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Hard Numbers: Geoglyph spotting, AI revenue surge, CAPTCHAS solved, ByteDance’s chip hoard, Helene’s chip damage
303: Archaeologists have discovered 303 giant symbols carved into Peru’s Nazca Desert, thanks to artificial intelligence. The famous and mysterious Nazca geoglyphs are giant drawings in the ground, easily visible from high up — some are nearly 2,000 years old. The research team, led by Japan’s Yamagata University with help from IBM’s Watson Research Center, trained an AI model on existing geoglyphs to identify potentially undiscovered symbols.
11: AI companies are making money more quickly than previous waves of hyped-up software companies, according to a new data analysis from the payments company Stripe. It found that it took only 11 months for the top 100 highest-grossing privately held AI companies to make $1 million in annualized revenue as opposed to software-as-a-service companies in 2018, which took 15 months to hit that mark.
100: AI bots are now smart enough to solve 100% of those pesky traffic-image CAPTCHA — the ones put it in place to make sure you’re, you know, human. Thankfully, those images, known as Google’s ReCAPTCHA v2, are no longer industry standard. The newest version, reCAPTCHA v3, is an “invisible” test that tries to prove humanity based on how you interact with a given web page.
100,000: ByteDance reportedly has ordered 100,000 Ascend 910B chips from Huawei to aid the training of a new AI model. TikTok’s parent company also depends on Nvidia chips and Microsoft cloud services, but the new model will be mostly trained with chips from Huawei, a fellow Chinese tech giant. A ByteDance spokesperson refuted the report from Reuters, saying, “The entire premise here is wrong. No new model is being developed.”
70: Hurricane Helene has ravaged North Carolina, including a small town called Spruce Pine, which is home to 70% of the naturally occurring high-purity quartz. This kind of quartz is critical to the global semiconductor trade — used for crucibles, containers that can hold high-temperature materials, and other parts of chips themselves. The two companies there, Quartz Corp and Unimin, have temporarily halted operations — if they can’t get back up and running soon, delays could afflict the global chip supply chain.
Bots battle Bibi
X has become a critical means for politicians and the public to broadcast their views on current events, often triggering controversy, trolling, and bitter battles in the new political arena: the comments section. Trouble is, it’s not just people posting. Social media bots — programs that automate interactions and post content on social media in ways that mimic human behavior — are also flooding the comments section, which means you may be responding to fake accounts, not humans.
We partnered with Cyabra, an Israel-based data firm that investigates fake actors on the internet, and found that bots flocked to Bibi’s post in droves. They made up over 43% of all replies, and of the bots spreading negative sentiment about the post, 19% used keywords like “genocide,” “kids,” and “children.”
The investigation also found that while real accounts outnumbered fake ones, the bots were far more active, with many commenting multiple times. Across the board, they found that up to 31% of comments responding to posts from key political figures are fueled by fake accounts.
Are bots trying to undermine Donald Trump?
In an exclusive investigation into online disinformation surrounding the reaction to Donald Trump’s hush-money trial, GZERO asks whether bots are being employed to shape debates about the former president’s guilt or innocence. We investigated, with the help of Cyabra, a firm that specializes in tracking bots, to look for disinformation surrounding the online reactions to Trump’s trial. Is Trump’s trial the target of a massive online propaganda campaign – and, if so, which side is to blame?
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Adult film actress Stormy Daniels testified on Tuesday against former President Donald Trump, detailing her sexual encounter with Trump in 2006 and her $130,000 hush money payment from Trump's ex-attorney Michael Cohen before the 2016 election. In the process, she shared explicit details and said she had not wanted to have sex with Trump. This led the defense team to call for a mistrial. Their claim? That the embarrassing aspects were “extraordinarily prejudicial.”
Judge Juan Merchan denied the motion – but also agreed that some of the details from Daniels were “better left unsaid.”
The trouble is, plenty is being said, inside the courtroom and in the court of public opinion – aka social media. With so many people learning about the most important trials of the century online, GZERO partnered with Cyabra to investigate how bots are influencing the dialogue surrounding the Trump trials. For a man once accused of winning the White House off the steam of Russian meddling, the results may surprise you.
Bots – surprise, surprise – are indeed rampant amid the posts about Trump’s trials online. Cyabra’s AI algorithm analyzed 7,500 posts with hashtags and phrases related to the trials and found that 17% of Trump-related tweets came from fake accounts. The team estimated that these inauthentic tweets reached a whopping 49.1 million people across social media platforms.
Ever gotten into an argument on X? Your opponent might not have been real. Cyabra found that the bots frequently comment and interact with real accounts.
The bots also frequently comment on tweets from Trump's allies in large numbers, leading X’s algorithm to amplify those tweets. Cyabra's analysis revealed that, on average, bots are behind 15% of online conversations about Trump. However, in certain instances, particularly concerning specific posts, bot activity surged to over 32%.
But what narrative do they want to spread? Well, it depends on who’s behind the bot. If you lean left, you might assume most of the bots were orchestrated by MAGA hat owners – if you lean right, you’ll be happy to learn that’s not the case.
Rather than a bot army fighting in defense of Trump, Cyabra found that 73% of the posts were negative about the former president, offering quotes like “I don’t think Trump knows how to tell the truth” and “not true to his wife, not true to the church, not true to the country, just a despicable traitor.”
Meanwhile, only 4% were positive. On the positive posts, Cyabra saw a pattern of bots framing the legal proceedings as biased and painting Trump as a political martyr. The tweets often came in the form of comments on Trump’s allies’ posts in support of the former president. For example, in a tweet from Marjorie Taylor Greene calling the trials “outrageous” and “election interference,” 32% of the comments were made by inauthentic profiles.
Many of the tweets and profiles analyzed were also indistinguishable from posts made by real people – a problem many experts fear is only going to worsen. As machine learning and artificial intelligence advance, so too will the fake accounts and attempts to shape political narratives.
Moreover, while most of the bots came from the United States – it was by no means all of them. The location of some of the bots does not exactly read like a list of usual suspects, with only three in China and zero in Russia (see map below).
Cyabra
This is just one set of data based on one trial, so there are limitations to drawing broader conclusions. But we do know, of course, that conservatives have long been accused of jumping on the bot-propaganda train to boost their political fortunes. In fact, Cyabra noted last year that pro-Trump bots were even trying to sow division amongst Republicans and hurt Trump opponents like Nikki Haley.
Still, Cyabra’s research, both then and now, shows that supporters of both the left and the right are involved in the bot game – and that, in this case, much of the bot-generated content was negative about Trump, which contradicts assumptions that his supporters largely operate bots. It’s also a stark reminder to ensure you’re dealing with humans in your next online debate.
In the meantime, check out Cyabra’s findings in full by clicking the button below.
Get AI out of my health care
You fall and break an arm. Doctors set the break and send you to rehab. It’s pricy, but insurance should take care of it, so you submit your claim – only to be denied. Was it a claims examiner who rejected it? Or AI?
On Feb. 6, the US government sent a memo to certain Medicare insurers clarifying that no, they cannot use artificial intelligence to deny claims. While machine-learning algorithms can be used to assist them in making determinations, an algorithm alone cannot be the basis for denying care.
This memo, sent by the Centers for Medicare & Medicaid Services, follows lawsuits against health insurers for allegedly using AI to erroneously deny deserved care to patients. United Healthcare and Humana have each been sued by patients claiming the companies used the AI model nH Predict nefariously — a model they claim has a 90% error rate. It’s a clear and present danger of the technology at a time when many regulators and critics are focusing on far-off threats of AI.
CMS also said it’s concerned about the propensity for algorithms to “exacerbate discrimination and bias” and said the onus is on insurers to make sure these models comply with the Affordable Care Act’s anti-discrimination requirements. And it’s not just the federal government: A number of states including New York and California have issued warnings to insurance companies to ensure their own algorithms aren’t discriminatory.