Why the U.S. Govt Paid Just $1 for ChatGPT

A closer look at the unexpected AI deal, what it means for OpenAI, and how it could shape future government tech partnerships

Welcome, AI Creators!

$1 ChatGPT deal by the U.S. government, Microsoft’s self-adapting AI solving complex scientific problems, and SOTA open-source models automating and debugging tasks — key breakthroughs reshaping the future of AI-driven innovation.

Today’s Highlights

  • Why the U.S. Govt Paid Just $1 for ChatGPT

  • Automate & Debug with SOTA Open-Source Models

  • Microsoft’s AI Solves Science Problems with Self-Adapting Tech

Also Inside

  • Discover AI Courses to Boost Your Skills

  • Essential AI Tools to Improve Your Workflow

  • In-Depth Tutorial for Creating AI Research Reports

  • Trending Topics and Viral Highlights

💡 The U.S. government secured access to ChatGPT for just $1 under a research deal — a strategic move to explore AI’s potential in public services. Meanwhile, powerful open-source models are automating tasks and Microsoft’s self-adapting AI is solving real science problems.

🔍 Key Highlights

 $1 ChatGPT deal enables AI use in government research.
 SOTA open-source models automate and debug efficiently.
 Microsoft’s AI tackles complex scientific challenges.

🔥 Why It Matters

From public AI adoption to automated coding and AI-led discoveries, these breakthroughs show how AI is quickly becoming central to innovation across sectors.

Ask ChatGPT

💡 Powerful open-source AI models are now helping developers automate tasks and debug code with speed and precision — saving time and reducing errors across industries.

🔍 Key Highlights

Automates repetitive coding tasks
Speeds up debugging with smart suggestions
Boosts productivity using accessible AI tools

🔥 Why It Matters

With these tools, any developer can now harness the power of AI automation, making software development faster, cleaner, and more efficient than ever.

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💡 Microsoft’s next-gen AI is self-adapting — meaning it can learn and improve on its own, solving tough scientific problems in fields like biology, chemistry, and climate research.

🔍 Key Highlights

AI that learns from data with minimal human input
Tackles complex research questions in real time
Accelerates discovery in key scientific fields

🔥 Why It Matters

This is a big step toward AI-driven research, where machines not only assist scientists — they become active problem-solvers, pushing the limits of what’s possible.

Latest tool Update

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📝 Kitten TTS - A 15M parameter text-to-speech model that runs without GPU

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 AI Job Opportunities

🧠 Meta - AI Research Scientist, Computer Vision

🎨 Descript - Product Designer

🤝 Deepmind - People Partner, GenAI

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Quick Tutorial

ChatGPT Prompt Writing Masterclass | Learn to Use AI Like a Pro

ChatGPT Prompt Writing 101 helps you write better prompts that get smarter AI results — with real examples, frameworks, and ready-to-use templates.

 Key Points

  • Prompting basics

  • Proven frameworks

  • Use cases for all

  • Bonus PDFs

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📰 Everything else in AI today

  • AI in Action, Aug 6: Discover how MongoDB Atlas + Azure turn vectors into real-world value in this webinar with MongoDB + Microsoft. Build scalable, secure, flexible AI apps.*

  • Cohere introduced Command A Vision, a new model that achieves SOTA performance in multimodal vision tasks for enterprises.

  • OpenAI has reportedly reached $12B in annualized revenue for 2025, with around 700M weekly active users for its ChatGPT platform.

  • StepFun released Step3, an open-source multimodal reasoning model that achieves high performance at low cost, outperforming Kimi K2, Qwen3, and Llama 4 Maverick.

  • Both Runway and Luma AI are exploring robotics training and simulations with their video models as a source of revenue, according to a new report from The Information.

  • AI infrastructure platform Fal raised a new $125M funding round, bringing the company’s valuation to $1.5B.

  • Agentic AI startup Manus launched Wide Research, a feature that leverages agent-to-agent collaboration to deploy hundreds of subagents to handle a single task.

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