The Wild West days of self-driving are ending. Nobody told Tesla.

Even as regulatory concerns mount, Tesla continues to push its self-driving tech forward.

The Wild West days of self-driving are ending. Nobody told Tesla.

At its AI Day on Thursday, Tesla went deep on its self-driving tech.

Photo: Tesla

Tesla's "AI Day" on Thursday ended with a bang. The company unveiled the Tesla Bot, a humanoid robot intended to leverage the company's AI to navigate the world and "eliminate dangerous, repetitive, and boring tasks," as Elon Musk put it. Musk said he hoped it would help bring about a future in which "physical work will be a choice."

But while the Tesla Bot certainly stole the show, the vast majority of AI Day focused on self-driving systems. Tesla executives ventured deep in the weeds on simulation, data labeling and the proprietary Dojo chip (which promises breakthroughs in training neural networks). The event was meant as a recruiting exercise for AI experts, and the overall message was clear: Tesla is as bullish as ever on its ability to deliver full self-driving technology, and to do it fast.

That confidence comes as a bit of a surprise, though, given the mounting regulatory scrutiny surrounding Tesla.

  • The National Highway Traffic Safety Administration announced Monday that it would examine whether Tesla's Autopilot system has a tendency to malfunction at first responder sites, potentially due to lights, flares and reflective equipment. The investigation will center on eleven documented crashes. If the NHTSA finds fault in Tesla's systems, it could demand a recall or impose limits on driverless features for an estimated 765,000 Tesla vehicles sold in the U.S.
  • Two days later, Tesla's week went from bad to worse: Democratic Sens. Richard Blumenthal and Ed Markey sent a letter to FTC Chair Lina Khan, asking her to investigate Tesla for calling its system "Full Self-Driving" when, it turns out, it's not full self-driving.
  • Sens. Blumenthal and Markey also seemingly anticipated the bold claims at Tesla's AI Day event. They wrote in the letter: "As Tesla makes widely available its FSD and Autopilot technology and doubles down on its inflated promises, we are alarmed by the prospect of more drivers relying more frequently on systems that do not nearly deliver the expected level of safety."

The new regulatory push suggests the Wild West days of self-driving are nearing an end.

  • Until recently, federal agencies have held off on imposing strict self-driving regulations, likely out of fear that doing so would limit innovation. But in a February 2021 letter, the National Transportation Safety Board's then-chairman Robert Sumwalt expressed concerns over what he saw as the NHTSA's "willingness to let manufacturers and operational entities define safety."
  • Tesla has long adopted the "ask for forgiveness, not permission" stance toward regulators. Sometimes a lack of regulation allows for innovation: Tesla rolled out a Smart Summon feature in 2019, for example, that lets passengerless cars navigate parking lots at slow speeds. Smart Summon is pretty much the NHTSA's worst nightmare, but it's also fun and hasn't yet caused an epidemic of violent parking lot crashes (ok, maybe a few, but still).
  • But there are also cases in which underregulation has enabled reckless behavior. For instance, there aren't yet strict standards for making sure drivers pay attention with self-driving engaged. Some cars use eye-tracking to enforce driver compliance, while others (including most Tesla vehicles) simply monitor the steering wheel for occasional driver input. Critics argue that Tesla's approach has been too lax, and their case could be bolstered by several high-profile incidents in which drivers appear to have been completely disengaged.

As self-driving technology becomes more prevalent, the NHTSA can no longer afford to take a hands-off approach. Instead, the agency will likely soon set safety standards for things like driver engagement checks, hazardous conditions tests and backup crash avoidance systems.

For Tesla, complying with new regulations would also mean changing the company's culture.

  • Tesla is a polarizing company, in part because its CEO so brazenly flaunts his disdain for rules and regulations. (Musk has several ongoing Twitter beefs with regulators, and a few weeks after settling SEC fraud charges called the agency the "Shortseller Enrichment Commission.")
  • Sumwalt even once claimed that Musk hung up on him after he called to request that Musk stop disclosing information about an Autopilot crash investigation.

The renewed push for regulation sends a clear message: It's time for Tesla and Musk to get serious about safety or risk paying a hefty price. But there's no sign that Tesla's going to slow down anytime soon. Full Self-Driving is "clearly headed to way better than a human, without question," Musk said toward the end of AI Day. And that apparently goes both for cars and robots.

A version of this story will appear in tomorrow's Source Code newsletter. Sign up now.

Fintech

Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

Keep ReadingShow less
Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

Keep ReadingShow less
FTA
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.
Enterprise

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

It will be the second re:Invent with CEO Adam Selipsky as leader of the industry’s largest cloud provider after his return last year to AWS from data visualization company Tableau Software.

Keep ReadingShow less
Donna Goodison

Donna Goodison (@dgoodison) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

Keep ReadingShow less
Bennett Richardson

Bennett Richardson ( @bennettrich) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.

Enterprise

Why large enterprises struggle to find suitable platforms for MLops

As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

Keep ReadingShow less
Kate Kaye

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia.org and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

Latest Stories
Bulletins