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How Artificial Intelligence Is Totally Changing Everything

Moreover, he believed, it was possible to create software for a digital computer that enabled it to observe its environment and to learn new things, from playing chess to understanding and speaking a human language.

Artificial intelligence, commonly referred to as AI, gives machines the ability to learn from experience and perform cognitive tasks, the sort of stuff that once only the human brain seemed capable of doing.

On an everyday level, AI figures out what ads to show you on the web, and powers those friendly chatbots that pop up when you visit an e-commerce website to answer your questions and provide customer service.

And AI-powered personal assistants in voice-activated smart home devices perform myriad tasks, from controlling our TVs and doorbells to answering trivia questions and helping us find our favorite songs.

As AI technology grows more sophisticated and capable, it's expected to massively boost the world's economy, creating about $13 trillion worth of additional activity by 2030, according to a McKinsey Global Institute forecast.

AI is "basically the results of our attempting to understand and emulate the way that the brain works and the application of this to giving brain-like functions to otherwise autonomous systems (e.g., drones, robots and agents),"

And while humans don't really think like computers, which utilize circuits, semi-conductors and magnetic media instead of biological cells to store information, there are some intriguing parallels.

"One thing we're beginning to discover is that graph networks are really interesting when you start talking about billions of nodes, and the brain is essentially a graph network, albeit one where you can control the strengths of processes by varying the resistance of neurons before a capacitive spark fires,"

"A single neuron by itself gives you a very limited amount of information, but fire enough neurons of varying strengths together, and you end up with a pattern that gets fired only in response to certain kinds of stimuli, typically modulated electrical signals through the DSPs [that is digital signal processing] that we call our retina and cochlea."

AI works by combining large amounts of data with intelligent algorithms — series of instructions — that allow the software to learn from patterns and features of the data, as this SAS primer on artificial intelligence explains.

AI is different from, but related to, robotics, in which machines sense their environment, perform calculations and do physical tasks either by themselves or under the direction of people, from factory work and cooking to landing on other planets.

If you expand AI to cover machine learning, this would also include spell checkers, text-recommendation systems, really any recommendation system, washers and dryers, microwaves, dishwashers, really most home electronics produced after 2017, speakers, televisions, anti-lock braking systems, any electric vehicle, modern CCTV cameras.

AI, for example, is capable of processing millions of social media network interactions and gaining insights that can influence users' behavior — an ability that the AI expert worries may have "not so good consequences."

But AI hasn't made as much progress so far in replicating human creativity, Honavar notes, though the technology already is being utilized to compose music and write news articles based on data from financial reports and election returns.

Inventor and futurist Ray Kurzweil has predicted that by the 2030s, AI have achieved human levels of intelligence, and that it will be possible to have AI that goes inside the human brain to boost memory, turning users into human-machine hybrids.

How Artificial Intelligence Is Helping Identify Thousands of Unknown Civil War Soldiers

Samuel Holmes Doten of Plymouth, Mass., was born June 5, 1812, so after the Civil War ended in 1865, he would joke that he “served in the infantry in the war of that date.”

but in the course of the last year, he identified them using Civil War Photo Sleuth, a website that uses facial recognition technology, a form of artificial intelligence (A.I.), to identify the men in such photos.

And in 2020 the site is planning to add a new feature, after a successful test: a way for users to get second opinions on potential photo matches.

While the Civil War started 158 years ago, the market for Civil War photography collections is relatively new, according to Ron Coddington, one of the site’s collaborators and the publisher and editor of Military Images magazine.

But by the time the centennial of the beginning of the Civil War arrived in 1961, bringing a new wave of interest in the conflict among history buffs, albums from that period were increasingly held by collectors rather than private families.

Though books about Civil War photographs, with basic biographical information, started coming out in the ’80s, many collectors had no easy way of learning the names of the people in the pictures they owned.

Get your history fix in one place: sign up for the weekly TIME History newsletter The founder of Civil War Photo Sleuth, Kurt Luther, a professor of History and Computer Science at Virginia Tech, got interested in Civil War photography in 2013 after he stumbled across a photo album containing an image of his great-great-great uncle, who served in Company E of the 134th Pennsylvania, in an exhibit on Pennsylvania’s role in the Civil War at the Senator John Heinz History Center in Pittsburgh.

selfies, the facial recognition technology for Civil War Photo Sleuth uses a set of 27 facial landmarks, such as the corners of the mouth or the tip of the nose, to analyze a given photo.

(Sometimes discoloration or holes in such old images can obscure these facial landmarks and prevent identifications.) The site then pulls up previously uploaded images that match the new one, with the hope that one of the matches will help identify the man in the picture.

The system isn’t perfect: Identifications suggested by the site might be simply the best guesses of another uploader, and it’s unclear if every user has done follow-up research to confirm the identifications.

Artificial Intelligence, Foresight, and the Offense-Defense Balance

Senior defense officials have commented that the United States is at “an inflection point in the power of artificial intelligence” and even that AI might be the first technology to change “the fundamental nature of war.” However, there is still little clarity regarding just how artificial intelligence will transform the security landscape.

One of the most important open questions is whether applications of AI, such as drone swarms and software vulnerability discovery tools, will tend to be more useful for conducting offensive or defensive military operations.

It could help us to foresee new threats to stability before they arise and act to mitigate them, for instance by pursuing specific arms agreements or prioritizing the development of applications with potential stabilizing effects.

In the lead-up to the First World War, for instance, most analysts failed to recognize that the introduction of machine guns and barbed wire had tilted the offense-defense balance far toward defense.

In particular, as we argue in a recent paper, changes that essentially scale up existing capabilities are likely to be much easier to analyze than changes that introduce fundamentally new capabilities.

In contrast, the subsequent naval arms race — which saw England and Germany competing to manufacture ever larger numbers of dreadnoughts — represented a quantitative change.

One particular reason why foresight about such changes is difficult is that the introduction of a new form of force — from the tank to the torpedo to the phishing attack — will often warrant the introduction of substantially new tactics.

If the sizes of two armies double in the lead-up to an invasion, for example, then it is not safe to assume that the effect will simply cancel out and leave the balance of forces the same as it was prior to the doubling.

Rather, research on combat dynamics suggests that increasing the total number of soldiers will tend to benefit the attacker when force levels are sufficiently low and benefit the defender when force levels are sufficiently high.

A large swarm of individually expendable drones may be able to overwhelm the defenses of individual weapon platforms, such as aircraft carriers, by attacking from more directions or in more waves than the platform’s defenses are capable of managing.

The phenomenon of offensive-then-defensive scaling suggests that growing swarm sizes could initially benefit attackers — who can focus their attention increasingly intensely on less well-defended targets and parts of targets — before potentially allowing defensive swarms to win out if sufficient growth in numbers occurs.

The computer security expert Bruce Schneier has suggested that continued progress will ultimately make it feasible to discover and patch every single vulnerability in a given piece of software, shifting the cyber offense-defense balance significantly toward defense.

Our contribution here is to point out one particularly precise way in which AI could impact the offense-defense balance, through quantitative increases of capabilities in domains that exhibit offensive-then-defensive scaling.

In foreseeing and understanding these potential impacts, policymakers could be better prepared to mitigate the most dangerous consequences, through prioritizing the development of applications that favor defense, investigating countermeasures, or constructing stabilizing norms and institutions.

Finland offers crash course in artificial intelligence to EU

HELSINKI (AP) — Finland is offering a techy Christmas gift to all European Union citizens — a free-of-charge online course in artificial intelligence in their own language, officials said Tuesday.

Teemu Roos, a University of Helsinki associate professor in the department of computer science, described the nearly $2 million project as “a civics course in AI” to help EU citizens cope with society’s ever-increasing digitalization and the possibilities AI offers in the jobs market.

Since its launch in Finland in 2018 “The Elements of AI” has been phenomenally successful — the most popular course ever offered by the University of Helsinki, which traces its roots back to 1640 — with more than 220,000 students from over 110 countries having taken it so far online, Roos said.

Megan Schaible, COO of Reaktor Education, said during the project’s presentation in Brussels last week that the company decided to join forces with the Finnish university “to prove that AI should not be left in the hands of a few elite coders.” An official University of Helsinki diploma will be provided to those passing and Roos said many EU universities would likely give credits for taking the course, allowing students to include it in their curriculum.