coordination


Needed: Humans To Break Artificial Intelligence Out Of Its Silo

#artificialintelligence

AI is nothing without the people behind it. AI will fill many roles, but perhaps its greatest potential is in its ability to reach across or break through organizational silos. At this point, however, with most implementations in pilot stages, labs or focused on single tasks such as chatbots, AI has yet to break out of its own silo. For AI to be a truly revolutionary force across organizations, it needs to be liberated, in a very human way. That's the word from Sharmila Chatterjee and Zoran Latinovic, both with MIT, speaking in a webcast hosted by MIT Sloan Management Review.


Needed: Humans To Break Artificial Intelligence Out Of Its Silo

#artificialintelligence

AI is nothing without the people behind it. AI will fill many roles, but perhaps its greatest potential is in its ability to reach across or break through organizational silos. At this point, however, with most implementations in pilot stages, labs or focused on single tasks such as chatbots, AI has yet to break out of its own silo. For AI to be a truly revolutionary force across organizations, it needs to be liberated, in a very human way. That's the word from Sharmila Chatterjee and Zoran Latinovic, both with MIT, speaking in a webcast hosted by MIT Sloan Management Review.


Gartner: What supply chain managers should know about control towers

#artificialintelligence

This is an opinion piece written by Christian Titze, vice president analyst at Gartner. Opinions are the author's own. Control towers are the artificial intelligence (AI) of supply chain. Everyone wants to have it, but nobody quite knows how it works. Supply chain leaders see the term in vendor presentations, usually connected with the promise that a control tower will make the supply chain better, faster and smarter.


Realizing the Potential of AI Localism by Stefaan G. Verhulst & Mona Sloane

#artificialintelligence

But even by the usual standards, artificial intelligence has had a turbulent run. Is AI a society-renewing hero or a jobs-destroying villain? As always, the truth is not so categorical. At more than 1,000 pages, Thomas Piketty's doorstop sequel to his previous opus, Capital in the Twenty-First Century, does not disappoint. But whether it will fundamentally change the global debate about inequality is an open question.


#305: Coordination, Cooperation, and Collaboration, with Vijay Kumar

Robohub

He also explains where he draws inspiration from in his research, and why robotics has yet to meet science fiction. Vijay Kumar is the Nemirovsky Family Dean of Penn Engineering with appointments in the Departments of Mechanical Engineering and Applied Mechanics, Computer and Information Science, and Electrical and Systems Engineering at the University of Pennsylvania. Kumar's group works on creating autonomous ground and aerial robots, designing bio-inspired algorithms for collective behaviors, and on robot swarms. They have won many best paper awards at conferences, and group alumni are leaders in teaching, research, business and entrepreneurship. Kumar is a fellow of ASME and IEEE and a member of the National Academy of Engineering.


Learning Optimal Temperature Region for Solving Mixed Integer Functional DCOPs

arXiv.org Artificial Intelligence

Distributed Constraint Optimization Problems (DCOPs) are an important framework that models coordinated decision-making problem in multi-agent systems with a set of discrete variables. Later work has extended this to model problems with a set of continuous variables (F-DCOPs). In this paper, we combine both of these models into the Mixed Integer Functional DCOP (MIF-DCOP) model that can deal with problems regardless of its variables' type. We then propose a novel algorithm, called Distributed Parallel Simulated Annealing (DPSA), where agents cooperatively learn the optimal parameter configuration for the algorithm while also solving the given problem using the learned knowledge. Finally, we empirically benchmark our approach in DCOP, F-DCOP and MIF-DCOP settings and show that DPSA produces solutions of significantly better quality than the state-of-the-art non-exact algorithms in their corresponding setting.


R-MADDPG for Partially Observable Environments and Limited Communication

arXiv.org Artificial Intelligence

There are several real-world tasks that would benefit from applying multiagent reinforcement learning (MARL) algorithms, including the coordination among self-driving cars. The real world has challenging conditions for multiagent learning systems, such as its partial observable and nonstationary nature. Moreover, if agents must share a limited resource (e.g. network bandwidth) they must all learn how to coordinate resource use. This paper introduces a deep recurrent multiagent actor-critic framework (R-MADDPG) for handling multiagent coordination under partial observable set-tings and limited communication. We investigate recurrency effects on performance and communication use of a team of agents. We demonstrate that the resulting framework learns time dependencies for sharing missing observations, handling resource limitations, and developing different communication patterns among agents.


Iraq considers deepening military ties with Russia

The Japan Times

BAGHDAD – Iraq and Russia discussed prospects for deepening military coordination, Iraq's Defense Ministry said Thursday, amid a strain in Baghdad-Washington relations after a U.S. airstrike killed a top Iranian general inside Iraq. The ministry statement followed a meeting in Baghdad between Iraqi army chief of staff Lt. Gen. Othman Al-Ghanimi and Iraq's Russian Ambassador Maksim Maksimov, as well as a newly arrived defense attache. The meeting comes during an uncertain moment in the future of Iraq-U.S. military relations, following the Jan. 3 U .S. drone strike that killed Iran's most powerful military commander, Gen. Qassem Soleimani, and Iraqi senior militia leader Abu Mahdi al-Muhandis near Baghdad airport. The attack continues to create friction, prompting powerful Shiite parties to call for an overhaul of the existing strategic set-up between Iraq and the U.S.-led coalition. Al-Ghanimi praised Moscow's role in the battle against the Islamic State group, saying they had provided "our armed forces with advanced and effective equipment and weapons that had a major role in resolving many battles," according to the ministry statement.


AI Automation Startup Zinier Raises $90M - SDxCentral

#artificialintelligence

Zinier, a company that uses artificial intelligence (AI) to automate field work, has raised $90 million in a Series C funding round, bringing its total amount raised to $120 million. The startup plays heavily in the telecom sector -- 80% of its existing customers are in the space, including network operators, equipment vendors and suppliers, contractors, and engineers, according to Zinier's co-founder and CEO Arka Dhar. That's also reflected by the firms that returned to invest in this latest round, including Nokia-backed NGP Capital and Qualcomm Ventures. New investor Iconiq Capital led the round with participation from Tiger Global Management, Accel, Founders Fund, and Newfund Capital. "Zinier is going to play a very, very important role there," Dhar said in a phone interview.


Should Artificial Intelligence Governance be Centralised? Design Lessons from History

arXiv.org Artificial Intelligence

Can effective international governance for artificial intelligence remain fragmented, or is there a need for a centralised international organisation for AI? We draw on the history of other international regimes to identify advantages and disadvantages in centralising AI governance. Some considerations, such as efficiency and political power, speak in favour of centralisation. Conversely, the risk of creating a slow and brittle institution speaks against it, as does the difficulty in securing participation while creating stringent rules. Other considerations depend on the specific design of a centralised institution. A well-designed body may be able to deter forum shopping and ensure policy coordination. However, forum shopping can be beneficial and a fragmented landscape of institutions can be self-organising. Centralisation entails trade-offs and the details matter. We conclude with two core recommendations. First, the outcome will depend on the exact design of a central institution. A well-designed centralised regime covering a set of coherent issues could be beneficial. But locking-in an inadequate structure may pose a fate worse than fragmentation. Second, for now fragmentation will likely persist. This should be closely monitored to see if it is self-organising or simply inadequate.