Systems & Languages


Thirteenth International Distributed AI Workshop

AI Magazine

This article discusses the Thirteenth International Distributed AI Workshop. An overview of the workshop is given as well as concerns and goals for the technology. The central problem in DAI is how to achieve coordinated action among such agents, so that they can accomplish more as a group than as individuals. The DAI workshop is dedicated to advancing the state of the art in this field. This year's workshop took place on the Olympic Peninsula in Washington State on 28 to 30 July 1994 and included 45 participants from North America, Europe, and the Pacific Rim.


Why blockchain is perfect for building a distributed AI platform

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"The next AI revolution is going to solve these problems: It's going to bring more intelligence, it's going to coordinate and connect many different special AIs together, and it's going to enable AI to be applied for broader benefit," says SingularityNET's CEO Ben Goertzel. TechRepublic's Dan Patterson spoke with Goertzel to discuss why blockchain technology is perfect for building an open and distributed artificial intelligence (AI) platform. Blockchain gives users the ability to create a decentralized network of AIs where anyone can post their AI online, and their AI can participate in the network, Goertzel said. So when someone needs AI-as-a-Service, they can send out a request to the network and find agents that can do the task they are looking to accomplish. The concept of SingularityNET is that it's an open market for AIs.


Associative memory AI aids in the battle against financial crime

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Check out AI-Powered Crime Prediction at the Strata Business Summit at the Strata Data Conference in San Jose, March 5-8, 2018. Hurry--early price ends January 19. In this episode of the O'Reilly Media Podcast, I spoke with Gayle Sheppard, vice president and general manager of Saffron AI Group at Intel, and David Thomas, chief analytics officer for Bank of New Zealand (BNZ). Our conversations centered around the utility of artificial intelligence in the financial services industry. According to Sheppard, associative memory AI technologies are best thought of as reasoning systems that combine the memory-based learning seen in humans--recognizing patterns, spotting anomalies, and detecting new features almost instantly--with data.


Top Graphical Models Applications in Real World

@machinelearnbot

Now we are going to explain the various Graphical Models Applications in real life such as – Manufacturing, finance, Steel Production, Handwriting Recognition etc. At last, we will discuss the case study about the use of Graphical Models in the Volkswagen. Making the production of low cost and most reliable components at a high rate is possible. Graphs, because they are pictures. They are particularly appropriate for presentation of financial information.


Robust distributed decision-making in robot swarms

Robohub

Reaching an optimal shared decision in a distributed way is a key aspect of many multi-agent and swarm robotic applications. As humans, we often have to come to some conclusions about the current state of the world so that we can make informed decisions and then act in a way that will achieve some desired state of the world. Of course, expecting every person to have perfect, up-to-date knowledge about the current state of the world is unrealistic, and so we often rely on the beliefs and experiences of others to inform our own beliefs. We see this too in nature, where honey bees must choose between a large number of potential nesting sites in order to select the best one. When a current hive grows too large, the majority of bees must choose a new site to relocate to via a process called "swarming" – a problem that can be generalised to choosing the best of a given number of choices.


Arm announces PSA security architecture for IoT devices

ZDNet

Arm has unveiled PSA, a new systems architecture designed to help secure and protect today's connected devices. The British semiconductor firm said on Monday ahead of TechCon 2017 that the new system, Platform Security Architecture (PSA), is intended to act as a common industry framework for developers, hardware, and silicon providers as a means to enhance the security of Internet of Things (IoT) devices built on system-on-a-chip (SoC) Arm Cortex processors. Last year, Arm and SoftBank Chairman Masayoshi Son predicted a trillion connected devices could be in play by 2035. These devices will require protection at not only the network but hardware level, to prevent them being used for more nefarious purposes such as in the case of the Mirai botnet. This is where PSA comes in, according to Arm.



Building--and scaling--a reliable distributed architecture

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I recently asked Joseph Breuer and Robert Reta, both Senior Software Engineers at Netflix, to discuss what they have learned through implementing a service at scale at Netflix. Joseph and Robert will be presenting a session on Event Sourcing at Global Scale at Netflix at O'Reilly Velocity Conference, taking place October 1-4 in New York. The primary challenge when operating a service in a distributed architecture at scale is managing for the behavior of your downstream dependencies. Continue reading Building--and scaling--a reliable distributed architecture.


To Code or Not to Code with KNIME

@machinelearnbot

Many modern data analysis environments allow for code-free creation of advanced analytics workflows. The advantages are obvious: more casual users, who cannot possibly stay on top of the complexity of working in a programming environment, are empowered to use existing workflows as templates and modify them to fit their needs, thus creating complex analytics protocols that they would never have been able to create in a programming environment. In some areas this may not be as dramatic, as the need for new ways of solving (parts of) problems isn't as critical anymore and a carefully designed visual environment may capture everything needed. The screenshot below shows how expert code written in those two languages can be integrated in a KNIME analytical workflow.


A Distributed AI Lab – AI Grant

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Together, we're excited to announce AI Grant 2.0! AI Grant 2.0 Fellows will receive some new treats, including: We've learned from the previous cohort that $2,500 will satisfy the needs of most projects. Our aspiration with AI Grant is to build a distributed AI lab. Stop reading, and click here to start the application.