Top Tweets for #PerturbVideoCompetition

nofad

@nofadsec

21 days ago

Can your AI be fooled? Meet Modelo 🤖 My entry for @perturbaix #PerturbVideoCompetition

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σℓαigє τ

@_olaige

21 days ago

Everyone wants AI to get smarter. But who's making sure it gets safer? As AI becomes more powerful, its vulnerabilities become more consequential. Perturb (SN26) is exposing those weaknesses and helping build resilient AI. @perturbaix #PerturbVideoCompetition #PerturbVideo

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Trenchwalker

@Trenchwalker_io

24 days ago

Your eyes see a panda. The AI sees a gibbon, 99.3% sure. Nothing visible changed. A few invisible edits were enough to flip the answer and that weakness is what my #PerturbVideo entry is about, submitted to #PerturbVideoCompetition. Now put that flaw inside a self-driving car reading a stop sign, a bank approving a fake ID photo, or a hospital scanner missing a tumour. These failures usually stay hidden until the model is already live. @perturbaix turns the problem into a competition on Bittensor. Every 2 minutes a new image goes out, and miners race to find the smallest invisible change that makes the AI wrong. Validators re-run the model, confirm the answer really flipped, check the edit stays imperceptible, and match the file to the fingerprint the miner committed. Copies score zero. The cleaner and smaller the attack, the higher the score and speed earns nothing. It's like picking a lock with the lightest touch instead of kicking the door in. Companies get a robustness score and real examples that fooled their model, so they can fix the holes before attackers find them. Scans start at $99. Image models are what's live today, with text and multimodal on the roadmap. AI can be tricked by changes you can't see. Perturb pays the world's hackers to find them first. https://t.co/WcdDK58IGu #Bittensor #PerturbVideo #PerturbVideoCompetition

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Bryant

@bryantheden

25 days ago

A bank approves an applicant's ID photo, unaware that a few hidden edits fooled its automated screening. The scenario is fictional, but it frames The Trust Check, my #PerturbVideo entry Submitted to #PerturbVideoCompetition under Angle 15: Bittensor through Perturb. In the film, one false pass leaves the lender exposed to fraud losses and costly manual review, with customers ultimately sharing the burden @perturbaix tackles this through open competition, where miners are paid to find inputs that make AI models confidently wrong. Each races to locate the smallest modification that flips a classifier's answer Validators then establish that the prediction really changed, verify the alteration stays imperceptible within pixel and perceptual similarity limits, and match the file to its committed hash. Copies earn nothing Tighter, cleaner perturbations rank higher, and response speed carries no weight. Consensus across the network decides who collects the most TAO Organizations receive a robustness score, a vulnerability heatmap, verified attack data for retraining and an on-chain certificate Operations began in May 2026, with image-model scanning live today. Text, LLM and multimodal attacks remain on the roadmap, and November presales are a target, not a confirmed result https://t.co/mfKuyI9pkl · Bittensor Subnet 26

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