The goal of this group is to help you navigate the complex and rapidly evolving world of data science and artificial intelligence. This is your hub to stay up-to-date on the latest trends, learn specialized skills to turn raw data into valuable insights, connect with a community of like-minded individuals, and ultimately, become a Data Alchemist. Together, let's decode the language of data and shape a future where knowledge and community illuminate our way. Rules - Don't sell anything here or use Data Alchemy as any kind of funnel - We delete low effort community posts, and posts with poor English. Proofread your post first. - Help us make the posts high quality. If you see a low quality post, then click on the 3 dots on the post and "Report To Admins". Start by checking out these links - Classroom - Introduction - Roadmap - Contribution Be Aware of Scammers - Please be aware that this is a public group. Unfortunately, some people abuse the Skool platform to send DMs or post comments to trick people. This is the internet, so always do your own due diligence. Never automatically trust someone here on the Skool platform other than @Dave Ebbelaar's official account. To kick things off, please comment below, introducing yourself. Let us know: 1. Your name and where you're from 2. What project(s) you're currently focused on See you in the comments!

Google DeepMind's bipedal bots go head-to-head after years of prep. Very impressive! End of soccer? I don't think so... 😃 https://www.popsci.com/technology/deepmind-robot-soccer/

Responsible AI, is a suite of tools for a customized, end-to-end responsible AI experience It's an approach to assessing, developing, and deploying AI systems in a safe, trustworthy and ethical manner. https://responsibleaitoolbox.ai/ https://github.com/microsoft/responsible-ai-toolbox

Introducing DBRX, an open, general-purpose LLM created by Databricks. Across a range of standard benchmarks, DBRX sets a new state-of-the-art for established open LLMs. - mixture-of-experts (MoE) architecture with 132B total parameters, of which 36B parameters are active on any input - trained on 12 trillion tokens — Llama 2 was 2T - maximum context length of 32k tokens - Llama-like license: non-commercial terms set at 700 million users and cannot train on outputs.  https://www.databricks.com/blog/introducing-dbrx-new-state-art-open-llm

If 2023 was the year of chatbots, then 2024 is set to be the year of agents. And they are going to change everything. But what are these so-called "agents"? Well, what makes an agent different from a standard software program is that an agent can autonomously perceive and act within a certain environment to achieve specific goals without being explicitly programmed to do so. Sounds cool, but also kind of scary, right? In the current project that I am working, we are using various agents working together in a multi-agent system to complete tasks, where each agent handles specific subtasks. It's actually not much different from how humans operate. And that's what I find most exciting about this: the best way to build intelligent agent solutions is to ask yourself, "How would a human solve this problem?" Can you imagine having several agents assisting you with your tasks? Let me know in the comments what agents you would like to build!