hadiaz

watch a demo of my generating a billing report by asking for it: https://youtu.be/6KUtdyW9Yrg

rich discussion here

Beta is out, try it for free

My takeaways: 1. buy NVDA, TSLA, GOOGL, MSFT and META. At least one will breakout big for sure 2. do not train your own model, that's a race to the bottom 3. play in the vertical AI game

You don't need to retain commands in your head anymore. Just type what you want in natural language using the word hey <what_you_want_here> Eg, hey make a dockerfile for this dir using the ubuntu image

No need to retain commands in your head anymore, use bash, docker, kubernetes, aws etc from your terminal in plain english

You are deploying or coding - you face an issue Instead of google+stackoverflow for 30min, juste paste the error message and get the best answer from the web

You don't need to retain Terminal commands in your head. Now you can work with docker, kubernetes, AWS, GCP, Terraform ... and many more command lines with natural language (English) instructions.

AI model based on GPT3, trained to answer your technical troubleshooting questions, better and faster than Google+Stackoverflow https://concisefix.co/

On it. Sorry about that

AI model based on GPT3, trained to answer your technical troubleshooting questions, better and faster than Google+Stackoverflow http://concisefix.co/

You don't need to retain Terminal commands in your head. Now you work with docker, kubernetes, AWS, GCP, Terraform ... and many more command lines with natural language (English) instructions. Join https://www.heycli.com

You don't need to retain Terminal commands in your head. Now you work with docker, kubernetes, AWS, GCP, Terraform ... and many more command lines with natural language (English) instructions. Join https://www.heycli.com

You don't need to retain Terminal commands in your head. Now you can work with docker, kubernetes, AWS, GCP, Terraform ... and many more command lines with natural language (English) instructions.

TL;DR Logs are valuable information describing runtime events. However, because of the sheer amount of logs generated by large online services, it is impossible to get any insights from them in real time using traditional observability tools. This is why at PacketAI, we built a real-time log analysis engine based on text mining and machine learning algorithms. Since logs are mainly unstructured textual data, the first step towards automated analysis of logs is the “representation phase”, where raw log lines are transformed into structured data ready for downstream tasks such as anomaly detection. In this article, we present our design for Log2template, a universal log parsing engine that is agnostic to log formats. Log2template at its core, is based on word embedding using neural networks.

Visual summary of the 20M log lines your stack generated yesterday?

Sure,

- Select sources of data - Take a quick look on logs but don’t try to read them all. You can’t - Click “Patterns”. Somebody grouped your logs for you, by pattern - Errors and warnings ? filter in - What the heck is this “internal server error”?! zoom in to see the problematic logs - Done