A couple of recent events made me think it would be good to post a brief but (hopefully) balanced summary of the discussion about superintelligence. Our brains are existence proof that ordinary matter organised the right way can generate general intelligence – an intelligence which can apply itself to any domain. They were created by evolution, which is slow, messy and inefficient. It is also un-directed, although non-random. We are now employing the powerful, fast and purposeful method of science to organise different types of ordinary matter to achieve the same result.

SEOUL – Months before the first summit between the leaders of the two Koreas in 2000, South Korean tech giant Samsung Electronics Inc. invested $730,000 in Pyongyang's top computer lab. North Korean programmers there would develop online chess games and food recipes for Samsung to sell outside the North. Samsung quit the business as inter-Korea relations later deteriorated, and the lab -- Korea Computer Center -- was blacklisted last year for its alleged contribution to the North's weapons program. As companies from South Korea to Russia and China again look to cash in on easing tensions with Pyongyang, Samsung's now defunct businesses in Pyongyang and hundreds of similar failed joint ventures underline North Korea's status as one of the world's highest-risk investment destinations. Yet days before the historic meeting between U.S. President Donald Trump and North Korean leader Kim Jong Un in Singapore, a conference in Seoul to explore investment opportunities in North Korea drew about 600 attendees.

AI can detect signs of nuclear weapons testing banned under the Comprehensive Nuclear-Test-Ban Treaty, according to research from the US Pacific Northwest National Laboratory. A group of scientists have built a neural network to sniff out any unusual nuclear activity. Researchers from the Pacific Northwest National Laboratory (PNNL), one of the United States Department of Energy national laboratories, decided to see if they could use deep learning to sort through the different nuclear decay events to identify any suspicious behavior. The lab, buried beneath 81 feet of concrete, rock and earth, is blocked out from energy from cosmic rays, electronics and other sources. It means that the data collected is less noisy, making it easier to pinpoint unusual activity.

Armed conflict has led to an unprecedented number of internally displaced persons (IDPs) - individuals who are forced out of their homes but remain within their country. IDPs often urgently require shelter, food, and healthcare, yet prediction of when large fluxes of IDPs will cross into an area remains a major challenge for aid delivery organizations. Accurate forecasting of IDP migration would empower humanitarian aid groups to more effectively allocate resources during conflicts. We show that monthly flow of IDPs from province to province in both Syria and Yemen can be accurately forecasted one month in advance, using publicly available data. We model monthly IDP flow using data on food price, fuel price, wage, geospatial, and news data. We find that machine learning approaches can more accurately forecast migration trends than baseline persistence models. Our findings thus potentially enable proactive aid allocation for IDPs in anticipation of forecasted arrivals.

Many datasets can be represented as graphs, being the graph explicitely embedded in data (e.g., the friendship relation of a social network) or built through some suitable similarity measure between data items (e.g., the number of papers coauthored by two researchers). Such graphs often exhibit a complex, multi-scale community structure where each node is invoved in many groups of nodes, so-called communities, of different sizes. One of the most popular graph clustering algorithm is known as Louvain in name of the university of its inventors [Blondel et al., 2008]. It is based on the greedy maximization of the modularity, a classical objective function introduced in [Newman and Girvan, 2004]. The Louvain algorithm is fast, memory-efficient, and provides meaningful clusters in practice. It does not enable an analysis of the graph at different scales, however [Fortunato and Barthelemy, 2007, Lancichinetti and Fortunato, 2011].

With the wide‑spread implementation of electronic health records (EHRs) and the tremendous amount of electronic information being created and collected, the health care industry is a new (or not quite-so-new) frontier for Artificial Intelligence (AI). AI is finding its way onto physicians' desks to provide information about drug interactions, and in to EHRs to pull-up requested patient records, and wearables used by health plans to track health care metrics, promote wellness and address chronic conditions. But, health care is heavily regulated – and Part 1 of this blog we explained how using AI applications and systems like those noted above may trigger a multitude of requirements for AI developers, health care providers, and health plans. An important law that may affect AI in the health care setting is the Health Insurance Portability and Accountability Act and its implementing regulations (HIPAA), the federal law establishing a floor for privacy, security, and breach notification related to most health information. A critical threshold question is at what point does an AI vendor become subject to HIPAA?

On 18 June, UAE's Minister of State for Artificial Intelligence (AI) Mr Omar Sultan Al Olama signed a Memorandum of Understanding (MoU) with the Dr Ali Sebaa Al Marri, Executive President of Mohammed Bin Rashid School of Government (MBRSG), to enhance cooperation and empower young Emiratis. The collaboration seeks to help prepare a future generation of leaders by honing their leadership skills, developing their practical experience and enhancing their knowledge in employing AI technology in government work through training, educational courses and workshops. At the MoU signing ceremony, Minister Al Olama highlighted the potentials of using AI for innovation solutions and the importance of empower future leaders to use the technology. According to him, the creation of government services, programmes and initiatives that enhance the quality of life in the community and support having a competitive knowledgeable economy requires tools, skills and future potentials. "Preparing young Emiratis in AI and the use of its techniques to create innovative solutions to future challenges, supports the vision and directives of our (the UAE's) leadership, to strengthen the UAE's position as a global hub in the use of AI to shape the future," said Minister Al Olama.

On June 17th, Salesforce CEO Marc Benioff retweeted images from a CBS reporter of a detention facility in McAllen, Texas where children slept on the floor, covered in emergency blankets. Just a few days later, Microsoft CEO Satya Nadella sent an all-staff email calling President Donald Trump's immigration policy "cruel and abusive." In March, Beinoff's company signed a contract with US Customs and Border Patrol (CBP) to provide cloud services in order to boost the agency's hiring efforts, something that CBP has long struggled with. And at Microsoft, employees have organized to demand that Microsoft cancel its $19.4 million contract with Immigration and Customs Enforcement (ICE) for data processing and, potentially, facial recognition software. An NBC investigation also identified active contracts between ICE and a host of prominent tech companies--Hewlett Packard Enterprise, Thomson Reuters, Motorola Solutions, and Palantir--each worth tens of millions.

El Camino Hospital, located in the heart of Silicon Valley, has a problem. Its nurses, tending to patients amid a chorus of machines, monitors, and devices, are only human. One missed signal from, say, a call light--the bedside button patients press when they need help--could set in motion a chain of actions that end in a fall. "As fast as we all run to these bed alarms, sometimes we can't get there in time," says Cheryl Reinking, chief nursing officer at El Camino. Falls are dangerous and costly.

In science news around the world, the European Commission proposes spending €13 billion on military R&D from 2021 to 2027, of which €4.1 billion would be for research--a 20-fold increase over an existing pilot fund. The British Business Bank, a public company owned by the U.K. government, unveils a £2.5 billion fund called British Patient Capital that will make long-term investments in technology companies. Google announces plans to open an artificial intelligence research center in Accra later this year, its first such laboratory in Africa. Israel says it will begin pumping desalinated water into the Sea of Galilee starting next year to alleviate the effects of a 5-year drought. The launch of the European Space Agency's Euclid mission to study dark energy will be delayed by 2 years to 2022 because of problems with its infrared sensors.