Masaya Nakamura, who pioneered game arcades and founded the video game company behind the smash-hit Pac-Man, has died at 91. Nakamura founded gaming company Namco -- part of what today is known as Bandai Namco -- in 1955. His Jan. 22 death was confirmed a week later on Bandai Namco's website on Monday. After starting with two mechanical horse rides on a rooftop, Namco went on to pioneer amusement parks and game arcades, the Associated Press reports. The company released the coin-operated game Pac-Man, designed by Namco engineer Toru Iwatani, in 1980. The game expanded into consoles before being merchandised into a television series, a film and various theme parks.

You may have once seen a giant face in the clouds. Perhaps it took you aback, amused you, or maybe it prompted an "uncanny valley" kind of sensation--realness, but with a lingering unease. It's thought that a similar experience was shared by an early hominid approximately 3 million years ago. Researchers say a rock that bore resemblance to a face was carried, over some four kilometers from where it was probably found, to an Australopithecine home. Known as the Makapansgat pebble, it was found in 1925 in a South-African cave, in what may well have been a camp or dwelling.

The founder of video game company Bandai Namco, which released cult game Pac-Man, has died at the age of 91, the firm has announced. Masaya Nakamura established Nakamura Manufacturing, which went on to become the Nakamura Amusement Machine Manufacturing Company (Namco) in 1956. He started out installing two electric horses on the roof of a department store in Japan as amusement rides. He was known as the "father" of Pac-Man because it was a Namco release in 1980. The game was developed by Toru Iwatani and in 2016 was named the highest-grossing arcade game of all time by the website US Gamer.

Masaya Nakamura, the founder of game developer and distributor Namco Ltd. and known as "the father of Pac-Man," died Jan. 22, Bandai Namco Holdings Inc. announced Monday via a corporate website. The cause of death was not announced. After graduating in 1948 from Yokohama Kogyo Senmon Gakko (now Yokohama National University), he founded Nakamura Seisakusho in 1955, which was renamed Namco in 1977. The company developed numerous hit video games, including "Galaxian," "Pac-Man" and "Ridge Racer," that could be played on home consoles or in entertainment facilities such as game centers. Namco merged with Bandai Co. in 2005 to form Bandai Namco Group, and its game production assets were branched into Bandai Namco Games Inc. in 2006, which is now known as Bandai Namco Entertainment Inc. Nakamura was a chairman and a supreme adviser of Bandai Namco Entertainment since 2006.

A Northwestern University team developed a new computational model that performs at human levels on a standard intelligence test. This work is an important step toward making artificial intelligence systems that see and understand the world as humans do. "The model performs in the 75th percentile for American adults, making it better than average," said Northwestern Engineering's Ken Forbus. "The problems that are hard for people are also hard for the model, providing additional evidence that its operation is capturing some important properties of human cognition." The new computational model is built on CogSketch, an artificial intelligence platform previously developed in Forbus' laboratory.

A soft robotic sleeve placed around the heart in a pig model of acute heart failure. The actuators embedded in the sleeve support heart function by mimicking the outer heart muscles that induce the heart to beat. An international team of scientists has developed a soft robotic sleeve that can be implanted on the external surface of the heart to restore blood circulation in pigs (and possibly humans in the future) whose hearts have stopped beating. The device is a silicon-based system with two layers of actuators: one that squeezes circumferentially and one that squeezes diagonally, both designed to mimic the movement of healthy hearts when they beat. Heart failure affects 41 million people worldwide.

Lecture 20, which focuses on the AI business, is not available in MIT Lecture Videos due to unknown reasons..

Stanford researchers say they've created a new artificial intelligence system that can identify skin cancer as well as trained doctors can. According to a study they published in science journal Nature, the program was able to distinguish between cancerous moles and harmless ones with more than 90 percent accuracy. The researchers trained the system by feeding it nearly 130,000 images of moles and lesions, with some of them being cancerous. The system scanned the images pixel by pixel, identifying characteristics that helped it make each diagnosis. Using machine learning, the A.I. grew more accurate as it studied more samples.

We start with a description of Lacan's work that we then take into our analytics methodology. In a first investigation, a Lacan-motivated template of the Poe story is fitted to the data. A segmentation of the storyline is used in order to map out the diachrony. Based on this, it will be shown how synchronous aspects, potentially related to Lacanian registers, can be sought. This demonstrates the effectiveness of an approach based on a model template of the storyline narrative. In a second and more comprehensive investigation, we develop an approach for revealing, that is, uncovering, Lacanian register relationships. Objectives of this work include the wide and general application of our methodology. This methodology is strongly based on the "letting the data speak" Correspondence Analysis analytics platform of Jean-Paul Benz\'ecri, that is also the geometric data analysis, both qualitative and quantitative analytics, developed by Pierre Bourdieu.

Recent empirical results on long-term dependency tasks have shown that neural networks augmented with an external memory can learn the long-term dependency tasks more easily and achieve better generalization than vanilla recurrent neural networks (RNN). We suggest that memory augmented neural networks can reduce the effects of vanishing gradients by creating shortcut (or wormhole) connections. Based on this observation, we propose a novel memory augmented neural network model called TARDIS (Temporal Automatic Relation Discovery in Sequences). The controller of TARDIS can store a selective set of embeddings of its own previous hidden states into an external memory and revisit them as and when needed. For TARDIS, memory acts as a storage for wormhole connections to the past to propagate the gradients more effectively and it helps to learn the temporal dependencies. The memory structure of TARDIS has similarities to both Neural Turing Machines (NTM) and Dynamic Neural Turing Machines (D-NTM), but both read and write operations of TARDIS are simpler and more efficient. We use discrete addressing for read/write operations which helps to substantially to reduce the vanishing gradient problem with very long sequences. Read and write operations in TARDIS are tied with a heuristic once the memory becomes full, and this makes the learning problem simpler when compared to NTM or D-NTM type of architectures. We provide a detailed analysis on the gradient propagation in general for MANNs. We evaluate our models on different long-term dependency tasks and report competitive results in all of them.