According to federal prosecutors, Michele Spagnuolo made more than $1 million on the prediction market platform using confidential information about Google Search traffic. A Google security engineer has been charged with crimes stemming from allegedly placing trades on Polymarket using confidential internal information from the tech giant. Michele Spagnuolo, a 36-year-old Italian citizen, was arrested this morning in New York, as first reported by ABC News. Spagnuolo is charged with one count each of commodities fraud, wire fraud, and money laundering. He has worked at Google since 2014 and was based out of the company's Zurich, Switzerland, offices.

Amid ongoing economic anxieties, BLK and other companies are giving away basic essentials to appeal to the public. While Gen Z catches a lot of flack for being single, or even antisocial, there's a brutal economic reality underscoring why some people aren't going out: They simply don't have the disposable income . Dating apps, already struggling to maintain user bases due to enshittification and a lack of quality matches, are contending with this affordability crisis. In a dystopian sign of the times, BLK, the app for Black singles, announced on Wednesday that it is giving away free gas in an attempt to incentivize people to go on dates. As part of the promotion, BLK is providing $500 gas gift cards to 10 people who download the app and tag three friends in the campaign post across its social channels.

CFTC chairman Michael Selig sat down with WIRED to discuss how the agency scours Polymarket and other prediction markets for illegal activity. For most of the past year, it looked like prediction markets had kicked off a new golden age of fraud. On Polymarket, traders raked in fortunes from suspiciously timed bets on geopolitical events like the raid on Venezuela and the Iran War. It wasn't clear whether the US government would bother pursuing some of the most flagrant bad actors, since Polymarket's crypto-based platform was technically offshore and not regulated or licensed within the country. Now, however, the Commodity Futures Trading Commission, which oversees prediction markets, wants you to know that it's watching very, very closely.

Truth Predict was supposed to be the Trump family's biggest leap yet into prediction markets. Now it's looking more like a tiptoe. The odds that the Trump family will launch a full-fledged prediction market product this year just plummeted. Last year, the Trump Media and Technology Group announced Truth Predict, a partnership with the cryptocurrency company Crypto.com. The initial announcement touted Truth Predict as a "new product" that would allow Truth Social users to make trades on sports, inflation, elections, and more through an "embedded" prediction market service.

A new executive order seen by WIRED prohibits New York state employees from using insider knowledge to enrich themselves with prediction market bets. New York has banned state employees from using insider information to trade on prediction markets . In an executive order signed today and viewed by WIRED, Governor Kathy Hochul forbade the state's government workforce from using "any nonpublic information obtained in the course of their official duties" to participate on prediction market platforms, or to help others profit using those services. "Getting rich by betting on inside information is corruption, plain and simple," Hochul said in a statement provided to WIRED. "Our actions will ensure that public servants work for the people they represent, not their own personal enrichment. While Donald Trump and DC Republicans turn a blind eye to the ethical Wild West they've created, New York is stepping up to lead by example and stamp out insider trading."

As the prediction market boom continues, backlash is growing, too, with Arizona filing criminal charges against Kalshi and public outcry after Polymarket traders threatened a journalist. Kalshi CEO Tarek Mansour posted a video on Wednesday of six men decked out in business casual doing push-ups on the sidewalk. "This is how Kalshi Q1 board meeting ended," he wrote on X. The board members are laughing and smiling in the video after their impromptu cardio session, and the mood is jubilant. The next day, it became clear that the team had ample reason to celebrate: Kalshi had just raised $1 billion at a $22 billion valuation, making the company worth on paper roughly double what it was only a few months ago.

A judge ordered Kalshi to immediately halt sports and election contracts in the state, intensifying a growing regulatory battle over prediction markets. Kalshi has been temporarily banned in Nevada, marking the latest escalation in the widening regulatory war over prediction markets. The First Judicial District Court of Nevada has issued a 14-day restraining order, effective immediately, barring the company from "offering a derivatives exchange and prediction market which offers event-based contracts relating to sports, election, and entertainment related events" without first obtaining gaming licenses. This is the first time a US state has forced the company to cease operations. This particular legal battle began just over a year ago, when Nevada regulators sent Kalshi a cease-and-desist letter demanding that it stop offering sports-related events contracts.

Prediction markets like Kalshi and Polymarket are booming, and so is a fight among regulators, lawmakers, and advocates over their legality. Former New Jersey governor Chris Christie, who currently serves as an advisor to the American Gaming Association, has criticized prediction markets. The political fight in the US over the future of prediction markets like Polymarket and Kalshi has escalated into a full-blown war, and battle lines aren't being neatly drawn along party lines. Instead, conservative Mormons have aligned themselves with Las Vegas bigwigs and MAGA royalty is siding with liberal Democrat lobbyists. One side argues that the platforms are breaking the law by operating as shadow casinos.

Reinforcement Learning with Verifiable Rewards (RLVR) has been an effective approach for improving Large Language Models' reasoning in domains such as coding and mathematics. Here, we apply RLVR methods towards forecasting future real-world events - a challenging task for RL due to the very noisy (and delayed) outcomes involved. Using a novel dataset of recent questions from a prediction market, and accompanying relevant news headlines, we show that a compact (14B) reasoning model can be trained to match or surpass the predictive accuracy of frontier models like o1, while greatly improving probabilistic calibration. The model's performance is also practically meaningful: in a Polymarket trading simulation, we estimate that its bets would have yielded a return on investment of over 10% across all questions in the test set. We detail and compare approaches used in training our model, including augmenting our training-data with synthetic prediction questions, guardrails for learning stability, and median prediction sampling at inference-time.