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23/25 ๐—š๐—ฒ๐—ป๐—˜๐˜†๐—ฒ๐—ฃ๐—ผ๐˜€๐—ฒ: ๐—ฃ๐—ฎ๐˜๐—ถ๐—ฒ๐—ป๐˜-๐—™๐—ฟ๐—ฒ๐—ฒ, ๐—ž๐—ป๐—ผ๐˜„๐—น๐—ฒ๐—ฑ๐—ด๐—ฒ-๐—•๐—ฎ๐˜€๐—ฒ๐—ฑ ๐—ฆ๐—ฎ๐—ฐ๐—ฐ๐—ฎ๐—ฑ๐—ถ๐—ฐ ๐—˜๐˜†๐—ฒ ๐— ๐—ผ๐˜ƒ๐—ฒ๐—บ๐—ฒ๐—ป๐˜ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐—ถ๐—ป๐—ด ๐—ณ๐—ผ๐—ฟ ๐——๐—ถ๐—ด๐—ถ๐˜๐—ฎ๐—น ๐—ก๐—ฒ๐˜‚๐—ฟ๐—ผ๐—ฝ๐—ต๐˜†๐˜€๐—ถ๐—ผ๐—น๐—ผ๐—ด๐—ถ๐—ฐ ๐—•๐—ถ๐—ผ๐—บ๐—ฎ๐—ฟ๐—ธ๐—ฒ๐—ฟ ๐——๐—ฒ๐˜ƒ๐—ฒ๐—น๐—ผ๐—ฝ๐—บ๐—ฒ๐—ป๐˜ To address the lack of robust AI-enabled solutions for detecting saccadic signatures in neurologic diseases due to privacy and scarce datasets, this paper proposes the first fully synthetic, patient-free, multimodal eye movement generation pipeline. A deep learning classifier trained on this synthetic data achieved an AUROC of 0.76 and a sensitivity of 0.71 on real clinical data, demonstrating strong potential for generalizable clinical applications like screening and precise neuroanatomic localization. #SyntheticData #EyeMovements #SaccadicSignatures #NeurologyAI #DigitalBiomarkers #DeepLearning #MedicalAI #DataGeneration Paper Link: arxiv.org/abs/2606.09681
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On behalf of all SYNTHIA Partners, we wish you a Happy New Year filled with new opportunities and achievements! May #2026 bring continued #innovations in #research that contribute to a healthier future for all. Here's to a successful and impactful year ahead! #SYNTHIA #SyntheticData #DataGeneration #DataScience #DataInnovation #AIinHealthcare #DigitalHealth #HealthData #PublicPrivatePartnership #CollaborativeResearch #PersonalizedMedicine #PersonalizedHealthcare #HealthcareInnovation #DataPrivacy #AIHealth #HealthTech #TheFutureIsHere #FutureOfMedicine #EUResearch #EUInnovation #HealthResearch #IHITransformingHealth #HorizonEU #EUResearch
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ใ€Ž่‡ชๅ‹•่ปŠ่ฃฝ้€ ๅทฅๅ ดใงๅƒใๆฑŽ็”จไบบๅž‹ใƒญใƒœใƒƒใƒˆ(่ปŠ่ผช็งปๅ‹•ๅผ)ใ€ ๆง˜ใ€…ใชไฝœๆฅญใ‚’ๅ‡ฆ็†ใ—ใชใŒใ‚‰่†จๅคงใช้‡ใฎๅฎŸ็จผๅƒใƒ‡ใƒผใ‚ฟใ‚’็”Ÿๆˆใ™ใ‚‹ youtu.be/2Lt8CP8W9LY #humanoidrobot #wheeled #GeneralPurpose #manufacturing #automotive #factory #EmbodiedAI #GOVLA #DataGeneration #AI2Robotics
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Replying to @Immortalshiv1
H100s were used for most for datageneration for each iteration, you need around 20 h100 hours finetuning is possible on colab, and many have been done there itself usually 3 languages, 3 iterations - full pipeline took ~ 7 days codebase- github.com/deeps73/CycleDistโ€ฆ
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Fast-forward through our day in neuroimmunology ๐Ÿ”ฌ โ€” where every pipette move brings us closer to the next discovery. #Neuroimmunology #LabWork #DataGeneration #PaperPrep #Pipetting #StainingHumanCells
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How does @FractionAI_xyz ensure quality data? By having AI agents compete to generate it! This dynamic process, judged by AI trained on human preferences, ensures only the best data defines the next generation of AI. #FractionAI #DataGeneration #QualityData #AIEvolution
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What if you could test #edgecases before they break your AI in production? Itโ€™s possible with Synthetic data ๐Ÿ’ซ With #SyncoraAI, you can โ€” โœ…Simulate, โœ…Stress-test, โœ…Validate โ€” your models before they go live. Avoid failure. Train smart. Start here: syncora.ai/ ๐Ÿ’ช #AI #AIprojects #datageneration #syntheticdata #syntheticdatageneration #AIsuccess #ML
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๐Ÿค”Have you ever spent 3 months waiting for #labeleddata? Or spent 100 hours cleaning it once it arrives? Weโ€™ve been there and thatโ€™s a headacheโ€ฆ Thatโ€™s why we built #SyncoraAI ๐Ÿ’ช ๐Ÿง  Autonomous #data agents. ๐Ÿ“ฆ Quality synthetic data. โฑ๏ธ Delivered in minutes. All data cleaning, structuring, and labeling done while you grab your coffee. Try it here: syncora.ai/ #datacommunity #datascientists #datageneration #syntheticdata #syntheticdatageneration #AIML
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How your AI model feel when it finally gets clean, bias-free, high-quality #data๐Ÿ‘‡ Try #SycnoraAI to generate high-quality & bias-free synthetic data instantly. #AI #AIML #syntheticdata #syntheticdatageneration #ML #datageneration #datascience #datacommunity #datameme #AImeme
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