Lifeboat Foundation

MANILA, Philippines — A dengue case forecasting system using space data made by Philippine developers won the 2019 National Aeronautics and Space Administration’s International Space Apps Challenge. Over 29,000 participating globally in 71 countries, this solution made it as one of the six winners in the best use of data, the solution that best makes space data accessible, or leverages it to a unique application.

Dengue fever is a viral, infectious tropical disease spread primarily by Aedes aegypti female mosquitoes. With 271,480 cases resulting in 1,107 deaths reported from January 1 to August 31, 2019 by the World Health Organization, Dominic Vincent D. Ligot, Mark Toledo, Frances Claire Tayco, and Jansen Dumaliang Lopez from CirroLytix developed a forecasting model of dengue cases using climate and digital data, and pinpointing possible hotspots from satellite data.

Correlating information from Sentinel-2 Copernicus and Landsat 8 satellites, climate data from the Philippine Atmospheric, Geophysical and Astronomical Services Administration of the Department of Science and Technology (DOST-PAGASA) and trends from Google search engines, potential dengue hotspots will be shown in a web interface.

Using satellite spectral bands like green, red, and near-infrared (NIR), indices like Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and Normalized Difference Vegetation Index (NDVI) are calculated in identifying areas with green vegetation while Normalized Difference Water Index (NDWI) identifies areas with water. Combining these indices reveal potential areas of stagnant water capable of being breeding grounds for mosquitoes, extracted as coordinates through a free and open-source cross-platform desktop geographic information system QGIS.

Check out the website here: http://aedesproject.org/

https://www.forbes.com/sites/forbestechcouncil/2020/01/23/ar…ngularity/

Artificial Intelligence (AI) is an emerging field of computer programming that is already changing the way we interact online and in real life, but the term ‘intelligence’ has been poorly defined. Rather than focusing on smarts, researchers should be looking at the implications and viability of artificial consciousness as that’s the real driver behind intelligent decisions.

Consciousness rather than intelligence should be the true measure of AI. At the moment, despite all our efforts, there’s none.

Significant advances have been made in the field of AI over the past decade, in particular with machine learning, but artificial intelligence itself remains elusive. Instead, what we have is artificial serfs—computers with the ability to trawl through billions of interactions and arrive at conclusions, exposing trends and providing recommendations, but they’re blind to any real intelligence. What’s needed is artificial awareness.

Elon Musk has called AI the “biggest existential threat” facing humanity and likened it to “summoning a demon,”^[1] while Stephen Hawking thought it would be the “worst event” in the history of civilization and could “end with humans being replaced.”^[2] Although this sounds alarmist, like something from a science fiction movie, both concerns are founded on a well-established scientific premise found in biology—the principle of competitive exclusion.^[3]

Continue reading “Is artificial consciousness the solution to AI?” »

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“She thought her solution was obvious. Her colleagues, though, were sure their solution was correct—and the two didn’t match. Was the problem with one of their answers, or with the puzzle itself?”

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What is the ultimate goal of Artificial General Intelligence?

In this video series, the Galactic Public Archives takes bite-sized looks at a variety of terms, technologies, and ideas that are likely to be prominent in the future. Terms are regularly changing and being redefined with the passing of time. With constant breakthroughs and the development of new technology and other resources, we seek to define what these things are and how they will impact our future.

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In a previous essay, I suggested how we might do better with the unintended consequences of superintelligence if, instead of attempting to pre-formulate satisfactory goals or providing a capacity to learn some set of goals, we gave it the intuition that knowing all goals is not a practical possibility. Instead, we can act with a modest confidence having worked to discover goals, developing an understanding of our discovery processes that allows asserting an equilibrium between the risk of doing something wrong and the cost of work to uncover more stakeholders and their goals. This approach promotes moderation given the potential of undiscovered goals potentially contradicting any particular action. In short, we’d like a superintelligence that applies the non-parametric intuition, the intuition that we can’t know all the factors but can partially discover them with well-motivated trade-offs.

However, I’ve come to the perspective that the non-parametric intuition, while correct, on its own can be cripplingly misguided. Unfortunately, going through a discovery-rich design process doesn’t promise an appropriate outcome. It is possible for all of the apparently relevant sources not to reflect significant consequences.

How could one possibly do better than accepting this limitation, that relevant information is sometimes not present in all apparently relevant information sources? The answer is that, while in some cases it is impossible, there is always the background knowledge that all flourishing is grounded in material conditions, and that “staying grounded” in these conditions is one way to know that important design information is missing and seek it out. The Onion article “Man’s Garbage To Have Much More Significant Effect On Planet Than He Will” is one example of a common failure at living in a grounded way.

In other words, “staying grounded” means recognizing that just because we do not know all of the goals informing our actions does not mean that we do not know any of them. There are some goals that are given to us by the nature of how we are embedded in the world and cannot be responsibly ignored. Our continual flourishing as sentient creatures means coming to know and care for those systems that sustain us and creatures like us. A functioning participation in these systems at a basic level means we should aim to see that our inputs are securely supplied, our wastes properly processed, and the supporting conditions of our environment maintained.

Continue reading “Limits to the Nonparametric Intuition: Superintelligence and Ecology” »

I will admit that I have been distracted from both popular discussion and the academic work on the risks of emergent superintelligence. However, in the spirit of an essay, let me offer some uninformed thoughts on a question involving such superintelligence based on my experience thinking about a different area. Hopefully, despite my ignorance, this experience will offer something new or at least explain one approach in a new way.

The question about superintelligence I wish to address is the “paperclip universe” problem. Suppose that an industrial program, aimed with the goal of maximizing the number of paperclips, is otherwise equipped with a general intelligence program as to tackle with this objective in the most creative ways, as well as internet connectivity and text information processing facilities so that it can discover other mechanisms. There is then the possibility that the program does not take its current resources as appropriate constraints, but becomes interested in manipulating people and directing devices to cause paperclips to be manufactured without consequence for any other objective, leading in the worse case to widespread destruction but a large number of surviving paperclips.

This would clearly be a disaster. The common response is to take as a consequence that when we specify goals to programs, we should be much more careful about specifying what those goals are. However, we might find it difficult to formulate a set of goals that don’t admit some kind of loophole or paradox that, if pursued with mechanical single-mindedness, are either similarly narrowly destructive or self-defeating.

Suppose that, instead of trying to formulate a set of foolproof goals, we should find a way to admit to the program that the set of goals we’ve described is not comprehensive. We should aim for the capacity to add new goals with a procedural understanding that the list may never be complete. If done well, we would have a system that would couple this initial set of goals to the set of resources, operations, consequences, and stakeholders initially provided to it, with an understanding that those goals are only appropriate to the initial list and finding new potential means requires developing a richer understanding of potential ends.

Continue reading “The Nonparametric Intuition: Superintelligence and Design Methodology” »

“An exclusive inside look at how artificial intelligence and machine learning work at Apple”

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