The Prompt: Perplexity's Erroneous AI Election Info

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Perplexity launched a new platform that aims to keep track of election results but reports have found that it contained factual inaccuracies.

On the heels of the 2024 US presidential election, AI search startup Perplexity launched a new platform that aims to keep track of election results and offer information about candidates, their policies and endorsements in the form of AI-generated summaries. But the Verge reported that some of these summaries were ridden with factual errors.

Perplexity’s push into providing election-related information comes at a time when AI chatbots released by others like Google and OpenAI have largely stayed away from answering questions about the election.

Now let’s get into the headlines.

AI-generated images portraying Americans making political endorsements have gotten millions of interactions on Facebook, according to research conducted by the nonprofit Center for Countering Digital Hate. Researchers found 169 AI-generated posts on Facebook depicting veterans, police officers and protesters making political statements like “Kamala Harris is so extreme, she’d even tax your lemonade stand!”

Users managing these Facebook pages are often based outside of the US in countries like Morocco and Pakistan, according to the report. In August, Forbes found dozens of American patriotism-themed Facebook pages that were propagating fake news and being run by users based overseas.

As of last week, the social media behemoth earned about $1 million, running hundreds of ads, some of which AI-generated depictions of Kamala Harris, that falsely claimed that the upcoming election may be rigged or could be postponed by Democrats, Forbes reported.

On X, a pro-Trump account posted a deepfake video falsely depicting Martin Luther King Jr. urging Black voters to vote for Trump, the Washington Post reported. His daughter Bernice King called the video "vile," in a post and asked for it to be deleted.

A few weeks after Netflix shuttered its game studio and laid off a team of 35 game developers, Netflix executive Mike Verdu announced his new role on Linkedin: VP of GenAI for Games at Netflix, 404 Media reported. The streaming giant plans to use generative AI tools to help smaller teams build games faster, Verdu said in a post. “I am focused on a creator-first vision for AI, one that puts creative talent at the center, with AI being a catalyst and an accelerant,” he said.

Google’s less known AI project called Big Sleep, which uses large language models to spot real world security vulnerabilities, has discovered a previously-unknown exploitable safety bug all on its own — a first for an AI agent ever, the company claims. Researchers reported the bug to developers in October, who fixed it on the same day. This comes days after Google CEO Sundar Pichai said a quarter of all new code generated by the search giant is written with AI.

Physical intelligence, which is building a general purpose foundational AI model that can be slotted into any type of robot, has raised $400 million at a $2 billion valuation from Jeff Bezos, Thrive Capital, Lux Capital and OpenAI. It’s not the only AI startup with a mission to build a one-size-fits-all brain for robots. Competitors like Skild AI are developing similar software.

Also notable: New York-based Ataraxis has raised $4 million in seed funding to develop an AI-based diagnostic system for cancer patients and help them avoid unnecessary treatments, Forbes reported.

When John Jumper got the call earlier this month from the Royal Swedish Academy of Sciences that he was winning the Nobel Prize, he almost didn’t answer.

The director of Google DeepMind, the tech giant’s formidable AI lab, recognized the Swedish area code on his phone and froze, unable to believe what was on the precipice of happening. But on October 9, he was awarded the Nobel Prize in Chemistry, alongside DeepMind cofounder Demis Hassabis, for their creation of AlphaFold, an AI model that predicts the structure of proteins, the building blocks of biology, based on their chemical sequence.

“I really didn't think it was going to happen,” Jumper told Forbes.

The two Google scientists split the award with David Baker, a professor at the University of Washington who used software to invent a new protein. Baker, who founded the university’s Institute of Protein Design in 2012, told Forbes earlier this year that he was shocked to see how much the field has grown in recent years. “It was always this kind of lunatic, fringe thing. Very much out of the mainstream,” he said.

For more than half a century, protein folding had been one of the most vexing and promising problems in modern science: predicting the shape and structure of proteins is key in understanding how they’ll interact with the external environment, paving the way for drug discoveries and the development of new materials. With AlphaFold, DeepMind was able to predict millions of folding patterns using generative AI — exponentially quicker and cheaper than it would take to traditionally perform those computations.

Jumper, who joined DeepMind in 2017, is the youngest Nobel laureate in Chemistry in over 70 years. He chatted with Forbes about winning the award, the AI landscape, and building AlphaFold.

Read the full conversation on Forbes.

$10 billion

Microsoft’s revenue from its AI-related business is slated to reach this annual run rate by the next quarter, CEO Satya Nadella said during an earnings call last week. If that prediction holds up, it will be the fastest business segment in the company’s history to achieve the milestone, the company said.

This company is launching an AI imaging system to help patients better understand dental X rays.

Check if you got it right.

Mark Zuckerberg had plans to build a massive nuclear power-based data center to support Meta’s fast growing AI ambitions. But the billionaire was met with an unlikely roadblock: a rare species of bees were discovered on the land earmarked for the infrastructure, according to the Financial Times. The complications come as Meta’s rivals Google, Amazon and Microsoft have all struck deals to acquire nuclear power plants to continue building power-hungry AI models.