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Akim Mousterou

AkimfromParis

AkimfromParis

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posted an update 1 day ago

💵 Polymarket is leveraging “Chatbot Arena LLM Leaderboard” on HuggingFace for online gambling on the “Top AI model on January 31?”. 🤗 As of January 3rd, 2025: -1./ Gemini (83%) -2./ ChatGPT (13%) -3./ Other (2%) -4./ Claude (2%) -5./ Grok (1%) -6./ Llama (<1%) 🇺🇸 The market opinion is following historical data. It's clearly bias towards US historical AI giants, yet Polymarket is forbidden in the USA and for US citizens. 🇨🇳 In the “Other”, you might have Chinese AI labs that are probably the future AI leaders (Qwen, DeepSeek, Yi). ⚖️ In the market resolution, if two models are tied in the evaluation, they will take the alphabetical order. (e.g. if both were tied, “Google” would resolve to “Yes”, and “xAI” would resolve to “No”). 🙃 That might be illegal usage of the Chatbot Arena policy? And maybe HuggingFace? @clem Or maybe authors and contributors should get a cut each month as “market markers”. @weichiang @angelopoulos

upvoted an article 2 days ago

🇪🇺✍️ EU AI Act: Systemic Risks in the First CoP Draft Comments ✍️🇪🇺

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huggingface/open-source-ai-year-in-review-2024

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1126

💵 Polymarket is leveraging “Chatbot Arena LLM Leaderboard” on HuggingFace for online gambling on the “Top AI model on January 31?”. 🤗

As of January 3rd, 2025:
-1./ Gemini (83%) -2./ ChatGPT (13%) -3./ Other (2%) -4./ Claude (2%) -5./ Grok (1%) -6./ Llama (<1%)

🇺🇸 The market opinion is following historical data. It's clearly bias towards US historical AI giants, yet Polymarket is forbidden in the USA and for US citizens.

🇨🇳 In the “Other”, you might have Chinese AI labs that are probably the future AI leaders (Qwen, DeepSeek, Yi).

⚖️ In the market resolution, if two models are tied in the evaluation, they will take the alphabetical order. (e.g. if both were tied, “Google” would resolve to “Yes”, and “xAI” would resolve to “No”). 🙃

That might be illegal usage of the Chatbot Arena policy? And maybe HuggingFace? @clem
Or maybe authors and contributors should get a cut each month as “market markers”. @weichiang @angelopoulos

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1634

🇺🇸 🇨🇦 🇬🇧 Nobel Prize winners against USSR & Japanese AI pioneers ☭🇯🇵

🇩🇪 Prof. Jürgen Schmidhuber: “The #NobelPrize in Physics 2024 for Hopfield & Hinton turns out to be a Nobel Prize for plagiarism. They republished methodologies developed in #Ukraine and #Japan by Ivakhnenko and Amari in the 1960s & 1970s, as well as other techniques, without citing the original inventors.”

1965 - First Deep Learning - USSR ☭ (Ukraine 🇺🇦 now)
Ivakhnenko and Lapa introduced the first deep learning in deep MLPs that learn internal representations of input data.

1967/68 - Deep Learning by Stochastic Gradient Descent - Japan 🇯🇵
Shun-Ichi Amari trained MLPs with many layers in non-incremental end-to-end fashion from scratch by stochastic gradient descent (SGD).

1969 - Rectified linear unit - Japan 🇯🇵
In 1969, Kunihiko Fukushima introduced ReLU in the context of visual feature extraction in hierarchical neural networks.

1970 - Backpropagation - Finland 🇫🇮 😃
In 1970, Seppo Linnainmaa was the first the reverse mode of automatic differentiation, now known as backpropagation.

1972 - Recurrent Neural Network - Japan 🇯🇵
In 1972, Shun-Ichi Amari published a learning recurrent neural network based on Lenz-Ising model (Amari's net was later called the "Hopfield network". Hopfield republished in 1982, without citing Amari papers.)

1979 - First Convolutional neural network - Japan 🇯🇵
CNN architecture was introduced in 1979 by Kunihiko Fukushima, also known as Neocognitron.

https://people.idsia.ch/~juergen/deep-learning-history.html#AMH2

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