Hello! I am eyeing to compete in a maze runner competition. I did some research and it seems that micromouses are the best for those. Could I get recommendations/list of electronic parts to build a fast and reliable micromouse robot? Like what mircocontroller should I use or what wheels should I get or what sensors are the fastest in reacting? Oh, last thing, do have information on where I can but them? Thank you!!! submitted by /u/Big_Criticism_3517 [link] [Kommentare]

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Building a cross-chain risk detection tool (MetaChain, via Michigan Tech's MTEC SmartZone incubator) and doing customer discovery. Not selling anything here. If you've ever been caught in a rug pull/exploit, or actively work to avoid them: what signals do you actually rely on before entering a position? And was there anything in hindsight that would've warned you earlier? Happy to do a quick DM follow-up with anyone willing to go deeper (15 min, no pitch). Just trying to learn from real experience. submitted by /u/labslizard [link] [Kommentare]

Databricks Genie Ontology shows why the model is swappable but governed context compounds. Why the enterprise context layer should be neutral not a vendor moat.

Despite all his wealth, Musk’s existence is a cautionary tale.

It is a kind of stereo image you make by looping frames together, like as a GIF. I am something of an indecisive photographer and when I like an angle I will take a lot of frames, from slightly different angles etc., looking for "the shot". And since I am also a bit of a hoarder I never clear out my camera roll. "Same shot from different angles"? You know what that sounds a bit familiar. Sure enough my phone is full of wigglegrams that I took by accident. Years' worth, waiting for me to sit down and stitch them together. Or, perhaps, for something to stitch them together. It occurred to me last weekend that I can use perceptual hashing - what TinEye (et al.) uses for reverse image search - to try and find runs of similar images and pull them out from my library automatically. So I wrote a little script to hash all my pictures: Hashing is quick but downloading photos from iCloud is not. The result is a hash that - unlike a cryptographic function like sha1 - will share more bits with hashes of similar-looking images than with dissimilar ones. We can use that to calculate the hamming distance between pairs of images and find a threshold: A few of them I am guilty of taking intentionally. But most are true accidents. As such many of them come out as less "stereoscopic" and more "kinescopic" - like little unintentional movies. Animals are a natural fit for the concept, unpredictable as they are: Design-work also. (I am always indecisive.) What fun. I have the script up on Github if you want to play with it - it'll work on your iCloud photos library if you're on a Mac, or you can point it at a directory of pictures otherwise.

Moji ist eine persönliche KI, die in WhatsApp, Telegram und LINE lebt — ein echter Agent mit eigenem Computer. Erinnerungen, Pläne, Antworten und Infos, genau dort, wo du eh schon chattest.

Interactive React components for network diagrams, fiber networks, and rack infrastructure visualization.

The Future Is Here

Play Historic Firsts, the daily history timeline game where you sort landmark inventions, discoveries, breakthroughs, and historic firsts from earliest to latest.