I am looking at rewriting my Skills Matrix app and wondering what everyone's take on their favorite LLMs is. What are the Pros, the cons, etc.? My app will load a CV and compare it against job descriptions that match particular criteria. The output will be a percentage match score and a radar graph of what you hit and missed to see your overall score. I have previously developed this in Python using dash, NLTK and scikil-learn. I am now thinking of redoing it with crew to do some heavy lifting. Currently, it looks like this. The longer term people in the community have probably seen it before

Jeremy Howard released FastHTML for python devs. It helps develop interactive websites with the power of Python instead of having to learn a stack in another language (ala React, Nextjs, etc). I have not tried it yet but will be playing with it this weekend. If you try it out, lmk how simple it was for you. p.s. Jeremy taught the fantastic and free Fast AI deep learning classes that were my first intro into ML. https://x.com/jeremyphoward/status/1818036923304456492

Hey guys! I'm super excited to announce that my brand-new RAG tutorial for AI enthusiasts is now live on YouTube! In this video, you'll master RAG with CrewAI, Firecrawl, and advanced techniques to take your AI projects to the next level. This tutorial combines everything you need to know about Retrieval Augmented Generation into an easy-to-follow guide so that you can build powerful AI applications and streamline your workflow. Why You Shouldn't Miss This: - Made for All Skill Levels: We’ll start from the basics and build up to more advanced topics, ensuring you have a solid foundation. By the end, you'll be able to create AI tools, implement advanced RAG techniques, and use Firecrawl for web scraping. - Real Code Examples: This tutorial is packed with practical examples using the latest version of CrewAI. You can follow along step-by-step and see exactly how everything fits together. Don’t wait! Click the link below to watch the RAG tutorial and start building your own AI projects today. I'm really looking forward to seeing the amazing things you'll create with RAG and CrewAI. If you have any ideas or suggestions for future videos, please drop them below! Cheers, Brandon Hancock 🥂🤖 P.S. Because you guys are awesome, here's a link to the source code ❤️ https://github.com/bhancockio/crewai-rag-deep-dive

Hey gang! I’m pumped to announce our very first AMA (Ask Me Anything) session and Creator Spotlight featuring @Ashita Achuthan! 🎉 Join us this Sunday at 10 AM PST / 1 PM EST for a fun and informative session where we dive deep into Ashita’s journey and her incredible projects. ​ ​Whether you are just starting your AI journey or an AI expert, this AMA will have something for you! Ashita is not only a developer; she’s an entrepreneur with a ton of hands-on experience in building Gen AI applications that she’ll be sharing in the AMA. ​ ​Why You Shouldn’t Miss This AMA​ Ashita is not only a developer; she’s an entrepreneur with a ton of hands-on experience in building Gen AI applications that she’ll be sharing in the AMA. She’s the founder of Otto (ottowrites.co), an innovative app that helps users create personal biographies. Before Otto, she grew Fantoons (fantoons.xyz) to over 60,000 users and has been a vital contributor to our AI Developer Accelerator community. Her journey from a Product Manager at Twitter, Amazon, and eBay to a successful entrepreneur is packed with valuable insights and lessons. Additionally, Ashita co-founded Women In Product, a community of over 50,000 women PMs, showcasing her dedication to empowering women in tech. ​ ​What to Expect: - Introduction: Learn about the Spotlight Creator of the Month initiative, aiming to celebrate developers who are building amazing things with Gen AI. - Ashita’s Story: Hear Ashita’s inspiring journey and explore her projects like Otto and Fantoons. - Tech Deep Dive: Get insights into the tools and tech stack Ashita uses to build her apps. - Audience Q&A: Have your questions answered live! You can ask in the chat or unmute and join the conversation. ​ Before the AMA, take some time to explore the amazing work Ashita is doing: Otto: ottowrites.co​ Fantoons: fantoons.xyz

Good morning Brandon I just saw your youtube video about rag dive dive. I have a simple question, the embedding file is similar to a .lora or .safetensors like stable difussion generate when you are training images? also, there is any way that the embedding also can know about the image? maybe through a metadata or classifying the content of the image like a prompt like stable difussion does with images like for example when you use an interrogator for an image it will give you the prompt of that image. That will be a very robust embedding with also the information of the image.