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OpenAI to Train 4 Lakh Teachers in US to Build AI-Ready Classrooms

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OpenAI is doubling down on its commitment to democratise AI education by launching large-scale initiatives in the United States. The company has partnered with the American Federation of Teachers (AFT) to launch the National Academy for AI Instruction, a five-year initiative aimed at training four lakh K-12 teachers, nearly one in 10 across the country, to use and teach AI in classrooms effectively.

With a $10 million contribution over five years, including $8 million in funding and $2 million in engineering and computing support, OpenAI will help establish a flagship training hub in New York City and support the development of additional centres by 2030.

The initiative promises free workshops, hands-on training, and AI tools specifically built for educators, with a strong focus on equity and accessibility in underserved school districts.

“Educators make the difference, and they should lead this next shift with AI,” OpenAI CEO Sam Altman said, recalling how a high school teacher sparked his own early curiosity in AI.

The academy is also backed by the United Federation of Teachers, Microsoft and Anthropic, and aims to ensure that teachers are at the forefront of setting commonsense guardrails and using AI to enhance, rather than replace, human teaching.

Meanwhile, in a parallel development, OpenAI announced the launch of OpenAI Academy India in collaboration with the IndiaAI Mission under the IT and electronics ministry. This marks the first international expansion of OpenAI’s educational platform, aiming to train one million teachers in generative AI skills.

The partnership will deliver AI training in English and Hindi (with more regional languages to follow), and extend to civil servants via the iGOT Karmayogi platform. Additional efforts include six-city workshops, hackathons across seven states, and $100,000 in API credits to 50 AI startups.

Union minister Ashwini Vaishnaw hailed the initiative as a step towards making AI knowledge accessible to every citizen. Jason Kwon, chief strategy officer at OpenAI, called India “one of the most dynamic countries for AI development”.



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India-France Partnership to Build Drones for Defence and Global Exports

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RRP Defence (RRP Group), through its entity Vimananu, has entered into a strategic partnership with the Franco-American firm CYGR to establish an advanced drone manufacturing facility in India. 

The project, based in Navi Mumbai, aims to support India’s ‘Make in India’ initiative by developing unmanned aerial vehicles (UAVs) for defence, surveillance, and industrial applications.

The collaboration will manufacture three categories of drones: hand-launched fixed-wing drones for field operations, compact nano drones for close-range use, and ISR drones tailored for intelligence, surveillance, and reconnaissance missions. 

Production is expected to start with hundreds of units annually, with an initial contract valued at over $20 million.

Rajendra Chodankar, chairman of RRP Defence, said, “This collaboration is a defining moment for India’s UAV ecosystem. By combining our local manufacturing strength and field understanding with CYGR’s world-class drone technologies, we’re building systems that meet India’s unique operational needs.”

The facility will also contribute to high-skill employment and export-focused manufacturing, further positioning India as a key player in the global UAV supply chain.

The initiative strengthens India’s self-reliance in aerospace and defence technology. Zaynah, the global advisor in Make in India global exports in defence for the collaboration, confirmed that an immediate Letter of Intent (LoI) is being released as part of the $20 million contract for global defence exports.

George El Aily, director of CYGR France, added, “India is a key strategic partner for us. Through this collaboration with RRP Defence Ltd, we are not only transferring technology but also co-developing future-ready solutions that support India’s defence and surveillance landscape.”

The project will focus on sectors including defence, homeland security, and industrial monitoring. The companies aim to deliver solutions customised for India’s operational environments while expanding global market access through technology localisation.

This joint venture marks a step forward in India’s ambition to become a global drone hub through international cooperation and indigenous expertise.



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7 Python Web Development Frameworks for Data Scientists

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7 Python Web Development Frameworks
Image by Author | Canva

 

Python is widely known for its popularity among engineers and data scientists, but it’s also a favorite choice for web developers. In fact, many developers prefer Python over JavaScript for building web applications because of its simple syntax, readability, and the vast ecosystem of powerful frameworks and tools available.

Whether you are a beginner or an experienced developer, Python offers frameworks that cater to every need, from lightweight micro-frameworks that require just a few lines of code, to robust full-stack solutions packed with built-in features. Some frameworks are designed for rapid prototyping, while others focus on security, scalability, or lightning-fast performance. 

In this article, we will review seven of the most popular Python web frameworks. You will discover which ones are best suited for building anything from simple websites to complex, high-traffic web applications. No matter your experience level, there is a Python framework that can help you bring your web project to life efficiently and effectively.

 

Python Web Development Frameworks

 

1. Django: The Full-Stack Powerhouse for Scalable Web Apps

Django is a robust, open-source Python framework designed for rapid development of secure and scalable web applications. With its built-in ORM, admin interface, authentication, and a vast ecosystem of reusable components, Django is ideal for building everything from simple websites to complex enterprise solutions. 

Learn more: https://www.djangoproject.com/

 

2. Flask: The Lightweight and Flexible Microframework

Flask is a minimalist Python web framework that gives you the essentials to get started, while letting you add only what you need. It’s perfect for small to medium-sized applications, APIs, and rapid prototyping. Flask’s simplicity, flexibility, and extensive documentation make it a top choice for developers who want full control over their project’s architecture.

Learn more: https://flask.palletsprojects.com/

 

3. FastAPI: Modern, High-Performance APIs with Ease

FastAPI is best known for building high-performance APIs, but with Jinja templates (v2), you can also create fully-featured websites that combine both backend and frontend functionality within the same framework. Built on top of Starlette and Pydantic, FastAPI offers asynchronous support, automatic interactive documentation, and exceptional speed, making it one of the fastest Python web frameworks available.

Learn more: https://fastapi.tiangolo.com/

 

4. Gradio: Effortless Web Interfaces for Machine Learning

Gradio is an open-source Python framework that allows you to rapidly build and share web-based interfaces for machine learning models. It is highly popular among the machine learning community, as you can build, test, and deploy your ML web demos on Hugging Face for free in just minutes. You don’t need front-end or back-end experience; just basic Python knowledge is enough to create high-performance web demos and APIs.

Learn more: https://www.gradio.app/

 

5. Streamlit: Instantly Build Data Web Apps

Streamlit is designed for data scientists and engineers who want to create beautiful, interactive web apps directly from Python scripts. With its intuitive API, you can build dashboards, data visualizations, and ML model demos in minutes.No need for HTML, CSS, or JavaScript. Streamlit is perfect for rapid prototyping and sharing insights with stakeholders.

Learn more: https://streamlit.io/

 

6. Tornado: Scalable, Non-Blocking Web Server and Framework

Tornado is a powerful Python web framework and asynchronous networking library, designed for building scalable and high-performance web applications. Unlike traditional frameworks, Tornado uses a non-blocking network I/O, which makes it ideal for handling thousands of simultaneous connections, perfect for real-time web services like chat applications, live updates, and long polling.

Learn more: https://www.tornadoweb.org/en/stable/guide.html 

 

7. Reflex: Pure Python Web Apps, Simplified

Reflex (formerly Pynecone) lets you build full-stack web applications using only Python, no JavaScript required. It compiles your Python code into modern web apps, handling both the frontend and backend seamlessly. Reflex is perfect for Python developers who want to create interactive, production-ready web apps without switching languages.

Learn more: https://reflex.dev/ 

 

Conclusion

 
FastAPI is my go-to framework for creating REST API endpoints for machine learning applications, thanks to its speed, simplicity, and production-ready features. 

For sharing machine learning demos with non-technical stakeholders, Gradio is incredibly useful, allowing you to build interactive web interfaces with minimal effort.

Django stands out as a robust, full-featured framework that lets you build any web-related application with complete control and scalability.

If you need something lightweight and quick to set up, Flask is an excellent choice for simple web apps and prototype.

Streamlit shines when it comes to building interactive user interfaces for data apps in just minutes, making it perfect for rapid prototyping and visualization.

For real-time web applications that require handling thousands of simultaneous connections, Tornado is a strong option due to its non-blocking, asynchronous architecture.

Finally, Reflex is a modern framework designed for building production-ready applications that are both simple to develop and easy to deploy.
 
 

Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in technology management and a bachelor’s degree in telecommunication engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.



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Perplexity Leads ChatGPT on Apple App Store in India Post Airtel Offer

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Just one day after Airtel announced its offer of a complimentary Perplexity Pro subscription, the Perplexity app has seen an unprecedented surge in downloads, particularly on iOS. 

Thanks to the Airtel promotion, the AI search engine has climbed to the top spot on the App Store in India, overtaking OpenAI’s ChatGPT. This milestone was announced by Perplexity AI’s CEO, Aravind Srinivas, in a post on LinkedIn.

As reported by Mint News, Google’s Gemini ranks fifth among the top free apps on the App Store, following Perplexity and ChatGPT. 

On the other hand, ChatGPT remains at the top of the charts on the Google Play Store, while Perplexity has not yet tried to compete for a position among the leading free apps.

Perplexity Pro offers users access to advanced AI models, including GPT-4.1, Claude, Grok 4, and others, as well as image generation capabilities across compatible models. Subscribers also gain access to the company’s newly introduced Comet browser, which is currently available only to free users through an invitation.

Following Airtel’s announcement of its major partnership with an AI startup based in the US to offer a complimentary year-long subscription to Perplexity AI Pro, numerous Airtel subscribers took advantage of the promotion. 

The Perplexity AI Pro subscription is highly advantageous for students, researchers, professionals, and educators. In India, the annual subscription to the Pro tier costs Rs 17,000 when purchased directly from Perplexity.

With the Airtel promotion, a full year’s subscription is now available for free, encouraging more individuals to sign up and try it out. This initiative has led to a significant number of subscribers downloading the app via App Stores, as using the app is the simplest method to access the AI model.



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