Grammarly has announced the acquisition of Superhuman, the high-speed, AI-powered email client, marking its most ambitious step yet toward transforming into a full-scale AI productivity platform.

The deal, disclosed Tuesday, comes as Grammarly seeks to deepen its foothold in core professional workflows and bring its AI capabilities into a tool that professionals use every day: email.

Though neither Grammarly nor Superhuman disclosed the financial terms of the acquisition, the move is significant. Superhuman, founded by Rahul Vohra, Vivek Sodera, and Conrad Irwin, has raised more than $114 million from top-tier investors such as Andreessen Horowitz (a16z), IVP, and Tiger Global. The company was last valued at $825 million, according to data from venture analytics firm Traxcn.

Over 100 Superhuman employees, including CEO Rahul Vohra, will join Grammarly as part of the deal.

A Strategic Expansion into Email

Grammarly CEO Shishir Mehrotra said the acquisition aligns with the company’s vision of embedding AI deeply into daily professional tasks and enabling seamless collaboration between multiple AI agents.

“Email isn’t just another app; it’s where professionals spend significant portions of their day, and it’s the perfect staging ground for orchestrating multiple AI agents simultaneously,” Mehrotra said in a statement.

With the acquisition, Grammarly gains direct control over a well-loved email platform optimized for speed, intelligence, and user focus. It also brings in a layer of innovation that Superhuman had been building over recent months, including features that assist with scheduling, replying, triaging, and categorizing emails—using AI.

Superhuman CEO Rahul Vohra echoed the synergy between the two companies, stating that “Email is the main communication tool for billions of people worldwide and the number-one use case for Grammarly customers.” He added that joining forces with Grammarly would allow Superhuman to invest more in its core experience while pioneering a new way of working where AI agents assist users across daily communication tools.

Building the Future of AI Workflows

Grammarly’s ambitions go beyond spelling and grammar. In recent years, the company has been quietly transforming its business model to encompass full-spectrum productivity. In 2023, Grammarly acquired Coda, a collaborative document platform, and elevated Coda co-founder Shishir Mehrotra to CEO. Now, with Superhuman, Grammarly owns not just how people write and collaborate—but also how they communicate.

The company is pursuing a vision where multiple AI agents work in unison to help users handle their work more effectively. Email, given its frequency of use and complexity, is now central to that plan.

“The future of productivity will be shaped by AI agents that can handle tasks like drafting responses, prioritizing messages, managing schedules, and integrating across platforms,” Grammarly said in a blog post. “With Superhuman, we now have the foundation to make this vision a reality.”

Grammarly’s latest move positions it more directly against other tech giants like Google, Microsoft, and Salesforce, all of which are embedding AI across email and productivity suites. What differentiates Grammarly is its singular focus on agentic AI—that is, purpose-specific AI agents capable of working across tools, understanding user context, and executing semi-autonomous tasks.

The company also has the financial backing to support this vision. In May, Grammarly secured a $1 billion non-dilutive investment from General Catalyst. Rather than give up equity, Grammarly will repay the money as a capped percentage of revenue generated from projects funded with the capital. The investment gives Grammarly the fuel to scale its product vision without diluting existing shareholder value.

Grammarly plans to integrate Superhuman’s functionality into its broader suite while continuing to support Superhuman as a standalone email client. Users can expect features such as AI-powered triage, personalized summaries, and multi-agent task execution to begin appearing in both platforms in the coming months.

Additionally, Grammarly says its acquisition of Superhuman accelerates its goal of making email a command center for agentic AI—where users can draft responses, schedule meetings, file attachments, and automate workflows without switching apps.

The company is also eyeing enterprise adoption, with Superhuman’s speed and efficiency complementing Grammarly’s growing suite of enterprise tools. Email remains a universal and essential tool for professional communication, and owning the stack allows Grammarly to embed intelligent agents directly into one of the most time-consuming areas of work.

The acquisition comes amid heightened competition in the AI productivity space. Microsoft is embedding its Copilot AI across Outlook and Teams, Google is pushing Gemini into Gmail and Docs, and startups like Anthropic and Notion are racing to define how AI integrates with daily workflows.

With over 40 million daily users and more than 50 million weekly email-based corrections already running through its systems, Grammarly has the user base and data pipeline to make its agentic vision a reality. Owning Superhuman adds a premium, fast-moving frontend to that backend infrastructure.

Microsoft has unveiled results from a major internal study claiming its medical AI system, dubbed the AI Diagnostic Orchestrator, outperformed experienced human doctors by a wide margin in diagnosing complex medical cases.

In a blog post released Monday, the company said the AI system correctly diagnosed nearly 86% of clinical cases tested—four times more accurately than human physicians working under the same constraints.

The tech giant’s announcement comes as artificial intelligence continues to push deeper into healthcare, raising both hopes for innovation and urgent questions about the future role of doctors in an AI-driven medical environment.

Inside the Study: AI vs. Doctors

The Microsoft-led study involved 304 real-world clinical case studies taken from the New England Journal of Medicine, a source widely respected for its complexity and diagnostic rigor. In the trial, the AI and 21 practicing physicians from the U.S. and U.K. were asked to diagnose the cases in stages—mirroring real-life practice—by ordering tests, asking follow-up questions, and narrowing down differential diagnoses.

Physicians participating in the study had between five and 20 years of clinical experience but were restricted from using tools they would typically rely on—like reference books, second opinions, or digital assistants.

While the doctors achieved an average diagnostic accuracy of just 20%, Microsoft’s AI system, when paired with OpenAI’s new o3 large language model, correctly diagnosed 85.5% of the cases. Microsoft tested the AI with other models too, including those from Meta, Anthropic, and Google, but found the strongest results in the OpenAI collaboration.

Cost, Accuracy, and Efficiency

Beyond accuracy, Microsoft also claimed that its AI solved cases more cost-effectively, raising the possibility of reducing waste in healthcare—a key concern in the U.S., where nearly 20% of GDP is spent on health, and up to 25% of that is believed to be unnecessary or wasteful.

In Microsoft’s view, AI could address both cost and diagnostic quality simultaneously.

“Our findings also suggest that AI can reduce unnecessary healthcare costs,” the company wrote, pointing to misdiagnosis, redundant testing, and administrative delays as areas ripe for disruption.

Mustafa Suleyman, head of Microsoft AI and cofounder of DeepMind, called the study a “big step toward medical superintelligence,” adding that the cases used were “some of the toughest and most diagnostically complex” challenges that doctors face.

Does This Mean AI Will Replace Doctors?

Despite the eye-catching headline numbers, Microsoft was careful to say that the goal is not to replace doctors, but to augment them.

“This technology represents a complement to doctors and other health professionals,” the company stated.

“While this technology is advancing rapidly, clinical roles are much broader than simply making a diagnosis. They need to navigate ambiguity and build trust with patients and their families in a way that AI isn’t set up to do,” Microsoft added.

Healthcare professionals appear to agree. Dr. Shravan Verma, CEO of a Singapore-based health tech startup, told Business Insider last month that AI tools may be well suited for handling the “first mile” of healthcare—triage, information gathering, or simple diagnosis—but emphasized that “AI can’t replicate physicians’ presence, empathy, and nuanced judgment in uncertain or complex conditions.”

However, others in tech are more bullish. Microsoft co-founder Bill Gates previously said on the People by WTF podcast in April that AI could eventually help solve the global shortage of doctors, arguing that AI systems could deliver “medical IQ” at scale.

A Broader Trend in AI and Healthcare

Microsoft is the latest in a growing list of tech giants racing to make inroads in the health sector. Google has developed its own medical AI tools and partnered with the Mayo Clinic. Amazon has expanded into telehealth. OpenAI, whose language model powers Microsoft’s system, has also acknowledged the medical space as a key future target.

The trend has not gone unnoticed by regulators and ethicists. With such powerful tools emerging, calls for guardrails around algorithmic bias, patient data privacy, medical liability, and the ethics of automation are also intensifying.

While Microsoft’s AI Diagnostic Orchestrator may mark a breakthrough in accuracy, the question remains how such tools will be integrated into real-world clinics, where human judgment, trust, and complexity still define much of the patient-doctor interaction.

Microsoft, for now, is signaling that it sees a future in which AI is not a replacement but a co-pilot for physicians—one capable of drastically improving diagnostic speed and quality if used responsibly.

Senator Ted Cruz’s plan to impose a sweeping ban on state-level regulation of artificial intelligence collapsed on Tuesday, as the U.S. Senate voted 99-1 to strike the controversial measure from President Donald Trump’s sweeping domestic policy bill.

Cruz himself was forced to vote in favor of removing the provision, after it became clear that the opposition—both within and outside his party—had reached insurmountable levels.

The Texas Republican’s proposal would have blocked states from receiving billions in broadband funding if they passed laws governing AI technologies, such as rules targeting deepfakes, robocalls, algorithmic bias, or the use of AI in surveillance and autonomous vehicles. It had been quietly inserted into the broader GOP-backed budget legislation under the guise of a regulatory “pause,” but quickly drew backlash from both Democrats and Republicans.

Initially, the plan would have disqualified states from accessing a $42 billion federal broadband deployment fund if they enacted AI-related laws. After mounting criticism, Cruz attempted to dial it back by limiting the moratorium to five years and shrinking the financial penalty to just $500 million in AI grants. But the core of the proposal remained the same: tie state access to federal dollars to a prohibition on AI regulation.

Republican leadership tried to market the scaled-down version as a “temporary” freeze on regulation to allow the federal government to craft unified standards. Yet the revised provision still alarmed many lawmakers who saw it as a backdoor move to restrict state autonomy and provide legal cover for tech firms.

“Wolf in Sheep’s Clothing”

Democratic Senator Ed Markey of Massachusetts slammed the revised version as “a wolf in sheep’s clothing,” warning that it still gave the Trump administration too much power to punish states for attempting to protect consumers.

“Despite Republican efforts to hide the true impact of the AI moratorium,” he said, “the language still allows the administration to use federal broadband funding as a weapon against the states.”

Senator Maria Cantwell (D-Washington), who co-authored the amendment to strike the clause, said the GOP’s attempts to dress up the provision as a five-year pause did not change its core danger.

“This was another giveaway to tech companies,” she said, accusing Cruz of misleading assurances. “It gives AI and social media a brand-new shield against litigation and state regulation.”

Senator Marsha Blackburn (R-Tennessee), a conservative Republican who initially explored a compromise with Cruz, ultimately joined Cantwell to kill the measure. Blackburn argued that the bill, even in its updated form, would leave states unable to respond to urgent consumer protection needs, especially when it comes to children and data privacy.

“This provision could allow Big Tech to continue to exploit kids, creators, and conservatives,” Blackburn said. “Until Congress passes real, federally preemptive laws like the Kids Online Safety Act and an online privacy framework, we can’t tie the hands of our state legislatures.”

Cruz Retreats Under Pressure

Faced with bipartisan opposition, Cruz eventually withdrew support for his own measure. In a floor statement, he blamed “outside interests” for torpedoing the deal, insisting that the five-year moratorium had backing from President Trump and was intended to “protect kids and creative artists.” But critics said it was less about children and more about shielding Silicon Valley from oversight.

The failure marked a significant political blow to Cruz, who had been one of the most vocal champions of preempting state regulation of emerging technologies. Ironically, his plan lost steam just as his home state of Texas enacted its own AI legislation—undermining his case that states were unfit to legislate on the topic.

The final vote to remove the AI moratorium—99 in favor, 1 opposed—left Senator Thom Tillis (R-North Carolina) as the only lawmaker supporting it. Cruz’s decision to join the majority was seen as a reluctant concession to political reality.

Broad Coalition Rejected the Proposal

The resistance to the AI provision extended beyond Capitol Hill. Cantwell’s office cited unified opposition from 17 Republican governors, 40 state attorneys general, and policy organizations ranging from the Heritage Foundation to the Center for American Progress. The rare cross-ideological alliance highlighted just how deeply unpopular the provision had become.

“Despite several revisions by its author and misleading assurances about its true impact, this proposal would have opened the door to unchecked AI deployment while stripping states of their right to act,” Cantwell said after the vote.

Lawmakers also emphasized that the federal government has yet to pass comprehensive AI legislation, meaning states remain the only line of defense for consumer protection in this rapidly advancing sector. In 2023 alone, at least 24 states introduced or passed some form of AI-related laws and regulations that could have been invalidated or chilled under Cruz’s plan.

What’s Next for AI Regulation?

The Senate’s overwhelming rejection of the moratorium leaves the door open for states to continue setting their own standards while Congress continues to work on a federal framework. The episode also served as a warning shot to federal lawmakers attempting to sneak sweeping tech policy changes into must-pass legislation.

“The Senate came together tonight to say that we can’t just run over good state consumer protection laws,” Cantwell said.

Even as the broader budget bill advances—now cleared of the Cruz amendment—many lawmakers are calling for a standalone debate on AI legislation, not backdoor policy crafted in closed-door budget negotiations.

American Bitcoin, backed by Eric Trump, raised $220 million to purchase Bitcoin and mining equipment, with $10 million of the equity sold in Bitcoin, as part of its strategy to build a significant Bitcoin reserve and scale mining operations through a merger with Gryphon Digital Mining, expected to close in Q3 2025. Regarding FTX, creditors with claims under $50,000, classified as “Convenience Class,” began receiving 120% payouts in February 2025, with a second distribution starting May 30, 2025, through platforms like Bitgo or Kraken, based on November 2022 crypto valuations.

These payouts reflect FTX’s bankruptcy plan to distribute recovered assets, though some creditors are dissatisfied due to the significant rise in Bitcoin prices since 2022. The developments involving American Bitcoin and FTX payouts highlight significant trends and tensions in the crypto ecosystem, with implications for market dynamics, investor sentiment, and economic divides.

American Bitcoin, backed by Eric Trump, raising $220 million to buy Bitcoin and mining equipment signals strong institutional interest in Bitcoin as a store of value and investment asset. This move, especially with $10 million of equity sold in Bitcoin, reinforces the narrative of Bitcoin as a legitimate financial instrument, potentially boosting market confidence. The merger with Gryphon Digital Mining, aiming for a public listing, further integrates crypto into traditional financial systems, likely attracting more institutional capital.

By building a significant Bitcoin reserve, American Bitcoin could reduce the circulating supply, potentially driving up Bitcoin prices if demand remains steady or grows. This aligns with the strategy of firms like MicroStrategy, which have similarly accumulated large Bitcoin holdings, contributing to price volatility and upward pressure. The investment in mining equipment could enhance American Bitcoin’s hashing power, but it also raises concerns about mining centralization. If large players dominate mining, it could undermine Bitcoin’s decentralized ethos, increasing vulnerability to regulatory scrutiny or network control by a few entities.

Eric Trump’s involvement introduces a political dimension, potentially polarizing perceptions of Bitcoin. It may attract supporters aligned with the Trump brand while alienating others, influencing adoption and regulatory attitudes depending on political climates. The 120% payouts to FTX creditors with claims under $50,000, starting in February and May 2025, demonstrate progress in the bankruptcy process, providing relief to smaller retail investors.

However, the payouts are based on November 2022 crypto prices, when Bitcoin was around $16,000-$20,000, compared to its 2025 highs (potentially $80,000-$100,000 based on market trends). This discrepancy fuels discontent among creditors who feel shortchanged, potentially dampening trust in crypto platforms. The structured payout process, using platforms like Bitgo and Kraken, sets a precedent for handling crypto bankruptcies. It highlights the challenges of valuing volatile assets in insolvency cases and may push regulators to develop clearer frameworks for crypto asset recovery, impacting future platform operations.

The payouts prioritize smaller claims, leaving larger creditors (e.g., institutional investors) waiting longer, which could reshape perceptions of fairness in crypto insolvencies. This may influence how retail versus institutional investors approach risk in crypto markets. The firm’s raise and strategy cater to institutional players, with high-profile backing and large-scale Bitcoin accumulation. Retail investors may feel priced out or marginalized as large entities dominate Bitcoin holdings and mining, potentially concentrating wealth and influence.

Smaller retail creditors benefit from early payouts, but the 120% recovery based on outdated valuations means they miss out on Bitcoin’s price appreciation. Institutional creditors with larger claims face delays, creating friction between retail and institutional recovery timelines. American Bitcoin’s corporate approach, backed by a politically charged figure, contrasts with Bitcoin’s original decentralized, anti-establishment ethos. This could deepen the divide between crypto purists and those embracing institutional adoption.

FTX’s payouts highlight the tension between crypto’s promise of financial freedom and the reality of centralized platform failures, where legal systems dictate outcomes, frustrating those who expected crypto to bypass traditional financial gatekeepers. The ability of firms like American Bitcoin to raise $220 million underscores the capital-intensive nature of crypto’s evolution, favoring well-funded entities. Meanwhile, FTX creditors, particularly retail investors, are locked into recoveries that don’t reflect current market gains.

The political branding of American Bitcoin may also alienate segments of the crypto community, creating a cultural divide that could influence adoption and market participation. Institutional moves like American Bitcoin’s could drive Bitcoin prices higher, benefiting early investors and large holders while making entry cost-prohibitive for retail investors. FTX’s payout structure further highlights how retail investors often bear the brunt of market volatility and platform failures.

The FTX saga erodes trust in centralized crypto platforms, pushing some toward decentralized alternatives, while American Bitcoin’s institutionalization may attract those comfortable with traditional finance. This creates a split in how different groups perceive crypto’s future. The political ties of American Bitcoin and the FTX bankruptcy could intensify regulatory scrutiny, with differing impacts on retail (more protection) versus institutional players (more compliance costs), potentially widening operational gaps.

American Bitcoin’s raise and FTX’s payouts reflect a crypto market at a crossroads: institutionalization versus decentralization, retail versus institutional priorities, and ideological purity versus pragmatic adoption. These dynamics could deepen economic and social divides, shaping the trajectory of crypto’s integration into global finance.