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Decomposable Probability-of-Success Metrics in Algorithmic Search Artificial Intelligence

There are three components to a search problem. The first is the finite discrete search space, Ω, which is the set of elements to be examined. Next is the target set, T, which is a nonempty subset of the search space that we are trying to find. Finally, we have an external information resource, F, which provides an evaluation of elements of the search space. Typically, there is a tight relationship between the target set and the external information resource, as the resource is expected to lead to or describe the target set in some way, such as the target set being elements which meet a certain threshold under the external information resource. Within the framework, we have an iterative algorithm which seeks to find elements of the target set, shown in Figure 1. The algorithm is a black-box that has access to a search history and produces a probability distribution over the search space. At each step, the algorithm samples over the search space using the probability distribution, evaluates that element using the information resource, adds the result to the search history, and determines the next probability distribution. The abstraction of finding the next probability distribution as a black-box algorithm allows the search framework to work with all types of search problems.

The Futility of Bias-Free Learning and Search Machine Learning

Building on the view of machine learning as search, we demonstrate the necessity of bias in learning, quantifying the role of bias (measured relative to a collection of possible datasets, or more generally, information resources) in increasing the probability of success. For a given degree of bias towards a fixed target, we show that the proportion of favorable information resources is strictly bounded from above. Furthermore, we demonstrate that bias is a conserved quantity, such that no algorithm can be favorably biased towards many distinct targets simultaneously. Thus bias encodes trade-offs. The probability of success for a task can also be measured geometrically, as the angle of agreement between what holds for the actual task and what is assumed by the algorithm, represented in its bias. Lastly, finding a favorably biasing distribution over a fixed set of information resources is provably difficult, unless the set of resources itself is already favorable with respect to the given task and algorithm.

Should We Fear Artificial Superintelligence?


Speaking at a conference in Lisbon, Portugal shortly before his death, Stephen Hawking told attendees that the development of artificial intelligence might become the "worst event in the history of our civilization," and he had every reason for concern. Known as an artificial superintelligence (ASI) by AI researchers, ethicists, and others, it has the potential to become more powerful than anything this planet has ever seen and it poses what will likely be the final existential challenge humanity will ever face as a species. To better understand what concerned Stephen Hawking, Elon Musk, and many others, we need to deconstruct many of the popular culture depictions of AI. The reality is that AI has been with us for a while now, ever since computers were able to make decisions based on inputs and conditions. When we see a threatening AI system in the movies, it's the malevolence of the system, coupled with the power of a computer, that scares us.

AI could bring an end to famine, says World Bank president


Traditionally famine is classified in five stages, from "minimal" food insecurity through "crisis" to "famine". Modelling of last year's famine in Somalia suggested intervening before stage five could reduce aid costs by 30 per cent. But the real saving, Mr Kim said, would be in preventing the permanent developmental damage done to children by malnutrition, which leaves them with "fewer neural connections" and less ability to participate in the workforce. Research shows that children born during a famine earn around 13 per cent less over their lifetime. Mr Kim said: "One of the things that has been shown in Ethiopia is that if you think a famine is coming, if you do something really simple like double the amount of cash transfers that poor people get, you can actually stop the famine from going forward.

The risks of regulating artificial intelligence algorithms


The usual people are teaming up with the usual people to try to harness artificial intelligence (AI). That is, Google, Amazon and Microsoft are tying up with the UN, the World Bank and the Red Cross to try to use algorithms to predict famine. Every conference this year contains a dead human genius reincarnated as software system or a robot. Yes, there is a lot of hype, but there is real worth in AI and Machine Learning. Read our counseling on how to avoid adopting "black box" approach.

The World Bank and tech companies want to use AI to predict famine


At this week's United Nations General Assembly, the World Bank, the United Nations, and the Red Cross teamed up with tech giants Amazon, Microsoft, and Google to announce an unlikely new tool to stop famine before it starts: artificial intelligence. The Famine Action Mechanism (FAM), as they're calling it, is the first global tool dedicated to preventing future famines -- no small news in a world where one in nine people don't have enough food. Building off of previous famine-prediction strategies, the tool will combine satellite data of things like rainfall and crop health with social media and news reports of more human factors, like violence or changing food prices. It will also establish a fund that will be automatically dispersed to a food crisis as soon as it meets certain criteria, speeding up the often-lengthy process for funding famine relief. For a famine to be declared in a country or region, three criteria have to be met: At least one in five households has an extreme lack of food; over 30 percent of children under five have acute malnutrition; and two out of 10,000 people die each day.

Microsoft, Amazon, Google join fight to prevent famine, tap AI tech The Japan Times


WASHINGTON – Tech giants Microsoft, Amazon and Google are joining forces with international organizations to help identify and head off famines in developing nations using data analysis and artificial intelligence, a new initiative unveiled Sunday. Rather than waiting to respond to a famine after many lives already have been lost, the tech firms "will use the predictive power of data to trigger funding" to take action before it becomes a crisis, the World Bank and United Nations announced in a joint statement. "The fact that millions of people -- many of them children -- still suffer from severe malnutrition and famine in the 21st century is a global tragedy," World Bank Group President Jim Yong Kim said in a statement. "We are forming an unprecedented global coalition to say, 'no more.' " Last year more than 20 million people faced famine conditions in Nigeria, Somalia, South Sudan and Yemen, while 124 million people currently live in crisis levels of food insecurity, requiring urgent humanitarian assistance for their survival, the agencies said. Over half of them live in areas affected by conflict.

The World Bank's latest tool for fighting famine: Artificial intelligence

Washington Post - Technology News

Despite being a slow-moving disaster, famine is notoriously difficult to predict. The reason for this, experts say, is that severe food shortages are hardly ever about food supply alone. A famine might be triggered by drought or some other climatic interference in crop production, but other powerful forces usually bring the scourge to full bloom: food price inflation, political instability, military conflict and even too much rain. "The root cause of famine is extremely complex," said Franck Bousquet, senior director of the World Bank Fragility, Conflict, and Violence Group (FCV). "Usually, the poorest and most vulnerable are the most affected and the least able to cope with shocks that other populations can absorb.

Here Are All the Ways the World Ends in the Biggest Upcoming Video Games From E3


So this year's E3, currently underway in Los Angeles, has been good news for gamers but terrible news for a wide variety of fictional planet Earths. In game after game at the big Microsoft and Sony press conferences, developers showed off crumbling cities, violent hordes of survivors in various states of physical and mental decline, and lots of nigh-indistinguishable gunplay. To help you tell one post-apocalyptic wasteland from another, we've sorted the trailers based on which horseman seems most responsible. Nothing says "apocalypse" like "global thermonuclear warfare," so it's no surprise that mushroom clouds play a big role in several of these upcoming games. Fallout 76's new trailer gets pride-of-place for showing a doomed soldier take it all in before the blast wave knocks him or her to the ground for what looks like a pretty slow and painful death, as deaths caused by nuclear weapons go: Fallout 76 turns out to be an online multiplayer game rather than the single-player adventures that have characterized the Fallout series so far.

KFC: Enemy of waistlines, AI, arteries and logistics software


Brits suffering through the nationwide KFC famine can enjoy with wry amusement the fact that an AI can be fooled into thinking an image of Colonel Sanders and the restaurant's logo are a stop sign.