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- š OpenAI rolls out āOpenAI for Countries"
š OpenAI rolls out āOpenAI for Countries"
Google launched an early preview of Gemini 2.5 Pro (I/O edition), OpenAI rolls out āOpenAI for Countriesā, Anthropic launched AI for Science program & more.

Hello Everyone, Weāve rounded up the most interesting updates in AI.
Hereās a quick look at whatās inside the newsletter:
OpenAI rolls out āOpenAI for Countriesā
Google launched an early preview of Gemini 2.5 Pro (I/O edition)
Anthropic launched its AI for Science program
AI Course of the Day
AI - Word of the Day
š OpenAI rolls out āOpenAI for Countriesā

The new āOpenAIāÆforāÆCountriesā program would coāfinance dataācenter campuses and bespoke ChatGPT instances for partner governments, pitching itself as a ādemocraticā counterāweight to authoritarian tech.
AI infrastructure is becoming the foundation of tomorrowās economy, and OpenAI wants democratic nations to shape that future.
The idea? Help countries build their own AI powerhouses, grounded in democratic values like freedom, privacy, and fairness. No centralized control. No black-box decision-making.
What does this actually mean?
Countries can build secure, local data centers , giving them full control over their data and enabling homegrown innovation.
People will get access to localized versions of ChatGPT , designed to fit their language, culture, and public service needsāwhether itās better education, smoother healthcare, or more efficient governance.
As AI gets more powerful, OpenAI will work with partners to keep things safe and ethical, building in the kind of security and oversight that respects both rights and responsibilities.
And perhaps most exciting - national startup funds will be launched to fuel new businesses, create jobs, and grow entire AI ecosystems within each country.
The first phase will involve partnerships with up to 10 countries. Itās an ambitious plan, but one that could shape how the world develops AI for years to come.
ā” Google launched an early preview of Gemini 2.5 Pro (I/O edition)

Google has unveiled an early preview of Gemini 2.5 Pro (I/O edition), its most advanced AI model to date, emphasizing significant enhancements in coding and interactive web application development.
This updated model excels in tasks like code transformation, editing, and constructing complex agentic workflows. It has achieved a notable +147 Elo point increase on the WebDev Arena Leaderboard, reflecting its superior performance in creating visually appealing and functional web applications.
Additionally, Gemini 2.5 Pro demonstrates state-of-the-art capabilities in video understanding, scoring 84.8% on the VideoMME benchmark. Developers can access this model through the Gemini API via Google AI Studio and Vertex AI, while general users can experience its features in the Gemini app, including tools like Canvas, facilitating the development of interactive web applications with minimal input.
š§ŖAnthropic launched its AI for Science program
Anthropic has launched its AI for Science program on May 5, 2025, aiming to fast-track scientific breakthroughs using AI. This initiative offers free API credits to researchers working on high-impact projects, especially in biology and life sciences . Anthropic believes advanced AI can revolutionize how scientists analyze data, form hypotheses, and communicate results.
The program aligns with their mission to build AI that serves humanity, particularly in areas like genetic analysis, drug discovery, and agricultural innovation . Researchers from accredited institutions can apply through a dedicated form, and selections will be based on scientific merit and the potential for AI to accelerate their work.
Read more here .
š AI Course of the Day!

AI For Everyone
Key Takeaways:
How to navigate the AI landscape without technical jargon
How to work with AI teams effectively
Social and ethical aspects of deploying AI
š§ AI Word of the Day: "Reinforcement Learning"
Reinforcement Learning (RL) is a type of machine learning where an AI agent learns by interacting with an environment and receiving rewards or penalties based on its actions.
Example:
An RL agent in a maze gets a reward when it finds the exit. Over time, it learns the fastest path by trial and error.
Thatās all for today!
I hope you enjoyed todayās edition.
Best,
Harsh