Our AI Tutor is live!!!
and our Pro Tips for Improving AI Responses and Performance
Good morning fellow AI enthusiast! This is the third iteration of my new video series for our free course "Training & Fine-Tuning LLMs for Production"!
In this one, we dive into unlocking the full potential of large language models (LLMs). I also have an exciting announcement to share with you...
In the same sense, since it is totally related to this week's video topic, here's a very useful product if you are already working with LLMs: Lakera Guard!
1️⃣ Protect AI Applications with Lakera Guard (sponsor)
Stop worrying about security risks and start moving your exciting LLM apps into production. Lakera Guard protects your entire organization - add one line of code to get all the protection, and none of the headaches. Lakera’s vulnerability database contains tens of millions of attack data points, and is growing by 100k+ entries every day. Built by ML and security experts, accessible through Lakera's API.
2️⃣ Pro Tips for Improving AI Responses and Performance: How to tune your Language Models
In this video, we dive into advanced techniques for controlling LLM outputs, mitigating biases, and enhancing performance.
Learn about temperature, stop sequences, frequency and presence penalties, and explore practical examples to tailor LLMs to your specific needs.
Your journey to mastering and commercializing LLMs starts here:
3️⃣ Our AI Tutor is live!!!
Last week, we released our LLM course. We are excited to announce another related project: our own AI tutor!
Thanks to the thousands of articles published under the Towards AI publication, all the content from our LangChain and LLM course, and other great available sources like Huggingface Transformers and Wikipedia, we were able to build a powerful retrieval augmented generation (RAG)-based chatbot that can answer any AI-related question and even credit its sources!
RAG is a powerful approach to reducing hallucination risks and providing a way to reference the knowledge shared by a chatbot so you can dive in and learn more. So, the only thing required to build such an AI tutor is an excellent chatbot (GPT), a great knowledge base (Towards AI), and some handwork.
We are excited to announce it is live and free! Please try it and give us feedback on how to improve it! Are the responses too short, too detailed, and wrong sources…? Help us make it better for you! We plan to keep improving it and keep it free for all our students!
Try our question-and-answer (Q&A) chatbot built for the GenAI 360 suite, which can answer questions for anything LLM-related!
4️⃣ More about our course in collaboration with Towards AI, Activeloop, and the Intel Corporation disruptor initiative!
Tl;dr: The course is about showing everything about LLMs (train, fine-tune, use RAG…), and it is completely free!
Is the course for you?
If you want to learn how to train and fine-tune LLMs from scratch, and have intermediate Python knowledge, you should be all set to take and complete the course.
This course is designed with a wide audience in mind, including beginners in AI, current machine learning engineers, students, and professionals considering a career transition to AI.
We aimed to provide you with the necessary tools to apply and tailor Large Language Models across a wide range of industries to make AI more accessible and practical.
Start the course for free now:
And that's it for this iteration! I'm incredibly grateful that the What's AI newsletter is now read by over 13,000+ incredible human beings and counting. Share this iteration with a friend if you learned something new!
Looking for more cool AI stuff? 👇
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If you need more content to go through your week, check out the podcast!
Please reach out with any questions or details on sponsorships, or visit my Passionfroot profile to see the sponsorship offers.
Thank you for reading, and we wish you a fantastic week! Be sure to have enough rest and sleep!
Louis