Just days out from the election, candidates are making their final pitches to the American public. But in the age of AI fakery, how can voters be sure it is indeed a real politician speaking in that robocall or video ad?

Audio deepfake detection service Pindrop has rounded up some of the most common expected scams for which to be on guard—as well as resources and tips to avoid them—as Election Day looms. Those include fake voter registration links and polling locations, as well as various deepfakes and voice clones.

While political AI-generated imagery, video, and audio has certainly spread online as generative tools have become more freely available, there isn’t much evidence yet that deepfake campaigns have managed to sway voters in any great numbers. But Pindrop CEO Vijay Balasubramaniyan said the amount of synthetic media is only growing as November approaches, and bad actors have honed techniques to make it seem more convincingly real.

Undue urgency: Any robocalls or other communication calling on you to take action with an abnormal sense of urgency should be seen as a red flag, Balasubramaniyan said, though it may be hard to tell as campaigns have often turned to attention-grabbing desperation in texts and emails.

“Beware of urgency,” Balasubramaniyan said.

Keep reading here.—PK

It’s 1993. Bill Clinton just took office, Janet Jackson and Whitney Houston are topping the charts, and Visa is experimenting with neural networks designed to cut down on credit card fraud.

“It was simpler AI at the time, as you can imagine. I call it good old-fashioned AI—rule-based, simple math equations and so on,” Rajat Taneja, Visa’s president of technology, told Tech Brew.

Fast-forward more than three decades and the payments giant is still at it with a new generation of AI. Taneja said the company’s long history with the technology is a key asset as it attempts to make the best use of a new class of language models at a time when AI is seemingly on the tip of every business exec’s tongue.

Much of the company’s AI operation is still focused on combating fraud—Taneja said these models saved Visa $40 billion last year—but the company has also begun to apply large language models to writing code, customer support, and marketing personalization.

The journey: Years after the early foray into machine learning, Visa began its latest effort to consolidate data and ramp up AI around a decade ago, retooling for the deep-learning revolution of the mid-2010s. The company has sunk $3.3 billion into AI and data infrastructure over the past 10 years, according to Taneja.

Taneja said his team was early to the current language model era, which ultimately traces back to a seminal 2017 research paper on transformer models. Starting around five years ago, Visa began using generative AI to create synthetic data—generated output meant to imitate, in this case, fraudulent payments—to train the company’s deep authorization model, which scores transactions based on risk. This helped “overcome the AI’s well-known problem of cold start,” he said.

Keep reading here.—PK

EVs were a boon for some and a bust for others in the auto industry’s latest round of earnings reports.

Market leader Tesla handed in strong Q3 results, beating analysts’ profit expectations and predicting robust sales growth next year. General Motors had a solid quarter and assured Wall Street it’s moving toward making its EVs profitable. Ford’s report was more downbeat, with its EV business weighing on results.

Tesla’s stock is up around 4% year to date. GM’s is up around 45%, while Ford’s is down about 14%.

Gradual progress: Ford on Monday reported Q3 profits of $900 million on revenue of $46 billion. The automaker said that results were muted by high warranty costs and a $1 billion charge related to dialing back some of its electrification plans. Executives said they expect full-year earnings to come in at the lower end of their guidance, at about $10 billion.

While its commercial and combustion engine vehicle businesses were profitable, Ford’s EV business unit lost $1.2 billion. The company said that YoY cost improvements “were offset by expected industry-wide pricing pressure.” The company reported that it has achieved nearly $1 billion in cost improvements in the EV business so far this year, but still expects full-year losses of $5 billion.

“No doubt there’s a global price war and it’s fueled by overcapacity, a flood of new EV nameplates, and massive compliance pressure,” Ford CEO Jim Farley said on the company’s earnings call.

Keep reading here.—JG