Wanna build the next ChatGPT?

Here's a 6 month learning plan for AI large language models (LLMs) from scratch.

(thread)
1. Familiarize yourself with basic machine learning concepts and Python programming.

Books:

1.1. Introduction to Machine Learning with Python by Andreas Müller and Sarah Guido

1.2. Python Machine Learning by @rasbt
2. Learn about natural language processing (NLP) and its applications.

Books:

2.1. Speech and Language Processing by Daniel Jurafsky and James H. Martin

2.2. Natural Language Processing with Python by Steven Bird, Ewan Klein, and Edward Loper
3. Learn about the specific architecture and inner workings of language models, such as the transformer architecture used in GPT3.

Paper:

Attention Is All You Need by Vaswani et al.

proceedings.neurips.cc/paper/2017/fil…
4. Train your own small-scale language model using an open-source library such as TensorFlow or PyTorch.

Study the @TensorFlow and @PyTorch documentations, as well as tutorials and courses on websites like @kaggle and @coursera.
5. Learn about fine-tuning pre-trained language models and apply this knowledge to a specific task of your choice.

The @huggingface documentation on fine-tuning will be very helpful.

huggingface.co/docs/transform…
6. Explore the latest research in language models and their applications.

The papers from @NeurIPSConf (nips.cc) and @TheICLR (iclr.cc) are a good starting point.
7. The best part about this is that everything is basically free. Happy learning and good luck!

If you enjoyed this thread, you'll probably love the next ones! Like, retweet and follow me for more.

#machinelearning #ai #gpt3 #chatgpt #llms #nlp #python #tensorflow @OpenAI

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More from @CristiVlad25

Jan 29
Privilege escalation in Windows using 4 tools for red teamers and pentesters.

(thread)
1. WinPEAS - it's a simple .exe script you can run as: winpeas.exe > outputfile.txt

Get it here: github.com/carlospolop/PE…
2. PrivescCheck - a powershell script

Get it here: github.com/itm4n/PrivescC…
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Jan 27
In this week's newsletter:

- building the next ChatGPT | Network Pentesting | Full-blown Winter -

(thread) Image
1. I'm talking about the 6 month learning plan to understand AI large language models from scratch - the stuff that #chatGPT is built on.
2. I'm also talking about the heavy workload of pentests and appsec assessments from this past week.
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Jan 22
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1. socket: A library that provides low-level core networking services.
2. scapy: A powerful interactive packet manipulation library and tool.
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Jan 21
Look for these file extensions in your pentests and appsec assessments.

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1. .env - commonly used to store environment variables, including sensitive information such as passwords and tokens.
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Jan 20
In this week's newsletter:

- iOS Pentesting | ChatGPT my Teacher | Recon -

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1. How I'm using ChatGPT as a virtual teacher. And of course, how you can use it too.
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Jan 19
Squeezing the juices out of robots.txt.

A fully automated workflow that you've never seen before.

(thread)
1. This script scrapes the disallowed paths from the robots.txt files of a list of domains and saves them to a single file. It also removes any unwanted entries and sorts the file in a particular way.

Can you write it yourself? Here’s how the script should look like.
2. Create a directory called "massrobots" in the pwd. This is where you'll save all the robots.txt files for later processing.
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