Hi, I'm thinking of building a small community of 10-15 people where we can help each other to learn something new. The primary focus will be on ML research and open-source projects. If you're interested, DM me. knowledge of machine learning is a plus, as want to keep this a high-impact, collaborative group. Only for the moderators, since my last post was removed and I was asked to post in the monthly hiring thread: This post is not related to hiring. If I post it in the monthly hiring thread, hardly anyone will see it, so it defeats the purpose. My last post was removed very quickly, but in the mean time I've received 3 comments and 3 DMs. This clearly shows that people are interested, so I kindly request that you don't remove this post. ​ submitted by /u/Tall-Gold-3553 [link] [Kommentare]

This draw io diagram summarizes the perception pipeline I'm building for robotic object localization: - Capture real RGB-D data with an eye-in-hand camera setup. - Bootstrap a small labeled dataset - Fine-tune a YOLO-Seg model - Generate assisted labels for additional real captures - Compose synthetic RGB-D views using masks, depth, camera intrinsics and in-painted backgrounds. - Retrain the segmentation model with the expanded dataset - Input 2D masks, classes and confidences into 3D using depth and camera intrinsics - Extract 3D object localization outputs usable for robotic tasks -- Feedback is welcome! submitted by /u/nettrotten [link] [Kommentare]

Every blockchain today relies on mathematics that could be unraveled by a sufficiently powerful quantum computer. In this video, Algorand Foundation CSMO Mark Van-lerberghe, CTO Bruno Martins, and CSO Professor Chris Peikert, detail Algorand’s comprehensive roadmap to achieve full quantum resilience by 2027. ​ Discover how Algorand is addressing the "Q-Day" threat through crypto agility, hybrid signature schemes, and cutting-edge research. submitted by /u/semanticweb [link] [Kommentare]

I've noticed something interesting while browsing ML, Data Science, and programming books. A surprising number of them have animals on the cover. Not just one or two books, but entire shelves full of them. Examples include books on Python, Machine Learning, Hadoop, Linux, Data Engineering, and many other technical topics. I was curious: - Is there any historical reason behind this? - Do the animals have some symbolic connection to the subject matter? - Did one publisher start the trend and others copied it? - Or is it purely a branding/design choice? I'm especially curious about whether specific animals were intentionally chosen to represent certain technologies or if they're mostly random. Would love to hear the story behind this from people who've been in tech longer than I have. submitted by /u/Rough-Usual-275 [link] [Kommentare]

Hi, I'm thinking of building a small community of 10-15 people where we can help each other to learn something new. The primary focus will be on ML research and open-source projects. We'll decide the direction based on the interests and ideas of the group members. If you're interested, DM me. knowledge of machine learning is a plus, as want to keep this a high-impact, collaborative group. ​ submitted by /u/Tall-Gold-3553 [link] [Kommentare]

Trained in mjlab with a relatively simple reward function mainly rewarding torso height and end pose + some simple energy, self collision etc penalty. submitted by /u/floriv1999 [link] [Kommentare]

I just found two of my MetaMask wallets got hacked and most of cryptos inside were transferred out of those wallets last month. I lost about 6 ETH and some other alter coins. I was running a NFT trading program on AWS so I had to put the private key of my wallets in the code file of the program. I stopped running it by the end of 2025 since the NFT market was almost dead. After that, I shut down the AWS instance and deleted it. I didn’t touch the image and snapshot until last month. I noticed it still incurred a monthly bill so I deleted the image and snapshot last month. My wallets got hacked right after that. I suspect an AWS backend employee scanned my image files and then got my private keys. I have no evidence but it should be it. I have 4 private keys on my local computer. If my computer were hacked, all 4 wallets would have been stolen. The 2 wallets got stolen were exactly the ones I put on AWS. I am not trying to get my money back, which I know is impossible. I just want to warn people who are doing similar things on AWS or other cloud services. Keep it in mind when using them. submitted by /u/hamson2024 [link] [Kommentare]

In this python simulation: a robot spins a sensor and receives the distance. I made the distance more inaccurate the farther it is from a wall. The white lines are the actual walls The green dots are the raw, inaccurate data points the blue lines are my attempt at trying to interpret the data points into walls The algorithm works like this: For every green dot, if there are two close dots, it finds the best fit line, deletes the middle dot, and moves the other two onto the best fit line. This averages out the slopes between the green dots to allow for slope comparison. For every green dot, if the angle of the lines connected the green dot in front and behind are similar, then they are clipped into just two dots (similar to the first filter). However, as you can see, it is making walls even farther off from the green points, especially for vertical sections. I suspect this is because I'm using y=mx+b, and the slope for a vertical line is undefined, so I think the algorithm has a hard time approaching that. For context, I'm an incoming freshman trying to design an algorithm for a roomba without any prior knowledge on SLAM algorithms, so I would greatly appreciate any resources for a better implementation or just general feedback. submitted by /u/ExerciseCrafty1412 [link] [Kommentare]