Category: Business

Canary Capital thrust Pepe into the limelight on Wednesday with an application for an exchange-traded fund that tracks the meme coin’s price, but the token’s muted reaction may serve as the latest sign of Wall Street’s tepid appetite for assets that trade on vibes.

On Thursday, Pepe changed hands around $0.00000359, up about 0.6% over the last day, according to CoinGecko. The day before, trading volume rose 10% to $432 million.

Not long ago, meme coins served as key growth drivers for firms like Wintermute. Yet the crypto market maker acknowledged last year that its prediction of a core asset manager debuting a meme coin ETF, particularly Dogecoin, was intended to be tongue-in-cheek.

Today, four crypto asset managers offer U.S.-listed Dogecoin ETFs. Still, it remains “very hard for institutional investors to construct a credible investment rationale around something like Doge, which is perhaps more geared towards the retail audience,” James Butterfill, head of research at crypto asset manager CoinShares, told Decrypt.

Dogecoin is ranked 17th out of all crypto ETFs that CoinShares tracks, generating $13 million worth of year-to-date inflows. Outside of ETFs tracking Bitcoin, Ethereum, Solana, and XRP, Butterfill noted that ETFs tied to other altcoins represent 9% of total assets under management.

“They’re just not popular with investors,” he said. “It’s the big four and not much else.”

Decrypt has reached out to Canary for comment.

SEC Chair Paul Atkins indicated last November that most cryptocurrencies, including meme coins, shouldn’t be treated as securities. That sentiment was bolstered by SEC guidance published last month, which categorized meme coins as a form of “digital collectibles.”

Under generic listing standards for crypto ETFs established last year, exchanges are able to list commodity-based ETFs without requiring case-by-case approval. Among key factors, digital assets underlying them have to have a six-month history of regulated futures trading.

Pepe futures currently trade on crypto exchange Kraken. Canary’s filing noted that contracts for the meme coin “are typically traded on regulated or registered trading venues.”

Canary has filed applications for ETFs that track other meme coins, including Mog, Pudgy Penguins’ PENGU, and President Donald Trump’s meme coin, TRUMP. Bloomberg Senior ETF Analyst Eric Balchunas expressed skepticism that the Trump-related ETF would pass when Canary’s application landed on the SEC’s desk last year, citing a lack of futures trading.

Balchunas once noted to Decrypt that the ETF industry is famous for “throwing spaghetti at the wall.” Meanwhile, Butterfill described a flurry of filings across ETFs from some issuers on Thursday as a “machine gun approach.”

Tuttle Capital Management, in some ways, has taken further steps to appeal to degens. In January, the ETF issuer filed applications for leveraged TRUMP, BONK, and MELANIA ETFs. But the SEC hasn’t offered a final verdict on those applications yet.

Enterprise revenue now makes up more than 40% of AI behemoth OpenAI’s total revenue, according to the company. And it’s on pace to reach parity with consumer revenue by the end of 2026.

OpenAI hit $25 billion in annualized revenue in February, up from $20 billion at the end of 2025.

“I have never seen this level of conviction spread so quickly and consistently within the industries,” OpenAI Chief Revenue Officer Denise Dresser, who spent more than a decade at Salesforce before running Slack, wrote in an official note on Wednesday.

Companies at the front of this wave have moved well past using AI to write emails or summarize documents. They’re now deploying what Dresser calls “teams of agents,” basically groups of AI systems that coordinate with each other, hold context across sessions, and take action inside business tools without constant human oversight. The question seems to have shifted from “should we use AI?” to “how many agents should we run?”

OpenAI launched its enterprise agent platform to build a user base beyond everyday retail consumers, who are still its core revenue stream. Codex, its AI coding agent, has already crossed 3 million users, a figure that was, according to Dresser, “almost zero” at the start of the quarter. Paying business users hit 9 million in February, up from 5 million in August. Weekly active users across all of OpenAI’s products reached 910 million.

The company also launched ChatGPT Agent, which can plan trips, book hotel rooms, research competitors, generate slide decks, and place online orders without a human in the loop.

But as hyped up as agentic AI is, Dresser believes companies need a straightforward path to integrate the tech without rebuilding their business structure.

“What’s really missing still for most companies is just a simple way to unleash the power of agents as teammates that can operate inside the business without the need to rework everything,” she said. OpenAI’s agent platform wants to be the answer to that problem.

OpenAI recently brought on Peter Steinberger, founder of the world’s most popular open source agentic AI platform OpenClaw, to lead its push into personal AI agents—a signal that the company isn’t only building for corporations. OpenAI CEO Sam Altman has positioned multi-agent systems at the center of OpenAI’s next product phase, and the momentum behind enterprise adoption suggests that framing is holding up in the market.

The company is also preparing for an IPO, with CFO Sarah Friar confirming this week that retail investors will get a share of the allocation. OpenAI projects reaching $85 billion in revenue by 2030—a number that only makes sense if agents become the default way businesses interact with AI, not just a feature layered on top of a chat interface.

Researchers from the Google Cloud AI team have introduced PaperOrchestra, an AI framework that autonomously transforms messy lab notes and scattered research data into submission-ready academic manuscripts.

Unlike existing AI writing tools that focus on text generation, the system aims to tackle the full intellectual workflow of academic paper creation—from organizing raw materials to generating figures and conducting literature reviews.

The system employs five specialized agents working in parallel: Outline Agent, Plotting Agent, Literature Review Agent, Section Writing Agent, and Content Refinement Agent. Each agent handles specific aspects of manuscript preparation, from structuring arguments to creating visualizations and ensuring proper academic citations through API-grounded references.

To evaluate performance, researchers created PaperWritingBench, the first standardized benchmark reverse-engineered from 200 top-tier AI conference papers. In side-by-side human evaluations, researchers noted, PaperOrchestra achieved win rate margins of 50%-68% for literature review quality and 14%-38% for overall manuscript quality compared to autonomous baselines.

PaperOrchestra emerges as AI systems are increasingly making inroads on knowledge work and specialized domains that are traditionally the preserve of humans, with the emergence of AI research agents and growing evidence of AI ghostwriting in academic papers.

The framework’s multi-agent approach—where specialized components tackle different aspects of a complex task—mirrors similar architectures being deployed across legal document analysis, financial modeling, and other domains requiring multi-step intellectual processes.

The use of AI tools in academic research has proved divisive, however, with some scholars dismissing the practice as “vibe coding,” and noting that the flood of AI-assisted papers in certain fields is putting “considerable strain” on peer-review systems.

Meta and CoreWeave have expanded a long-term artificial intelligence infrastructure agreement worth about $21 billion, extending their partnership through December 2032. Both companies have seen their shares rise Thursday following the announcement.

CoreWeave announced the expanded deal Thursday, describing it as an extension of the companies’ existing relationship and an increase in infrastructure supporting Meta’s AI operations.

“This is another example that leading companies are choosing CoreWeave’s AI cloud to run their most demanding workloads,” CoreWeave co-founder, CEO, and Chairman Michael Intrator said in a statement.

The agreement gives Meta access to AI cloud capacity from CoreWeave to support the development and deployment of its AI systems, including inference workloads that run trained models at scale.

The infrastructure will be deployed across multiple locations and will include some of the first deployments of Nvidia’s Vera Rubin platform. CoreWeave said the distributed deployment is intended to optimize performance, resilience, and scalability for Meta’s AI systems, and reflects rising demand for infrastructure capable of supporting large-scale AI workloads.

Meta and CoreWeave previously struck a $14 billion AI infrastructure deal in 2025, under which the cloud provider agreed to supply computing power to Meta through 2031.

The news comes as Meta accelerates its push into advanced AI systems. On Wednesday, the company introduced Muse Spark, a natively multimodal model capable of processing text, images, and voice and designed to tackle complex reasoning tasks using multiple AI agents.

Meta has also outlined a new Advanced AI Scaling Framework that expands how it evaluates risks and tests its most capable models before deployment.

“As we build more capable and more personalized AI, reliability, security, and user protections are more important than ever,” Meta said in a statement. “Advanced models require an advanced approach to safety—one that scales with the technology.”

Shares of Meta and CoreWeave rose after the companies announced their expanded AI infrastructure deal. Currently, Meta (META) is trading above $630 per share, up about 3% on the day, while CoreWeave (CRWV) has jumped 5.5% to a recent price of $93.70.