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  • The WIRED Guide to Protecting Yourself From Government Surveillance

    The WIRED Guide to Protecting Yourself From Government Surveillance

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    “If you’re trying to not be tracked, not having a phone is often the easiest,” Sandvik says. “Leave it at home.”

    For most people most of the time, though, this solution isn’t practical. You can put your devices in airplane mode or turn them off completely to limit connectivity. But to be totally certain that everything is off the grid, you can put your devices in special pouches or cases known as Faraday bags that block all electromagnetic signals going to or coming from a device. Faraday bags allow you to carry your devices while keeping them from exposing your location; for example, concealing your whereabouts on a given afternoon or the route you took to get to a destination. The downside of Faraday bags is the device must stay in the bag to protect your privacy, so it takes planning to use them effectively. Removing your phone means that the (location) cat is out of the bag.

    Financial Privacy

    Financial surveillance is among the most powerful tracking tools in the government’s arsenal. Credit card payments or other transactions linked to your bank account are essentially transparent to any law enforcement agency that demands them.

    That “follow the money” form of surveillance also has a relatively simple analog defense: dollar bills. “Forensic accounting is a thing,” warns Holmes. “So yeah, use cash.”

    For those seeking more convenient or long-distance transactions, payment apps like Paypal, Venmo, and Cash App may seem slightly more cash-like than a credit card or check, but in fact are just as vulnerable to law enforcement data requests as any bank. Cryptocurrency may appear to be a tempting alternative. But despite the long-running mythical reputation of cryptocurrency as anonymous cash for the internet, bitcoin and most other cryptocurrencies offer no real privacy, given the ease of tracing bitcoin transactions on its blockchain and the difficulty of buying or selling cryptocurrency from a cryptocurrency exchange that complies with US know-your-customer laws.

    Some cryptocurrencies like Monero and Zcash do offer privacy properties that make them vastly more difficult to trace than other cryptocurrencies—at least in theory. Mixer services like the Ethereum-based Tornado Cash, too, promise to blend users’ coins with those of others to complicate the task of following the money. Still, given the ongoing advances in cryptocurrency tracing—and the indelible evidence of any security slipup that public blockchains make available to the cats in that cat-and-mouse game—it’s far safer to stick with cash whenever possible.

    A Note on Burner Phones

    Burner phones, or prepaid phones that aren’t connected to any of your credit cards or digital accounts, can be a useful tool for protecting your location data and other information. They are meant to have no traceable connection to you and to be used for a limited time. In other words, they are meant to provide anonymity.

    The advantage to using burner devices is that you don’t need to worry as much about the personal information they are collecting or inadvertently leaking while you use them because the devices are not linked to you. They merely show that someone is going here and there or that someone has, say, planned to meet someone else at 8 pm on the park benches. Over time, though, if you, use the device to communicate often, log into any digital accounts that are associated with you from the device, give a burner number to people who don’t use burners themselves, or bring it to a location associated with you while it’s on, like your house, the phone could quickly be linked to you.

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  • Two Upstart Search Engines Are Teaming Up to Take on Google

    Two Upstart Search Engines Are Teaming Up to Take on Google

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    Ask the search engine Ecosia about “Paris to Prague” and flight booking websites dominate the results. Ecosia’s CEO Christian Kroll would prefer to present more train options, which he considers better for the environment. But because its results are licensed from Google and Microsoft’s Bing, Ecosia has little control over what’s shown. Kroll is ready for that to change.

    Berlin-based Ecosia, which donates its profits to tree planting, and its Paris-based competitor Qwant are announcing Tuesday that they will team up to develop an index of the web.

    The for-profit joint venture, dubbed European Search Perspective and located in Paris, could allow the small companies and any others that decide to join up to reduce their reliance on Google and Bing and serve results that are better tailored to their companies’ missions and Europeans’ tastes. “We could de-rank results from unethical or unsustainable companies and rank good companies higher,” Kroll says of the eco-minded Ecosia.

    Losing a bit of licensing revenue won’t be much of a hit to Microsoft or Google, which together own about 95 percent of the global search industry outside China. But at a time when services such as ChatGPT and TikTok are already redefining how users search, tiny rivals potentially becoming more attractive to users could force the bigger companies to accelerate their investments in regional upgrades.

    Ownership of European Search Perspective, or EUSP, will be split equally between Ecosia and Qwant, with Ecosia providing cash and data while Qwant supplies the labor. Technical infrastructure will come from OVHcloud, which shares ownership with Qwant. Ecosia has about 1 percent search market share in France and Germany and claims about 20 million users globally, while Qwant reports about 6 million users.

    For Ecosia and Qwant, taking on more of the world beyond French- and German-speaking users will require succeeding at home and growing revenue, which largely comes from running ads. The challenge is evident. Ecosia’s sales, according to its disclosures, are down 8 percent to €24.2 million through the first nine months of this year compared to the same period in 2023. More precise results aren’t guaranteed to help boost the business—the ads are still provided by Microsoft and Google. Kroll says that’s going to change anytime soon.

    The companies are open to both raising outside funding for EUSP and licensing its index to other companies, including those that might want to use the data to train AI systems. “We’re bringing together the most experienced search engineers to build sovereign tech in Europe—especially for the French and German language, and we’re supremely confident that this will appeal to the investment community,” Kroll says.

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  • Elon Musk’s Twitter Takeover Set Off a Race to the Bottom

    Elon Musk’s Twitter Takeover Set Off a Race to the Bottom

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    But for years, public pressure from government officials, civil society, and the media pushed tech companies to invest in teams and tools that could at least somewhat address issues of hate speech or misinformation on their platforms, so they could say they were making a good faith effort to deal with the issue.

    Musk’s purchase of Twitter signaled a change, according to six former trust and safety employees from Twitter and Meta.

    When Musk took over Twitter in October 2022, he quickly fired more than 50 percent of the company’s workers, including almost all of the company’s trust and safety and policy staff—the people tasked with creating and enforcing the platform’s policies around things like hate speech, violent content, conspiracy theories, and mis- and disinformation. Since then, Meta, Google, Amazon, and Discord have all made cuts to trust and safety staff.

    Shortly after Musk purged Twitter of its trust and safety teams, other companies began layoffs. In November 2022, Meta laid off 11,000 employees, including many trust and safety employees. In January 2023, Google followed suit, axing 12,000 people. Earlier this year, Twitch, which is owned by Amazon, disbanded its Safety Advisory Council.

    “I think that Elon really opened the floodgates,” says one former Meta employee. “So then other tech brands were like, ‘We can do that too, because we won’t be the black sheep for it.’”

    Meta spokesperson Corey Chambliss tells WIRED that the company has “40,000 people globally working on safety and security—more than during the 2020 cycle, when we had a global team of 35,000 people working in this area,” though he did not address how many of those people are staff versus outsourced workers.

    Musk’s sudden firings made it so that “anybody else could come along and nicely fire their teams and give them severance and it was nicer. Better,” says a former Twitter employee who was fired by Musk.

    After Musk fired the trust and safety staff, experts warned that this cut, coupled with Musk’s “free speech absolutism,” would allow toxic content to flood the platform and ultimately cause an exodus of users and advertisers, leading to Twitter’s eventual demise. Hate speech and misinformation did increase and advertisers did pull their dollars. Last year, X fired members of what remained of its elections team. Around the same time, Musk posted on X, saying, “Oh you mean the ‘Election Integrity’ Team that was undermining election integrity? Yeah, they’re gone.”

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  • The Guy Behind the Fake AI Halloween Parade Listing Says You’ve Got It All Wrong

    The Guy Behind the Fake AI Halloween Parade Listing Says You’ve Got It All Wrong

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    I appreciate that.

    We own this mistake.

    So your name is Nazir Ali, but when you say “we”—

    We are not going to give you any personal information that might be harmful for us. Everyone is writing about us, and they are telling us that we are scammers.

    Would you be comfortable telling me about the reports that you’re based in Pakistan? Is that true?

    We hire some of the content creators, and one is from Pakistan, and others are from some other countries. But I don’t want to actually reveal their nationalities. People will blame the country if I say I’m from Dubai, then whenever you write an article, if you say that a guy from Pakistan, a guy from India, guy from Ireland, a guy from the UAE, it actually hurts some of the citizens of that country.

    Would you be comfortable telling me how long you’ve had this Halloween website?

    You will be shocked to know that we ranked our site in three months on the Google first page.

    So you’ve only been in operation for three months?

    Yes.

    Why holiday events?

    It’s a huge topic, but only for one day. So it is easy for us to generate revenue for that one day—then we don’t have to put in effort throughout the year. We just do work for three or four months, and then we’ll get the revenue.

    Could you explain more about your business model. How do you make money?

    Our business model is Google Ads. Google Ads and affiliate marketing.

    Has this made you reconsider the ways that you operate? Will you change how you use AI going forward?

    It is our mistake. We should double check it. Not only double, but triple check it. One more thing I want to add is that people should not consider Google as the standard. Google is just a search engine, and any person can post anything on it. Don’t just believe it. Just cross check!

    Are you concerned that Google will downrank you now?

    Definitely. We are expecting Google will derank.

    Is there anything you could try to do to prevent that?

    No, there is nothing. And this is because of all the misinformation provided by the journalists. They don’t actually know what our intentions are, but they are showing that our intentions are wrong. But right now the guys are very depressed. Listen to me. If we wanted to scam people, we can easily do so by selling fake tickets. But we never mentioned any tickets on the website. That would be very simple, but we didn’t even mention the ticket thing.

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  • AI search could break the web

    AI search could break the web

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    In short, governments have shown they are willing to regulate the flow of value between content producers and content aggregators, abandoning their traditional reluctance to interfere with the internet.

    However, mandatory bargaining is a blunt solution for a complex problem. These reforms favor a narrow class of news organizations, operating on the assumption that platforms like Google and Meta exploit publishers. In practice, it’s unclear how much of their platform traffic is truly attributable to news, with estimates ranging from 2% to 35% of search queries and just 3% of social media feeds. At the same time, platforms offer significant benefit to publishers by amplifying their content, and there is little consensus about the fair apportionment of this two-way value. Controversially, the four bargaining codes regulate simply indexing or linking to news content, not just reproducing it. This threatens the “ability to link freely” that underpins the web. Moreover, bargaining rules focused on legacy media—just 1,400 publications in Canada, 1,500 in the EU, and 62 organizations in Australia—ignore countless everyday creators and users who contribute the posts, blogs, images, videos, podcasts, and comments that drive platform traffic.

    Yet for all its pitfalls, mandatory bargaining may become an attractive response to AI search. For one thing, the case is stronger. Unlike traditional search—which indexes, links, and displays brief snippets from sources to help a user decide whether to click through—AI search could directly substitute generated summaries for the underlying source material, potentially draining traffic, eyeballs, and exposure from downstream websites. More than a third of Google sessions end without a click, and the proportion is likely to be significantly higher in AI search. AI search also simplifies the economic calculus: Since only a few sources contribute to each response, platforms—and arbitrators—can more accurately track how much specific creators drive engagement and revenue.  

    Ultimately, the devil is in the details. Well-meaning but poorly designed mandatory bargaining rules might do little to fix the problem, protect only a select few, and potentially cripple the free exchange of information across the web. 

    Industry has a narrow window to build a fairer reward system

    However, the mere threat of intervention could have a bigger impact than actual reform. AI firms quietly recognize the risk that litigation will escalate into regulation. For example, Perplexity AI, OpenAI, and Google are already striking deals with publishers and content platforms, some covering AI training and others focusing on AI search. But like early bargaining laws, these agreements benefit only a handful of firms, some of which (such as Reddit) haven’t yet committed to sharing that revenue with their own creators. 

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  • Europe’s Big Tech Hawks Brace for a Post-Biden Future

    Europe’s Big Tech Hawks Brace for a Post-Biden Future

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    For Europe, the outcome of next week’s US election will have profound consequences. NATO funding is at stake, as is a potential peace deal between Russia and Ukraine. Projections suggest a trade war with Donald Trump could hit GDP in the bloc’s biggest economy, Germany, by 1.5 percent. The future of big tech, by comparison, is a sideshow—but a fraught one. President Joe Biden’s administration ushered in a new era of confrontation with the likes of Meta, Microsoft and Nvidia, which all faced legal action during his time in office. A proposal to break-up Google is still pending.

    Unlike many other places in the world where US tech reigns, when the European Union makes new rules, these companies pay attention. In the Biden era, the EU found an ally in its ambitions to reign in big tech, says Max von Thun, director of Europe and Transatlantic partnerships at the Open Markets Institute. “Under Trump or really even under [former President Barack] Obama, there was this feeling that if the EU went too far, there would be a backlash from the US,” von Thun explains, meaning regulators felt that ordering companies to break-up their business was off the table. “Whereas under Biden, because the US is pursuing those types of remedies, the EU thinks, well we can do that too.”

    Many in Brussels would like that alignment to continue. Most Europeans defer to American search engines, scroll American social media feeds, and shop on American ecommerce sites. There’s longstanding concern that the dominance of the big five—Alphabet, Amazon, Apple, Meta and Microsoft—is stifling European competition and shortchanging consumers. This is not only an issue for EU regulators. It’s also preoccupying the minds of ordinary Americans, according to Democratic pollster Lake Research Partners. A survey of 600 likely voters in seven crucial battleground states and Ohio found that 67 percent believe corporate power—and the lack of government pushback—to be one of the country’s biggest problems. With the new Digital Markets Act, Europe has made its intention to limit the tech giants’ reach clear . Enforcing those new rules, however, would be a lot easier with American buy-in.

    Big tech politics in this election are messy. Silicon Valley titans are split between Democrats and Republicans. Throughout their campaigns, both Trump and Kamala Harris have been non-committal about how they would regulate the world’s biggest companies. Trump has gestured, vaguely, that “something” should be done about Google, to make the company “more fair”. Harris, meanwhile, has so far been mute on whether she agrees with Democratic megadonor and LinkedIn co-founder Reid Hoffman’s characterisation of the Federal Trade Commission’s (FTC) antitrust policy as a “war on American business”.

    How much Harris would continue Biden’s relatively confrontational approach is unclear. Biden diverged from the policies of his own running mate, Obama, who hit back at European scrutiny of Google and Facebook by accusing the bloc of protectionism, saying European companies “can’t compete.” Harris’ own comments on antitrust have been sparse, although she has long expressed interest in data protection. “I think Facebook has experienced massive growth and has prioritized its growth over the best interest of its consumers—especially on the issue of privacy,” she said in a CNN interview back in 2019. When pushed on whether the company should be broken up, she responded: “Yes, I think we should seriously take a look at that.”

    But big tech hawks in Brussels have been closely tracking Harris’ ties to Silicon Valley. Her brother-in-law, Tony West, who has been acting as a close adviser, is chief legal officer for Uber. The company announced in August that he would be taking a unpaid leave of absence to focus on the campaign. Google attorney Karen Dunn has also been linked to Harris, and prepped her for the ABC debate last month.

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  • A Running List of the Tech CEOs Donald Trump Claims Are Calling Him to Suck Up

    A Running List of the Tech CEOs Donald Trump Claims Are Calling Him to Suck Up

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    Trump’s relationship with Apple CEO Tim Cook is one of the most congenial the former president has shared with a Silicon Valley leader. Cook maintained a relationship with Trump during his time in office, often meeting with the president and serving on advisory panels influencing policy decisions that affect Apple’s business, such as tariffs and immigration.

    Cook has not publicly confirmed that this most recent call took place. Apple did not immediately respond to a request for comment from WIRED.

    Meta CEO Mark Zuckerberg

    Shortly after the assassination attempt against Trump in Butler, Pennsylvania, this summer, the former president claimed that Zuckerberg called him. In an interview with New York magazine, Trump claimed that Zuckerberg said, “‘I will never vote for people running against you after watching what you did.’”

    A Meta spokesperson contested what Trump told the magazine, saying, “As Mark has said publicly, he’s not endorsing anybody in this race and has not communicated to anybody how he intends to vote.” (Zuckerberg did not endorse any candidate in the 2016 and 2020 elections and has said that he won’t this cycle either.)

    While Meta wouldn’t detail the contents of the call, Zuckerberg confirmed he had called Trump after the assassination attempt, calling the former president “bad ass” in July.

    “Seeing Donald Trump get up after getting shot in the face and pump his fist in the air with the American flag is one of the most badass things I’ve ever seen in my life,” Zuckerberg said.

    Under Trump, Meta CEO Mark Zuckerberg sustained countless attacks from the Trump administration and conservative lawmakers over censorship allegations. In 2020, Zuckerberg donated $350 million in pandemic support to election departments around the country. Republicans accused these “Zuckerbucks” donations of being unfairly distributed to Democratic districts. In 2021, following the January 6 riot at the Capitol, Trump was banned from Facebook and Instagram.

    Blue Origin CEO and Amazon founder Jeff Bezos

    Former Amazon CEO Jeff Bezos has been under fire in recent days after he decided that the Washington Post would no longer endorse presidential candidates, despite the paper having a Harris endorsement in the works.

    Trump has long criticized Bezos for his ownership of the Washington Post, but Trump said that Bezos had called him after this summer’s assassination attempt. “It is the most incredible thing I’ve ever watched,” Trump said Bezos told him. “I said, ‘Despite the fact you own the Washington Post, I appreciate it.” Amazon’s CEO, Andy Jassy, reportedly called Trump after the July shooting as well.

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  • Google, Microsoft, and Perplexity Are Promoting Scientific Racism in Search Results

    Google, Microsoft, and Perplexity Are Promoting Scientific Racism in Search Results

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    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,” Sears 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.”

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  • Google’s Visual Search Can Now Answer Even More Complex Questions

    Google’s Visual Search Can Now Answer Even More Complex Questions

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    When Google Lens was introduced in 2017, the search feature accomplished a feat that not too long ago would have seemed like the stuff of science fiction: Point your phone’s camera at an object and Google Lens can identify it, show some context, maybe even let you buy it. It was a new way of searching, one that didn’t involve awkwardly typing out descriptions of things you were seeing in front of you.

    Lens also demonstrated how Google planned to use its machine learning and AI tools to ensure its search engine shows up on every possible surface. As Google increasingly uses its foundational generative AI models to generate summaries of information in response to text searches, Google Lens’ visual search has been evolving, too. And now the company says Lens, which powers around 20 billion searches per month, is going to support even more ways to search, including video and multimodal searches.

    Another tweak to Lens means even more context for shopping will show up in results. Shopping is, unsurprisingly, one of the key use cases for Lens; Amazon and Pinterest also have visual search tools designed to fuel more buying. Search for your friend’s sneakers in the old Google Lens, and you might have been shown a carousel of similar items. In the updated version of Lens, Google says it will show more direct links for purchasing, customer reviews, publisher reviews, and comparative shopping tools.

    Lens search is now multimodal, a hot word in AI these days, which means people can now search with a combination of video, images, and voice inputs. Instead of pointing their smartphone camera at an object, tapping the focus point on the screen, and waiting for the Lens app to drum up results, users can point the lens and use voice commands at the same time, for example, “What kind of clouds are those?” or “What brand of sneakers are those and where can I buy them?”

    Lens will also start working over real-time video capture, taking the tool a step beyond identifying objects in still images. If you have a broken record player or see a flashing light on a malfunctioning appliance at home, you could snap a quick video through Lens and, through a generative AI overview, see tips on how to repair the item.

    First announced at I/O, this feature is considered experimental and is available only to people who have opted into Google’s search labs, says Rajan Patel, an 18-year Googler and a cofounder of Lens. The other Google Lens features, voice mode and expanded shopping, are rolling out more broadly.

    The “video understanding” feature, as Google calls it, is intriguing for a few reasons. While it currently works with video captured in real time, if or when Google expands it to captured videos, entire repositories of videos—whether in a person’s own camera roll or in a gargantuan database like Google—could potentially become taggable and overwhelmingly shoppable.

    The second consideration is that this Lens feature shares some characteristics with Google’s Project Astra, which is expected to be available later this year. Astra, like Lens, uses multimodal inputs to interpret the world around you through your phone. As part of an Astra demo this spring, the company showed off a pair of prototype smart glasses.

    Separately, Meta just made a splash with its long-term vision for our augmented reality future, which involves mere mortals wearing dorky glasses that can smartly interpret the world around them and show them holographic interfaces. Google, of course, already tried to realize this future with Google Glass (which uses fundamentally different technology than that of Meta’s latest pitch). Are Lens’ new features, coupled with Astra, a natural segue to a new kind of smart glasses?

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  • Google says its AI designs chips better than humans – experts disagree

    Google says its AI designs chips better than humans – experts disagree

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    Can AI design a chip that’s more efficient than human-made ones?

    Yuichiro Chino/Getty Images

    Google DeepMind says its artificial intelligence has helped design chips that are already being used in data centres and even smartphones. But some chip design experts are sceptical of the company’s claims that such AI can plan new chip layouts better than humans can.

    The newly named AlphaChip method can design “superhuman chip layouts” in hours, rather than relying on weeks or months of human effort, said Anna Goldie and Azalia Mirhoseini, researchers at Google DeepMind, in a blog post. This AI approach uses reinforcement learning to figure out the relationships among chip components and gets rewarded based on the final layout quality. But independent researchers say the company has not yet proven such AI can outperform expert human chip designers or commercial software tools – and they want to see AlphaChip’s performance on public benchmarks involving current, state-of-the-art circuit designs.

    “If Google would provide experimental results for these designs, we could have fair comparisons, and I expect that everyone would accept the results,” says Patrick Madden at Binghamton University in New York. “The experiments would take at most a day or two to run, and Google has near-infinite resources – that these results have not been offered speaks volumes to me.” Google DeepMind declined to offer additional comment.

    Google DeepMind’s blog post accompanies an update to Google’s 2021 Nature journal paper about the company’s AI process. Since that time, Google DeepMind says that AlphaChip has helped design three generations of Google’s Tensor Processing Units (TPU) – specialised chips used to train and run generative AI models for services such as Google’s Gemini chatbot.

    The company also claims that the AI-assisted chip designs perform better than those designed by human experts and have been improving steadily. The AI achieves this by reducing the total length of wires required to connect chip components – a factor that can lower chip power consumption and potentially improve processing speed. And Google DeepMind says that AlphaChip has created layouts for general-purpose chips used in Google’s data centres, along with helping the company MediaTek develop a chip used in Samsung mobile phones.

    But the code publicly released by Google lacks support for common industry chip data formats, which suggests the AI method is currently more suited for Google’s proprietary chips, says Igor Markov, a chip design researcher. “We really don’t know what AlphaChip is today, what it does and what it doesn’t do,” he says. “We do know that reinforcement learning takes two to three orders of magnitude greater compute resources than methods used in commercial tools and is usually behind [in terms of] results.”

    Markov and Madden critiqued the original paper’s controversial claims about AlphaChip outperforming unnamed human experts. “Comparisons to unnamed human designers are subjective, not reproducible, and very easy to game. The human designers may be applying low effort or be poorly qualified – there is no scientific result here,” says Markov. “Imagine if AlphaGo reported wins over unnamed Go players.”

    In 2023, an independent expert who had reviewed Google’s paper retracted his Nature commentary article that had originally praised Google’s work. That expert, Andrew Kahng at the University of California, San Diego, also ran a public benchmarking effort that tried to replicate Google’s AI method and found it did not consistently outperform a human expert or conventional computer algorithms. The best-performing methods were commercial software for chip design from companies such as Cadence and NVIDIA.

    “On every benchmark where there’s what I would consider a fair comparison, it seems like reinforcement learning lags behind the state of the art by a wide margin,” says Madden. “For circuit placement, I don’t believe that it’s a promising research direction.”

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