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  • Axelera AI and Almawave Partner for Multilingual Edge AI Solutions
    Axelera AI and Almawave Partner for Multilingual Edge AI Solutions

    Axelera AI together with Almawave Edge AI that speaks your language, wherever you are. That's what this partnership unlocks. Almawave, based in Rome and part of the Almaviva Group, has built Velvet, a family of multilingual large language models natively developed in Italy and available in 24 languages. We've signed a Memorandum of Understanding to bring those models to Axelera AI's enterprise edge hardware, starting with Metis. Velvet 2B is already available through the Voyager SDK model zoo today. Together, we're exploring optimization of multimodal workloads and joint go-to-market across smart cities, security, healthcare, telecommunications, and industrial applications. This partnership reflects something we believe in deeply: sovereign AI crafted in Europe, trusted by the world, running at the edge, tuned for real-world context. Almawave brings the multilingual intelligence. We bring the purpose-built hardware to run it efficiently where it matters. Multilingual. Multimodal. Built for the edge. #AxeleraAI #Almawave #EdgeAI #GenerativeAI #SovereignAI #LLM #EuropeanTech #DIMC #VoyagerSDK

    → View original post on X — @axeleraai, 2026-04-01 16:04 UTC

  • VLM Image Interpretation for Diagnosis: Reliability Concerns

    Currently we use a VLM to interpret images to diagnose outcomes but that is not always reliable.

    → View original post on X — @ken_goldberg

  • DeepReinforce Wins Top Spot in AI Contest

    DeepReinforce took first place in a competitive programming contest, with its AI Agent, outperforming all human contenders. Earlier, the previous best result was achieved by Gemini 3.1, hitting 8th place in February 2026. "GrandCode is a multi-agent AI system powered by

    → View original post on X — @testingcatalog

  • Deep Generative Model for Cell ATACseq and RNAseq Profiling

    A Deep Generative Model for Profiling of cell ATACseq and RNAseq. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
    geni.us/Gen-RNASeq

    → View original post on X — @gp_pulipaka

  • AI Efficiency in Radiology and Its Impact on Radiologist Demand
    AI Efficiency in Radiology and Its Impact on Radiologist Demand

    I just read this news, and it makes sense. Up until now, it's always been said that more AI in application (using radiology as an example) leads to more people being able to see radiologists due to increased efficiency, and therefore more human radiologists would be needed

    → View original post on X — @kimmonismus

  • AB PM-JAY AutoAdjudication Hackathon: AI Healthcare Claims Innovation Challenge
    AB PM-JAY AutoAdjudication Hackathon: AI Healthcare Claims Innovation Challenge

    The future of healthcare is intelligent, automated and efficient, and it starts with transforming how claims are processed. Join the AB PM-JAY #AutoAdjudicationHackathon and build AI-powered solutions for automated claims adjudication, driving speed, accuracy and better patient outcomes. 💡 This is your chance to turn innovation into real-world impact in healthcare delivery. 🗓️ Registrations open till: April 13, 2026 🏁 Finale: May 8–9, 2026| Indian Institute of Science, Bengaluru 🔍 Build. Innovate. Transform healthcare. #HealthTech #AIforGood #DigitalHealth #InnovationChallenge #ABPMJAY @AshwiniVaishnaw @jitinprasada @PIB_India @SecretaryMEITY @abhish18 @kavitabha @GoI_MeitY @_DigitalIndia @mygovindia @AyushmanNHA

    → View original post on X — @officialindiaai, 2026-04-01 11:13 UTC

  • AI Hackathon for Healthcare Data Processing with CDSCO Support
    AI Hackathon for Healthcare Data Processing with CDSCO Support

    Can your AI solution efficiently extract, verify and anonymise critical information from unstructured healthcare data? Join the Hackathon to refine your solution with support and guidance from the Central Drugs Standard Control Organisation (CDSCO). Winners receive a chance to secure ₹50 Lakh and an opportunity to deploy their solution with CDSCO. Apply by: April 17th, 2026 🔗 Download Guidelines & Apply Now: aikosh.indiaai.gov.in/home/c… #NLP #IntelligentDocumentProcessing #HealthcareInnovation #IndiaAI #RegTech #MeitY @AshwiniVaishnaw @jitinprasada @PIB_India @SecretaryMEITY @abhish18 @kavitabha @GoI_MeitY @_DigitalIndia @mygovindia @CDSCO_INDIA_INF

    → View original post on X — @officialindiaai, 2026-04-01 08:35 UTC

  • Healthcare AI Project: Podcast and Vibe-Coding Innovation

    Je devais faire un projet avec des étudiants en dernière année de BUT info. J'explique dès le début que j'ai un podcast Medicbrain sur spotify où j'explique des solutions IA pour la santé (mon fils de 11 ans a eu un cancer). Je leur dit que je m'oriente vers le vibe-coding, je

    → Voir le post original sur X — @jessyseonoob

  • AI Fundraising Milestone for Cancer Research Initiative

    Wow ma cagnotte pour #Medicbrain vient d'atteindre 1 million d'euros ! Je ne sais pas quoi dire, pour vous remercier. Vous êtes formidables. Merci pour vos partages et vos engagements et vos dons. On va pouvoir trouver des solutions contre les cancers avec l'IA. Je vais

    → Voir le post original sur X — @jessyseonoob

  • AI-Generated Medical Papers: Progress Without Revolutionary Claims
    AI-Generated Medical Papers: Progress Without Revolutionary Claims

    This is a solid, innovative step toward AI-augmented scientific workflows in medicine. It seems better at structured medical tasks than generic LLMs, with manuscripts that can fool experts in blind tests (and also fool conferences – although that seems relatively easy these days). It demonstrates progress in autonomous agents for research pipelines. However, it's not yet a revolutionary "AI scientist" replacing human researchers or immediately flooding journals with validated breakthroughs. Real impact will depend on extensive external validation and whether it’s a black box or provides mechanistic interpretation. Can we stop it with the dramatic pronouncements describing legitimate papers which are clearly AI-written? Ihtesham Ali (@ihtesham2005) 🚨BREAKING: Stanford and Microsoft just built an AI scientist that writes medical research papers that actually pass peer review. Not summaries. Not drafts. Full papers reviewed and accepted by real scientists. This is not a demo and this is not a prototype. A peer-reviewed conference just accepted a paper that no human wrote, and most people have absolutely no idea it happened. The system is called Medical AI Scientist and it works in three stages that run completely on their own. First, it reads medical literature, identifies real clinical gaps, and generates a research hypothesis grounded in actual disease evidence, not a hallucination and not a generic idea pulled from thin air. Then it writes the code, runs the experiment inside a secure environment, catches its own errors, and fixes them without any human stepping in. Then it writes the full paper, including the introduction, methods, results, figures, ethics statement, citations, and LaTeX formatting, from start to finish, autonomously. They tested it against GPT-5 and Gemini 2.5 Pro across 171 real medical research cases covering 19 clinical tasks, and the results were not close. Medical AI Scientist successfully completed experiments 91 to 93 percent of the time. GPT-5 managed 60 to 75 percent. Gemini 2.5 Pro collapsed somewhere between 40 and 53 percent. Then they ran the part that genuinely broke my brain. Ten independent medical experts with over five years of first-author publishing experience reviewed the AI-generated papers side by side with real human papers from MICCAI, ISBI, and BIBM, the top conferences in medical imaging, and nobody knew which was which. The AI papers scored competitively on novelty, clarity, coherence, and reproducibility across the board, and one paper was accepted at a peer-reviewed conference after a full review process. Here is what nobody is saying out loud. Medical research has a brutal bottleneck where ideas pile up, experiments take months, papers take even longer, and patients wait the entire time. That problem just got a serious solution, and the implications for healthcare are enormous. — https://nitter.net/ihtesham2005/status/2039009949276319824#m

    → View original post on X — @sallyeaves, 2026-04-01 06:55 UTC