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  • Modulate’s Velma API Achieves 98.9% Deepfake Detection Accuracy
    Modulate’s Velma API Achieves 98.9% Deepfake Detection Accuracy

    By

    @sumanth_077

    –

    Massive breakthrough in voice deepfake detection! @modulate_ai just released a deepfake detection API that topped @huggingface's leaderboard at 98.9% accuracy. Here's the problem with how most companies handle deepfake detection. They check the first 10 seconds of a call. If it passes, they assume the whole call is clean. Gate check. One scan. Done. Fraudsters know this. So they open the call with a real voice. Their own voice, a colleague, a quick recording. Pass the check. Then switch to the AI-generated clone mid-call. The system already gave them the green light. They're through. The fix is obvious. Monitor the entire call. Not just the opening. Not random spot checks. Every segment, continuously, in real-time. But that was too expensive. Until now. Velma is Modulate's real-time and batch deepfake detection API. Here's what changed. • Real-time streaming detection. Analyzes audio every 2 seconds during live calls. Catches mid-call voice switches instantly. • 120x cheaper than competitors. $0.25 per hour instead of $30-150. Now you can actually afford to monitor full conversations instead of spot-checking. • Only needs 2.5 seconds of audio. Faster detection, works with short segments. • 98.9% accuracy, ranked first on HuggingFace. Lower error rate than models 10x larger. First 1000 API credits are free. I've shared the link in the replies!

    → View original post on X — @sumanth_077, 2026-04-05 14:09 UTC

  • Huawei’s Smart Noise Scheduler Improves Diffusion LLM Logic Learning
    Huawei’s Smart Noise Scheduler Improves Diffusion LLM Logic Learning

    By

    @jiqizhixin

    –

    What if Diffusion LLMs learned logic more efficiently? Huawei's Noah's Ark Lab proposes a breakthrough: their "smart noise scheduler" uses priority masking to focus training on only information-dense data, making DLLMs master core reasoning and structure. This boosts average accuracy by 4% on Code & Math reasoning, beating uniform baselines and unlocking DLLM potential. Mask Is What DLLM Needs: A Masked Data Training Paradigm for Diffusion LLMs Paper: arxiv.org/abs/2603.15803 Dataset: huggingface.co/datasets/malr… Our report: mp.weixin.qq.com/s/1yTd36hev… 📬 #PapersAccepted by Jiqizhixin

    → View original post on X — @jiqizhixin, 2026-04-05 14:05 UTC

  • Top Python Packages for Data Science and Machine Learning
    Top Python Packages for Data Science and Machine Learning

    By

    @gp_pulipaka

    –

    A List of Top #Python Packages for Data Science! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #RStats #TensorFlow #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
    geni.us/List-of-Py-Pac
    kages
    …

    → View original post on X — @gp_pulipaka

  • AI Investment Gap: Why Spending Doesn’t Guarantee Performance

    By

    @nicochan33

    –

    ⚡ Most leaders think higher AI investment leads to better performance. The real shift is that investment no longer predicts outcomes. As Roland Berger highlights, organizations now split into distinct groups despite similar levels of AI commitment. High investment and rapid deployment are widespread, but performance is increasingly uneven. 1️⃣ Structural Shift: Only a small group of “industrializers” convert AI into real value. They align strategy, execution, and operating models. 2️⃣ Leadership Blind Spot: Nearly half of organizations remain “observers” or “stalled,” running pilots or scaling activity without translating it into returns. 3️⃣ Strategic Risk: High spend without execution discipline creates the illusion of progress. Organizations move fast, but stay in the same place. This is why performance divergence is accelerating. It is no longer about access to AI. It is about how it is operationalized. The real question is not who is investing more. It is who is actually converting AI into enterprise value. via Roland Berger Why AI deployment is outpacing value realization – and how organizations can close the gap rolandberger.com/en/Insights… @corixpartners @Transform_Sec @Corix_JC @ILoveBooks786 @COSTESLionelEr @ramonvidall @RLDI_Lamy @FrRonconi @timo_vi @Nicochan33 @NathaliaLeHen @TCyberCast @arigatou163 @VivMilanoFSL @MathildaLoco @faryus88 @bbailey39 @BindIdeas971 @FmFrancoise @EduFirst @rameshambastha @DonaldGavis @ricardo_ik_ahau @sulefati7 @ozsilverfox @BCAgroup @9SManagement @O_Berard @DavidTaboada @yd_engoue @giuliog @Hajer_Alqassimi @EdwardHarkins @Evanskipropcrim @ranya_artistry @Howie7951 @iamtunslaw @gvalan

    → View original post on X — @nicochan33

  • Neural Networks For Beginners: Complete Guide
    Neural Networks For Beginners: Complete Guide

    By

    @gp_pulipaka

    –

    Neural Networks For Beginners! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
    geni.us/Neural-Nets-Ne
    wbies
    …

    → View original post on X — @gp_pulipaka

  • Best Machine Learning Books for Data Science Experts

    By

    @gp_pulipaka

    –

    Best #MachineLearning Books for Experts in Data Science! #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode

    → View original post on X — @gp_pulipaka

  • Graph Neural Networks Evolution: Predictions and Future Trends
    Graph Neural Networks Evolution: Predictions and Future Trends

    By

    @gp_pulipaka

    –

    Predicting Evolution of Graph Neural Networks. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
    geni.us/Predicting-Gra
    ph-NNs
    …

    → View original post on X — @gp_pulipaka

  • Essential Data Science Books for Engineers and Scientists
    Essential Data Science Books for Engineers and Scientists

    By

    @gp_pulipaka

    –

    Best Books for #DataScience. #BigData #Analytics #DataScience #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Books #Programming #Coding #100DaysofCode https://
    geni.us/Best-Books-Exp
    erts
    …

    → View original post on X — @gp_pulipaka

  • Skull Vibrations as Next-Generation Password Authentication Technology
    Skull Vibrations as Next-Generation Password Authentication Technology

    By

    @ronald_vanloon

    –

    Vibrations in your skull may be your next password
    by Rutgers University @TechXplore_com Learn more: https://
    bit.ly/4m8EyHZ #EmergingTech #Innovation #Tech #Technology

    → View original post on X — @ronald_vanloon

  • DiscoveryPrime: First Premium AI Recruitment Procedure Revealed
    DiscoveryPrime: First Premium AI Recruitment Procedure Revealed

    By

    @ceobillionaire

    –

    👑👑👑👑👑👑👑👑 MONTREAL.AI (@Montreal_AI) 🌌 DiscoveryPrime — the first live premium procurement, fully revealed. montrealai.github.io/discove… Where intelligence is discovered, proven, and deployed. Not just selecting talent.
    Allocating the world's most powerful capabilities. #AIAgents #AGIJobs #Jobs [Translated from EN to English]

    → View original post on X — @ceobillionaire, 2026-04-05 13:38 UTC