MAROKO133 Breaking ai: Listen Labs raises $69M after viral billboard hiring stunt to scale

📌 MAROKO133 Update ai: Listen Labs raises $69M after viral billboard hiring stunt

Alfred Wahlforss was running out of options. His startup, Listen Labs, needed to hire over 100 engineers, but competing against Mark Zuckerberg's $100 million offers seemed impossible. So he spent $5,000 — a fifth of his marketing budget — on a billboard in San Francisco displaying what looked like gibberish: five strings of random numbers.

The numbers were actually AI tokens. Decoded, they led to a coding challenge: build an algorithm to act as a digital bouncer at Berghain, the Berlin nightclub famous for rejecting nearly everyone at the door. Within days, thousands attempted the puzzle. 430 cracked it. Some got hired. The winner flew to Berlin, all expenses paid.

That unconventional approach has now attracted $69 million in Series B funding, led by Ribbit Capital with participation from Evantic and existing investors Sequoia Capital, Conviction, and Pear VC. The round values Listen Labs at $500 million and brings its total capital to $100 million. In nine months since launch, the company has grown annualized revenue by 15x to eight figures and conducted over one million AI-powered interviews.

"When you obsess over customers, everything else follows," Wahlforss said in an interview with VentureBeat. "Teams that use Listen bring the customer into every decision, from marketing to product, and when the customer is delighted, everyone is."

Why traditional market research is broken, and what Listen Labs is building to fix it

Listen's AI researcher finds participants, conducts in-depth interviews, and delivers actionable insights in hours, not weeks. The platform replaces the traditional choice between quantitative surveys — which provide statistical precision but miss nuance—and qualitative interviews, which deliver depth but cannot scale.

Wahlforss explained the limitation of existing approaches: "Essentially surveys give you false precision because people end up answering the same question… You can't get the outliers. People are actually not honest on surveys." The alternative, one-on-one human interviews, "gives you a lot of depth. You can ask follow up questions. You can kind of double check if they actually know what they're talking about. And the problem is you can't scale that."

The platform works in four steps: users create a study with AI assistance, Listen recruits participants from its global network of 30 million people, an AI moderator conducts in-depth interviews with follow-up questions, and results are packaged into executive-ready reports including key themes, highlight reels, and slide decks.

What distinguishes Listen's approach is its use of open-ended video conversations rather than multiple-choice forms. "In a survey, you can kind of guess what you should answer, and you have four options," Wahlforss said. "Oh, they probably want me to buy high income. Let me click on that button versus an open ended response. It just generates much more honesty."

The dirty secret of the $140 billion market research industry: rampant fraud

Listen finds and qualifies the right participants in its global network of 30 million people. But building that panel required confronting what Wahlforss called "one of the most shocking things that we've learned when we entered this industry"—rampant fraud.

"Essentially, there's a financial transaction involved, which means there will be bad players," he explained. "We actually had some of the largest companies, some of them have billions in revenue, send us people who claim to be kind of enterprise buyers to our platform and our system immediately detected, like, fraud, fraud, fraud, fraud, fraud."

The company built what it calls a "quality guard" that cross-references LinkedIn profiles with video responses to verify identity, checks consistency across how participants answer questions, and flags suspicious patterns. The result, according to Wahlforss: "People talk three times more. They're much more honest when they talk about sensitive topics like politics and mental health."

Emeritus, an online education company that uses Listen, reported that approximately 20% of survey responses previously fell into the fraudulent or low-quality category. With Listen, they reduced this to almost zero. "We did not have to replace any responses because of fraud or gibberish information," said Gabrielli Tiburi, Assistant Manager of Customer Insights at Emeritus.

How Microsoft, Sweetgreen, and Chubbies are using AI interviews to build better products

The speed advantage has proven central to Listen's pitch. Traditional customer research at Microsoft could take four to six weeks to generate insights. "By the time we get to them, either the decision has been made or we lose out on the opportunity to actually influence it," said Romani Patel, Senior Research Manager at Microsoft.

With Listen, Microsoft can now get insights in days, and in many cases, within hours.

The platform has already powered several high-profile initiatives. Microsoft used Listen Labs to collect global customer stories for its 50th anniversary celebration. "We wanted users to share how Copilot is empowering them to bring their best self forward," Patel said, "and we were able to collect those user video stories within a day." Traditionally, that kind of work would have taken six to eight weeks.

Simple Modern, an Oklahoma-based drinkware company, used Listen to test a new product concept. The process took about an hour to write questions, an hour to launch the study, and 2.5 hours to receive feedback from 120 people across the country. "We went from 'Should we even have this product?' to 'How should we launch it?'" said Chris Hoyle, the company's Chief Marketing Officer.

Chubbies, the shorts brand, achieved a 24x increase in youth research participation—growing from 5 to 120 participants — by using Listen to overcome the scheduling challenges of traditional focus groups with children. "There's school, sports, dinner, and homework," explained Lauren Neville, Director of Insights and Innovation. "I had to find a way to hear from them that fit into their schedules."

The company also discovered product issues through AI interviews that might have gone undetected otherwise. Wahlforss described how the AI "through conversations, realized there were like issues with the the kids short line, and decided to, like, interview hundreds of kids. And I understand that there were issues in the liner of the shorts and that they were, like, scratchy, quote, unquote, according to the people interviewed." The redesigned product became "a blockbuster hit."

The Jevons paradox explains why cheaper research creates more demand, not less

Listen Labs is entering a massive but fragmented market. Wahlforss cited research from Andreessen Horowitz estimating the market research ind…

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🔗 Sumber: venturebeat.com

📌 MAROKO133 Hot ai: Elon Musk Orders Sweeping Layoffs as xAI Fails to Catch Up Waj

In a Thursday tweet, Elon Musk said he was looking to rebuild his AI startup xAI “from the foundations up” after admitting it wasn’t “built right first time around.”

The news comes amid a major exodus of cofounders, with a striking majority of them jumping ship over the last year. Amid the resulting leadership vacuum, the Financial Times reported on Friday that Musk had omitted a key detail in his latest missives on his social media platform. According to the paper’s sources, he’s ordered a round of sweeping layoffs at the company after becoming frustrated with a lack of progress on its AI coding software.

Many roles are reportedly being scrutinized. Musk reportedly ordered higher-ups from Tesla and SpaceX, the latter of which xAI was folded into earlier this year, to conduct audits and weed out anybody deemed to be underperforming — likely not what staffers, who were already complaining of burnout, wanted to hear.

The news comes just over a month after Musk announced he had “reorganized” xAI, admitting that it “unfortunately required parting ways with some people.”

The pressure is on. Following SpaceX and xAI’s merger, the space company is looking to go public at a staggering valuation of $1.25 trillion.

But keeping up in the heated AI race is proving far more difficult than Musk may have anticipated, given his decision to rework the entire thing mere months ahead of the biggest stock market listing in history.

Coding, in particular, has become a major focus, with Musk poaching two senior employees from AI coding startup Cursor. According to the FT, staffers have grown concerned that the training data of xAI’s chatbot Grok was lacking, causing it to lag far behind Anthropic’s popular Claude Code and OpenAI’s Codex.

“Grok is currently behind in coding,” Musk said at a conference earlier this week, as quoted by Business Insider. “The reason I was late for this was that I was just in a giant sort of all-hands on coding, going through all the things that need to happen to essentially exceed our competitors on coding, which I think we’ll do.”

Musk’s messaging surrounding the company’s AI product has been opaque. In August, the mercurial CEO announced the company’s latest AI project, “Macrohard,” a tongue-in-cheek jab squarely aimed at competitor Microsoft. Musk also said that he was combining Tesla and xAI’s efforts to develop a “digital Optimus,” a nod to the carmaker’s humanoid robot.

The man who was leading the “Macrohard” effort, former DeepMind researcher Toby Pohlen, left the company just 16 days after being put in charge of the project late last month.

Where that leaves the future of xAI’s coding tool remains to be seen.

Apart from being pushed out by Musk, who’s now trying to reboot the company from scratch, inside sources told the paper that people are quitting because they’re burnt out, an unsurprising development given the CEO’s infamously brutal micromanagement style. Insiders told the FT that the revolving door of talent was destroying morale.

“My next priorities: sleep for more than 8h, write down all the things I’ve learnt (I have a list), and then think about what I want to do next,” Pohlen wrote.

More on xAI: Elon Musk Says He’s Epically Screwed Up at xAI, Is Rebuilding “From the Foundations”

The post Elon Musk Orders Sweeping Layoffs as xAI Fails to Catch Up appeared first on Futurism.

🔗 Sumber: futurism.com