According to Andrew Ng on Twitter, the DeepLearningAI engineering team leveraged advanced AI coding tools to quickly develop and deploy a clone of basic Cloudflare functionalities after a major Cloudflare outage. This innovative use of AI for rapid infrastructure replacement enabled DeepLearningAI’s website to resume operations significantly ahead of other major sites impacted by the downtime. The event demonstrates the practical application of AI in crisis-driven DevOps scenarios, highlighting new business opportunities for AI in automated disaster recovery and web infrastructure resilience (Source: Andrew Ng, Twitter).

According to DeepLearning.AI (@DeepLearningAI), a new short course titled 'Jupyter AI: AI Coding in Notebooks' has been launched, taught by Andrew Ng and Brian Granger (@ellisonbg), co-founder of Project Jupyter. The course demonstrates practical applications of Jupyter AI, empowering users to generate code, debug errors, and receive explanations directly within the Jupyter notebook environment. Learners can build real-world AI applications, such as a book research assistant and stock data analysis workflow, showcasing the integration of AI tools in data science workflows. The course emphasizes AI coding best practices to maximize efficiency and accuracy when guiding AI models. This educational initiative highlights the growing trend of embedding AI capabilities into popular development environments, creating new business opportunities for AI-powered productivity tools in the software and data science sectors. (Source: DeepLearning.AI Twitter, Nov 6, 2025)

According to Greg Brockman (@gdb), GPT-5 demonstrates exceptional coding abilities, especially when users apply optimized prompting techniques (source: Twitter, August 30, 2025). This advancement positions GPT-5 as a powerful tool for automating software development tasks, accelerating code generation, debugging, and refactoring workflows. Businesses leveraging GPT-5 can streamline development cycles, reduce costs, and enhance productivity, making AI-driven code generation a strategic asset for competitive advantage.

According to @GoogleAI, the Gemma 3B E4B model is a significant breakthrough in the AI industry, supporting over 140 languages for text, 35 languages for multimodal understanding, and delivering major improvements in math, coding, and reasoning tasks. Notably, it is the first model under 10 billion parameters to surpass a 1300 score on the Lmarena AI benchmark, showcasing efficient performance and broad applicability for global, multilingual, and cross-domain AI solutions (source: @GoogleAI via Twitter, goo.gle/gemma-3n-general-ava).

According to Sundar Pichai on Twitter, the Gemini 2.5 Pro update is now in preview and delivers significant improvements in AI coding, reasoning, scientific, and mathematical capabilities. The update demonstrates higher performance across key industry benchmarks such as AIDER Polyglot, GPQA, and HLE. Notably, Gemini 2.5 Pro leads the @lmarena_ai leaderboard with a 24-point Elo score increase compared to the previous version (source: Sundar Pichai, Twitter, June 5, 2025). These advancements signal new business opportunities for enterprises looking to integrate state-of-the-art AI for software development, scientific research, and data analysis.