deploy apps to the cloud, set-up kubernetes with CI/CD Auto Devops | multi cloud architec| create_dockerfiles | CI/CD knowledge & template transfer x@IBM
Tools like LangChains enable you to pipe AI prompts into large language models (LLMs). Giving a prompt.
Example, create 1️⃣ query to analyze context, 1️⃣ for prompt instructions, and 1️⃣ for how specific it is. And pipe all to make suggestions on how to improve the prompt.
I discovered that there are techniques for analyzing your prompts and ensuring that your message is understood. Ask for: Context, review the task to be performed, how specific it is, and embrace iterative, meaning ensure you can queue tasks on top of the results.
I'm role playing GPT, there are more prompt engineering to develop, the first message is critical to set the model, and there are techniques to set {variables} to the model. It is critical to consider it as a continuous printer.
Ai is removing some jobs, which is a good thing. It has always been a good thing for humanity because it means more sophisticated work, services, and products in the long run. Recognize that you can ride the waves or get crash by it, choice is yours!!
If you already have a knowledge database, it's time to boost it with AI. We are entering a tooling phase in which this is available not only to computer scientists but also to software engineers. Huge rewards are waiting for the brave ones!
@lukesprosser Pick and choose the right libraries and stack for the job. Coding is about fixing today's problems and supporting tomorrow features, some stack may slow you down at the future.
6/ Ensure that the platform complies with data privacy and security regulations, particularly because it contains sensitive client information as medical/health records.
1/ I'm developing a GPT personal trainer platform for a client; here's how we're going about it: start creating a system for tracking clients' progress, including their goals, workout history, and any relevant health information
5/ By incorporating GPT, we will be able to offer clients a highly personalized and data-driven training experience, increasing the likelihood of their success and satisfaction.
@sayanee_ I use it to generate code. If is complex I use this approach: prompt for overview/strategy planning; change according to my plan and then ask to gen code based on my feedback
In #Kubernetes, size does matter! Smaller Docker images mean faster deployments, better resource utilization, and more efficient clusters.
📈 #cloudcomputing
@hkshambesh I worked for IBM, migrating internal automation tools used to manage virtual machines (health check, data backup, and security check) to the public cloud. The majority of the work was done in Python and Go, optimizing Docker images and establishing pipelines for CICD.⚙️💾🌩️🐍🐳🚀
@gregmberry Do you intend to optain data insight from your auction marketplace? You can consult chatGPT about strategies for "fine-tuning" the model to your specific needs.
If you're looking for prompts, take a look at this list:
https://t.co/LvZufnDdUA