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Anthropic catches OpenAI using Claude to build GPT-5


Welcome back. OpenAI's latest funding round was so oversubscribed that early investors got smaller allocations to make room for new partners—because when you're raising $8.3 billion at a $300 billion valuation, everyone has to wait in line. Dragoneer Investment Group wrote a casual $2.8 billion check, representing roughly 10% of their entire fund, which is either extreme confidence or the world's most expensive FOMO.
1. Anthropic catches OpenAI using Claude to build GPT-5
2. AI infrastructure spending rivals 19th-century railroads
3. Researcher who almost joined OpenAI for $175K turns down $1.5 billion from Meta
THE AI RACE
Anthropic catches OpenAI using Claude to build GPT-5

Anthropic pulled the plug on OpenAI's Claude access last week after discovering that OpenAI engineers were systematically using Claude Code to benchmark and improve GPT-5, violating terms of service just weeks before the model's expected August launch.
OpenAI had integrated Claude directly into internal development tools through API access, running systematic comparisons across coding tasks, creative writing and even sensitive safety scenarios involving content like self-harm and defamation. Anthropic's terms explicitly prohibit using their service to "build competing products" or "train competing AI models."
OpenAI called the practice "industry standard" benchmarking. Spokesperson Hannah Wong said they were "disappointed" considering their API remains available to Anthropic. But Anthropic spokesperson Christopher Nulty wasn't buying it: "This is a direct violation of our terms of service."
Back in June, Anthropic cut off Windsurf's Claude access after OpenAI tried to acquire the coding startup for $3 billion. Microsoft blocked the deal over IP rights concerns, then Google hired Windsurf's CEO and key staff for $2.4 billion while Cognition acquired what remained of the company.
Corporate surveillance and data warfare have deep roots in tech:
Facebook's "Project Ghostbusters" used Onavo VPN to spy on Snapchat, intercepting encrypted traffic from 33 million users to inform Instagram Stories development and acquisition decisions
Facebook blocked Twitter's Vine app in 2013, with Mark Zuckerberg personally approving the decision within hours of launch
Twitter's API purge decimated apps like Block Party, forcing complete business pivots when access disappeared overnight
Countries are now blocking DeepSeek while hundreds of companies ban the Chinese AI over espionage concerns

There's something deeply satisfying about watching OpenAI get caught red-handed like this. Using your competitor's best coding tool to build your own competing product, then calling it "industry standard" when you get cut off, is peak Silicon Valley behavior.
These companies are spending billions on compute and talent to build these systems. Why would you hand your competitors a roadmap to beat you? The collaborative early days of AI development are over. We're now in the era where models are treated like nuclear secrets.
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ECONOMY
AI infrastructure spending rivals 19th-century railroads

AI capital expenditure now represents roughly 2% of US GDP, according to analyst estimates based on Nvidia's datacenter revenue. That's around $520 billion annually, putting AI infrastructure spending within shouting distance of peak 19th-century railroad construction.
The scale becomes clearer when you consider that without AI datacenter investment, Q1 GDP contraction could have been closer to -2.1% instead of the mild downturn we actually saw. We're essentially running a massive private sector stimulus program disguised as an AI buildout.
This explains one of the more puzzling aspects of the current economy. Despite tariffs, political uncertainty, and the usual economic headwinds, growth has held up better than expected. The answer appears to be that Big Tech is spending so aggressively on GPUs and datacenters that it's masking underlying weakness.
The scale becomes clear when you look at individual company commitments. Microsoft plans $80 billion for AI datacenters in fiscal 2025, Amazon expects over $100 billion, Google allocated $75 billion and Meta budgeted $60-65 billion. Combined, these four companies alone are spending over $315 billion this year.
But that money is coming from somewhere else. Non-life science venture capitalists are primarily funding AI startups at present. Amazon recently announced cloud layoffs driven by spiraling AI costs. Manufacturing and traditional infrastructure are being starved for capital as it gets rerouted to data centers.
Even Xi Jinping is sounding the alarm, with 250+ datacenters under construction in China and the Chinese president threatening intervention.
The spending has already surpassed peak telecom capex during the dot-com bubble as a percentage of GDP.
The uncomfortable truth is that we're building short-lived infrastructure on rapidly depreciating technology curves, not century-spanning railroads. And when this particular spending spree ends, the economic support it's providing disappears with it.
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KEY PLAYERS
Researcher who almost joined OpenAI for $175K turns down $1.5 billion from Meta

Andrew Tulloch, a co-founder at Thinking Machines Lab (TML), just rejected a billion-dollar package from Mark Zuckerberg that could have reached $1.5 billion over six years with bonuses and stock performance.
This is the same researcher who almost joined OpenAI back in 2016, when Greg Brockman wrote to Elon Musk that Tulloch was "very close to saying yes" but "concerned about taking such a large paycut" from his $800,000 Facebook salary to OpenAI's $175,000 base with $125,000 bonus.
Eight years later, Tulloch finally made the jump to work for Mira Murati at TML, where he's now wealthy enough to turn down generational wealth from his former employer
Not a single TML researcher took Zuckerberg's offers, despite Meta approaching more than a dozen employees at the roughly 50-person startup
Tulloch's background makes this particularly brutal for Meta. The Australian researcher graduated with the highest GPA among science students at the University of Sydney, became a distinguished engineer at Facebook, and was considered "an extreme genius" by former Facebook executive Mike Vernal
When Murati left OpenAI in September, more than 20 colleagues followed her to TML, including co-founder John Schulman. The loyalty runs deeper than just Murati's leadership style.
TML recently raised funding at a $12 billion valuation, meaning researchers hold equity that could appreciate far beyond Meta's cash offers. When your startup is worth more than many Fortune 500 companies, walking away from even a billion-dollar corporate job becomes much easier.
We've moved from an era where Big Tech could outbid anyone to one where the most valuable researchers control billion-dollar startups themselves. Zuckerberg is no longer just competing against other companies for talent — he's competing against the wealth his targets have already accumulated. And apparently, that's a fight even a billion dollars can't win.
LINKS

Why open-source AI became an American national priority
Apple’s new ‘Answers’ team eyes ChatGPT-like product in AI push
The uproar over Vogue’s AI-generated ad isn’t just about fashion
Lina Khan points to Figma IPO as vindication of M&A scrutiny
Fundamental Research Labs nabs $30M+ to build AI agents across verticals
Google releases Gemini 2.5 Deep Think for AI Ultra subscribers
Senate confirms Sean Cairncross to be national cyber director under Trump
Amazon is toying around with putting ads in Alexa+
Apple has now shipped 3 billion iPhones

Gemini 2.5 Deep Think: Version of the model that achieved an IMO gold medal, using parallel "thinking time"
Ollama Desktop App: Ollama’s macOS and Windows now include a way to download and chat with models
Mixio: Create an AI avatar of yourself that streams 24/7 (this one feels a bit Black Mirror?)
Delve: AI agents that help you get compliant with SOC 2, HIPAA and more overnight*

A QUICK POLL BEFORE YOU GO
Using a competitor’s API this way is… |

![]() | “The angle on the tip of the boat for [the other image] was slightly off. It was the only thing that made me question the image.” “The people in [this image] were sufficiently random and “normal” |
![]() | “The reflections and shadows on the bow of the boat in [the other image] didn't feel right to me. Also the black flag on the bow seemed fake.” “These have to be both AI photos, no chance of being non-AI for either of them.” (Here’s the original real image :-) |

The Deep View is written by Faris Kojok and The Deep View crew. Please reply with any feedback. Thanks for reading today’s edition of The Deep View! We’ll see you in the next one.
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