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Forecast Election Results With Presidential Plinko

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You see The New York Times’ “election needle,” and you get anxiety. You read FiveThirtyEight, and you wonder how your candidate can lose after being up by some seemingly impressive number of “points” or polls prior to an election.

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Welcome to the wide world of uncertainty, which many people—including myself—tend to discount when glancing at statistics, probability, and flat-out guesses. A prediction based on polling can be true and not true at the same time; yes, your candidate can be ahead in a poll, theoretically, but still end up losing because the poll didn’t quite accurately capture the will of the people that it intended to represent. And that little thing called the “margin of error” is important, too, even though we often pretend it doesn’t exist.

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To help us better understand this, Matthew Kay, an assistant professor of computer science at Northwestern University, devised a rather clever way to show how uncertainty can affect polling data.

He’s using that classic The Price is Right game, Plinko, to represent how forecasting can still produce results that swing one way or the other. It all depends on how the chip—or virtual Plinko ball—falls. As Kay describes:

“The short version is, I approximate each forecaster’s predictive distribution with a scaled-and-shifted binomial distribution, which ultimately determines the height of each board. I then determine plausible paths through the board that could have lead to the final predictive distribution, which is shown as a quantile dotplot. Thus, while the output looks random, the final distribution is exactly the forecaster’s published distribution, down to the resolution of the dotplot. Full details of the methodology and source code are in the Github repository.”

That’s all well and good, but I find myself dropping ball after ball after ball in Kay’s Plinko game—which you can do for yourself, too, at his site. You get the option to drop a single ball or just let ‘em all fall.

I think the former is the route you’ll want to go, if you make the generalization that your single, virtual ball represents the election and however it lands is the outcome we’ll all get. Spoiler: Your candidate might not win, but that’s the entire point of this exercise. Probability is a science, not a time machine. Remember 2016?

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As for the aforementioned ‘Needle’ that many of us are familiar with from The New York Times, it’s a useful tool to gauge sentiment over the election when people understand what it’s doing. Kay argues that the use of a needle, however, allowed people to more easily misinterpret the Times noble approach.

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“I think the Needle got one thing right and another thing wrong. What it got right was that this kind of animation can help people experience uncertainty. 
This makes the visualization more powerful, and the uncertainty harder to ignore. The visualization made people anxious, because they were uncertain about something they cared about. But if you’re uncertain about something you care about, you should be anxious,” he writes.

“However, I think the Needle also fell victim to a deterministic construal error: 
many people more readily associate the mechanism of a needle with some deterministic measurement, not an uncertain quantity. Those people understandably thought the rapid movement of the needle reflected that the forecast itself was changing just as rapidly.”

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Now, when can we get our election predictions modeled by Hole in One (or Two)? That’s what I want to know.

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New AI-powered sensor measures starlight distortion to help discover new planets

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Sydney University scientists have invented a sensor that neutralizes a star’s twinkle, which could help astronomers find new planets in distant solar systems.

The sensor uses an advanced light convertor and AI to measure and correct the distortion of starlight caused by the Earth’s atmosphere. It will now be installed on the 8.2m Subaru telescope on the summit of Maunakea, Hawaii, one of the largest optical-infrared telescopes in the world.

“The main way we identify planets orbiting distant stars is by measuring regular dips in starlight caused by planets blocking out bits of their sun,” said study lead author Dr Barnaby Norris in a statement.

“This is really difficult from the ground, so we needed to develop a new way of looking up at the stars. We also wanted to find a way to directly observe these planets from Earth.”

[Read: What audience intelligence data tells us about the 2020 US presidential election]

The “photonic wavefront sensor” will help astronomers directly image exoplanets around distant stars from Earth.

“Unlike conventional wavefront sensors, it can be placed at the same location in the optical instrument where the image is formed,” explained Dr Norris. “This means it is sensitive to types of distortions invisible to other wavefront sensors currently used today in large observatories.”

You can read the full research study in Nature Communications.

Published October 21, 2020 — 17:32 UTC

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Kite adds support for 11 new languages to its AI code completion tool

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When Kite, the well-funded AI-driven code completion tool, launched in 2019, its technology looked very impressive, but it only supported Python at the time. Earlier this year, it also added JavaScript and today, it is launching support for 11 new languages at once.

The new languages are Java, Kotlin, Scala, C/C++, Objective C, C#, Go, Typescript, HTML/CSS and Less. Kite works in most popular development environments, including the likes of VS Code, JupyterLab, Vim, Sublime and Atom, as well as all Jetbrains IntelliJ-based IDEs, including Android Studio.

This will make Kite a far more attractive solution for a lot of developers. Currently, the company says, it saves its most active developers from writing about 175 “words” of code every day. One thing that always made Kite stand out is that it ranks its suggestions by relevance — not alphabetically as some of its non-AI driven competitors do. To build its models, Kite fed its algorithms code from GitHub .

The service is available as a free download for Windows users and as a server-powered paid enterprise version with a larger deep learning model that consequently offers more AI smarts, as well as the ability to create custom models. The paid version also includes support for multi-line code completion, while the free version only supports line-of-code completions.

Kite notes that in addition to adding new languages, Kite also spent the last year focusing on the user experience, which should now be less distracting and, of course, offer more relevant completions.

Image Credits: Kite

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Who is Google’s market power hurting?

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Yesterday, the Department of Justice and 11 states sued Google for violating antitrust law. The complaint argued that Google had become “the unchallenged gateway to the internet for billions of users worldwide,” but that its success depends on unfair and monopolistic behavior. In some ways, the case is an obvious and long-awaited move. But it’s also an early test of how American antitrust law will handle the coming decade’s tech giants.

Since the late 1970s, antitrust cases have typically focused on demonstrating consumer harm, like a company cornering the market on oil and jacking up gas prices with its power. This can be less straightforward with free services like Google search, but it’s hardly impossible. The landmark Microsoft antitrust case — which this complaint is modeled on — started when it released the free but widely disliked Internet Explorer browser while stifling the innovative paid competitor Netscape Navigator and limiting the overall market.

Google has countered by saying that 2020 is a different era. “This isn’t the dial-up 1990s, when changing services was slow and difficult, and often required you to buy and install software with a CD-ROM,” it said in a blog post. “Today, you can easily download your choice of apps or change your default settings in a matter of seconds—faster than you can walk to another aisle in the grocery store.”

The Justice Department lays out a multipronged argument for why this isn’t right. It argues that Google has tipped the scales across web browsers, mobile devices, and emerging products like smart devices, ensuring that “all search access points funnel users in one direction: toward Google.” It pays for placement as Safari’s default iOS search engine — possibly providing a hefty chunk of Apple’s profits — and requires Android phone makers to preinstall search widgets on their phones. Meanwhile, its Chrome browser has around 60 percent of the US browser share, giving Google yet another venue for promoting search. “By using distribution agreements to lock up scale for itself and deny it to others, Google unlawfully maintains its monopolies,” the complaint says.

The filing touches on how this might affect consumers. It notes that some search companies, like privacy-focused startup DuckDuckGo or the subscription-based Neeva, could appeal to consumers who distrust Google’s targeted advertising or data collection policies. “Google’s control of search access points means that these new search models are denied the tools to become true rivals.”

Google disagreed by saying that people proactively choose its product, even when it’s not the first option. In 2014, for example, Mozilla started offering Yahoo as its default search engine. “Most Americans promptly switched their search engine to their first choice —Google,” says Google. Mozilla ultimately terminated the deal early, citing “what’s best for our brand, our effort to provide quality web search, and the broader content experience for our users” as its reasons.

Some of the company’s critics have put forward counterexamples, making a case that Google’s search decisions aren’t actually good for users. In 2015, Yelp and legal scholar Tim Wu released a study arguing that Google’s reviews carousel offers inferior results from its own products rather than more relevant ones from third-party sites. When given a plug-in with alternative results, Google users would click more often on the non-Google offerings.

Yelp and TripAdvisor later launched a site called Focus On The User, which calls on Google to use an “organic, merit-based process” instead of favoring its own products. If this truly provided a better experience and Google faced more pressure to compete, the company would have a greater incentive to take that step. Accordingly, Yelp praised yesterday’s decision, with public policy head Luther Lowe calling it “a critical first step in confronting Google’s anticompetitive abuses and monopoly power in search.”

But there’s a bigger factor in play: lots of people want to overturn this consumer-centric standard, focusing on a much broader definition of harm. And that idea got a big boost earlier this month, when Congress released its sweeping report on monopolistic practices online. The Democratic majority called for establishing a legal standard “designed to protect not just consumers, but also workers, entrepreneurs, independent businesses, open markets, a fair economy, and democratic ideals.”

Critics of Google have offered reasons it fits that bill. “While Google’s anti-competitive practices hurt companies like us, the negative impact on society and democracy wrought by their surveillance business model is far worse,” said DuckDuckGo’s founder and CEO Gabriel Weinberg after the announcement. “The endless data collection and behavioral targeting originated by Google and forced onto the world through its search engine monopoly has led to discrimination, polarization, and the widespread false belief that getting privacy online is difficult.”

But the Justice Department is waiting for Congress to pass new laws that would let it focus on that case. According to some reports, the Department of Justice also rushed the case to announce it before the election. So it’s working with existing laws, at least for now.

Even so, Charlotte Slaiman of Public Knowledge, which praised the Justice Department’s complaint, says the processes can roll out in tandem. “I don’t think the case requires any changes to antitrust law in order to be successful. But I do think that Congress and an antitrust case can be working in parallel at the same time,” Slaiman says. As the Justice Department brings its case against Google, Congress can take a broader view of the industry — and potentially change the course of antitrust cases to come.

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