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A learning platform in Bamanankan — a language spoken by 20 million people and ignored by every major AI model. Cloud training in languages commercial platforms don't support. Personalized AI paths closing the gender gap in STEM. Tech leaders across Africa aren't waiting for perfect infrastructures to be ready....

6,770,001 次观看 • 27 天前 •via X (Twitter)

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The "big announcement" just dropped. I just watched Sundar Pichai and Demis Hassabis announce biggest AI infrastructure deal in history. $15 billion to build India's first complete AI hub. Let me break down what Google is building: A massive AI data center in Visakhapatnam (a coastal city in India). Think of it like this: • The compute power of thousands of Google data centers • New underwater internet cables connecting 4 continents • Clean energy plants to power everything • Training programs for 100+ million people All in one place, over 5 years. AI doesn't work without fast internet. Google is laying NEW cables under the ocean: → India to Singapore → India to South Africa → India to Australia → Mumbai to Western Australia Right now, most of the world's internet flows through cables landing in the US, Europe, or China. Google is creating an entirely new route, with India at the center. If you're in Africa, Asia, or South America, your AI tools will get FASTER. Why? Shorter distance = faster data. Instead of your request traveling: Africa → Europe → US → back to Africa It will go: Africa → India → back to Africa that's the infrastructure play everyone's missing. numbers that matter: 💰 $15 billion for the data centers and cables 💰 $30 million to help governments use AI 💰 $30 million for AI research grants 💰 100 million+ people getting free AI training But here's the kicker: Google is plugging AI directly into India's government. • 20 million government workers getting AI tools • Students getting AI tutors for entrance exams • Real-time translation in 70+ languages • Scam detection built into search This isn't "AI for tech companies." This is AI for clerks, teachers, railway staff, police officers, the people who actually run a country. ✅ 20 million+ people used Google's AI detection tool to spot fake images ✅ India is now #3 globally for AI chatbot usage ✅ AI scam detection helping millions avoid fraud daily ✅ 10+ million government workers already on the AI training platform Google is building the pipes that deliver AI to the entire Southern Hemisphere. Different game. Different strategy. If they're right, the next billion AI users won't connect through Silicon Valley. They'll connect through India. 🇮🇳

Shruti

399,771 次观看 • 6 个月前

99% of AI applications are cool-looking demos. Impressive, but don't get fooled by the hype. It takes a lot to build enterprise-grade products that deliver real value. I have at least three weekly conversations with companies that want to use a Large Language Model with their data. The demand is huge! Here is one idea about what you can do to help. The use cases that most of these companies want to solve are similar: They have an extensive knowledge base and want to build a simple application that uses that information to answer questions. In other words, they need help building Retrieval Augmented Generation (RAG) applications they can use in many different scenarios: 1. To train new employees 2. To help their support team 3. To search old meetings and documents 4. To help with their research However, building these systems is not straightforward. Yes, there's a lot of information online, but there aren't enough people who know how to create solutions that work. Here is the idea: Today, you can build an enterprise-grade RAG application without writing code. A couple of MIT PhDs with 10+ years of experience building AI applications created . It's a no-code platform for building applications using Large Language Models. They are partnering with me on this post. You can use Stack AI to create, test, and deploy an end-to-end production-ready AI system. It's SOC-2, HIPAA, and GDPR compliant and offers SSO, role management, access control, and on-premise deployments. Of course, you can use the platform with any LLM on the market now. It's the whole nine yards for building AI applications. Check them out here: 2023 was about models. 2024 is about the tools using these models to build production-ready applications. That's where I'd start.

Santiago

197,702 次观看 • 2 年前