allowed to maneuver on sidewalks and paths as well as roadways and will now technically be considered “pedestrians.” It’s the latest change in the evolving relationship between autonomous vehicles and humans.
Clip from Lew Later (7 Things Apple Should Steal From Android…) — https://youtu.be/GgNF1YuOOuc
Researchers affiliated with Nvidia and Harvard today detailed AtacWorks, a machine learning toolkit designed to bring down the cost and time needed for rare and single-cell experiments. In a study published in the journal Nature Communications, the coauthors showed that AtacWorks can run analyses on a whole genome in just half an hour compared with the multiple hours traditional methods take.
Most cells in the body carry around a complete copy of a person’s DNA, with billions of base pairs crammed into the nucleus. But an individual cell pulls out only the subsection of genetic components that it needs to function, with cell types like liver, blood, or skin cells using different genes. The regions of DNA that determine a cell’s function are easily accessible, more or less, while the rest are shielded around proteins.
AtacWorks, which is available from Nvidia’s NGC hub of GPU-optimized software, works with ATAC-seq, a method for finding open areas in the genome in cells pioneered by Harvard professor Jason Buenrostro, one of the paper’s coauthors. ATAC-seq measures the intensity of a signal at every spot on the genome. Peaks in the signal correspond to regions with DNA such that the fewer cells available, the noisier the data appears, making it difficult to identify which areas of the DNA are accessible.
Get ready for the robot basketball league. 😃
CHECK THIS OUT! Robots are coming for all the jobs — even the ones in professional sports. Toyota built a robot that can play basketball…
Summary: Combining brain activity data with artificial intelligence, researchers generated faces based upon what individuals considered to be attractive features.
Source: University of Helsinki.
Researchers at the University of Helsinki and University of Copenhagen investigated whether a computer would be able to identify the facial features we consider attractive and, based on this, create new images matching our criteria. The researchers used artificial intelligence to interpret brain signals and combined the resulting brain-computer interface with a generative model of artificial faces. This enabled the computer to create facial images that appealed to individual preferences.
Researchers at the University of California San Diego School of Medicine have shown that they can block inflammation in mice, thereby protecting them from liver disease and hardening of the arteries while increasing their healthy lifespan.
Researchers have succeeded in making an AI understand our subjective notions of what makes faces attractive. The device demonstrated this knowledge by its ability to create new portraits that were tailored to be found personally attractive to individuals. The results can be used, for example, in modeling preferences and decision-making as well as potentially identifying unconscious attitudes.
Researchers at the University of Helsinki and University of Copenhagen investigated whether a computer would be able to identify the facial features we consider attractive and, based on this, create new images matching our criteria. The researchers used artificial intelligence to interpret brain signals and combined the resulting brain-computer interface with a generative model of artificial faces. This enabled the computer to create facial images that appealed to individual preferences.
“In our previous studies, we designed models that could identify and control simple portrait features, such as hair color and emotion. However, people largely agree on who is blond and who smiles. Attractiveness is a more challenging subject of study, as it is associated with cultural and psychological factors that likely play unconscious roles in our individual preferences. Indeed, we often find it very hard to explain what it is exactly that makes something, or someone, beautiful: Beauty is in the eye of the beholder,” says Senior Researcher and Docent Michiel Spapé from the Department of Psychology and Logopedics, University of Helsinki.
“As several people mention in the replies to LenKusov, shooting or otherwise damaging that hefty lithium battery pack could make it explode—which is either very bad if you’re close-range, or exactly what you want if you’re somehow hitting it from a distance and trying for fireworks.”
It turns out that a flip through Spot’s user manual reveals its weaknesses.
There’s more AI news out there than anyone can possibly keep up with. But you can stay tolerably up to date on the most interesting developments with this column, which collects AI and machine learning advancements from around the world and explains why they might be important to tech, startups or civilization.
To begin on a lighthearted note: The ways researchers find to apply machine learning to the arts are always interesting — though not always practical. A team from the University of Washington wanted to see if a computer vision system could learn to tell what is being played on a piano just from an overhead view of the keys and the player’s hands.
Audeo, the system trained by Eli Shlizerman, Kun Su and Xiulong Liu, watches video of piano playing and first extracts a piano-roll-like simple sequence of key presses. Then it adds expression in the form of length and strength of the presses, and lastly polishes it up for input into a MIDI synthesizer for output. The results are a little loose but definitely recognizable.
Uber and OpenAI researchers say an advance in Go-Explore AI in beating Atari games could have applications for robotics and drug design.