Welcome to your weekly AI Newsletter from AITechCircle!
I’m Building, Implementing AI solutions, and sharing everything I learn along the way…
This week is a recap of 2024 with some of the key insights and the tools and recipes I have used or learned over the year with you as an AI community. Please take a moment to read and share this with a friend or colleague who might benefit from these valuable insights!
Today at a Glance:
- How to start your journey of AI & Generative AI project implementations in your organization
- Generative AI Use Cases
- AI ethics and Governance
- AI Courses to attend
- Open Tech Talks with AI industry leaders
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Wrapping up a year of learning…
Today’s edition summarizes the key areas discussed and covered in this newsletter.
So let me start with thank you for joining us and sharing your feedback.
This newsletter is being published on TechCircle’s portal, Medium AITechCircle at its portal, LinkedIn Newsletter, Medium, Substack, and in audio format on the podcast Open Tech Talks.
Two key factors drive me to keep doing it despite the challenges of time constraints and other factors.
- # 1 is to share whatever I learn while building and implementing AI and generative solutions.
- # 2 This newsletter also pushes me to learn something new every week. I don’t hesitate to experiment with new topics which is entirely new to me; however, I try to learn, understand, share, and/or document during this ride.
You are all wonderful, and I thank you from the bottom of my heart for your valuable feedback, suggestions, and comments, which have helped me continue on this journey.
Few statistics of this newsletter in the year 2024
- 44 weeks out of 56 weeks of the year, you have got the edition
- A total of 3,479 emails are sent, and portal subscribers are 364
- LinkedIn readers are 1624
Now, let’s start with a recap of the key topics that can support your journey.
3 Questions are on the table for AI
My experience working with AI and Generative AI shows that three questions repeatedly arise and are asked by the executives:
- How do I get started with AI?
- Where can AI deliver the most value?
- How do I scale and operationalize AI?
I have summarized several articles over the year to address the above areas; you can read them in depth below.
Before you start reading…
Embracing the New Year with New Opportunities
As we step into the year ahead, I’m energized by the possibilities that lie before us. The ever-evolving AI landscape presents exciting challenges and opportunities, and I remain dedicated to sharing what we are collectively learning as an AI community.
With deep gratitude, I wish you a year of health, growth, innovation, and exploration.
Here’s to learning, advancing, and succeeding together.
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AI Implementation Journey…How do I get started with AI?
If this is your first AI initiative, how to start it, and what to target in the organization, start here.
- Adopt (Takers) Phase: Starting the AI Implementation Journey link
- Buy (Shapers) Phase: Extending SaaS with Oracle’s Generative AI Managed Services link
- Build (Makers) Phase: AI Implementation Journey: Creating Custom Gen AI Models for Enterprise Success link
- Building a Game-Changing AI Strategy: Step-by-Step Guide and Exercises for Your Organization
- Simplified Architecture to take up Generative AI in the Cloud Applications
- Lost in AI use cases, don’t forget to put your AI Strategy first and align it with business
- Build Your business-specific LLMs Using RAG
- 5 approaches for deploying Generative AI
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Chief AI Officer (CAIO) Corner:
Chief AI Officer’s Playbook: Executing the First 90 Days link
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AI Conversations during AI events:
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How do I scale and operationalize AI?
AI, Generative AI Maturity Framework.
Here are the key resources covered over the year.
- Tool for assessing Generative AI maturity within an organization link
- Actionable, Responsible AI Maturity Roadmap
- 7 AI maturity assessment frameworks from leading organizations link
- Adopting AI Responsibly: Guidelines for Procurement of AI Solutions by the Private Sector, published by the World Economic Forum
- Generative AI Framework for HMG from the UK Center Digital and Data office has outlined 10 principles for the safe, responsible, and effective use of generative AI in government organizations. link
Responsible AI, Ethical AI, AI Governance
- Let’s build an AI Governance Framework for an organization link
- Diaries from the Field – Building Ethically Responsible AI Enterprise Solution link
- The Model AI Governance Framework for Generative AI (MGF for GenAI) from AI Verify Foundation outlines nine dimensions to create a trusted environment.
- Key Risks Associated with Generative AI
- AI Under the Guardrails of Regulations
- Learning the core principles of AI ethics
- AI Safety and Regulation: A Call to Action
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AI /ML / LLMs Courses to attend:
Below are the industry’s renewed courses for you to sharpen your talent
- Introduction to Generative AI for Newbies
- Unwrap 12 days of training to learn generative AI this December from Google link
- Building Agents: Free Course, 20 videos & notebooks focused on building agents from Langchain, link
- Stanford released a 1.5-hour lecture on Building Large Language Models on Youtube
- Practical Multi AI Agents and Advanced Use Cases with crewAI from DeepLearning
- Unwrap 12 days of training to learn generative AI this December from Google link
- 20-hour boot camp on Probability & Statistics from Steve Brunton, University of Washington.
- Introducing Multimodal Llama 3.2. Learn the details of Llama 3.2 prompting, tokenization, built-in, and custom tool calling. link
- Retrieval Optimization: From Tokenization to Vector Quantization. This course addresses how tokenization affects vector search and how to optimize search in LLM applications that use RAG. link
- LLM Agents from UC Berkeley, free course to attend.
- LM-class is an introduction-level education resource for contemporary language modeling, broadly construed. It relies on a prior understanding of machine learning and neural networks at the introduction level and undergraduate-level programming, probability theory, and linear algebra. The materials were developed for Cornell Tech’s CS 5740 Natural Language Processing.
- Generative AI with Large Language Models from Deep Learning & AWS. Gain foundational knowledge, practical skills, and a functional understanding of generative AI.
- CS324 – Large Language Models. In this course, students will learn the fundamentals of modeling, theory, ethics, and systems aspects of large language models and gain hands-on experience working with them.
- Prompt Compression and Query Optimization: In this course, you’ll learn to integrate traditional database features with vector search capabilities to optimize the performance and cost-efficiency of large-scale RAG applications.
- IBM: AI for Everyone: Master the Basics: Understand AI, its applications and use cases, and how it transforms our lives. Explain terms like Machine Learning, Deep Learning, and Neural Networks.
- Embedding Models: From Architecture to Implementation: This course covers the details of the architecture and capabilities of embedding models, which are used in many AI applications to capture the meaning of words and sentences.
- Federated Learning course from Flower, an open-source framework, to build a federated learning system and implement federated fine-tuning of LLMs with private data
- Pretraining LLMs from DeepLearning AI. This course explores the creation of large language models (LLMs) like Llama, Grok, and Solar using a technique called pretraining, which is the first step of training an LLM
- Generative AI Fundamentals Specialization from IBM covers the fundamental concepts, capabilities, models, tools, applications, and platforms of generative AI foundation models
- Understanding Large Language Models: Foundations and Safety, a course from UC Berkeley. Course Site, Youtube
- A course on AI and NLP from Hugging Face on YouTube
- CMU Multilingual NLP 2022 course on youtube
- CMU Advanced NLP Spring 2024 course on youtube
- Advanced Natural Language Processing (Fall 2020): Lectures from the Fall 2020 offering of CS 685 (advanced natural language processing) at UMass Amherst
- AI Agents in LangGraph: You will learn to build an agent from scratch using Python and an LLM and then rebuild it using LangGraph, learning about its components and how to combine them to build flow-based applications.
- Building Agentic RAG with LlamaIndex: In this course, created in collaboration between Deep Learning AI and LlamaIndex and taught by co-founder and CEO Jerry Liu, you will learn to build agents that can intelligently navigate, summarize, and compare information across multiple research papers from arXiv
- Learn Generative AI by building a project from DeapLearning. This provides a detailed project description, a step-by-step outline of the RAG process, and courses for you to learn.
- Learn how to implement Llama 3 From Scratch.
- Introduction to Data-Centric AI from MIT. This class covers algorithms for finding and fixing common issues in ML data and constructing better datasets, concentrating on data used in supervised learning tasks like classification.
- Natural Language Understanding from Stanford Online. Taught by professor Christopher Potts. Covers theoretical concepts from linguistics, natural language processing, and machine learning.
- Stanford XCS224U: Natural Language Understanding, taught by Professor Christopher Potts, this course covers theoretical concepts from linguistics, natural language processing, and machine learning.
- LangChain for LLM Application Development from Deep Learning AI. This course enables you to apply LLMs to your proprietary data to build personal assistants and specialized chatbots
- Building Systems with the ChatGPT API from Deep Learning AI. This 1-hour course will assist you in building multi-step systems using large language models.
- LLMOps: Building Real-World Applications With Large Language Models
- Evaluating and Debugging Generative AI from Deep Learning AI
- ChatGPT Prompt Engineering for Developers from Deep Learning AI. Learn prompt engineering best practices for application development
- Red Teaming LLM Applications from Deep Learning: Learn to identify and evaluate vulnerabilities in large language model (LLM) applications.
- CS25: Transformers United V4 from Stanford
- Local LLM RAG with Unstructured and LangChain [Structured JSON] is an excellent video that enables you to replicate this.
- Deep Learning Foundations: Large Language Models from Soheil Feizi, CS Prof at UMD, ML/AI, MIT Alum.
- Hands-on Data Science: Complete your First Project from Mısra Turp
- Advanced RAG with LlamaParse and Reranker collab lab and video
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Open Tech Talks Podcast…
- 150 – Tips for Adopting AI and LLMs in Business: Lessons from Michael Vandi, The CEO of Addy AI Apple | Spotify | Amazon Music
- 147 – How organizations can start the journey of AI with Mark Wormgoor. In 2022, after 25+ years in technology in the corporate world, Mark decided to start Tairi. Tairi originates from his passion for leadership in tech. Apple | Spotify | Amazon Music
- 146 – Mastering Communication in the AI Era with expert Tips from TJ Walker.” Over 2 million students on Udemy mark TJ Walker’s commanding digital presence across more than 200 courses. He is the author of six books, including the USA Today #1 Bestseller “Secret to Foolproof Presentations” and “Media Training A to Z. Apple | SpotifyAmazon Music
- 145 – Building a Game-Changing AI Strategy: Step-by-Step Guide and Exercises for Your Organization; it will guide you through actionable steps and hands-on exercises to help your team develop an AI strategy that creates real impact and sets you apart from the competition. Apple | Spotify | Amazon Music
- 132 – Navigating the Rise of Generative AI: What Every CTO Needs to Know with Kevin Surace, Chairman & CTO, Appvance AI. Globally recognized futurist, inventor, and innovation leader credited as the pioneer of virtual assistants Apple | Spotify | Amazon Music
- 142 – From Blockchain to Generative AI: Deep Dive with JB Benjamin,” JB is not just an entrepreneur but an exceptionally technically proficient lead UI/UX developer. His imaginative approach has led to the development of multiple successful digital businesses. Apple | Spotify | Youtube
- 141 – Career Growth Strategies with Executive Coach Vladimir Baranov,” Founder and Certified Executive Coach of Human Interfaces. As an entrepreneur and the business leader behind several successful tech companies, he knows what it takes to survive and blossom in today’s chaotic business landscape. Apple | Spotify | Youtube
- 140 – Developing AI Products From Tech Stack to User Feedback with Jason Agouris. Jason’s extensive experience in systems integration across retail, fintech, wholesale, and supply chain logistics makes him our go-to data integration and strategy guru. Apple | Spotify | Youtube
- 139 – Building an AI-Driven Business with Gray Mabry. Gray Mabry, Co-Founder & CEO of iVenture Solutions, has over two decades of leadership experience. Apple | Spotify | Youtube
- 138 – Transforming Text to Audio: The Future of AI in Content Creation with Ian Harris. Founder of Pulse Podcasts has started his unique idea to help others capitalize on AI advancements. Apple | Spotify | Youtube
- 137 – Unlocking Startup Success: Insights from Leopold van Oosten. The CEO of Amsterdam Standard has built 18 startups in 20 years and has won 3 significant awards through his organizations. Apple | Spotify | Google Podcast | Youtube
- 135 – Building a Successful AI SaaS Product with Denzil Eden. She is the founder of Smarty ai. Apple | Spotify | Google Podcast | Youtube
- 134 – AI and the Art of Advertising with Robert Brill. He’s the Chief Executive Officer of Brill Media and has been immersed in the advertising industry since 2003. Apple | Spotify | Google Podcast | Youtube
- 133 – The Rise of AI in Creative Writing: Its Impact and Potential with Alex Shvartsman”. He’s the author of Kakistocracy (2023), The Middling Affliction (2022), and Eridani’s Crown (2019) fantasy novels. Over 120 of his short stories have appeared in Analog, Nature, Strange Horizons, and many other venues. Apple | Spotify | Google Podcast | Youtube
- 132 – Navigating the Rise of Generative AI: What Every CTO Needs to Know with Kevin Surace Apple | Spotify | Google Podcast | Youtube
- 130 – Digital Safeguards: Unlocking Cybersecurity Basics with Nick Lorizio. Founder, AstuteTechnologists. Apple | Spotify | Google Podcast
Tech and Tools…
- Chat with your Data in the Database without writing SQL
- RAG Basics: A Beginner’s Guide to Retrieval-Augmented Generation
- Chat with Knowledge Base through RAG
- Your Data Analyst AI Agent
- AI comes to the Database at the core of your data
- Openpilot is an operating system for robotics
- CodeGPT empowers you with an AI copilot, which can be self-hosted into your infrastructure.
- Skyvern automates browser-based workflows using LLMs and computer vision.
- Phidata: is a framework for building agentic systems
- LLM Finetuning toolkit is a config-based CLI tool for launching a series of LLM fine-tuning experiments on your data and gathering their results
- Citizen DJ: Make music using the free-to-use audio and video materials from the Library of Congress
- LongWriter: An open-source project built to generate outputs exceeding 10,000 words using long-context LLMs, with models fine-tuned for extended text generation and evaluated through custom benchmarks to ensure quality and length.
- Generative Agents: Interactive Simulacra of Human Behavior. It contains our core simulation module for generative agents, computational agents that simulate believable human behaviors and their game environment
- Llama Stack: This repository consists of Llama Stack API specifications, API Providers, and Llama Stack Distributions
- MLX Swift Examples: MLX is an array framework for machine learning research on Apple silicon. MLX Swift expands MLX to the Swift language, making study and experimentation easier on Apple silicon
- Supervision: write your reusable computer vision tools.
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And that’s a wrap!
Thank you, as always, for taking the time to read.
I’d love to hear your thoughts. Please reply and let me know what you find most valuable this week. Your feedback means a lot.
Until next week,
Kashif Manzoor
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The opinions expressed here are solely my conjecture based on experience, practice, and observation. They do not represent the thoughts, intentions, plans, or strategies of my current or previous employers or their clients/customers. The objective of this newsletter is to share and learn with the community.
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