Hi, as a consultant I am always curious to hear RL stories about how to use AI as a consultant, and how to make AI ones consultant domain. Hear a podcast I have found on the topic. It seems to be a young guy from Canada they are interviewing. (Have not gotten around to listen to it fully.) https://www.youtube.com/watch?v=3J3mGJ9lpsE&t=417s Please add similar resources if you have any ...

Hey everyone, I thought this was a super interesting & insightful comment about the current debate happening in the EU and the US about regulating the AI space. What are your thoughts on how to best approach this? "The UAE Minister of AI, Omar Al Aloma, points to a historical precedent of premature technology regulation motivated by fear: the ban of the printing press in 1515 by Sultan Selim I led to the decline of the Ottoman Empire.“We overregulated a technology, which was the printing press. It was adopted everywhere on Earth. The Middle East banned it for 200 years. The calligraphers came to the sultan and said: ‘We’re going to lose our jobs, do something to protect us’—so, job loss protection, very similar to AI. The religious scholars said people are going to print fake versions of the Quran and corrupt society—misinformation, second reason. It was fear of the unknown that led to this fateful decision." Source: comment by Yann LeCun, VP and Chief AI Scientist at Meta, inspired by https://fortune.com/2023/11/28/artificial-intelligence-ai-technology-regulation-policy-guardrails-uae-fortune-global-forum/

Hey! I want to teach people statistics, Probability, Calculus, and Linear Algebra . Honestly, I want to apply this idea to help myself do my best and help and encourage others. I am not an expert yet, But I want to try to apply this idea. What do you think about that? if you have any suggestions also try to put it I will appreciate that .

IS PYTHON WHICH I AM LEARNING FROM KAGGLE(MENTIONED IN THIS COURSE) ENOUGH TO START THE AI JOURNEY? OR DO I HAVE TO GAIN SOME EXTRA PYTHON KNOWLEDGE FROM SOME OTHER STUFF?

I have my first project. My wife has been in a sales business for over 20 years and has a list of 1744 clients with 25 columns. We want to do some targeted reach out based on multiple things. So my goal is to take her client list, get it into csv format, and use pandas and ai to start exploring the data. Once we have a good understanding of what is in the data and the different lists we want to create, I will save off separate lists from the main list. Not a super interesting project, but it will require me to use some of the skills that Dave has taught in the course.

Hi everyone! Hope you are doing great! Today, I came across a thought-provoking article on the Risks of Over-Optimizing Metrics in AI. You can find the article here. Here's a brief summary: The article discusses the concerning trend of blindly optimizing metrics in AI systems, leading to unintended consequences. Rachel Thomas, a machine learning expert, highlights key principles: 1. Metrics as Proxies: Metrics often serve as proxies for what truly matters. For instance, using time spent on YouTube as a proxy for user happiness inadvertently promoted radicalizing conspiracy theories. 2. Gaming Dilemma: Metrics are prone to manipulation. Examples include teachers cheating on standardized tests and platforms facing issues with fake clicks and followers to game algorithms. 3. Short-Term Focus: Metrics tend to overemphasize short-term goals, neglecting long-term considerations like reputation and societal impact. The Wells Fargo case, with its intense focus on cross-selling metrics, serves as a cautionary tale. 4. Addictive Environments: Online behavioral metrics often capture engagement in addictive environments, missing user preferences in healthier settings. 5. The article emphasizes that while metrics have value, they should be part of a broader picture, complemented by qualitative input from domain experts and impacted groups. As AI practitioners, it's crucial to apply metrics thoughtfully, considering their representations and limitations. AI's prowess in optimizing metrics necessitates responsible measurement to avoid unintended harms on a larger scale. Have a great day!!! 😁

I was talking with a guy in the hot springs tonight and it turns out he owns a supplement company. We got to talking about what I do for work and, long story short, I landed a project to build an AI assisted customer service chatbot!

Hi everyone, during a talk with Marco I got the idea that it might be helpful to lay down the areas of expertise needed to become an AI pro. (just focusing on LLM, rather than DS, ML, ...) Or rather the learning paths, because there are different roles to take. This is how I see it. Dave - What do you think? : @Dave Ebbelaar @Mamatha Naganna @Marco Bottaro @Ana Crosatto @Brandon Phillips A] AI Tech Knowledge ------------------------------- (in the order of going down the rabbit hole) 1) LLM Ecosystem / platform user (SaaS) Become proficient with ChatGPT, Bard, Claude Understand prompting, plugins, GPTs, ...; knowing some "super prompts" Also experimental Agent platforms like SuperAGI, AutoGPT, ... 2) LLM SaaS application user (SaaS) Learn about all the different end-user tools out there and use them in your area (video, presentations, translations, ...) 3) LLM NoCode application coder (PaaS) Web/Desktop: Learn about flowise, open gpt, open ai assistent (?) Cloud-Designers: Bedrock (?), Azure OpenAI Studio, Azure AI Studio 4) LLM Code application coder (the a16z essay is a good way to understand it) LLM frameworks and python libraries (langchain, autogen, ...), python knowledge Prompting, Vector Databases Coding environments (Desktop: VS Code) or alternatively Cloud-based Optional: everything else and non-AI related to building an application: web development, app development, UX-Design, design, ... 5) LLM model developers Fine-tuning models, Olama, ... B] Subject matter knowledge - Industry and Job role knowledge - applying the knowledge in your industry or job -------------------------------------------------------------------------------------------------------------------------------- Application of AI in your industry Application of AI for your job role / profession (agile coach, developer, business analyst, ...)

https://medium.com/@yaelaidata/custom-instructions-prompts-simple-steps-to-smarter-interactions-917977a099b3

Hi everyone, over the weekend I have finally found the time to start watching the recent developer conferences. I would like to share my ideas, and ask you for your ideas and clarifications First of all, the famous Open AI conference that has happened already a while ago. (November 6) OpenAI DevDay, Opening Keynote I noticed that I have somehow missed a couple of details like the fact that GPTs not only store data (RAG) but can also take actions. Second, the keynote of the Microsoft CEO at the Ignite 2023 (November 14) Full Keynote: Satya Nadella at Microsoft Ignite 2023 A lot of important points, some hardware news, but on the GenAI side mostly the new tools: Azure AI Studio (full LLM development environment https://azure.microsoft.com/en-us/products/ai-studio - will just like Bedrock also allow the use of open source models. afaik Azure OpenAI is 100% focused on OpenAI FM.) Copilot Studio (Customize the Microsoft365 copilot https://www.microsoft.com/en-us/copilot/microsoft-copilot-studio) Cooperation with Mistral Something about a NVidia AI Factory, that I did not quite understand Third, the presentations at the AWS re-invent (November 27) There are a couple of keynote speeches, I have not had the time to wathc them, no idea which is the most interesting and important one. https://www.youtube.com/watch?v=PMfn9_nTDbM https://youtu.be/UTRBVPvzt9w?si=d7IOJY7lqaAE95Ac AWS re:Invent 2023 - Keynote with Dr. Swami Sivasubramanian in any case the big GenAI news is: afaik the presentation of Q, something like ChatGPT from Amazon apparently Here a summary, from a website: https://www.infoq.com/news/2023/12/aws-reinvent-2023-recap/

https://youtu.be/dS2HYPY7T-4?si=BBTWY0ybc5dM-emQ

I did something pretty crazy in my last YouTube video. For a recent project that I worked on, I had to develop an AI WhatsApp bot. However, we needed to have complete control over the code and data, which meant we could not use any external services or platforms other than the WhatsApp API. So, I figured out how to build a WhatsApp bot with pure Python—nothing else! And I am giving it away completely for free, along with a video tutorial and all the code. (I have permission to share this, as I replaced the custom data part with a demo) You can easily sell this project for $5k+ to clients. Do you want to learn how to build and sell chatbots? Then check out the video below!

G’day all! Very new to this whole thing from a technical perspective but have more than a few years’ experience in cyber security to looking forward to exploring the cross section between AI and cyber security. Hit me up if you want to collaborate! Cheers!

the recent post of Mamatha made me think. https://www.skool.com/data-alchemy/role-of-a-business-analyst-in-ai for those people who like her have a non-tech background, what to learn, focus on SaaS out-of-the-box solutions, SaaS, these are important topics. Do you know some reports, good YT videos that cover that topic?

Excited to be part of this great learning platform. Looking forward to upskill in data/AI fields for common good and addressing African challenges through well-informed data driven decisions.

Many years ago when I was taking my first programming course (C+), a fellow student said there are two types of students 1) those who love programming, and 2) those who "want" to love it. I did not feel like I was of the former, but his statement likely impacted me so I did not feel like programming was "for me". I firmly believe now that whatever we DO with our time, we will become better at, and whatever we spend our time doing (and feel the satisfaction of getting better), we will enjoy more, and even come to feel "love" for. I am excited to say that I am 50% through the Python course (as part of Data Alchemy's HW). Still plugging away! To anyone who may not feel like coding is "natural" to them, I feel the same way most of the time, but I also enjoy when I "get" a code on the first try! Programming is not going anywhere, so we who are working towards having an understanding of it, will be in a much better position to help others (and the world) than those who do not understand it! Keep pushing through! Consistency is key!

I have 24+ years of experience and currently holds a position as Lead Business Analyst. I have been familiarizing myself with AI and its concepts. At the moment I am able to appreciate ML with limited knowledge on Supervised learning, Unsupervised learning and Reenforcement Learning .. their algorithms. As I am not a developer(still contemplating if I should explore Python) and given I am 49 years old.. I think I should position myself in leading AI projects analyse which algorithm/Model is best suited to solve a problem or something like that.. Thoughts?

I am curious to learn about the prerequisites or qualifications required to join the Data Freelancer(Q&A) call. What is a mastermind member? https://www.skool.com/data-alchemy/calendar

Can we please all choose a problem to solve with AI as our group project. It will be great working together as a team. Any ideas please and is everyone in support of this.

Ambitious woman how wants to learn via this platform to play with data

I am trying to do scraping as this is my first try. I am beginner but from last week I am not able to solve the issue. The whole information is in description. I have given class in my code but it is fetching the first row correct with all the right information but from second row it is not giving the accurate information. Even though it doesn't looks complex and i am not entering the link and fetching the information that would be my next step but in the first step only I am stuck. This is the link:https://www.softwaresuggest.com/services/procurement-companies I have also attached the my code and output file for reference to what kind of output is required. And I am using VS to do this. Hope any one call guide me so that i can learn and grow faster in this field My code is:

Hey guys, it's been a while since I've uploaded a video. I've been extremely busy the last couple of weeks, but I am back with a brand-new tutorial on the OpenAI Assistants API! In this video, you will not only learn the basics of the new API, but I am also going to provide you with a framework to build bots with it! So make sure to check it out and leave a like! 🙏🏻

Hello everyone, I hope you're doing well! What a beautiful week! So, I was thinking, as the 'Share Your Ideas' post got a bit overwhelming, of trying out the Miro board, Marco Bottaro 😉—still getting the hang of it, haha. You can check out all the ideas there or, if you prefer, read them here, where I'll be posting each one in the comments. I should note that in Miro, I had to make some edits to a few ideas since they were a bit lengthy. Also, there's a chance I might have missed adding your idea, so feel free to drop it here or in Miro. Link to Miro: Miro Thank you so much! @Slav Petkovic @Brandon Phillips @Marco Bottaro @Aziz Amari @Olu Akin @Dave Ebbelaar @Rod Langone @Zachary Mwarari @Bastian Brand @Shivkumar Honnukai @Thomas Kangah @Andersen Chang @Nick Griffin @Alberto Puma @Jorge L @Gabriel Vleisides @Muhammad Sohail @Sapnil Patel

Hello everyone, did anyone here already experimented with TimeGPT from Nixtla? It's a generative pre-trained model tailored for time series forecasting. I'm eager to learn from your experiences: - Have you tried TimeGPT in your projects? - Do you see potential use cases for it in your work? - What have been your successes or challenges with it? Thanks in advance for sharing your insights!

Today, I made a Python script that takes your prompt and generates a playlist on Spotify based on that prompt. First off, thanks to @Olu Akin for pointing me to the Mastering OpenAI Python APIs: Unleash ChatGPT and GPT4 course on Udemy. I've been doing non-stop exercises and am three quarters done. Colt Steele, the instructor, explained how he implemented the playlist generator. I did not code along. Instead, I listened, made notes and tried to understand. That was yesterday. Today, I did a closed book re-implementation and it worked. Lessons learned: 1. leverage the LLM's ability to respond with structured output 2. prompt engineering is not dead 3. speaking of prompt engineering: when you get a good response from the LLM, copy it into the prompt as an example to follow 4. most of the coding is the glue between the LLM's response and the service's API 5. UX is not dead: I showed my playlist generator from the terminal to my girlfriend. she shuddered and said: "no way am I ever going to use that" 🤷‍♂️

Hi amazing people! Hope you're doing awesome! Just a quick heads up about our upcoming meeting - don't want anyone missing out on the fun because of time zones! 😄 To keep things light and breezy, here's a cool timer that shows Denver time. Check out the Time zone website, add your city, and voila! No more worries about missing the virtual party. Meeting details: AI/ML/LLM Brain Dump/Storming Session Saturday, December 2 · 6:30 – 7:30am Time zone: America/Denver Google Meet joining info Video call link: https://meet.google.com/uiq-zkdb-mgz Or dial: ‪(US) +1 316-530-7992‬ PIN: ‪297 809 292‬# More phone numbers: https://tel.meet/uiq-zkdb-mgz?pin=4731822830925 See you guys tomorrow! @Slav Petkovic @Brandon Phillips @Marco Bottaro @Aziz Amari @Olu Akin @Dave Ebbelaar @Rod Langone @Zachary Mwarari @Bastian Brand @Shivkumar Honnukai @Thomas Kangah @Andersen Chang @Nick Griffin @Alberto Puma @Jorge L @Gabriel Vleisides @Muhammad Sohail @Sapnil Patel

A few days ago I had an interesting conversation with a fellow AI enthusiast of mine. It was the first time we properly met and spoke about AI and its potential and where each of us stand in our current journey. Both of us could agree on not only on the necessity of AI but also the necessity of people knowing how to properly use it. That’s when I remembered another conversation I had with a person working within the „chamber of commerce“ in my state. He pointed out that there is an ever growing need for businesses to be consulted about AI, how to use them, what to use and what to think and change about. This got me thinking: As the integration of AI into various business sectors accelerates, the gap between technological capabilities and practical know-how widens. It's becoming increasingly clear that AI consulting isn't just a luxury—it's a necessity. The role of an AI consultant goes beyond merely implementing technology; it encompasses understanding the unique needs of each business, identifying the right AI tools, and integrating them in a way that aligns with the company's goals and ethics. So, what should AI consulting focus on? First and foremost I think, it's crucial to educate businesses about what AI can and cannot do. Dispelling myths and setting realistic expectations is a key part of this process. Additionally, consultants should emphasize ethical AI practices, ensuring that AI implementations are fair, transparent, and respectful of privacy concerns. Now, I want to hear your thoughts on the arising topic of AI consulting. What do you think about it, what do you think needs to be consulted about? I am looking forward to reading your thoughts on this, and hopefully we can have a blooming discussion!