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Engin Dikmen retweeted
Heyman Tech Introduces Waterproof Humanoid Hand Built for Extreme Depths by @TheHumanoidHub #Robotics #MachineLearning #ArtificialIntelligence #ML #Innovation
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๐Ÿ“Š ๐—•.๐—”๐—œ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น ๐—Ÿ๐—ฒ๐—ฎ๐—ฑ๐—ฒ๐—ฟ๐—ฏ๐—ผ๐—ฎ๐—ฟ๐—ฑ ๐—œ๐˜€ ๐—ก๐—ผ๐˜„ ๐—Ÿ๐—ถ๐˜ƒ๐—ฒ AI adoption is accelerating fast. But one of the biggest challenges for users today is figuring out: Which models are actually being used? Which ones are gaining momentum? And which tools are delivering the strongest real-world engagement? Thatโ€™s where the new B.AI Leaderboard becomes valuable. The platform now gives users direct visibility into: โ†’ community model preferences โ†’ usage trends across the ecosystem โ†’ emerging model momentum โ†’ adoption shifts over time โ†’ comparative popularity between AI models Instead of relying only on marketing narratives, users can now observe how models are performing through actual platform activity and community behavior. ๐—ช๐—ต๐˜† ๐—ง๐—ต๐—ถ๐˜€ ๐— ๐—ฎ๐˜๐˜๐—ฒ๐—ฟ๐˜€ The AI space is evolving at an extremely rapid pace. New models launch constantly, capabilities improve weekly, and user attention shifts quickly. In environments moving this fast, data visibility becomes critical. Because understanding usage trends helps users: โ€ข optimize model selection โ€ข identify growing ecosystems early โ€ข track real adoption signals โ€ข compare performance popularity โ€ข adapt workflows more efficiently And as competition between AI models intensifies, transparent ecosystem insights become increasingly important. ๐—ช๐—ต๐˜† ๐—Ÿ๐—ฒ๐—ฎ๐—ฑ๐—ฒ๐—ฟ๐—ฏ๐—ผ๐—ฎ๐—ฟ๐—ฑ๐˜€ ๐—”๐—ฟ๐—ฒ ๐—•๐—ฒ๐—ฐ๐—ผ๐—บ๐—ถ๐—ป๐—ด ๐—œ๐—บ๐—ฝ๐—ผ๐—ฟ๐˜๐—ฎ๐—ป๐˜ Leaderboards are no longer just ranking systems. They are becoming: โ†’ discovery engines โ†’ trend indicators โ†’ ecosystem analytics tools โ†’ user behavior dashboards In many ways, they provide a real-time snapshot of where attention and utility are concentrating across AI ecosystems. That kind of transparency helps both users and builders make better decisions. ๐—›๐—ผ๐˜„ ๐˜๐—ผ ๐—จ๐˜€๐—ฒ ๐˜๐—ต๐—ฒ ๐—•.๐—”๐—œ ๐—Ÿ๐—ฒ๐—ฎ๐—ฑ๐—ฒ๐—ฟ๐—ฏ๐—ผ๐—ฎ๐—ฟ๐—ฑ 1๏ธโƒฃ Visit the leaderboard dashboard 2๏ธโƒฃ Explore the most actively used AI models 3๏ธโƒฃ Track changing usage patterns and rankings 4๏ธโƒฃ Identify models gaining adoption momentum 5๏ธโƒฃ Compare ecosystem engagement trends 6๏ธโƒฃ Use the data to optimize your AI workflow and model selection strategy As AI ecosystems continue expanding, platforms providing transparent usage intelligence may become increasingly valuable for navigating the next generation of models and applications. Explore here ๐Ÿ‘‡ chat.b.ai/leaderboard #AI #ArtificialIntelligence #BAI #MachineLearnin @justinsuntron @BAI_AGI #TRONEcoStar
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๐Ÿ“ฃ Strengthening ICPAC- Karlsruhe Institute of Technology (KIT) of Technology Collaboration on AI and Climate Science ๐Ÿ‘‰๐Ÿพ ICPAC recently hosted a delegation from the Karlsruhe Institute of Technology (KIT) to deepen a partnership built through projects like CONFER, SPS-Blue Nile, and FA(ST)ยฒAfrica. ๐Ÿ‘‰๐Ÿพ The visit focused on a joint proposal for a DAAD-funded Centre of African Excellence for Applied and Responsible AI in Kenya. This initiative seeks to develop practical academic programs and train high-level AI professionals across the continent. ๐Ÿ‘‰๐Ÿพ Key Collaboration Pillars: โ€ขResearch: Advancing meteorology and climate science. โ€ขCapacity Building: Training the next generation of East African scientists. โ€ขInnovation: Using AI and machine learning to improve climate services. โ€ขForecasting: Strengthening seamless weather and climate predictions. ๐Ÿ‘‰๐Ÿพ This partnership underscores ICPACโ€™s drive to use advanced technology to enhance early warning systems and climate services across the Greater Horn of Africa. #KIT #AI #MachineLearnin #ClimateScience #EW4ALL #DAAD #ClimateServices
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AI in medicine isnโ€™t about replacing doctors โ€” itโ€™s about making smarter decisions faster. But the tricky part? Understanding the data behind the models. How do you balance AI insights with human intuition? #MedicalAI #DataScience #HumanPerformance #AIinHealthcare #MachineLearnin
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Day 31! Explored AI and ML services on AWS โœ… AI Infrastructure (Trainium/Inferentia) โœ… Applied AI (Lex, Textract, Rekognition) โœ… Generative AI (Bedrock, SageMaker, Amazon Q) โœ… Benefits: Speed, Scale, & Cost Optimization The cloud is the powerhouse. #AWS #AI #MachineLearnin
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open ai is using a strategic collaboration with Broadcom to design and deploy 10 gigawatts worth of dedicated AI accelerators over the next few years. It is planned to begin use in the second half of 2026 and be completed in 2029 #entrepreneurlife #semuaorang #ai #machinelearnin
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Excited to share my internship project: a multi-agent AI to process PDFs, JSON, and emails, classify & route with shared context for seamless workflows. Hope Iโ€™ll get selected ๐Ÿ™ƒ. Appreciate your support & feedback! #AI #Internship #MachineLearnin #buildinpublic
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Excited to share my internship project: a multi-agent AI to process PDFs, JSON, and emails, classify & route with shared context for seamless workflows. Hope Iโ€™ll get selected ๐Ÿ™ƒ. Appreciate your support & feedback! #AI #Internship #MachineLearnin #buildinpublic
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๐Ÿ—“๏ธ DSA Journey: Day 8 Problem: Container With Most Water One more step forward in my DSA journeyLetโ€™s keep learning together๐Ÿค๐Ÿš€ #DSA #ProblemSolving #CodingPractice #LearningJourney #Leetcode #HackerRank #Python #CodingChallenge #100DaysOfCode #ProblemSolving #MachineLearnin
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๐Ÿ—“๏ธ DSA Journey: Day 7 Problem: Container With Most Water One more step forward in my DSA journey!Letโ€™s keep learning together. #DSA #ProblemSolving #PlacementPrep #TechWithKrish #Leetcode #Python #LeetCode #DataStructure #CodingChallenge #ProblemSolving #MachineLearnin
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@InferiumAI has revolutionized AI model deployment and inference. Key features: Letโ€™s discuss the AI Model Maze: InferiumAI has simplified the selection of model by offering an intelligent store and aggregator, enabling users to find models that best fit their specific needs. Bridging the Developer-User Gap: InferiumAI fosters better collaboration, ensuring AI models meet practical requirements effectively. Thereby, preventing the misalignment between developers and the users. InferiumAI addresses the prioritization of privacy by integrating homomorphic encryption, allowing secure AI inferences while maintaining compliance with regulations like GDPR and HIPAA. It also rewards the community for engagement on their platform through its incentivized MVP program. The users can earn rewards by engaging in daily check-ins, platform interactions, and completing tasks, fostering a vibrant and collaborative environment. #AI #InferiumAI #MachineLearnin
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๐Ÿ’ก Are you using OpenAI O3 for coding the right way? Avoid these 10 common mistakes and harness the full potential of AI-assisted coding! ๐Ÿš€ ๐Ÿ‘‰ Read the guide: #OpenAIO3 #AIforDevs #CodingHacks #machinelearnin geniusaiprompts.com/how-to-uโ€ฆ

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My recent PNAS paper on Theory of Mind (ToM) in LLMs (pnas.org/doi/abs/10.1073/pnaโ€ฆ) was featured in PsyPost. Our results suggest that ToM-like ability, once thought uniquely human, may have spontaneously emerged in LLMs. As humans use ToM when crafting their language, models trained to predict the next word in such language must reverse-engineer (or simulate) ToM. In other words, these are not simply language models; they're increasingly becoming the models of the human mind. The implications are profoundโ€”not just for AI development but for our understanding of intelligence itself. Read more: psypost.org/stanford-scientiโ€ฆ #ArtificialIntelligence #TheoryOfMind #AIResearch #CognitiveScience #MachineLearnin
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A significant advancement in medical AI has been the successful application of deep learning algorithms in detecting and analyzing cancer, showing promising results in enhancing diagnostic accuracy. #MedicalAI #DeepLearning #CancerDetection #AIinHealthcare #HealthTech #CancerResearch #MachineLearnin #PrecisionMedicine #Oncology
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๐Ÿšจ This is your final chance to join the last information session before our LLM Bootcamp kicks off. RSVP NOW: datasciencedojo.com/llm-infoโ€ฆ Join us on January 23rd at 11 AM PDT for an interactive session featuring a live Q&A with industry experts, a comprehensive bootcamp overview, and insights into the skills youโ€™ll gain to excel in the world of AI. #llm #largelanguagemodels #ai #rag #finetuning #machinelearnin
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I am an early user of @getgrass_io . Incentivized Beta is live! #getgrass Join and start earning here: app.getgrass.io/register/?reโ€ฆ #Crypto #Blockchain #iA #MachineLearnin

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