JSR Tech Consulting’s Post

Interesting read on AI https://lnkd.in/eGqyAati

At this point in the life of AI chatbots, we know that they can't necessarily be trusted. They CAN be helpful, but we're not at the point where we can take everything chatbots say at face value. We need to fact-check what AI bots tell us if we want to be sure they're giving us correct information. However, RAG, or retrieval-augmented generation, might change this. RAG differs from LLMs in a few key ways. One major difference is "Instead of offering a response rooted only in how the model was trained, RAG retrieves additional data provided to it by the person or organization implementing RAG... and incorporates it into its reply," writes Matthew Smith. While RAG isn't perfect, it's definitely a clearer path to better, smarter, and more accurate generative AI. #RetrievalAugmentedGeneration #AIRAG #AIChatbot

Bots, agents, and digital workers: AI is changing the very definition of work AI is no longer just replacing the tasks of workers—it can complete entire workflows. Here’s how we can redefine labor in the age of AI.

Here's a great overview of Cloud-Based Generative AI Services. Now organizations of all types can harness the power of #GenerativeAI. According to Rob Kerr, foundation models may appear similar, but they are unique beneath the surface. @kerrrob https://hubs.li/Q02Cky9c0

I know you know what a chatbot is, but could you explain the difference between a chatbot, an AI assistant, an autonomous agent, a co-pilot, and an embedded AI? Once you read Christopher Robert's excellent (and pithy) visual guide to today's text based AI/Gen AI lanscape, the answer will be yes 🤠 https://lnkd.in/eqzvGUzU

So what does having AI agents mean for the very definition of work itself?

Thank you Inc. Magazine for publishing my article on the next frontier in AI. Cognitive AI is revolutionizing complex decision-making processes, offering a path to augment and eventually substitute human agents. Unlike Generative AI, Cognitive AI doesn't suffer from hallucinations, lack of concept understanding and reasoning, and always needing humans to validate the output with expensive training methods. Check out my latest article to learn more. #AI #cognitiveAI #generatieveai #aigo

“To get better results from a generative AI chatbot, write your prompts CAREfully. Include these four key components in your prompts: Context: Describe the situation Ask: Request specific action Rules: Provide constraints Examples: Demonstrate what you want”

AI chatbots spew out nonsense too often. But there's a solution: retrieval-augmented generation. Retrieval-augmented generation, or RAG, uses additional data to provide AI chatbots precise answers, addressing generative-model issues. Read mode on following blog post!

Don't you wish the chatbot🤖 you're interacting with could understand the context of your queries and make a smarter search for solutions? Eliminating mundane and repetitive interactions altogether. 👉Our blog delves deep into understanding the use cases surrounding these concerns and talks in detail about the future of human-machine interactions. 🔗Explore more insights: https://lnkd.in/g8dztCpX #ai #futuretech #chatbot #usecases #searchunify