The LLM wars intensify as GPT-4o takes a significant lead – The gap is widening again after @OpenAI
's latest release. Based on data shared by @LiamFedus (
https://
x.com/LiamFedus/stat
us/1790064963966370209
…), GPT-4o significantly outperforms competitors on the LMSYS Chatbot Arena. – @RekaAILabs also
@maximelabonne
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GPT-4o Widens Lead in LMSYS Chatbot Arena Competition
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Joining Google Developer Experts as AI/ML Expert
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Happy to announce that I've joined the @GoogleDevExpert group as an AI/ML expert It's a nice opportunity to travel more, and connect with LLM experts worldwide. Expect more content inspired by my interactions with the LLM community. If you're interested in meeting up at an
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Hands-On GNN Python Book Becomes Amazon Best-Seller
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I'm proud to announce that the Hands-On #GNN Using #Python book is the best-selling new release in Machine Theory on Amazon! Thanks everyone for your support, your kind emails and DMs.
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SkyAGI: Human Behavior Simulation in LLM Agents
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SkyAGI: Emerging human-behavior simulation capability in LLM This Python package implements the idea of Generative Agents (see image). Characters interact with each other. Each of them has a personality, a current status, and memories. https://
github.com/litanlitudan/s
kyagi
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TANGO: Generate Sound Effects from Text Descriptions
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TANGO: Text to Audio using iNstruction-Guided diffusiOn Generate sound effects based on a text description. The code and model are available on GitHub. #AI https://
github.com/declare-lab/ta
ngo
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Efficient GPU Usage in AI Research Experiments
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I'm actually impressed they didn't spend more GPU hours in experiments. That's really efficient of them, especially considering the result.
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Integrating Bard AI into Google Colab for Enhanced Development
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It would be neat to have Bard directly integrated into Google Colab.
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Graph Neural Networks: Essential Resource Guide
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If you're interested in graph neural networks, I highly recommend checking it out. I'm confident that you'll find it to be an invaluable resource as you explore this exciting and rapidly growing field. Buy it now at
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Graph Neural Networks: Book Recommendations and Advanced Applications
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And here is the final result with 5 recommended books and their respective scores. Code: https://
github.com/PacktPublishin
g/Hands-On-Graph-Neural-Networks-Using-Python/blob/main/Chapter17/chapter17.ipynb
… You'll find two other advanced use cases, related to time series forecasting and anomaly detection (the topic of my PhD!).