One open model now sits months behind the American frontier on cyber and biology, and refused nothing it was asked to do. The closed model refused so often the test could not be finished. Months of capability separate them. The gap in restraint is total. Part four of four.
The White House finished its frontier AI framework on 1 August and has published nothing. The threshold is classified. The benchmarks are classified. Whether open weight models are covered at all remains unanswered. Part three of four on governing what cannot be recalled.
Washington is pushing its AI security perimeter deep inside the data centre, targeting Chinese-made components that move data between GPUs. The policy may reduce cyber and espionage risks, but it could also raise costs, slow construction and expose a new weakness in America’s AI race as AI scales.
Spur, an AI driven startup, has raised $4.5 million to automate website testing. Users type commands like “add to cart” or “apply for a job,” and Spur’s agent simulates the action, detects bugs and gives instant feedback, making quality checks faster and easier for development teams.
Two bold AI startups are making waves. One defies tradition while the other rewrites the rules. Cluely, created by a suspended Columbia student, challenges hiring norms. Spur, founded by Yale graduates, simplifies website testing. Both raised millions, proving that disruption still attracts serious backing.
Two Yale graduates, Sneha Sivakumar and Anushka Nijhawan, have secured $4.5 million in seed funding for their startup, Spur, which aims to transform how websites are tested for bugs. The round was led by Liz Wessel of First Round Capital, with participation from Pear VC, Neo, Conviction, and angel investors from Figma, Dropbox, and Rippling.
The announcement was shared on X with a snapshot of Spur's funding details and investor lineup:
We're excited to share that @spurtest_ has raised $4.5M, led by @firstround to allow teams to own high quality testing
— Spur (@spurtest_) April 17, 2025
We've partnered with some of the most customer centric companies like @wander @ycombinator @LivingSpaces @flynorse to deliver the best user experiences pic.twitter.com/1onAGfSgiw
Founded in 2024, Spur allows users to run software tests using everyday language. For example, users can instruct the system to “add a product to the cart” or “submit a job application,” and Spur’s agent will test those website functions automatically, offering feedback or debugging support.
“A lot of the other agents were not advanced enough,” said Sivakumar. “We were at the bleeding edge of what we were doing.”
The idea was born out of their final year at Yale, blending Sivakumar’s experience with manual QA at Figma and Nijhawan’s work on AI agents at DeepMind. They created a synthetic user capable of mimicking how people interact with websites—without the need for engineers to manually conduct time-consuming quality checks.
“We still use the original agent and computer we built in college,” Sivakumar added.
Spur recently shared a behind-the-scenes look at their tool in action, highlighting how it helps customers catch bugs before they reach end users:
We're excited to share that @spurtest_ has raised $4.5M, led by @firstround to allow teams to own high quality testing
— Spur (@spurtest_) April 17, 2025
We've partnered with some of the most customer centric companies like @wander @ycombinato @LivingSpaces @flynorse to deliver the best user experiences pic.twitter.com/gZLHK4ulp8
Spur joined Y Combinator’s Summer 2024 batch and has since gained traction within the startup community. Notably, Y Combinator itself is now a client.
The founders credit their success to a combination of technical skill and strong networking.
“It is all about putting yourself out there,” Sivakumar said. She also emphasized the importance of co-founding with someone you trust. “Doing this as a solo founder would have been very difficult.”
With growing interest in AI-driven automation, Spur is positioning itself as a practical solution for scaling software testing—offering developers faster and more efficient tools to catch bugs before users do.
At midyear, the AI race has become a contest for global power. Energy, chips, cybersecurity, capital markets and state intervention now shape who controls the inference economy, who pays for it, and who is left exposed in the next industrial order of machines, markets and sovereignty to come ahead.
Neura Robotics raises $1.4B backed by NVIDIA and Amazon to scale physical AI and humanoids to millions of units by 2030, as autonomous robot teams make their tactical debut at Eurosatory 2026.
Odyssey’s $310 million raise signals a new phase in AI, where the race moves beyond language models into world models. These systems aim to give machines an operating understanding of space, motion and causality, forming the physics layer needed for robotics, autonomous systems and physical AI now.
Cyera’s reported $300 million raise at a $12 billion valuation shows how quickly enterprise data security is being repriced as AI adoption accelerates. The figures should be framed carefully, because Cyera has disputed the reported numbers.
Where cybersecurity meets innovation, the CNC team delivers AI and tech breakthroughs for our digital future. We analyze incidents, data, and insights to keep you informed, secure, and ahead. Sign up for free!
