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Government AI leaked on GitHub
US government plans to both harness and control artificial intelligence
Dear Readers,
A country is building its own super AI. And no one would have noticed—if it hadn't been for a GitHub leak.
What initially looks like a digital accident turns out to be a significant political signal: with the AI.gov project, the US government wants nothing less than to usher in a new era of administrative digitization.
Uniform access to AI providers such as OpenAI, Google, and Anthropic, a cross-platform monitoring dashboard called “CONSOLE,” and a government chatbot – all under the control of a federal authority. Launch date: July 4. It couldn't be more symbolic.
This development is a turning point in several respects. First, it shows that artificial intelligence is no longer seen as a purely economic tool, but as a political infrastructure project. Second, it brings central questions of transparency, control, and ethics to the fore: Who writes the answers for the government bot? And who controls whether AI-based administration makes decisions – or just simulates them?
In Today’s Issue:
A surprise leak reveals America's ambitious plan to centralize its government AI
Powerful Qwen3 models are now optimized and ready for your Apple devices
Why choose one answer when Codex can now give you multiple options at once?
Jan-nano: the small new AI agent that's acing research benchmarks.
And more AI goodness…
All the best,

Government AI leaked on GitHub
The TLDR
A recent leak revealed "AI.gov," a US government project set to launch on July 4th that will systematically integrate AI into federal agencies. The platform includes a government chatbot, a centralized API to major AI providers like OpenAI and Google, and a "CONSOLE" dashboard to monitor AI use, raising urgent questions about efficiency, control, and ethical oversight.
A few days ago, a surprising leak shook the political world: planned AI access by the US government was accidentally revealed in a public GitHub repository—shortly before it was taken offline again.
At the center of it all is AI.gov, a project of the US federal agency GSA led by Thomas Shedd (formerly of Tesla/Musk Alliance). It is scheduled to launch on July 4 and comprises three core elements: a government chatbot, a centralized API to AI providers such as OpenAI, Google, Anthropic, AWS Bedrock, and Meta LLaMA, and a real-time monitoring dashboard called “CONSOLE” that monitors the use of AI tools within government agencies.
This is relevant for the AI community because it shows how large states want to radically digitize their administration and centrally control AI functions – a direct insight into real-world AI strategy. At the same time, it raises questions about transparency, data protection, and ethical guidelines: Who controls what a government chatbot recommends? And who monitors its use?
Looking on the bright side, how will this model develop further, and can such a platform also be used for democratic participation and global cooperation?
Why it matters: This initiative shows for the first time how AI is being systematically integrated into administration, with far-reaching effects on efficiency, control, and security.
At the same time, it opens up the discourse on responsible, transparent AI use in government institutions.
Sources:
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In The News
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While Baiont uses AI for short-term price forecasts, QuantumLight invests in 17 start-ups based on data and dispenses with traditional VC roles such as lead investments or board memberships
Turning point: This signals a structural change in the venture capital sector – from human intuition to algorithm-based decision-making logic.
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It analyzes 35,000 articles weekly and develops AI agents to estimate addressable markets.
Turning point: A new era of lightweight asset alphas without large teams – AI leads to efficiency gains in research and portfolio construction.
Economic relevance: Such models could shift industry standards – traditional asset managers must integrate AI or fight for survival, challenging margins, structure, and the cost landscape in asset management.
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Turning point: AI is shifting the architectural foundations of the financial system – from static models to dynamically learning systems.
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