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In a First, Facebook’s Superhuman Poker Beats World-Class Poker Professionals

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Can a machine or automated systems bluff?

A few months ago, the answer would probably be a negation. But not anymore!

In another incredible invention, an AI system can bluff better than any human. And, this time it’s Facebook and CMU’s superhuman AI which has bettered human professionals in the challenging game of poker.

Since, its inception, artificial intelligence robots have beaten humans in the game of chess, checkers and two-player poker. But, the AI bot developed by researchers at Carnegie Mellon University and Facebook AI lab has managed to defeat human professionals in a multi-player game of poker – a task which earlier was considered unachievable. Their bot called as Pluribus defeated some of the top players in the world in a series of no limit six-person poker game.

In 12 days and 10,000 hands, Pluribus played against top 12 poker players in two different environments. In one environment, the AI bot was up against 5 pros human players and in the second one, 5 AI bots played against one human player (the AI bots were unable to reach to a decisive conclusion in the second environment). In an unbelievable turn of events, Pluribus made around $1000 per hour, which is a considerable margin victory.

“It’s safe to say we’re at a superhuman level and that’s not going to change,” said Noam Brown, a research scientist at Facebook AI Research and co-creator of Pluribus.

Pluribus win is seen as a revolutionary landmark in AI because the earlier poker programs were designed with an altogether different algorithm. The previous bots focused only on two players, where it was easy to understand the strategy to beat the other player. But, the six-player poker game involves hell lot of variables and Pluribus outperforming them is a landmark achievement for the tech sector. Irrespective of the number of players, poker is probably one of the toughest game to program because unlike chess there is a lot of hidden information.

“Pluribus achieved superhuman performance at multiplayer poker, which is a recognized milestone in artificial intelligence and in game theory that has been open for decades,” said Tuomas Sandholm, a professor at Carnegie Mellon School of Computer Science, who helped develop the system.

What is more surprising is that during the game, Pluribus came out with completely unexpected moves. Because the program was built from scratch, it had no access to historical data or strategies.  The intelligent program picked up the game and made bluffs bigger than anyone else. During the entire game, Pluribus kept changing its strategy even when it was dealt with the same hand. This is surprising because picking up a pattern in a game of poker has always been impossible for humans.

To stay in the game, Pluribus initially followed the limping strategy, which is making the smallest bet. As the bot became a strong player, it eventually stopped limping – a move which has surprised many world-class poker players.

With professionals being beaten by the bots, the entire poker community is excited because the AI program is likely to teach new strategies to the players. The penetration of these strategies is expected to change the whole landscape of the online poker community.

The superhuman level capabilities displayed by the AI bot are likely to be transferrable to other situations such as cyber-security, financial negotiation and even fraud prevention. “It can even help navigate traffic with self-driving cars,” said Brown.

This groundbreaking invention is likely to fuel many revolutionary AI programs. The future of AI is definitely on the sunny side.

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An engineering graduate with an interest in the technology sector. Priya is fascinated by the fueling changes brought by AI in day-to-day life and loves to research on the future of AI.

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Intel’s New Neuromorphic Chips are 1,000 Times Faster Than Normal CPUs

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Intel’s new system codenamed Pohoiki Beach will be at the Consumer Electronics Show (CES) in Las Vegas. The device is built from 64 Loihi research chips, and the goal is for it to simulate the human brain when it comes to learning ability and energy efficiency. These neuromorphic chips are a simpler version of the way neurons and synapses function in the brain. 

Rich Uhlig, managing director of Intel Labs, spoke on the new technology. 

“We are impressed with the early results demonstrated as we scale Loihi to create more powerful neuromorphic systems. Pohoiki Beach will now be available to more than 60 ecosystem partners, who will use this specialized system to solve complex, compute-intensive problems.” 

The new AI neuromorphic chip can perform data-crunching tasks 1,000 times faster than normal processors like CPUs and GPUs while using a lot less power. 

The way it is based on brain neurons is not something entirely new. Many AI algorithms simulate neural networks in their programs. They use parallel processing for recognizing objects in images and words in speech. The new neuromorphic chips put these neural networks into silicon. While they are less flexible and powerful than some of the best general-purpose chips, they really perform when specialized in specific tasks. The new AI chip from Intel is 10,000 times more efficient than general processors. Since they are so energy efficient, the technology will be ideal for mobile devices, vehicles, industrial equipment, cybersecurity, and smart homes. AI researchers have already begun to use the system for things like improving prosthetic limbs so that they can adapt better to uneven ground, as well as creating digital maps to be used by self-driving cars. 

Chris Eliasmith, co-CEO of Applied Brain Research and professor at the University of Waterloo, is one of the several researchers using the new technology. 

“With the Loihi chip we’ve been able to demonstrate 109 times lower power consumption running a real-time deep learning benchmark compared to a GPU, and 5 times lower power consumption compared to specialized IoT interface hardware…Even better, as we scale the network up by 50 times, Loihi maintains real-time performance results and uses only 30 percent more power, whereas the IoT hardware uses 500 percent more power and is no longer real-time,” Chris Eliasmith said. 

Konstantinos Michmizos is a professor of Rutgers University, and his lab does work with SLAM which will be presented at the International Conference on Intelligent Robots and Systems (IROS) in November. 

“Loihi allowed us to realize a spiking neural network that imitates the brain’s underlying neural representations and behavior. The SLAM solution emerged as a property of the network’s structure. We benchmarked the Loihi-run network and found it to be equally accurate while consuming 100 times less energy than a widely used CPU-run SLAM method for mobile robots,” he said. 

As of right now, Pohoiki Beach is an 8 million neuron system. Rich Uhlig, head of Intel Labs, thinks that the company will be able to create a system that is able to simulate 100 million neurons by the end of 2019. This new technology will be able to be used by researchers for a wide range of things such as improvement of robot arms. These new developments and research are leading to what will likely be the commercialization of neuromorphic technology. 

According to the company, “Later this year, Intel will introduce an even larger Loihi system named Pohoiki Springs, which will build on the Pohoiki Beach architecture to deliver an unprecedented level of performance and efficiency for scaled-up neuromorphic workloads.” 

 

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AI Brings New Potential for Prosthetics with 3D-Printed Hand

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A new 3D-printed prosthetic hand paired with AI has been developed by Biological Systems Lab at Hiroshima University in Japan. This new technology can dramatically change the way prosthetics work. It is another step in the direction of combining both the physical human body with artificial intelligence, something that we are most definitely heading towards. 

The 3D-printed prosthetic hand has been paired with a computer interface to create the lightest and cheapest model yet. This version is the most reactive to motion intent that we have seen. Before the current model, they were normally made from metal which caused them to be both heavier and more expensive. The way this new technology works is by a neural network that is trained to recognize certain combined signals, these signals have been named “muscle synergies” by the engineers working on the project. 

The prosthetic hand has five independent fingers that can make complex movements. Compared to previous models, these fingers are able to move around more as well as all at the same time. These developments make it possible for the hand to be used for tasks like holding items such bottles and pens. Whenever the user of the technology wants to move the hand or fingers in a certain way, they only have to imagine it. Professor Toshio Tsuji of the Graduate School of Engineering at Hiroshima University explained the way a user can move the 3D-printed hand. 

“The patient just thinks about the motion of the hand and then the robot automatically moves. The robot is like a part of his body. You can control the robot as you want. We will combine the human body and machine like one living body.”

The 3D-printed hand works when electrodes in the prosthetic measures electrical signals that come from nerves through the skin. It can be compared to the way ECG and heart rates work. The measured signals are then sent to a computer within five milliseconds at which point the computer recognizes the desired movement. The computer then sends the signal back to the hand. 

There is a neural network that helps the computer learn the different complex movements, it has been named Cybernetic Interface. It can differentiate between the 5 fingers so that there can be individual movements. Professor Tsuji also spoke on this aspect of the new technology.

“This is one of the distinctive features of this project. The machine can learn simple basic motions and then combine and then produce complicated motions.”

The technology was tested among seven people, and one of the seven was an amputee who has been wearing a prosthesis for 17 years. The patients performed daily tasks, and they had a 95% accuracy rate for single simple motion and a 93% rate for complex movements. The prosthetics that were used in this specific test were only trained for 5 different movements with each finger; there could be many more complex movements in the future. With just these 5 trained movements, the amputee patient was able to pick up and put down things like bottles an notebooks. 

There are numerous possibilities for this technology. It could decrease cost while providing extremely functional prosthetic hands to amputee patients. There are still some problems like muscle fatigue and the capability of software recognizing many complex movements. 

This work was completed by Hiroshima University Biological Systems Engineering Lab along with patients from the Robot Rehabilitation Center in the Hygo Institute of Assistive Technology, Kobe. The company Kinki Gishi was responsible for creating the socket which was used on the arm of the amputee patient. 

 

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Robot Ants and Swarm Intelligence

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Researchers within Professor Jamie Paik’s Laboratory at Ecole Polytechnique Fédérale de Lausanne have developed ant-like robots that bring a whole new aspect to AI. These 10-gram robot ants don’t have much physical intelligence as individuals, but when you put a group together, they are able to communicate and act as a collective unit. They have different locomotion modes, and each one is able to navigate on any type of surface. As a collective group, they are able to move objects that weigh a lot compared to their bodies; it is similar to a group of ants carrying a stick. As individuals, they act completely autonomous and are disconnected. Each ant robot consists of infrared and proximity sensors that are used to detect objects and communicate with each other. There is the possibility of adding more and different types of sensors than the ones they have now. 

These small, three-legged ant robots are shaped like a T and named Tribots. Because of their small size and easy build, they are suitable for mass production. They consist of thin, multi-material sheets that are folded into a stack. Based on the real-life Odontomachus ants that have the trap-jaw which is used to jump between leaves, each one of these AI ants has five different traits. The different movements are vertical and horizontal jumping, somersaulting, walking on textured terrain, and moving on flat surfaces. 

These robotic ants, whenever in a collective group, have distinct individual roles that include the explorer, the leader, and the worker. The explorers look for physical obstacles ahead, the leaders dictate the actions of the group, and the workers move objects. The ants are not tied or limited to one role; they can change whenever and in an instant. 

This type of technology can be used in real-life scenarios like emergency search missions as well as the health sector. In theory, they could enter into the bloodstream and detect certain problems; they could also carry the medicine into those precise problem areas. Because of the relative easiness of mass production, they can be used in large numbers. 

Another benefit is that they would be able to detect targets without having to use any type of GPS. Researcher Jamie Paik spoke on the possibilities of this technology. 

“With their unique collective intelligence, our tiny robots can demonstrate better adaptability to unknown environments; therefore, for certain missions, they would outperform larger, more powerful robots.” 

These robot ants are part of a new development within the AI world called Swarm Intelligence; think of ants, bees, wasps, and any other organisms that can work both autonomously and as a collective group. They will also be able to operate in our environment simultaneously with humans. 

They are made up of sensors, software, and connectivity components that allow them to physically move, contain algorithms that help make intelligent decisions, and communicate with each other. These are a huge development in AI as they will be able to collect information while they interact with the environment and one another. This will continue to develop them and make them more useful in infrastructure, products, and services. 

These swarms of robots have a shared common goal that they work towards while being autonomous. They are mostly self-sustainable in the sense that they can self-deploy, self-repair, and self-optimize. As a swarm, they are able to spread out the work between each other which allows for more efficiency and less communication disruptions. 

Just like with any AI, these robot ants need to have some restrictions. There will have to be a system of overrides and human interventions in case they do not follow proper instructions. They will also be vulnerable to privacy threats, and with the ever increasing interconnectivity of machines and AI, it is a serious problem. Certain regulations and privacy controls will need to be established. 

This new technology is just another aspect of the endless development that is taking place within the AI field. These will have a huge impact on our AI and what it can be used for.

 

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