Gaspard @GaspardGoupy
PhD student at @univ_lille. I study supervised learning in spiking neural networks. ggoupy.github.io Lille, France Joined October 2018-
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New Research: Paired competing neurons improving STDP supervised local learning in Spiking Neural Networks frontiersin.org/articles/10.33… #FrontiersIn #Neuroscience
Our latest paper is now published. In this work, we studied classification with STDP-based SNNs. We showed how winner-takes-all competition can naturally promote, in a supervised context, neuron specialization toward target and non-target samples.
Our latest paper is now published. In this work, we studied classification with STDP-based SNNs. We showed how winner-takes-all competition can naturally promote, in a supervised context, neuron specialization toward target and non-target samples.
CPU vs FPGA
Llama 2 7B chat, running 100% private on Mac, powered by CoreML! ⚡️ We're optimising this setup to get much more faster generation. 🔥
Has any founder ever had as much impact on their tech ecosystem as Xavier Niel in France? He’s behind: * Station F - Europe’s biggest startup campus * 42 - complete reinvention of CS education * Kima Ventures (most prolific seed VC), NewWave, other funds * now this:
Our paper making neural networks more modular, sparse and interpretable by penalizing neuron length is now on arXiv. Less is more! @ZimingLiu11 arxiv.org/abs/2305.08746
I've been studying machine learning for half a decade, and here is the most popular function we use every day: f(x) = max(0, x) Yet many people don't understand a fundamental characteristic of this function. Here is what you need to know:
Data Science Challenge: Obviously this graphic seems wrong but can you explain what common data visualization mistakes are being made here?
I spent New Years building GPTZero — an app that can quickly and efficiently detect whether an essay is ChatGPT or human written
Looks like the first open source equivalent of ChatGPT has arrived: github.com/lucidrains/PaL… I.e., an implementation of RLHF (Reinforcement Learning with Human Feedback) on top of Google’s 540 billion parameter PaLM architecture
Are you wondering how large language models like ChatGPT and InstructGPT actually work? One of the secret ingredients is RLHF - Reinforcement Learning from Human Feedback. Let's dive into how RLHF works in 8 tweets!
Announcing OPT-IML: a new language model from Meta AI with 175B parameters, fine-tuned on 2,000 language tasks — openly available soon under a noncommercial license for research use cases. Research paper & more details on GitHub ⬇️
I'm proud to announce the publication of my first paper as first author! This project, part of my end of master internship, explores unsupervised & hardware-friendly learning in convolutional SNNs.
I'm proud to announce the publication of my first paper as first author! This project, part of my end of master internship, explores unsupervised & hardware-friendly learning in convolutional SNNs.
Cerebellum has over 50% of the total number of neurons in the brain: #neuroscience by G. Dunn

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