Vast Data Series F Funding: $1B Raised at $30B Valuation

Vast Data raised $1 billion in Series F at a $30 billion valuation. The round closed with both primary and secondary capital, reflecting strong market appetite for AI‑centric data infrastructure and confirming the company’s ability to scale to meet the needs of “the world’s most demanding AI environments.”

Drive Capital and Access Industries led the Series F, with participation from Nvidia, Fidelity Management and Research Company and NEA. CNBC reported on 2026-04-22 that the financing will support the company’s continued development of its software infrastructure for massive AI workloads.

2016 Launch and $4B Bookings Milestone

Founded in 2016, Vast Data builds software infrastructure for managing large amounts of data, with a focus on AI applications. The company says it supports projects powering millions of GPUs and counts CoreWeave, Mistral, the U.S. Air Force and Cursor among its customers. It has surpassed $4 billion in cumulative bookings and exited the previous fiscal year with more than $500 million in committed annual recurring revenue. “The scale and speed of AI adoption are creating a new class of infrastructure company,” said Chris Olsen, cofounder and partner at Drive Capital.

Drive Capital, Access Industries and Nvidia: Why They Invested

Drive Capital’s decision to lead rather than co‑invest suggests a higher conviction in Vast’s market position, while Access Industries brings deep industry connections. Nvidia’s participation underscores its strategy to back companies that enable GPU‑heavy workloads. The article notes Vast’s valuation is more than triple the $9.1 billion it hit when it last raised in 2023, highlighting rapid growth.

Nvidia’s Parallel AI Deals: OpenAI, Anthropic, xAI, Nscale, Wayve

Nvidia has also contributed to major funding rounds for AI labs OpenAI, Anthropic and xAI, alongside other startups such as neocloud Nscale and autonomous‑driving company Wayve, demonstrating its broad commitment to the AI ecosystem.

Nvidia has ramped up its financial backing of private startups in the past year, cementing its role at the heart of the AI boom.

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Agentic AI Top 2026 Threat: 48% Cite Anthropic’s Mythos

Anthropic privately warned U.S. officials that its unreleased Mythos AI model can autonomously penetrate corporate, government and municipal systems with unprecedented sophistication, Axios reported. The private warnings highlight the model’s potential to dramatically lower the barrier for sophisticated cyber operations. Top AI and government officials were briefed that Anthropic and other tech giants are preparing models that are ‘scary good at hacking sophisticated systems at scale.’ This follows Anthropic’s disclosure of the first documented cyberattack largely executed by AI, where a Chinese state-sponsored group used agents to autonomously hack roughly 30 global targets, with the AI handling 80-90% of tactical operations independently. The warnings underscore the threat of a likely surge in large-scale cyberattacks this year. Axios reported on March 29, 2026, that Anthropic’s unreleased Mythos model is currently far ahead of any other AI model in cyber capabilities. An unpublished Anthropic blog post obtained by Fortune describes Mythos as capable of exploiting vulnerabilities in ways that far outpace defenders. The model can autonomously hack systems with agents that think, act, reason and improvise without rest, allowing bad actors to scale attacks simply by adding more compute. A single individual could now run campaigns once requiring entire teams, democratizing cybercrime. These capabilities position Mythos as a significant advancement in offensive AI. Anthropic has not disclosed the model’s pricing or availability, per Axios. According to Axios, CEO Jim VandeHei said his tech team considers this ‘the biggest threat to Axios right now.’ This assessment highlights the immediate risk from agentic AI capabilities like those in Mythos. The ability to operate without rest enables round-the-clock attacks, while reasoning and improvisation allow real-time adaptation to defenses. The scaling via compute means resource-constrained actors can launch large-scale operations, lowering the entry barrier for cybercrime. The combination of powerful new models and widespread unsupervised experimentation creates a ‘perfect storm for cybercrime,’ as Axios noted. These factors require companies to implement strict controls on AI agent usage and create isolated testing environments. The persistent nature of these attacks means that even automated defenses may struggle to keep pace, necessitating continuous monitoring and adaptive response mechanisms. per Axios, no companies are identified as beneficiaries of Mythos’s capabilities, while headwinds include the rise of ‘shadow AI,’ where employees connect home-experimented AI agents to corporate systems, creating new attack vectors. Axios also reports that a Dark Reading poll found 48% of cybersecurity professionals rank agentic AI as the top attack vector for 2026, above deepfakes. This consensus indicates a shift in threat priorities, with agentic AI now considered more dangerous than traditional vectors. The expansion of shadow AI exponentially increases the attack surface, as home networks lack enterprise security. Companies are therefore urged to educate employees on these dangers and establish secure testing environments to mitigate the escalating risks. OpenAI is among the competitors developing advanced AI models with significant cyber capabilities, Axios reported. While specific product details are scarce, the briefing indicated these models are ‘scary good at hacking sophisticated systems at scale,’ matching the threat level of Mythos. This competitive dynamic indicates that multiple major AI players are pushing the boundaries of offensive AI. The involvement of numerous firms increases the likelihood that such capabilities will become widely available, potentially lowering the barrier for malicious actors. Companies should therefore monitor developments across the AI sector, not just from Anthropic, to understand the evolving threat landscape. The proliferation of these models could lead to an arms race in both offensive and defensive AI technologies, prolonging the cybersecurity challenge. Axios reported that Anthropic has not disclosed a specific roadmap for Mythos. The unpublished blog post warned that Mythos presages an upcoming wave of models that can exploit vulnerabilities even faster, indicating continued development in offensive AI. Without public release dates, companies must prepare for more advanced models to emerge in the near future, extending the cybersecurity challenge. The lack of transparency around release timelines complicates defensive planning, as organizations cannot anticipate when to expect such capabilities in the wild. This uncertainty underscores the need for proactive measures and continuous adaptation in cybersecurity strategies. As AI research advances, the gap between offensive and defensive capabilities may widen, requiring sustained investment in security innovation.

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