Google – Page 8

Welcome to Google’s nightmare: US reveals plan to destroy search monopoly

android, Antitrust law, duckduckgo, Google, google ai overviews, google chrome, google search, google search monopoly, Policy, us department of justice / Beth Washington / November 21, 2024

Hepner expects that the DOJ plan may be measured enough that the court may only “be interested in a nip-tuck, not a wholesale revision of what plaintiffs have put forward.”

Kamyl Bazbaz, SVP of public affairs for Google’s more privacy-focused rival DuckDuckGo, released a statement agreeing with Hepner.

“The government has put forward a proposal that would free the search market from Google’s illegal grip and unleash a new era of innovation, investment, and competition,” Bazbaz said. “There’s nothing radical about this proposal: It’s firmly based on the court’s extensive finding of fact and proposes solutions in line with previous antitrust actions.”

Bazbaz accused Google of “cynically” invoking privacy among chief concerns with a forced Chrome sale. That “is rich coming from the Internet’s biggest tracker,” Bazbaz said.

Will Apple finally compete with Google in search?

The remedies the DOJ has proposed could potentially be game-changing, Bazbaz told Ars, not just for existing rivals but also new rivals and startups the court found were previously unable to enter the market while it was under Google’s control.

If the DOJ gets its way, Google could be stuck complying with these proposed remedies for 10 years. But if the company can prove after five years that competition has substantially increased and it controls less than 50 percent of the market, the remedies could be terminated early, the DOJ’s proposed final judgment order said.

That’s likely cold comfort for Google as it prepares to fight the DOJ’s plan to break up its search empire and potentially face major new competitors. The biggest risk to Google’s dominance in AI search could even be its former partner, whom the court found was being paid handsomely to help prop up Google’s search monopoly: Apple.

On X (formerly Twitter), Hepner said that cutting off Google’s $20 billion payments to Apple for default placements in Safari alone could “have a huge effect and may finally kick Apple to enter the market itself.”

Welcome to Google’s nightmare: US reveals plan to destroy search monopoly Read More »

Android will soon instantly log you in to your apps on new devices

android, app restore, Google, phone backup, Tech / Kelly Newman / November 21, 2024

If you lose your iPhone or buy an upgrade, you could reasonably expect to be up and running after an hour, presuming you backed up your prior model. Your Apple stuff all comes over, sure, but most of your third-party apps will still be signed in.

Doing the same swap with an Android device is more akin to starting three-quarters fresh. After one or two Android phones, you learn to bake in an extra hour of rapid-fire logging in to all your apps. Password managers, or just using a Google account as your authentication, are a godsend.

That might change relatively soon, as Google has announced a new Restore Credentials feature, which should do what it says in the name. Android apps can “seamlessly onboard users to their accounts on a new device,” with the restore keys handled by Android’s native backup and restore process. The experience, says Google, is “delightful” and seamless. You can even get the same notifications on the new device as you were receiving on the old.

Android will soon instantly log you in to your apps on new devices Read More »

Google stops letting sites like Forbes rule search for “Best CBD Gummies“

affiliate, affiliate marketing, Biz & IT, forbes, forbes marketplace, Google, guest posts, parasite seo, SEO, site reputation, Tech / Beth Washington / November 20, 2024

Under the strength of Forbes’ long-existing and well-linked site, Forbes Marketplace/Advisor has dominated the search term “best cbd gummies” for “an eternity,” according to SEO analyst Lily Ray. Forbes has similarly dominated “best pet insurance,” and long came up as the second result for “how to get rid of roaches,” as detailed in a blog post by Lars Lofgren. If people click on this high-ranking result, and then click on a link to buy a product or request a roach removal consultation, Forbes typically gets a cut.

Forbes Marketplace had seemingly also provided SEO-minded review services to CNN and USA Today, as detailed by Lofgren. Lofgren’s term for this business, “Parasite SEO,” took hold in corners critical of the trend. Ars has contacted Forbes for comment and will update this post with response.

“The unfair, exploitative nature” of “parasite SEO”

Google writes that it had reviewed “situations where there might be varying degrees of first-party involvement” (most publishers’ review sites indicate some kind of oversight or editorial standards linked to the primary site). But however arranged, “no amount of first-party involvement alters the fundamental third-party nature of the content or the unfair, exploitative nature of attempting to take advantage of the host sites’ ranking signals.”

As such, using third-party content in such a way as to take advantage of a high search quality ranking, outside the site’s primary focus, is considered spam. That delivers a major hit to a site’s Google ranking, and the impact is already being felt.

The SEO reordering does not affect more established kinds of third-party content, like wire service reports, syndication, or well-marked sponsored content, as detailed in Google’s spam policy section about site reputation abuse. As seen on the SEO subreddit, and on social media, Google has given sites running afoul of its updated policy a “Manual Action” rather than relying only on its algorithm to catch the often opaque arrangements.

Google stops letting sites like Forbes rule search for “Best CBD Gummies“ Read More »

ChatGPT’s success could have come sooner, says former Google AI researcher

AI, AI technology, Attention is all you need, biotechnology, Biz & IT, chatgpt, chatgtp, Google, GPT-3, GPT-4, Inceptive, Jakob Uszkoreit, large language models, openai, RNA, RNA vaccines, Transformers / Beth Washington / November 14, 2024

A co-author of Attention Is All You Need reflects on ChatGPT’s surprise and Google’s conservatism.

Jakob Uszkoreit Credit: Jakob Uszkoreit / Getty Images

In 2017, eight machine-learning researchers at Google released a groundbreaking research paper called Attention Is All You Need, which introduced the Transformer AI architecture that underpins almost all of today’s high-profile generative AI models.

The Transformer has made a key component of the modern AI boom possible by translating (or transforming, if you will) input chunks of data called “tokens” into another desired form of output using a neural network. Variations of the Transformer architecture power language models like GPT-4o (and ChatGPT), audio synthesis models that run Google’s NotebookLM and OpenAI’s Advanced Voice Mode, video synthesis models like Sora, and image synthesis models like Midjourney.

At TED AI 2024 in October, one of those eight researchers, Jakob Uszkoreit, spoke with Ars Technica about the development of transformers, Google’s early work on large language models, and his new venture in biological computing.

In the interview, Uszkoreit revealed that while his team at Google had high hopes for the technology’s potential, they didn’t quite anticipate its pivotal role in products like ChatGPT.

The Ars interview: Jakob Uszkoreit

Ars Technica: What was your main contribution to the Attention is All You Need paper?

Jakob Uszkoreit (JU): It’s spelled out in the footnotes, but my main contribution was to propose that it would be possible to replace recurrence [from Recurrent Neural Networks] in the dominant sequence transduction models at the time with the attention mechanism, or more specifically self-attention. And that it could be more efficient and, as a result, also more effective.

Ars: Did you have any idea what would happen after your group published that paper? Did you foresee the industry it would create and the ramifications?

JU: First of all, I think it’s really important to keep in mind that when we did that, we were standing on the shoulders of giants. And it wasn’t just that one paper, really. It was a long series of works by some of us and many others that led to this. And so to look at it as if this one paper then kicked something off or created something—I think that is taking a view that we like as humans from a storytelling perspective, but that might not actually be that accurate of a representation.

My team at Google was pushing on attention models for years before that paper. It’s a lot longer of a slog with much, much more, and that’s just my group. Many others were working on this, too, but we had high hopes that it would push things forward from a technological perspective. Did we think that it would play a role in really enabling, or at least apparently, seemingly, flipping a switch when it comes to facilitating products like ChatGPT? I don’t think so. I mean, to be very clear in terms of LLMs and their capabilities, even around the time we published the paper, we saw phenomena that were pretty staggering.

We didn’t get those out into the world in part because of what really is maybe a notion of conservatism around products at Google at the time. But we also, even with those signs, weren’t that confident that stuff in and of itself would make that compelling of a product. But did we have high hopes? Yeah.

Ars: Since you knew there were large language models at Google, what did you think when ChatGPT broke out into a public success? “Damn, they got it, and we didn’t?”

JU: There was a notion of, well, “that could have happened.” I think it was less of a, “Oh dang, they got it first” or anything of the like. It was more of a “Whoa, that could have happened sooner.” Was I still amazed by just how quickly people got super creative using that stuff? Yes, that was just breathtaking.

Jakob Uskoreit presenting at TED AI 2024. — Jakob Uszkoreit presenting at TED AI 2024. Credit: Benj Edwards

Ars: You weren’t at Google at that point anymore, right?

JU: I wasn’t anymore. And in a certain sense, you could say the fact that Google wouldn’t be the place to do that factored into my departure. I left not because of what I didn’t like at Google as much as I left because of what I felt I absolutely had to do elsewhere, which is to start Inceptive.

But it was really motivated by just an enormous, not only opportunity, but a moral obligation in a sense, to do something that was better done outside in order to design better medicines and have very direct impact on people’s lives.

Ars: The funny thing with ChatGPT is that I was using GPT-3 before that. So when ChatGPT came out, it wasn’t that big of a deal to some people who were familiar with the tech.

JU: Yeah, exactly. If you’ve used those things before, you could see the progression and you could extrapolate. When OpenAI developed the earliest GPTs with Alec Radford and those folks, we would talk about those things despite the fact that we weren’t at the same companies. And I’m sure there was this kind of excitement, how well-received the actual ChatGPT product would be by how many people, how fast. That still, I think, is something that I don’t think anybody really anticipated.

Ars: I didn’t either when I covered it. It felt like, “Oh, this is a chatbot hack of GPT-3 that feeds its context in a loop.” And I didn’t think it was a breakthrough moment at the time, but it was fascinating.

JU: There are different flavors of breakthroughs. It wasn’t a technological breakthrough. It was a breakthrough in the realization that at that level of capability, the technology had such high utility.

That, and the realization that, because you always have to take into account how your users actually use the tool that you create, and you might not anticipate how creative they would be in their ability to make use of it, how broad those use cases are, and so forth.

That is something you can sometimes only learn by putting something out there, which is also why it is so important to remain experiment-happy and to remain failure-happy. Because most of the time, it’s not going to work. But some of the time it’s going to work—and very, very rarely it’s going to work like [ChatGPT did].

Ars: You’ve got to take a risk. And Google didn’t have an appetite for taking risks?

JU: Not at that time. But if you think about it, if you look back, it’s actually really interesting. Google Translate, which I worked on for many years, was actually similar. When we first launched Google Translate, the very first versions, it was a party joke at best. And we took it from that to being something that was a truly useful tool in not that long of a period. Over the course of those years, the stuff that it sometimes output was so embarrassingly bad at times, but Google did it anyway because it was the right thing to try. But that was around 2008, 2009, 2010.

Ars: Do you remember AltaVista’sBabel Fish?

JU: Oh yeah, of course.

Ars: When that came out, it blew my mind. My brother and I would do this thing where we would translate text back and forth between languages for fun because it would garble the text.

JU: It would get worse and worse and worse. Yeah.

Programming biological computers

After his time at Google, Uszkoreit co-founded Inceptive to apply deep learning to biochemistry. The company is developing what he calls “biological software,” where AI compilers translate specified behaviors into RNA sequences that can perform desired functions when introduced to biological systems.

Ars: What are you up to these days?

JU: In 2021 we co-founded Inceptive in order to use deep learning and high throughput biochemistry experimentation to design better medicines that truly can be programmed. We think of this as really just step one in the direction of something that we call biological software.

Biological software is a little bit like computer software in that you have some specification of the behavior that you want, and then you have a compiler that translates that into a piece of computer software that then runs on a computer exhibiting the functions or the functionality that you specify.

You specify a piece of a biological program and you compile that, but not with an engineered compiler, because life hasn’t been engineered like computers have been engineered. But with a learned AI compiler, you translate that or compile that into molecules that when inserted into biological systems, organisms, our cells exhibit those functions that you’ve programmed into.

A pharmacist holds a bottle containing Moderna’s bivalent COVID-19 vaccine. Credit: Getty | Mel Melcon

Ars: Is that anything like how the mRNA COVID vaccines work?

JU: A very, very simple example of that are the mRNA COVID vaccines where the program says, “Make this modified viral antigen” and then our cells make that protein. But you could imagine molecules that exhibit far more complex behaviors. And if you want to get a picture of how complex those behaviors could be, just remember that RNA viruses are just that. They’re just an RNA molecule that when entering an organism exhibits incredibly complex behavior such as distributing itself across an organism, distributing itself across the world, doing certain things only in a subset of your cells for a certain period of time, and so on and so forth.

And so you can imagine that if we managed to even just design molecules with a teeny tiny fraction of such functionality, of course with the goal not of making people sick, but of making them healthy, it would truly transform medicine.

Ars: How do you not accidentally create a monster RNA sequence that just wrecks everything?

JU: The amazing thing is that medicine for the longest time has existed in a certain sense outside of science. It wasn’t truly understood, and we still often don’t truly understand their actual mechanisms of action.

As a result, humanity had to develop all of these safeguards and clinical trials. And even before you enter the clinic, all of these empirical safeguards prevent us from accidentally doing [something dangerous]. Those systems have been in place for as long as modern medicine has existed. And so we’re going to keep using those systems, and of course with all the diligence necessary. We’ll start with very small systems, individual cells in future experimentation, and follow the same established protocols that medicine has had to follow all along in order to ensure that these molecules are safe.

Ars: Thank you for taking the time to do this.

JU: No, thank you.

Benj Edwards is Ars Technica’s Senior AI Reporter and founder of the site’s dedicated AI beat in 2022. He’s also a widely-cited tech historian. In his free time, he writes and records music, collects vintage computers, and enjoys nature. He lives in Raleigh, NC.

ChatGPT’s success could have come sooner, says former Google AI researcher Read More »

$new-secret-math-benchmark-stumps-ai-models-and-phds-alike$

New secret math benchmark stumps AI models and PhDs alike

AI, AI benchmarks, Anthropic, benchmarks, Biz & IT, Claude 3.5, Epoch AI, FrontierMath, Google, GPT-4o, large language models, machine learning, o1-preview, openai, research papers, vibemarks / 9u50fv / November 12, 2024

Epoch AI allowed Fields Medal winners Terence Tao and Timothy Gowers to review portions of the benchmark. “These are extremely challenging,” Tao said in feedback provided to Epoch. “I think that in the near term basically the only way to solve them, short of having a real domain expert in the area, is by a combination of a semi-expert like a graduate student in a related field, maybe paired with some combination of a modern AI and lots of other algebra packages.”

A chart showing AI model success on the FrontierMath problems, taken from Epoch AI's research paper. — A chart showing AI models’ limited success on the FrontierMath problems, taken from Epoch AI’s research paper. Credit: Epoch AI

To aid in the verification of correct answers during testing, the FrontierMath problems must have answers that can be automatically checked through computation, either as exact integers or mathematical objects. The designers made problems “guessproof” by requiring large numerical answers or complex mathematical solutions, with less than a 1 percent chance of correct random guesses.

Mathematician Evan Chen, writing on his blog, explained how he thinks that FrontierMath differs from traditional math competitions like the International Mathematical Olympiad (IMO). Problems in that competition typically require creative insight while avoiding complex implementation and specialized knowledge, he says. But for FrontierMath, “they keep the first requirement, but outright invert the second and third requirement,” Chen wrote.

While IMO problems avoid specialized knowledge and complex calculations, FrontierMath embraces them. “Because an AI system has vastly greater computational power, it’s actually possible to design problems with easily verifiable solutions using the same idea that IOI or Project Euler does—basically, ‘write a proof’ is replaced by ‘implement an algorithm in code,'” Chen explained.

The organization plans regular evaluations of AI models against the benchmark while expanding its problem set. They say they will release additional sample problems in the coming months to help the research community test their systems.

New secret math benchmark stumps AI models and PhDs alike Read More »

Fate of Google’s search empire could rest in Trump’s hands

Antitrust law, Donald Trump, Google, google search monopoly, Policy, us department of justice / Mike M. / November 6, 2024

“Are you going to destroy the company?”

Trump may sway DOJ away from breaking up Google.

A few weeks before the US presidential election, Donald Trump suggested that a breakup of Google’s search business may not be an appropriate remedy to destroy the tech giant’s search monopoly.

“Right now, China is afraid of Google,” Trump said at a Chicago event. If that threat were dismantled, Trump suggested, China could become a greater threat to the US, because the US needs to have “great companies” to compete.

Trump’s comments came about a week after the US Department of Justice proposed remedies in the Google monopoly trial, including mulling a breakup.

“I’m not a fan of Google,” Trump insisted. “They treat me badly. But are you going to destroy the company by doing that? If you do that, are you going to destroy the company? What you can do, without breaking it up, is make sure it’s more fair.”

Now that Trump is presumed to soon be taking office before the remedies phase of the DOJ’s litigation ends next year, it seems possible that Trump may sway the DOJ away from breaking up Google.

Experts told Reuters that a final ruling isn’t expected until August, giving Trump plenty of time to possibly influence the DOJ’s case. But Trump’s stance on Google has seemed to shift throughout his campaign, so there’s no predicting his position once he takes power.

Business Insider noted that Trump was extremely critical of Google on the campaign trail, vowing to “do something” to curtail Google’s power after accusing the search giant of only highlighting negative stories about him in search results. (Google has repeatedly denied the accusation.) On Truth Social as recently as September, Trump vowed to prosecute Google “at the maximum levels,” seemingly less concerned then about how this could influence competition with China.

It would be unusual for Trump to meddle with the DOJ’s ongoing litigation, antitrust expert George Hay told Business Insider, but then again, “Trump is a bit more of a wild card.”

“It’s very rare that, at the presidential level, there’s any attempt to influence the course of cases which have already been filed. Those have a life of their own,” Hay said. “They depend on the judge, the courts, the lawyers who carry on a case. It’s extraordinarily unusual for the administration to become at all active.”

Trump may still feel some ownership over the DOJ’s investigation into Google’s core business since it began in 2019 under his administration, and tensions between Trump and Google have not diminished much since. The Verge noted that Trump warned Google to “be careful” in August because he “had a feeling Google is going to be close to shut down.” And earlier this year, Trump’s running mate, JD Vance, called for Google’s breakup on X (formerly Twitter), proclaiming that a stop to Google’s “monopolistic control of information” was “long overdue.”

Trump’s on-and-off feud with Google

For Trump, disabling Google’s search monopoly might feel personal, as he has spent years accusing Google of manipulating results to disfavor him.

His feud with Google appear to have begun in 2016 when Trump falsely accused Google of manipulating votes, claiming Google wanted to make it appear that he didn’t have a “big victory” over Hillary Clinton, CNN reported.

The feud continued through the 2020 election, Politico reported, with Trump warning Google that his administration was “watching Google very closely” after a former Google employee went on Fox News to claim that Google search results were biased against Trump. Google disputed the employee’s report.

And yet throughout this feud, there have also been times where Trump seems to warm to Google. During his last administration, he backtracked a threat to investigate Google’s alleged work with China’s military, Politico noted, after meeting with Google CEO Sundar Pichai. Most recently, he claimed Pichai reached out to praise Trump’s ability to trend on the search engine during Trump’s McDonald’s campaign stunt, SF Gate reported.

So far, Google is not commenting on Trump’s comments on the DOJ’s proposed breakup of its search business. But Pichai did send an internal memo to Google staff on the night before the election, The Verge reported, praising them for boosting accurate information during the US election and reminding them that “the outcome will be a major topic of conversation in living rooms and other places around the world.”

At a time when Trump might continue heavily criticizing Google from the Oval Office, Pichai told Googlers that maintaining trust in Google is a top priority.

“Whomever the voters entrust, let’s remember the role we play at work, through the products we build and as a business: to be a trusted source of information to people of every background and belief,” Pichai’s memo said. “We will and must maintain that.”

The DOJ may not even want to seek a breakup

When the DOJ finally proposed a framework for remedies last month, they emphasized that there’s still so much more to consider before landing on final remedies and that the DOJ reserves “the right to add or remove potential proposed remedies.”

That means that while the DOJ has said that requiring a divestment of Chrome or Android isn’t completely off the table, they currently aren’t committed to following through on ordering a breakup.

Through the remedies phase of litigation, the DOJ expects that discovery will reveal more about whether requiring a breakup is needed or if other remedies might resolve antitrust concerns while preserving Google’s search empire.

One reason it might be necessary to spin off Chrome or Android, however, would be to “prevent Google from using products such as Chrome, Play, and Android to advantage Google search and Google search-related products and features—including emerging search access points and features, such as artificial intelligence—over rivals or new entrants,” the DOJ said.

Google has warned that a breakup could hurt small businesses that depend on open source code Google develops for Android and Chrome. Costs of Android devices could also rise, Google warned.

Adam Epstein—the president and co-CEO of adMarketplace, which bills itself as “the largest consumer search technology company outside of Google and Bing”—told Ars last September that spinning out Android and Chrome may inflict “maximum pain” on Google. But it could also “cause pain to users and publishers and might not be the best way to create competition in search results and advertising.”

Buried in a story from The New York Times is perhaps the biggest clue that Trump may again be warming to Google as he likely heads back to Washington. The Times noted that at the Chicago event, Trump seemed to be echoing a Google talking point.

Google has argued that “a breakup could hurt America’s interests in a heated geopolitical competition with China over dominance in areas like artificial intelligence,” The Times reported. And Trump appeared to be running with that same logic when seemingly shifting his position on wanting to destroy Google in his final days on the campaign trail.

“It’s a very dangerous thing, because we want to have great companies,” Trump said. “We don’t want China to have these companies.”

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

Fate of Google’s search empire could rest in Trump’s hands Read More »

Google has no duty to refund gift card scam victims, judge finds

gift card scams, Google, google play, online scams, Policy / Beth Washington / November 5, 2024

But Freeman ruled that “May suffered economic harm because of third-party scammers’ fraudulent inducement, not Google’s omission or misrepresentation.”

Additionally, May failed to show that Google had any duty to refund customers after Google cited Target and Walmart policies to show that it’s common to refuse refunds.

Scam victims did not use gift card “as designed”

Freeman mostly sided with Google, deciding that the company engaged in no unfair practices, while noting that May had not used the gift cards “in their designed way.” The judge also agreed with Google that May’s funds were not considered stolen at the time she purchased the gift cards, because May still controlled the funds at that point in time.

Additionally, May’s attempt to argue that Google has the technology to detect scams failed, Freeman wrote, because May couldn’t prove that Google deployed that technology when her particular scam purchases were made. Even after May argued that she reported the theft to Google, Freeman wrote, May’s complaint failed because “there is no allegation that Google had a duty to investigate her report.”

Ultimately, May’s complaint “identifies no public policy suggesting Google has a duty to refund the scammed victims or that the harm of Google’s conduct outweighs any benefits,” Freeman concluded.

In her order, Freeman provided leave to amend some claims in the next 45 days, but Ars could not immediately reach May’s lawyer to confirm if the complaint would likely be amended. However, the judge notably dismissed a claim seeking triple damages because May’s complaint “failed to show a likelihood that May will be a victim of gift card scams again given her awareness of such scams,” which may deflate May’s interests to amend.

That particular part of the ruling may be especially frustrating for May, whose complaint was sparked by a claim that she never would have been victimized if Google had provided adequate warnings of scams.

Google did not immediately respond to Ars’ request to comment.

Google has no duty to refund gift card scam victims, judge finds Read More »

Pixel phones are getting an actual weather app in 2024, with a bit of AI

android, Google, pixel, Tech, Weather, weather app / Shannon Garcia / October 31, 2024

An AI weather report, expanded to read — Credit: Kevin Purdy

Customizable, but also not

There’s a prominent “AI generated weather report” on top of the weather stack, which is a combination of summary and familiarity. “Cold and rainy day, bring your umbrella and hold onto your hat!” is Google’s example; I can’t provide another one, because an update to “Gemini Nano” is pending.

Weather radar map from the Google Weather app. — Credit: Kevin Purdy

You can see weather radar for your location, along with forecasted precipitation movement. The app offers “Nowcasting” precipitation guesses, like “Rain continuing for 2 hours” or “Light rain in 10 minutes.”

Widgets with weather data, including a UV index of 2, sunrise and sunset times, visibility distances, and air quality, displayed as rearrangeable widgets. — Credit: Kevin Purdy

The best feature, one seen on the version of Weather that shipped to the Pixel Tablet and Fold, is that you can rearrange the order of data shown on your weather screen. I moved the UV index, humidity, sunrise/sunset, and wind conditions as high as they could go on my setup. It’s a trade-off, because the Weather app’s data widgets are so big as to require scrolling to get the full picture of a day, and you can’t move the AI summary or 10-day forecast off the top. But if you only need a few numbers and like a verbal summary, it’s handy.

Sadly, if you’re an allergy sufferer and you’re not in the UK, Germany, France, or Italy, Google can’t offer you any pollen data or forecasts. There is also, I am sad to say, no frog.

Google’s Weather app isn’t faring so well with Play Store reviewers. Users are miffed that they can’t see a location’s weather without adding it to their saved locations list; that other Google apps, including the “At a Glance” app on every Pixel’s default launcher, send you to the Google app’s summary instead of this app; the look of the weather map; and, most of all, that it does not show up in some phones’ app list, but only as a widget.

Pixel phones are getting an actual weather app in 2024, with a bit of AI Read More »

Russia fines Google an impossible amount in attempt to end YouTube bans

Google, Policy, russia, youtube / Beth Washington / October 31, 2024

Russia has fined Google an amount that no entity on the planet could pay in hopes of getting YouTube to lift bans on Russian channels, including pro-Kremlin and state-run news outlets.

The BBC wrote that a Russian court fined Google two undecillion rubles, which in dollar terms is $20,000,000,000,000,000,000,000,000,000,000,000. The amount “is far greater than the world’s total GDP, which is estimated by the International Monetary Fund to be $110 trillion.”

The fine is apparently that large because it was issued several years ago and has been repeatedly doubling. An RBC news report this week provided details on the court case from an anonymous source.

The Moscow Times writes, “According to RBC’s sources, Google began accumulating daily penalties of 100,000 rubles in 2020 after the pro-government media outlets Tsargrad and RIA FAN won lawsuits against the company for blocking their YouTube channels. Those daily penalties have doubled each week, leading to the current overall fine of around 2 undecillion rubles.”

The Moscow Times is an independent news organization that moved its operations to Amsterdam in 2022 in response to a Russian news censorship law. The news outlet said that 17 Russian TV channels filed legal claims against Google, including the state-run Channel One, the military-affiliated Zvezda broadcaster, and a company representing RT Editor-in-Chief Margarita Simonyan.

Kremlin rep: “I cannot even say this number”

Since Russia invaded Ukraine in 2022, Google has “blocked more than 1,000 YouTube channels, including state-sponsored news, and over 5.5 million videos,” Reuters wrote.

Russia fines Google an impossible amount in attempt to end YouTube bans Read More »

GitHub Copilot moves beyond OpenAI models to support Claude 3.5, Gemini

AI, Anthropic, Claude 3.5 Sonnet, coding, developer, Gemini 1.5 Pro, GitHub, GitHub Copilot, Google, GPT o1-mini, GPT o1-preview, GPT-4o, microsoft, openai, Programming, Tech, VS Code / Beth Washington / October 29, 2024

The large language model-based coding assistant GitHub Copilot will switch from using exclusively OpenAI’s GPT models to a multi-model approach over the coming weeks, GitHub CEO Thomas Dohmke announced in a post on GitHub’s blog.

First, Anthropic’s Claude 3.5 Sonnet will roll out to Copilot Chat’s web and VS Code interfaces over the next few weeks. Google’s Gemini 1.5 Pro will come a bit later.

Additionally, GitHub will soon add support for a wider range of OpenAI models, including GPT o1-preview and o1-mini, which are intended to be stronger at advanced reasoning than GPT-4, which Copilot has used until now. Developers will be able to switch between the models (even mid-conversation) to tailor the model to fit their needs—and organizations will be able to choose which models will be usable by team members.

The new approach makes sense for users, as certain models are better at certain languages or types of tasks.

“There is no one model to rule every scenario,” wrote Dohmke. “It is clear the next phase of AI code generation will not only be defined by multi-model functionality, but by multi-model choice.”

It starts with the web-based and VS Code Copilot Chat interfaces, but it won’t stop there. “From Copilot Workspace to multi-file editing to code review, security autofix, and the CLI, we will bring multi-model choice across many of GitHub Copilot’s surface areas and functions soon,” Dohmke wrote.

There are a handful of additional changes coming to GitHub Copilot, too, including extensions, the ability to manipulate multiple files at once from a chat with VS Code, and a preview of Xcode support.

GitHub Spark promises natural language app development

In addition to the Copilot changes, GitHub announced Spark, a natural language tool for developing apps. Non-coders will be able to use a series of natural language prompts to create simple apps, while coders will be able to tweak more precisely as they go. In either use case, you’ll be able to take a conversational approach, requesting changes and iterating as you go, and comparing different iterations.

GitHub Copilot moves beyond OpenAI models to support Claude 3.5, Gemini Read More »

Google accused of shadow campaigns redirecting antitrust scrutiny to Microsoft

Antitrust law, cispe, Cloud Computing, cloud services, European Union, Google, microsoft, open cloud coalition, Policy, united kingdom / DJ Henderson / October 28, 2024

On Monday, Microsoft came out guns blazing, posting a blog accusing Google of “dishonestly” funding groups conducting allegedly biased studies to discredit Microsoft and mislead antitrust enforcers and the public.

In the blog, Microsoft lawyer Rima Alaily alleged that an astroturf group called the Open Cloud Coalition will launch this week and will appear to be led by “a handful of European cloud providers.” In actuality, however, those smaller companies were secretly recruited by Google, which allegedly pays them “to serve as the public face” and “obfuscate” Google’s involvement, Microsoft’s blog said. In return, Google likely offered the cloud providers cash or discounts to join, Alaily alleged.

The Open Cloud Coalition is just one part of a “pattern of shadowy campaigns” that Google has funded, both “directly and indirectly,” to muddy the antitrust waters, Alaily alleged. The only other named example that Alaily gives while documenting this supposed pattern is the US-based Coalition for Fair Software Licensing (CFSL), which Alaily said has attacked Microsoft’s cloud computing business in the US, the United Kingdom, and the European Union.

That group is led by Ryan Triplette, who Alaily said is “a well-known lobbyist for Google in Washington, DC, but Google’s affiliation isn’t disclosed publicly by the organization.” An online search confirms Triplette was formerly a lobbyist for Franklin Square Group, which Politico reported represented Google during her time there.

Ars could not immediately reach the CFSL for comment. Google’s spokesperson told Ars that the company has “been a public supporter of CFSL for more than two years” and has “no idea what evidence Microsoft cites that we are the main funder of CFSL.” If Triplette was previously a lobbyist for Google, the spokesperson said, “that’s a weird criticism to make” since it’s likely “everybody in law, policy, etc.,” has “worked for Google, Microsoft, or Amazon at some point, in some capacity.”

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Google, Microsoft, and Perplexity promote scientific racism in AI search results

AI, Google, microsoft, Perplexity, Racism, syndication / Mike M. / October 26, 2024

AI-powered search engines are surfacing deeply racist, debunked research.

Literal Nazis

LOS ANGELES, CA – APRIL 17: Members of the National Socialist Movement (NSM) salute during a rally on near City Hall on April 17, 2010 in Los Angeles, California. Credit: David McNew via Getty

AI-infused search engines from Google, Microsoft, and Perplexity have been surfacing deeply racist and widely debunked research promoting race science and the idea that white people are genetically superior to nonwhite people.

Patrik Hermansson, a researcher with UK-based anti-racism group Hope Not Hate, was in the middle of a monthslong investigation into the resurgent race science movement when he needed to find out more information about a debunked dataset that claims IQ scores can be used to prove the superiority of the white race.

He was investigating the Human Diversity Foundation, a race science company funded by Andrew Conru, the US tech billionaire who founded Adult Friend Finder. The group, founded in 2022, was the successor to the Pioneer Fund, a group founded by US Nazi sympathizers in 1937 with the aim of promoting “race betterment” and “race realism.”

Hermansson logged in to Google and began looking up results for the IQs of different nations. When he typed in “Pakistan IQ,” rather than getting a typical list of links, Hermansson was presented with Google’s AI-powered Overviews tool, which, confusingly to him, was on by default. It gave him a definitive answer of 80.

When he typed in “Sierra Leone IQ,” Google’s AI tool was even more specific: 45.07. The result for “Kenya IQ” was equally exact: 75.2.

Hermansson immediately recognized the numbers being fed back to him. They were being taken directly from the very study he was trying to debunk, published by one of the leaders of the movement that he was working to expose.

The results Google was serving up came from a dataset published by Richard Lynn, a University of Ulster professor who died in 2023 and was president of the Pioneer Fund for two decades.

“His influence was massive. He was the superstar and the guiding light of that movement up until his death. Almost to the very end of his life, he was a core leader of it,” Hermansson says.

A WIRED investigation confirmed Hermanssons’s findings and discovered that other AI-infused search engines—Microsoft’s Copilot and Perplexity—are also referencing Lynn’s work when queried about IQ scores in various countries. While Lynn’s flawed research has long been used by far-right extremists, white supremacists, and proponents of eugenics as evidence that the white race is superior genetically and intellectually from nonwhite races, experts now worry that its promotion through AI could help radicalize others.

“Unquestioning use of these ‘statistics’ is deeply problematic,” Rebecca Sear, director of the Center for Culture and Evolution at Brunel University London, tells WIRED. “Use of these data therefore not only spreads disinformation but also helps the political project of scientific racism—the misuse of science to promote the idea that racial hierarchies and inequalities are natural and inevitable.”

To back up her claim, Sear pointed out that Lynn’s research was cited by the white supremacist who committed the mass shooting in Buffalo, New York, in 2022.

Google’s AI Overviews were launched earlier this year as part of the company’s effort to revamp its all-powerful search tool for an online world being reshaped by artificial intelligence. For some search queries, the tool, which is only available in certain countries right now, gives an AI-generated summary of its findings. The tool pulls the information from the Internet and gives users the answers to queries without needing to click on a link.

The AI Overview answer does not always immediately say where the information is coming from, but after complaints from people about how it showed no articles, Google now puts the title for one of the links to the right of the AI summary. AI Overviews have already run into a number of issues since launching in May, forcing Google to admit it had botched the heavily hyped rollout. AI Overviews is turned on by default for search results and can’t be removed without resorting to installing third-party extensions. (“I haven’t enabled it, but it was enabled,” Hermansson, the researcher, tells WIRED. “I don’t know how that happened.”)

In the case of the IQ results, Google referred to a variety of sources, including posts on X, Facebook, and a number of obscure listicle websites, including World Population Review. In nearly all of these cases, when you click through to the source, the trail leads back to Lynn’s infamous dataset. (In some cases, while the exact numbers Lynn published are referenced, the websites do not cite Lynn as the source.)

When querying Google’s Gemini AI chatbot directly using the same terms, it provided a much more nuanced response. “It’s important to approach discussions about national IQ scores with caution,” read text that the chatbot generated in response to the query “Pakistan IQ.” The text continued: “IQ tests are designed primarily for Western cultures and can be biased against individuals from different backgrounds.”

Google tells WIRED that its systems weren’t working as intended in this case and that it is looking at ways it can improve.

“We have guardrails and policies in place to protect against low quality responses, and when we find Overviews that don’t align with our policies, we quickly take action against them,” Ned Adriance, a Google spokesperson, tells WIRED. “These Overviews violated our policies and have been removed. Our goal is for AI Overviews to provide links to high quality content so that people can click through to learn more, but for some queries there may not be a lot of high quality web content available.”

While WIRED’s tests suggest AI Overviews have now been switched off for queries about national IQs, the results still amplify the incorrect figures from Lynn’s work in what’s called a “featured snippet,” which displays some of the text from a website before the link.

Google did not respond to a question about this update.

But it’s not just Google promoting these dangerous theories. When WIRED put the same query to other AI-powered online search services, we found similar results.

Perplexity, an AI search company that has been found to make things up out of thin air, responded to a query about “Pakistan IQ” by stating that “the average IQ in Pakistan has been reported to vary significantly depending on the source.”

It then lists a number of sources, including a Reddit thread that relied on Lynn’s research and the same World Population Review site that Google’s AI Overview referenced. When asked for Sierra Leone’s IQ, Perplexity directly cited Lynn’s figure: “Sierra Leone’s average IQ is reported to be 45.07, ranking it among the lowest globally.”

Perplexity did not respond to a request for comment.

Microsoft’s Copilot chatbot, which is integrated into its Bing search engine, generated confident text—“The average IQ in Pakistan is reported to be around 80”—citing a website called IQ International, which does not reference its sources. When asked for “Sierra Leone IQ,” Copilot’s response said it was 91. The source linked in the results was a website called Brainstats.com, which references Lynn’s work. Copilot also referenced Brainstats.com work when queried about IQ in Kenya.

“Copilot answers questions by distilling information from multiple web sources into a single response,” Caitlin Roulston, a Microsoft spokesperson, tells WIRED. “Copilot provides linked citations so the user can further explore and research as they would with traditional search.”

Google added that part of the problem it faces in generating AI Overviews is that, for some very specific queries, there’s an absence of high quality information on the web—and there’s little doubt that Lynn’s work is not of high quality.

“The science underlying Lynn’s database of ‘national IQs’ is of such poor quality that it is difficult to believe the database is anything but fraudulent,” Sear said. “Lynn has never described his methodology for selecting samples into the database; many nations have IQs estimated from absurdly small and unrepresentative samples.”

Sear points to Lynn’s estimation of the IQ of Angola being based on information from just 19 people and that of Eritrea being based on samples of children living in orphanages.

“The problem with it is that the data Lynn used to generate this dataset is just bullshit, and it’s bullshit in multiple dimensions,” Rutherford said, pointing out that the Somali figure in Lynn’s dataset is based on one sample of refugees aged between 8 and 18 who were tested in a Kenyan refugee camp. He adds that the Botswana score is based on a single sample of 104 Tswana-speaking high school students aged between 7 and 20 who were tested in English.

Critics of the use of national IQ tests to promote the idea of racial superiority point out not only that the quality of the samples being collected is weak, but also that the tests themselves are typically designed for Western audiences, and so are biased before they are even administered.

“There is evidence that Lynn systematically biased the database by preferentially including samples with low IQs, while excluding those with higher IQs for African nations,” Sear added, a conclusion backed up by a preprint study from 2020.

Lynn published various versions of his national IQ dataset over the course of decades, the most recent of which, called “The Intelligence of Nations,” was published in 2019. Over the years, Lynn’s flawed work has been used by far-right and racist groups as evidence to back up claims of white superiority. The data has also been turned into a color-coded map of the world, showing sub-Saharan African countries with purportedly low IQ colored red compared to the Western nations, which are colored blue.

“This is a data visualization that you see all over [X, formerly known as Twitter], all over social media—and if you spend a lot of time in racist hangouts on the web, you just see this as an argument by racists who say, ‘Look at the data. Look at the map,’” Rutherford says.

But the blame, Rutherford believes, does not lie with the AI systems alone, but also with a scientific community that has been uncritically citing Lynn’s work for years.

“It’s actually not surprising [that AI systems are quoting it] because Lynn’s work in IQ has been accepted pretty unquestioningly from a huge area of academia, and if you look at the number of times his national IQ databases have been cited in academic works, it’s in the hundreds,” Rutherford said. “So the fault isn’t with AI. The fault is with academia.”

This story originally appeared on wired.com

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