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Bill Fulkerson

Anatomy of an AI System - 1 views

shared by Bill Fulkerson on 14 Sep 18 - No Cached
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    "With each interaction, Alexa is training to hear better, to interpret more precisely, to trigger actions that map to the user's commands more accurately, and to build a more complete model of their preferences, habits and desires. What is required to make this possible? Put simply: each small moment of convenience - be it answering a question, turning on a light, or playing a song - requires a vast planetary network, fueled by the extraction of non-renewable materials, labor, and data. The scale of resources required is many magnitudes greater than the energy and labor it would take a human to operate a household appliance or flick a switch. A full accounting for these costs is almost impossible, but it is increasingly important that we grasp the scale and scope if we are to understand and govern the technical infrastructures that thread through our lives. III The Salar, the world's largest flat surface, is located in southwest Bolivia at an altitude of 3,656 meters above sea level. It is a high plateau, covered by a few meters of salt crust which are exceptionally rich in lithium, containing 50% to 70% of the world's lithium reserves. 4 The Salar, alongside the neighboring Atacama regions in Chile and Argentina, are major sites for lithium extraction. This soft, silvery metal is currently used to power mobile connected devices, as a crucial material used for the production of lithium-Ion batteries. It is known as 'grey gold.' Smartphone batteries, for example, usually have less than eight grams of this material. 5 Each Tesla car needs approximately seven kilograms of lithium for its battery pack. 6 All these batteries have a limited lifespan, and once consumed they are thrown away as waste. Amazon reminds users that they cannot open up and repair their Echo, because this will void the warranty. The Amazon Echo is wall-powered, and also has a mobile battery base. This also has a limited lifespan and then must be thrown away as waste. According to the Ay
Bill Fulkerson

The Archdruid Report: When The Shouting Stops - 0 views

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    "That said, there's another factor driving the reaction of Clinton's supporters, and the best way I can find to approach it is to consider one of the more thoughtful responses from that side of the political landscape, an incisive essay posted to Livejournal last week by someone who goes by the nom de Web "Ferrett Steinmetz." The essay's titled The Cold, Cold Math We'll Need to Survive the Next Twenty Years, and it comes so close to understanding what happened last Tuesday that the remaining gap offers an unsparing glimpse straight to the heart of the failure of the Left to make its case to the rest of the American people. At the heart of the essay are two indisputable points. The first is that the core constituencies of the Democratic Party are not large enough by themselves to decide who gets to be president. That's just as true of the Republican party, by the way, and with few exceptions it's true in every democratic society.  Each party large enough to matter has a set of core constituencies who can be counted on to vote for it under most circumstances, and then has to figure out how to appeal to enough people outside its own base to win elections. That's something that both parties in the US tend to forget from time to time, and when they do so, they lose. The second indisputable point is that if Democrats want to win an election in today's America, they have to find ways to reach out to people who don't share the values and interests of the Left. It's the way that Ferrett Steinmetz frames that second point, though, that shows why the Democratic Party failed to accomplish that necessary task this time. "We have to reach out to people who hate us," Steinmetz says, and admits that he has no idea at all how to do that. "
Bill Fulkerson

Globalization and the End of the Labor Aristocracy, Part 1 | naked capitalism - 0 views

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    "Twenty-first century imperialism has changed its form. In the 19th century and the first half of the 20th century, it was explicitly related to colonial control; in the second half of the 20th century it relied on a combination of geopolitical and economic control deriving also from the clear dominance of the United States as the global hegemon and leader of the capitalist world dealing with the potential threat from the Communist world. It now relies more and more on an international legal and regulatory architecture-fortified by various multilateral and bilateral agreements-to establish the power of capital over labor. This has involved a "grand bargain," no less potent for being implicit, between different segments of capital. Capitalist firms in the developing world gained some market access (typically intermediated by multinational capital) and, in return, large capital in highly developed countries got much greater protection and monopoly power, through tighter enforcement of intellectual property rights and greater investment protections."
Steve Bosserman

20 top lawyers were beaten by legal AI. Here are their surprising responses - 0 views

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    "The study, carried out with leading legal academics and experts, saw the LawGeex AI achieve an average 94% accuracy rate, higher than the lawyers who achieved an average rate of 85%. It took the lawyers an average of 92 minutes to complete the NDA issue spotting, compared to 26 seconds for the LawGeex AI. The longest time taken by a lawyer to complete the test was 156 minutes, and the shortest time was 51 minutes. The study made waves around the world and was covered across global media."
Bill Fulkerson

How Complex Web Systems Fail - Part 2 - Production Ready - Medium - 0 views

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    "In his influential paper How Complex Systems Fail, Richard Cook shares 18 brilliant observations on the nature of failure in complex systems. Part 1 of this article was my attempt to translate the first nine of his observations into the context of web systems, i.e., the distributed systems behind modern web applications. In this second and final part, I'm going to complete the picture and cover the other half of Cook's paper. So let's get started with observation #10!"
Bill Fulkerson

What You Should Know About Megaprojects and Why: An Overview by Bent Flyvbjerg :: SSRN - 0 views

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    "his paper takes stock of megaproject management, an emerging and hugely costly field of study. First, it answers the question of how large megaprojects are by measuring them in the units mega, giga, and tera, concluding we are presently entering a new "tera era" of trillion-dollar projects. Second, total global megaproject spending is assessed, at USD 6-9 trillion annually, or 8 percent of total global GDP, which denotes the biggest investment boom in human history. Third, four "sublimes" - political, technological, economic, and aesthetic - are identified to explain the increased size and frequency of megaprojects. Fourth, the "iron law of megaprojects" is laid out and documented: Over budget, over time, over and over again. Moreover, the "break-fix model" of megaproject management is introduced as an explanation of the iron law. Fifth, Albert O. Hirschman's theory of the Hiding Hand is revisited and critiqued as unfounded and corrupting for megaproject thinking in both the academy and policy. Sixth, it is shown how megaprojects are systematically subject to "survival of the unfittest," explaining why the worst projects get built instead of the best. Finally, it is argued that the conventional way of managing megaprojects has reached a "tension point," where tradition is challenged and reform is emerging. "
Steve Bosserman

Which Industries Are Investing in Artificial Intelligence? - 0 views

  • The term artificial intelligence typically refers to automation of tasks by software that previously required human levels of intelligence to perform. While machine learning is sometimes used interchangeably with AI, machine learning is just one sub-category of artificial intelligence whereby a device learns from its access to a stream of data.When we talk about AI spending, we’re typically talking about investment that companies are making in building AI capabilities. While this may change in the future, McKinsey estimates that the vast majority of spending is done internally or as an investment, and very little of it is done purchasing artificial intelligence applications from other businesses.
  • 62% of AI spending in 2016 was for machine learning, twice as much as the second largest category computer vision. It’s worth noting that these categories are all types of “narrow” (or “weak”) forms of AI that use data to learn about and accomplish a specific narrowly defined task. Excluded from this report is “general” (or “strong”) artificial intelligence which is more akin to trying to create a thinking human brain.
  • The McKinsey survey mostly fits well as evidence supporting Cross’s framework that large profitable industries are the most fertile grounds of AI adoption. Not surprisingly, Technology is the industry with highest AI adoption and financial services also makes the top three as Cross would predict.Notably, automotive and assembly is the industry with the second highest rate of AI adoption in the McKinsey survey. This may be somewhat surprising as automotive isn’t necessarily an industry with the reputation for high margins. However, the use cases of AI for developing self-driving cars and cost savings using machine learning to improve manufacturing and procurement efficiencies are two potential drivers of this industry’s adoption.
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  • AI jobs are much more likely to be unfilled after 60 days compared to the typical job on Indeed, which is only unfilled a quarter of the time. As the demand for AI talent continues to grow faster than the supply, there is no indication this hiring cycle will become quicker anytime soon.
  • One thing we know for certain is that it is very expensive to attract AI talent, given that starting salaries for entry-level talent exceed $300,000. A good bet is that the companies that invest in AI are the ones with healthy enough profit margins that they can afford it.
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