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

📌 MAROKO133 Eksklusif ai: Listen Labs raises $69M after viral billboard hiring stu

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 Eksklusif ai: Anthropic says DeepSeek, other Chinese AI firms scraped

Anthropic has accused three major Chinese AI firms of using fraudulent accounts to extract data from its Claude models in an effort to boost rival systems.

The San Francisco-based company said DeepSeek, MiniMax Group Inc. and Moonshot collectively generated more than 16 million exchanges with Claude by creating thousands of fake accounts and using proxy services to avoid detection.

The tactic, known as distillation, allows developers to train their own models on the outputs of more advanced systems.

Anthropic said the activity violated its terms of service and was aimed at reconstructing Claude/s higher-end capabilities.

DeepSeek alone generated more than 150,000 exchanges, while MiniMax accounted for more than 13 million interactions, the company said in a blog post on Monday.

The allegations come just over a week after Sam Altman-led OpenAI made similar claims against Chinese AI developers, intensifying scrutiny in Washington over whether these firms are gaining ground by leveraging American-built systems.

Distillation race heats up

Distillation is a common machine learning technique in which a smaller model learns from the outputs of a larger, more capable one. But Anthropic claims the scale and method used in this case crossed a line.

“These campaigns are growing in intensity and sophistication,” Anthropic said in the blog post. “The window to act is narrow, and the threat extends beyond any single company or region.”

The company said it identified the actors with “high confidence” by analyzing internet protocol addresses, metadata and corroborating signals from industry partners that observed similar behavior on their own platforms.

Proxy networks, which can mask a user’s location and identity online, were allegedly used to create and operate large volumes of accounts. Such networks can enable access from restricted regions and help users evade platform safeguards.

China’s AI surge worries US

DeepSeek shook the AI sector last year with the release of its R1 model, which it claimed was built at a fraction of the cost of leading US systems.

Since then, Chinese firms have rolled out a wave of lower-cost text, video and image generation tools, increasing pressure on American companies trying to monetize advanced AI.

OpenAI recently warned US lawmakers that DeepSeek had used distillation techniques as part of “ongoing efforts to free-ride on the capabilities developed by OpenAI and other US frontier labs.”

US officials, including White House AI czar David Sacks, have also raised concerns about the practice.

MiniMax debuted on public markets in January, while Moonshot is reportedly seeking a $10 billion valuation in a new funding round. The rapid expansion of these firms underscores how quickly China’s AI ecosystem is scaling.

Anthropic said it has strengthened its detection and verification systems to counter large-scale distillation efforts and is sharing threat intelligence with other AI developers.

“No company can solve this alone,” the company said. “Distillation attacks at this scale require a coordinated response across the AI industry, cloud providers and policymakers.”

🔗 Sumber: interestingengineering.com