Robert Simmons’ Post

Back in 1956, the very first AI Conference was in full swing. Back then, there was no announcement of the latest GPU technology, no robots, no large language models. Instead, there was a proposal, a vision of what AI could be. The ambition of John McCarthy, who is credited with coining the term Artificial Intelligence was impressive given how far away we were from anything close to AI. McCarthy gives us inspiration for the hardest part of the AI journey - setting a vision and getting started. Read more here about how exactly you can lay out a plan and begin moving forward with an AI strategy that delivers value early and often. https://lnkd.in/g7TgeFUj

What happens when you engage Paper Crane to work on an AI project? We start by working backwards. Borrowing from the concept created by Amazon, we start with an AI product or feature and work back through all of the steps needed to launch. We call this an AI Strategic Narrative. I've laid out the process in this blog article. Take a look and let me know what you think: https://lnkd.in/g7TgeFUj

Finding quality data is how we can effectively build generative solutions, so what if we used AI-generated data? Unfortunately, doing so would result in a "model collapse." InsideBIGDATA says it would be "learning from a distorted reflection of itself." Basically, it would be the technology version of the game telephone and would render it useless. #Data #AI #AIGeneratedData

I'm happy to be featured in this ABB Generations article about Generative AI and how this technology can support our industry. Coincidently OpenAI yesterday introduced the possibility to train ("fine tune") their GPT-3.5 model with your own data - something we discuss in the article. https://lnkd.in/dAuSTs2q

AI Definitions: Retrieval augmented generation (RAG) – This coding technique instructs the bot to cross-check its answer with what is published elsewhere, essentially helping the AI to self-fact-check. RAG lets companies “ground” AI models in their own data, ensuring that results come from documents within the company. More AI definitions here: https://lnkd.in/gr5d-SWT #AI #AI #bigdata #datascience #deeplearning #machinelearning #LLM #neuralnetworks #code #coding

As AI increasingly integrates into our daily routines, staying well-versed in the expanding vocabulary is no small feat! Whether you're an AI enthusiast stepping into this brave new world or a seasoned professional aiming to stay at the forefront, we've got you covered. 📘 Our blog post breaks down complex concepts like Autonomous Systems, Discriminator Networks, and the elusive Singularity. We've distilled these terms into plain language, making AI accessible to all. Read the full glossary here: https://lnkd.in/eT9mGQRH

Vectors. Vector search. Vector databases What do the above terms mean? And how are they used to build Generative AI applications? Check out this handy primer.👇 #DataStax https://dtsx.io/3QlD1jp

🚀 Let the AI magic handle the decoding, while you focus on what truly matters. Customize your reports, compare and contrast data – it’s like having your own document superhero! Check how in our latest blog! https://lnkd.in/dUA3a9Pa 🦸♂️📄 #MoodbitSuperpowers #DocumentDecoded

⭐️ New Journal ⭐️ Using AI to manage obsolescence: Making last order letters a thing of the past This informative post explains how generative AI and Large Language Models could make the last order letter a thing of the past.

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