Hello, all! I'm living in Romania at the moment and specializing in data science/ml with a total of 6 years of experience. I've been doing ML applied research at a big antivirus company, remote data engineering at a sillicone valley startup, and applied medical ML research at a german company. The thing is that i've always been the only one in the team...

I've created a video about classical neural networks, its problems and how spiking neural networks can solve them. Will be grateful for your feedback: https://youtu.be/gSyDlvzvhg8 For working on text i used ChatGPT: https://chat.openai.com/ For working on video midjourney and DALL-E: https://www.midjourney.com https://openai.com/index/dall-e-3/...

This article explores the use of AI to solve CAPTCHAs, a task often thought to be exclusively human. Through a controlled experiment using Claude 3 and Gemini 1.5, we demonstrate the feasibility of AI-powered CAPTCHA solutions, while underlining the importance of ethical considerations and responsible implementation. https://medium.com/@gbasilveira/are-you-human-yes-ai-am-db649c729688...

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I'm a web dev (Python, Django) looking to get into ML. I have lots of experience in Python and have started picking up TensorFlow and PyTorch. I'm wanting to start building AI apps for MacOS and I'm trying to figure out the best workflow for this. So far I can think of the following approaches: Using Python and then use packages for GUI (e.g. Tkinter)...

This paper KAN: Kolmogorov–Arnold Networks https://arxiv.org/pdf/2404.19756 (digested in https://towardsdatascience.com/kolmogorov-arnold-networks-the-latest-advance-in-neural-networks-simply-explained-f083cf994a85 ) suggests that any 2-hidden-layer MLP layers (like used in GPTs) can be approximated by KANs: "KANs outperform MLPs in terms of accuracy...