Lior Alexander

Finally, someone did it. Python for React.

React is the most popular front-end framework used to build interfaces and now all python devs can use it.

This means you can code an ML model, develop a backend and design a front end all in one language.

https://lnkd.in/dcjZ2nww

Microsoft just open-sourced GraphRAG. It might be the best Python library to extract insights from unstructured text.

It uses LLMs to automate the extraction of knowledge graphs from your datasets and text documents making it much more powerful than vanilla RAG.

How to use it:
- Library: !pip install graphrag
- Github: https://lnkd.in/gsUCUTAP

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This might be the biggest breakthrough of the year. Over 20+ AI labs partnered up and open-sourced the most powerful physics engine ever made.

Genesis is a physics engine with a VLM agent that turns text prompts into interactive 4D world. It's designed for general-purpose robotics and physical AI applications.

It's developed in pure Python, while being 10-80x faster than existing GPU-accelerated stacks.

It delivers a simulation speed ~430,000 faster than in real-time, and takes only 26 seconds to train a robotic locomotion policy transferrable to the real world.

Github: https://lnkd.in/gBm9buf3
Project: https://lnkd.in/g5mJ5sbW
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New breakthrough from Microsoft: 1-bit LLMs. New models that use ternary values (-1, 0, 1) instead of 16-bit.

This makes them 2.7x faster, use 3.5x less GPU memory, and 71x less energy.

Bitnet also matches or outperformed traditional models like LLaMA 3B.
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This is incredible. Fractal patterns were just found when plotting a grid search over neural network hyperparameters.

Blueish colors correspond to hyperparameters for which training converges, redish colors to hyperparameters for which training diverge.

This finding underscores the intricate relationship between hyperparameter settings and training behavior, offering a new perspective on neural network optimization.

This insight not only enhances our understanding of neural network optimization but also suggests a fundamental link between mathematical fractals and machine learning dynamics.

The discovery could lead to new approaches in tuning and understanding the complex landscapes of neural network hyperparameters.

Brilliant work by Jascha Sohl-Dickstein
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NN-SVG is a tool for creating Neural Network architecture drawings parametrically rather than manually! \n\nIt also provides the ability to export those drawings to Scalable Vector Graphics (SVG) files, suitable for inclusion in academic papers or web pages https://lnkd.in/dEbGVpga\n↓\nAre you technical? Check out https://AlphaSignal.ai to get a weekly summary of the latest research and breakthroughs in AI. Read by 120,000+ engineers and researchers.

xAI just opened access to their API. It's incredible.

You can now build an AI assistant capable of fetching news content from URLs and crafting posts in your writing style.

* 128k token context
* Function calling support
* Custom system prompt support
* Compatible with OpenAI & Anthropic SDKs
* $25/mo in free credits till EOY

Credit: Alvaro Cintas (@dr_cintas)
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A great read. Stop using the elbow criterion for k-means and how to choose the number of clusters instead (alternatives).

“..researchers and reviewers should reject conclusions drawn from the elbow method.“

Paper: https://lnkd.in/d8RBEUmd
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JUST IN: OpenAI announces DALLE-3, built natively on ChatGPT.

DALLE-3 not only outperforms DALLE-2 but can be used in combination with ChatGPT to generate tailored and detailed prompts.

The MidJourney competitor will be available to all ChatGPT+ users in early October and via the API in late fall.

https://lnkd.in/dKTTB4wY
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BREAKING: Tesla has introduced Optimus Gen 2! This is NOT sped up.

Features:
• 30% walk speed boost
• Tesla designed actuators and sensors
• 2-Dof actuated neck
• Actuators integrated electronics & harnessing
• Foot force/torque sensing
• 22lb weight reduction

http://tesla.com/ai
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Want to understand how LLMs and Transformers work? This is by far the best visualization I've seen.

The article makes you understand the fundamental concepts in 5 min.

https://lnkd.in/gtKS8Fqj
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This might be the beginning of a new field..
Researchers just reconstructed sounds from human brain activity using an fMRI and a generative AI model.
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This is a game changer. You can use ChatGPT to transform equations to python functions. Wish I had this 5 years ago.

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