Traders on prediction market platform Kalshi are increasingly betting that the U.S. Federal Reserve could raise interest rates again before the end of the year, underpinning persistent concerns about inflation even as policymakers remain divided over the appropriate path for monetary policy.

The latest pricing on Kalshi assigns a 54% probability that the Fed will deliver at least one interest rate increase this year. Although that is slightly lower than the 56% probability seen a day earlier, it still suggests that market participants view another rate hike as more likely than not.

The contract tracks when the next increase in the federal funds rate will occur, with outcomes covering a hike before the end of 2026, before July 2027, or before the end of 2027.

Beyond this year, traders see an even greater likelihood that U.S. borrowing costs will move higher.

Kalshi currently assigns a 62% probability that the Federal Reserve will raise rates before July 2027 and nearly an 80% chance that a rate increase will occur by 2028. The market expectations emerged shortly after the Federal Reserve released minutes from its June policy meeting, offering investors a clearer picture of how deeply divided officials remain over the direction of interest rates.

According to the minutes, policymakers expressed sharply different views on where the federal funds rate should stand by the end of the year. The document noted that “many participants” believed the appropriate policy rate would remain within or slightly below its current target range by year-end. However, the minutes also revealed that “many other participants” concluded the appropriate level of interest rates would be above the current target range before the end of the year.

The split underscores the difficult balancing act confronting the central bank as it attempts to contain inflation without unnecessarily slowing economic growth. The Federal Reserve’s benchmark interest rate currently stands at 3.50% to 3.75%, where it has remained since December 2025.

The debate over future policy comes as inflationary pressures continue to challenge policymakers. The Fed’s preferred inflation measure, the Personal Consumption Expenditures (PCE) Price Index, rose 4.1% year over year in May, its highest annual reading since April 2023.

The stronger-than-expected inflation data have bolstered concerns that price pressures remain too persistent for the central bank to begin easing monetary policy. In addition to domestic inflation, policymakers are also monitoring geopolitical developments, including rising tensions in the Middle East, which have the potential to push energy prices higher and add further pressure to consumer prices.

Those factors have complicated the Fed’s inflation outlook and contributed to differing opinions among officials about whether policy should remain restrictive or become even tighter.

Kalshi traders are also signaling that they expect little prospect of lower interest rates this year. A separate prediction market asking how many rate cuts the Federal Reserve will implement during 2026 currently assigns approximately a 76% probability that there will be no rate cuts before year-end.

Those expectations have remained relatively stable in recent weeks. The probability of no rate cuts rose sharply from 68% to 77% on June 16, coinciding with the first Federal Open Market Committee meeting chaired by Federal Reserve Chairman Kevin Warsh.

Since then, the market’s expectations have changed only modestly, including after the release of the June meeting minutes.

The prediction market’s outcome will ultimately be determined by the Federal Reserve’s official policy decisions. The divergence between policymakers’ views reflects the uncertainty surrounding the U.S. economy. Some officials believe inflation is likely to moderate sufficiently to allow interest rates to remain unchanged or edge lower, while others argue that persistent price pressures warrant maintaining restrictive policy for longer or even tightening further.

However, analysts believe the June minutes have offered investors few clear signals about the Fed’s next move, but confirmed that monetary policy remains highly data-dependent.

Future inflation reports, labor market data, and broader economic indicators are expected to play a decisive role in determining whether the central bank holds rates steady or concludes that further tightening is necessary to return inflation to its long-term target.

With prediction markets assigning only a slim majority to another rate increase while policymakers themselves remain divided, expectations for the remainder of the year remain finely balanced.

Artificial intelligence companies continue to consume vast amounts of online content while sending relatively little traffic back to the websites that produce it, according to new data from Cloudflare.

The development has bolstered growing concerns over the sustainability of the internet’s long-standing economic model.

The latest figures, covering the week of July 1 to July 7, show that Anthropic remains the largest outlier among major AI developers, with its web crawlers requesting pages roughly 2,800 times for every single referral its services sent back to publishers.

While that marks a substantial improvement from early April, when Cloudflare estimated Anthropic’s crawl-to-referral ratio at around 8,800-to-1, the broader trend suggests the company’s AI systems continue to collect online content at a pace that far exceeds the amount of traffic they return.

Cloudflare’s data also indicates that the improvement may not represent a sustained change.

During the first week of May, Anthropic’s bots reportedly crawled websites approximately 24,700 times for every referral, illustrating how dramatically the ratio can fluctuate over relatively short periods.

Among the major AI companies tracked by Cloudflare, OpenAI ranked second behind Anthropic, followed by AI search startup Perplexity. Microsoft and Google recorded lower crawl-to-referral ratios, while search engine DuckDuckGo stood out as one of the few companies approaching a more balanced exchange.

According to Cloudflare, DuckDuckGo generated roughly one referral for every three webpage crawls, a ratio far closer to the traditional relationship that has historically existed between search engines and publishers.

The data comes as AI-powered search tools increasingly replace conventional web searches.

For decades, website owners generally accepted search engines crawling their content because indexing generated traffic that could be monetized through advertising, subscriptions, or product sales.

The arrangement created a mutually beneficial ecosystem.

Search engines gained access to information, while publishers received visitors who generated revenue.

Generative AI is fundamentally changing that relationship.

Instead of directing users to external websites, AI chatbots and AI-powered search engines increasingly provide complete answers within their own interfaces. As a result, users often obtain the information they need without ever visiting the original source.

That shift has become one of the publishing industry’s biggest concerns as AI adoption accelerates. This is because if AI systems continue extracting content while reducing referral traffic, publishers could face declining advertising revenue and fewer incentives to invest in producing original journalism, research and educational material.

Cloudflare’s crawl-to-referral metric has therefore become an increasingly watched indicator of how AI companies interact with the broader web. Rather than measuring the absolute amount of data collected, the metric compares how frequently AI crawlers request webpages against how often users are sent back to those same sites.

Although the ratio does not capture every aspect of publisher traffic, it offers a proxy for whether AI companies are maintaining the economic exchange that has historically supported the open internet.

Anthropic’s position is particularly notable because the company has frequently emphasized AI safety and responsible development as core elements of its business strategy. The latest figures have therefore renewed debate over what constitutes responsible behavior when AI systems rely heavily on publicly available web content for search, retrieval and other services.

At the same time, Anthropic has recently taken a firm stance against the unauthorized use of its own AI technology. The company has criticized competitors for allegedly using outputs generated by Anthropic’s models to improve their own systems through a practice commonly referred to as model distillation. Anthropic argues that such activities violate its terms of service because they involve using its AI-generated outputs to train competing models.

Many companies in the AI industry now object to competitors using their proprietary AI outputs for commercial purposes while simultaneously relying on vast quantities of online content created by publishers, writers, researchers and other content producers.

Publishers have argued that AI companies should compensate content creators when their material contributes to commercial AI products, particularly as chatbot-generated answers reduce visits to original websites. Anthropic is currently facing a lawsuit for unlawful use of publishers contents.

Anthropic has previously challenged Cloudflare’s analysis.

The company said it could not independently verify Cloudflare’s methodology for calculating crawl-to-referral ratios and argued that recently introduced search features are increasing the number of users directed back to publishers. That suggests that Anthropic believes the reported figures may not fully reflect how its services generate referral traffic.

Google is rolling out a new feature that will allow users to see whether advertisements were created or modified using artificial intelligence, marking a broader push to improve transparency as generative AI becomes increasingly integrated into digital advertising.

The new disclosure tool expands Google’s efforts to help consumers distinguish between authentic product imagery and AI-generated content, addressing growing concerns that synthetic images could blur the line between marketing and reality.

The feature will be available through Google’s My Ad Center, which users can access globally by clicking the three-dot menu or information icon displayed on advertisements appearing in Google Search, YouTube, and Google Discover.

New “How this ad was made” section

Under the update, users will see a new option labeled “How this ad was made.”

When selected, the feature will indicate whether an advertisement was created or edited using artificial intelligence.

The disclosure is intended to provide additional context rather than suggest that AI-generated advertisements violate Google’s advertising policies.

Google continues to prohibit deceptive or misleading advertising regardless of whether AI is used to produce the content. Instead, the company said the new labels are designed to give users greater visibility into how digital advertisements are produced as AI-generated marketing materials become more common.

The move was necessitated by the rapid adoption of generative AI across the advertising industry. Businesses increasingly use AI tools to generate product images, create promotional graphics and place merchandise into digitally generated environments without conducting traditional photo shoots.

For advertisers, the technology can significantly reduce production costs, shorten campaign development times, and allow brands to produce multiple versions of advertisements tailored to different audiences. Retailers, for example, can use AI to place clothing, furniture or consumer products into a wide range of virtual settings without photographing each item individually.

While those capabilities improve efficiency, they have also raised concerns that consumers may assume AI-generated images are genuine photographs of products, potentially creating unrealistic expectations.

The new disclosure aims to address that concern by informing users when synthetic content has been used in creating an advertisement.

Automatic Labels for Google’s AI Tools

Google said advertisers using the company’s own generative AI advertising tools will not need to take additional action. If an advertisement is created using Google’s AI products, the disclosure will be applied automatically.

However, advertisements produced with third-party AI software will rely on advertiser self-reporting.

Google is introducing a new control that allows advertisers to indicate whether AI played a role in creating or editing their advertisements. The company said it will not independently verify whether third-party advertisements were generated using artificial intelligence. Instead, responsibility for providing accurate disclosures will rest with advertisers.

In certain jurisdictions, advertisements may also receive AI labels where required under local laws or regulations governing synthetic media.

The update represents a significant expansion of Google’s AI transparency efforts. Until now, the company primarily required AI-related disclosures for election advertising, where concerns about manipulated media and misinformation have attracted heightened regulatory scrutiny.

The broader rollout is targeted at the growing prevalence of generative AI in commercial advertising, where synthetic images and videos are increasingly used for mainstream marketing campaigns rather than only for political communications.

As AI-generated content becomes more sophisticated and often indistinguishable from traditional photography, technology companies have faced increasing pressure from regulators and consumer advocates to provide clearer disclosures.

However, Google’s move aligns with wider efforts across the technology industry to improve transparency around AI-generated content.

Governments in several jurisdictions are considering or implementing rules requiring companies to disclose the use of synthetic media, particularly where consumers could mistake AI-generated content for authentic images or videos.

Technology companies have also introduced measures such as digital watermarking, metadata standards and AI-generated content labels to help identify synthetic media.

Google said the feature will be available globally, giving users a clearer understanding of how the advertisements they encounter across Google’s platforms were created as artificial intelligence becomes a common tool in online marketing.