Learn AI Together — Towards AI Community Newsletter #24

Author(s): Towards AI Editorial Team

Originally published on Towards AI.

Good morning, AI enthusiasts!

This week, we have quite an actionable newsletter with opportunities to join beta tests, run demos, contribute to open-source projects, work on research projects, and more.

What’s AI Weekly

Have you wondered how ChatGPT decides when to stop answering? How does it know it has given a good enough answer? How does it stop talking? In this week’s video, I explore two concepts that can cause the model to stop generating: EOS tokens and Maximum Token Lengths. Check out the full video here, or if you prefer, read the article here!

— Louis-François Bouchard, Towards AI Co-founder & Head of Community

This issue is brought to you thanks to Latitude.sh:

Latitude.sh is Launching Launchpad!

The most powerful container GPU platform to date: join the Beta test and earn credits!

Latitude.sh entered the machine learning landscape by providing on-demand access to fully dedicated AI clusters with the latest and most advanced GPU chips from NVIDIA. Now, the company has released its own containerized GPU compute solution and is looking for new users to test it so it can be refined according to feedback collected directly from the ML community.

To join the Beta test program, it’s easy and simple:

• Create an account on the Latitude.sh platform
• Reach out to bearmetal_sh on Discord and share the email used to create the account;
• You will receive $ 300.00 in credits;
• Start using Launchpad and DM your feedback to their team on Discord

Sign Up Today!

Learn AI Together Community section!

Featured Community post from the Discord

Priyanshu2357 and his colleague are developing a Snowflake Cost Monitoring and Optimiser tool using Langchain, Snowflake Cortex, and Open AI. Multiple agents are working behind the scenes, using OpenAI and Cortex to find the best answers. Check out the demo here and support a fellow community member. If you have feedback on improving it, share it with them in the thread!

AI poll of the week!

We rely on you to make sure we give you what you want! Tell us all about EVERYTHING you want to learn in the Discord thread.

Collaboration Opportunities

The Learn AI Together Discord community is flooding with collaboration opportunities. If you are excited to dive into applied AI, want a study partner, or even want to find a partner for your passion project, join the collaboration channel! Keep an eye on this section, too — we share cool opportunities every week!

1. Akeshav is looking for individuals starting their ML journey and are interested in doing research. If you are interested, reach out in the thread!

2. Amjad1982 released a tool called BabyTorch, a minimalist deep-learning framework that mirrors PyTorch’s API. It is an open-source project; if you want to contribute, contact them in the thread!

3. R.raviyuvaraj is looking for experienced AI ML developers to collaborate on an Edu Tech project from scratch. If this sounds relevant, connect with him in the thread!

Meme of the week!

Meme shared by ghost_in_the_machine

TAI Curated section

Article of the week

Unpacking Kolmogorov-Arnold Networks by Shenggang Li

Researchers at MIT recently introduced a new neural network architecture called Kolmogorov-Arnold Networks (KANs). Unlike traditional neural networks that use activation functions at the nodes, KANs place these functions along the connections between nodes. This post will illustrate the innovative structure of Kolmogorov-Arnold Networks (KANs) through clear examples and straightforward insights, aiming to make these advanced concepts understandable and accessible to a broader audience.

Our must-read articles

1. Stacking Ensemble Method for Brain Tumor Classification: Performance Analysis by Cristian Rodríguez

This article delves into medical image analysis, specifically focusing on the classification of brain tumors. It introduces a novel approach that combines the power of stacking ensemble machine learning with sophisticated image feature extraction techniques. Through comparative evaluations, insights are provided into the effectiveness and potential applications of the proposed approach in medical imaging and diagnosis.

2. Exploring EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies: A Brief Overview by Vincent Liu

Anomaly detection in computer vision has come a long way, and many fantastic algorithms have been deployed in production. However, the community always seeks a more efficient solution without sacrificing accuracy. This article shares a disruptive breakthrough in anomaly detection published in February 2024, EfficentAD. It is an unsupervised learning approach.

3. Building Private Copilot for Development Teams with Llama3 by zhaozhiming

Many developers have likely used GitHub Copilot, a revolutionary development tool that significantly boosts productivity and gradually transforms programming habits. This article explores how to use Llama3 to build a team-exclusive private Copilot, enhancing team productivity while safeguarding code privacy.

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Published via Towards AI