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Pretty excited about this initiative. This isn’t another “what’s AI?” course. It a course that teaches you to *use* AI in practical ways. With Google AI Essentials, you’ll learn how to use generative AI tools to help speed up daily tasks, make more informed decisions, and develop new ideas and content. Check it out!

With the rise of generative AI is predictive AI (aka machine learning) going away? Actually, I expect to see more accurate models and wider adoption. Generative AI models are valuable for enhancing feature generation and converting results into conversational interfaces, which are increasingly embraced by business teams. For example, in the past, call recordings sat in object stores hoping to see the light of day. Now with generative AI, turning transcripts into text makes it easy for ML teams to develop and deploy feature pipelines that make better use of unstructured data. Here's a repo with walkthrough of how you can do it using an open source model inside Snowpark Container Services https://lnkd.in/gTkPFGwP

Sometimes we need to understand the fundamentals of generative AI. And if you want 4.5 hours of this kind of content, with behavioral shifting frameworks, interactive worksheets, and tools galore, for you or your organization, come check out Generative AI for Professions. Designed for enterprise. https://lnkd.in/eRrX-FNq

Ditch the blank page forever! Duet AI in Google Docs suggests outlines, generates creative content, and polishes my prose like a champ. #duetai #googleai #google #googledocs #googleworkspace #ai #aiwriting

Just finished the course “Introduction to Conversational AI”! Check it out: https://lnkd.in/gWx6mb_U

Just finished the course “Introduction to Conversational AI”! Check it out: https://lnkd.in/gd5MhCtq

Ready to build production-ready visual AI faster and easier? Join Harpreet Sahota 🥑for this free hands-on workshop on July 24 at 9AM PT to learn how to get started with FiftyOne. This workshop will cover: ✅ FiftyOne Basics ✅ Useful workflows to explore, understand, and curate your data ✅ How to load datasets from the FiftyOne Dataset Zoo ✅ Adding new sample and custom attributes to a dataset ✅ Generating and evaluating model predictions Register here: https://hubs.ly/Q02HvgyN0 #ComputerVision #DataScience #VisualAI #AI #FiftyOne

Just finished the course “Introduction to Conversational AI”! Check it out: https://lnkd.in/gGyk3fyA

A Quick Intro to LLM Embeddings 👇 If you want to understand how modern generative text AI works, you need to understand embeddings. Embeddings are a critical part of Transformer-based models. Transformers enable generative AI systems to understand and generate human-like text. Again: if you want to understand generative AI systems, you need to understand embeddings. In a previous document, I noted that Transformers convert a the "tokens" in a text prompt to integer data. But after that the embedding layer transforms the integer ID values to vectors. Embeddings are vectors. A vector is a sequence of numbers. For example, the 4 embedding vectors below each have 3 dimensions. Because embeddings are vectors, you can think of embeddings as arrows in a multidimensional space. For example, here, we have a vector (an arrow) in a 3 dimensional space. This might seem a little complicated, but a vector is just a different way to represent data. Instead of representing a word as text, or as an integer, we're just representing the information as a vector. You might be asking, "why transform text data to a vector?" To put it simply, embedding vectors are a format the model can understand. And they have some special properties that enable modern AI processing units (like Transformers and their attention modules) to work with them, and understand the nuances of the original input text. For example, words with similar meanings are closer in vector space. Essentially, the vector embedding format is critical for the specialized processing that we find in Transformers and LLMs. Also: keep in mind that I'm simplifying things. Embedding vectors are a bit complicated (and abstract), so I'm trying to make them simple to understand here. With that in mind, I've left out some nuance and details. Additionally, since this is a complicated topic, I'll write more about it later, to add more detail. #AI #generatieveai #datascience #machinelearning --------------------------------- Hi! I’m Joshua Ebner Founder of Sharp Sight We do data science and AI consulting. If you liked this post and want to learn more about how to use AI for business, then follow me on LinkedIn: https://lnkd.in/eTi-zg9N

Just finished the course “Introduction to Conversational AI”! Check it out: https://lnkd.in/gVgf6TXV