Localizing GitHub Repositories with LLMs
Large Language Models (LLMs) excel at compared to machine translation, as they process tokens of text in a context window. LLMs use attention mechanisms to weigh the relevance of each token relative to others in the sequence, allowing them to capture nuanced meanings and contextual dependencies effectivelyBuilding AI Agent Applications Series - Using AutoGen to build your AI Agents
In the previous content, we learned about AI Agent. If you didn't read it, please read my previous content - Understanding AI Agents. We have many different frameworks to implement AI Agents. AutoGen from Microsoft is a relatively mature AI Agents framework. Now AutoGen is mainly based on two programming languages .NET and Python. The more mature version is the Python version. The content in this article is mainly based on the Python version https://microsoft.github.io/autogen. If you want to learn the .NET version, you can visit here https://microsoft.github.io/autogen-for-netMastering Azure OpenAI Services: A Comprehensive Learning Path for Aspiring AI Engineers
Are you a computer science student looking to delve into the world of Azure OpenAI Services? Look no further! In this Microsoft Learning Pathway, "Develop Generative AI solutions with Azure OpenAI Service," you'll embark on an exciting journey to harness the power of OpenAI's vast language models like ChatGPT, GPT, Codex, and Embeddings. These models are pivotal for creating innovative Natural Language Processing (NLP) solutions that can comprehend, converse, and generate content.Azure OpenAI Services in teaching and education
With the advent of Large language models(LLMs) like GPT-3, we see a transformation in education. In this article, I present my views on the future of education considering these developments. The views presented here are based on my teaching - but are a personal perspective. Today, there is a lot of excitement and speculation about GPT-3, and it is natural to ask how intelligent GPT-3 is and whether it approaches human-level intelligence. But in many ways, that's the wrong question to ask. Instead, exploring the idea of how we can build ChatGPT-like functionality using our own data is more interesting. When framed this way, we focus on the pragmatic and ignore the esoteric. If the industry adopts the 'co-pilot first approach.', educators must follow this trend to keep up with the new job roles. This will need a complete rethinking of many of the current ideas on education and the adoption of some new ideas that I proposed in this article. The conversation changes from: 'chatGPT is used for exam cheating or not' to: How can I empower my students to take up jobs of the future if the co-pilot first mode of work becomes a default?'
