gem-hunter
主要言語: Python
Learn Cloud Applied Generative AI Engineering (GenEng) using OpenAI, Gemini, Streamlit, Containers, Serverless, Postgres, LangChain, Pinecone, and Next.js
This course is part of the Certified Cloud Applied Generative AI Engineer (GenEng)
Note: If possible register your account with a company email address.
Once you have a subscription id apply for Azure Open AI Service here:
https://azure.microsoft.com/en-us/products/ai-services/openai-service
From Microsoft to MIT MBA, the AI reeducation boot camp is coming for every worker and executive
Nvidia says generative AI will be bigger than the internet
Generative AI and Its Economic Impact: What You Need to Know
Must Read: OpenAI DevDay - a pivotal moment for AI
GenEng revolution being led by developers who build deep proficiency in how to best leverage and integrate generative AI technologies into applications
There is a clear separation of roles between those that create and train models (Data Scientists and Engineers) and those who use those models (Developers). This was already on the way, and it much clearer with the GenAI revolution - the future of the GenAI will be determined on how it will be driven to adoption - and it will be driven by how developers adopt it.
GenEng practitioners will need to have many of the same skills of traditional application development, including scalable architecting, integrating enterprise systems, and understanding requirements from the business user. These skills will be augmented with the nuances of building generative AI applications, such as involving the business domain experts in validating aspects of prompt engineering and choosing the right LLM based on price/performance and outcomes
The rise of GenEng: How AI changes the developer role
Google launches its largest and ‘most capable’ AI model, Gemini
Meta, IBM and Intel join alliance for open AI development while Google and Microsoft sit out
Sam Altman to return as CEO of OpenAI
The Year in Tech, 2024: The Insights You Need from Harvard Business Review
The Year in Tech 2024: The Insights You Need about Generative AI and Web 3.0 from Harvard Business Review will help you understand what the latest and most important tech innovations mean for your organization and how you can use them to compete and win in today's turbulent business environment. Business is changing. Will you adapt or be left behind? Get up to speed and deepen your understanding of the topics that are shaping your company's future with the Insights You Need from Harvard Business Review series. You can't afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas--and prepare you and your company for the future.
McKinsey Technology Trends Outlook 2023
Watch Introduction to Generative AI
McKinsey: The economic potential of generative AI: The next productivity frontier, McKinsey Digital report, June 2023
GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models, Tyna Eloundou, Sam Manning, Pamela Miskin, and Daniel Rock, March 2023 (arXiv:2303.10130)
Goldman Sachs: The Potentially Large Effects of Artificial Intelligence on Economic Growth, Joseph Briggs and Devesh Kodnani, March 2023
OpenAI API is a collection of APIs
APIs offer access to various Large Language Models (LLMs)
LLM: Program trained to understand human language
ChatGPT is a web service using the Chat completion API Uses:
Chat completion: Given a series of messages, generate a response
Function calling: Choose which function to call
Image generation: Given a text description generate an image
Speech to text: Given an audio file and a prompt generate a transcript
Fine tuning: Train a model using input and output examples
The new Assistants API is a stateful evolution of Chat Completions API meant to simplify the creation of assistant-like experiences, and enable developer access to powerful tools like Code Interpreter and Retrieval.
The primitives of the Chat Completions API are Messages, on which you perform a Completion with a Model (gpt-3.5-turbo, gpt-4, etc). It is lightweight and powerful, but inherently stateless, which means you have to manage conversation state, tool definitions, retrieval documents, and code execution manually.
The primitives of the Assistants API are
The OPL Stack stands for OpenAI, Pinecone, and Langchain. It's a collection of open-source tools and libraries that make building and deploying LLMs a breeze.
“AI will be the greatest wealth creator in history because artificial intelligence doesn’t care where you were born, whether you have money, whether you have a PhD,” Higgins tells CNBC Make It. “It’s going to destroy barriers that have prevented people from moving up the ladder, and pursuing their dream of economic freedom.”
It’s already valued at almost $100 billion, and expected to contribute $15.7 trillion to the global economy by 2030.
“It’s not that if you don’t jump on it now, you never can,” Higgins says. “It’s that now is the greatest opportunity for you to capitalize on it.”
A.I. will be the biggest wealth creator in history
Generative AI could add up to $4.4 trillion annually to the global economy
Silicon Valley Sees a New Kind of Mobile Device Powered by GenAI
Microsoft CEO: AI is "bigger than the PC, bigger than mobile" - but is he right?
Artificial General Intelligence Is Already Here
Inside the race to build an ‘operating system’ for generative AI
Business intelligence in the era of GenAI
The Convergence of AI and Web3: A New Era of Decentralized Intelligence
What is the potential of Generative AI and Web 3.0 when combined?
How Web3 Can Unleash the Power of Generative AI
LangChain Explained in 13 Minutes | QuickStart Tutorial for Beginners
LangChain Crash Course for Beginners
LangChain Crash Course for Beginners Video
LangChain for LLM Application Development
LangChain: Chat with Your Data
A Gentle Intro to Chaining LLMs, Agents, and Utils via LangChain
The LangChain Cookbook - Beginner Guide To 7 Essential Concepts
Greg Kamradt’s LangChain Youtube Playlist
1littlecoder LangChain Youtube Playlist
Pinecone
https://docs.pinecone.io/docs/quickstart
https://python.langchain.com/docs/integrations/vectorstores/pinecone
LangChain - Vercel AI SDK
https://sdk.vercel.ai/docs/guides/providers/langchain
Using Python and Flask in Next.js 13 API
https://github.com/wpcodevo/nextjs-flask-framework
https://vercel.com/templates/python/flask-hello-world
https://vercel.com/docs/functions/serverless-functions/runtimes/python
https://codevoweb.com/how-to-integrate-flask-framework-with-nextjs/#google_vignette
https://github.com/vercel/examples/tree/main/python
https://github.com/orgs/vercel/discussions/2732
https://flask.palletsprojects.com/en/2.3.x/tutorial/
https://flask.palletsprojects.com/en/2.3.x/
Reference Material:
Top 5 Resources to learn LangChain
Official LangChain YouTube channel
Building Custom Q&A Applications Using LangChain and Pinecone Vector Database
End to End LLM Project Using Langchain | NLP Project End to End
Build and Learn: AI App Development for Beginners: Unleashing ChatGPT API with LangChain & Streamlit
Total Questions: 40
Duration: 60 minutes