Tomer Gal ⚡

𝐌𝐮𝐬𝐭-𝐫𝐞𝐚𝐝, 𝐟𝐫𝐞𝐞 𝐛𝐨𝐨𝐤 𝐭𝐡𝐚𝐭 𝐩𝐫𝐨𝐯𝐢𝐝𝐞𝐬 𝐚 𝐩𝐚𝐭𝐡𝐰𝐚𝐲 𝐟𝐫𝐨𝐦 𝐆𝐀𝐈 𝐭𝐨 𝐀𝐆𝐈! ​ Yann LeCun has expressed skepticism about the potential of LLMs to achieve Artificial General Intelligence (AGI), citing limitations in memory, planning, and grounding in real-world understanding. However, we argue that 𝗟𝗟𝗠 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝘃𝗲 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 (𝗟𝗖𝗜)—particularly with multiple multimodal LLMs working together—offers a promising architecture to address these challenges and progress toward AGI. ​ Two key architectural innovations underlie LCI: ​ 𝐒𝐞𝐩𝐚𝐫𝐚𝐭𝐢𝐨𝐧 𝐨𝐟 𝐔𝐧𝐜𝐨𝐧𝐬𝐜𝐢𝐨𝐮𝐬 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐨𝐧𝐬𝐜𝐢𝐨𝐮𝐬 𝐑𝐞𝐚𝐬𝐨𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐏𝐥𝐚𝐧𝐧𝐢𝐧𝐠: Inspired by the human mind’s dual-layer structure, LCI divides its architecture into foundational and adaptive layers. The foundation layer, akin to unconscious processing, leverages extensive datasets to build robust pattern recognition, encoding essential responses much like human instincts. The adaptive layer, mirroring conscious thought, enables rapid adaptation and contextual reasoning. This dual-layer approach allows LLMs to perform complex tasks with foundational knowledge while adjusting to new information on the fly, much as a child learns new concepts within a developed cognitive framework. ​ 𝐃𝐢𝐬𝐭𝐢𝐧𝐜𝐭 𝐑𝐨𝐥𝐞𝐬 𝐟𝐨𝐫 𝐄𝐚𝐜𝐡 𝐋𝐋𝐌-𝐀𝐠𝐞𝐧𝐭: Each LLM-agent is assigned a specific role, such as executive (knowledge processing), legislative (behavior guardrails), and judicial (adapting to cultural norms). ​ Additionally, our validation of the LCI framework has been thoroughly tested through real-world deployment in applications across various domains, including healthcare, sales planning, investment, and debiasing news. These empirical deployments highlight the practical viability and adaptability of the LCI framework, showcasing its ability to enhance reasoning and decision-making through collaborative intelligence. ​ The eleven aphorisms presented in this free book illustrate the philosophical foundation of the LCI framework, backed by empirical studies. Through LCI, we envision a clear pathway to AGI, rooted in collaborative intelligence and flexible, context-aware adaptation. https://lnkd.in/gn74DkNj (free) https://lnkd.in/gszSvfqP ($6.98 printing fee)

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TSMC Leads the AI Surge, Apple Faces Headwinds, and NVIDIA Steps Up A recent discussion about TSMC’s and Foxconn’s strong 2024 performance was driven by AI momentum. We also explored Apple’s challenges with tariffs, declining market share, and the lack of clarity around the potential of Apple Intelligence in China. Finally, I shared my views on NVIDIA’s latest announcements at CES 2025 in Las Vegas. The tech sector is on track for more transformation, fueled by robust AI demand and innovation. #AI #Semiconductors #NVIDIA #Apple #Foxconn #TSMC #CES2025 #TechnologyTrends #DigitalTransformation

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𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 𝗔𝗻𝗻𝗼𝘂𝗻𝗰𝗲𝗺𝗲𝗻𝘁 (𝗔𝗴𝗮𝗶𝗻) 🔍 𝙊𝙥𝙚𝙣 𝙩𝙤 𝙉𝙚𝙬 𝙊𝙥𝙥𝙤𝙧𝙩𝙪𝙣𝙞𝙩𝙞𝙚𝙨 ( 𝙁𝙪𝙡𝙡 𝙏𝙞𝙢𝙚/𝘾𝙤𝙣𝙩𝙧𝙖𝙘𝙩) - 𝙄𝙢𝙢𝙚𝙙𝙞𝙖𝙩𝙚 𝘼𝙫𝙖𝙞𝙡𝙖𝙗𝙞𝙡𝙞𝙩𝙮 My Linkedin community. I'm seeking new challenges in Data Science, Computer vision, or Audio/Biomedical Signal Processing, with immediate availability. 𝗖𝗮𝗿𝗲𝗲𝗿 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀: 🔅 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻: Pioneered applications in gesture recognition, disease detection, predictive analytics and parameter optimization within various industries. 🔅 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆: Developed AI-based diagnostic systems, analytics software and medical device algorithms for hearing impaired, Continuous Glucose monitoring for diabetes, Glaucoma etc leading to enhanced patient outcomes. 🔅 𝗦𝗶𝗴𝗻𝗮𝗹 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴: Engineered innovative approaches in audio processing, satellite imagery enhancement, and biomedical signal analysis. 🔅𝗕𝗮𝗹𝗮𝗻𝗰𝗲𝗱 𝗦𝗸𝗶𝗹𝗹𝘀𝗲𝘁: Proven ability to excel as an 𝗶𝗻𝗱𝗶𝘃𝗶𝗱𝘂𝗮𝗹 𝗰𝗼𝗻𝘁𝗿𝗶𝗯𝘂𝘁𝗼𝗿 with hands-on expertise while thriving in 𝗰𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝘃𝗲 𝘁𝗲𝗮𝗺 𝘀𝗲𝘁𝘁𝗶𝗻𝗴𝘀. 🔅𝗣𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗥𝗲𝗰𝗼𝗴𝗻𝗶𝘁𝗶𝗼𝗻: Elevated to 𝗦𝗲𝗻𝗶𝗼𝗿 𝗜𝗘𝗘𝗘 𝗺𝗲𝗺𝗯𝗲𝗿𝘀𝗵𝗶𝗽 and secured 𝗘𝗕2-𝗡𝗜𝗪 (𝗡𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗲𝘀𝘁 𝗪𝗮𝗶𝘃𝗲𝗿) 𝗮𝗽𝗽𝗿𝗼𝘃𝗮𝗹 for my I-140 green card application, demonstrating recognized contributions to national interest. ➡️ ➡️ 𝗜𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲 𝗩𝗮𝗹𝘂𝗲 𝗣𝗿𝗼𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻: 📯Ready to start immediately. 📯Track record of successful technical projects 📯Demonstrated success adapting to diverse organizational scales, from agile small startup-like environments to large enterprise structures 𝗜𝗳 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 𝗼𝗳 𝗮𝗻𝘆 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀 𝗼𝗿 𝗰𝗼𝘂𝗹𝗱 𝗳𝗮𝗰𝗶𝗹𝗶𝘁𝗮𝘁𝗲 𝗶𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻𝘀, 𝗽𝗹𝗲𝗮𝘀𝗲 𝗿𝗲𝗮𝗰𝗵 𝗼𝘂𝘁 𝘃𝗶𝗮 𝗗𝗠 𝗼𝗿 𝗲𝗺𝗮𝗶𝗹.𝗖𝗼𝗻𝘁𝗮𝗰𝘁: I can be reached at 𝗟𝗶𝗻𝗸𝗲𝗱𝗶𝗻 https://lnkd.in/g3k5dCmF or My 𝗽𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼: https://lnkd.in/gkWBY5aN, #𝗢𝗽𝗲𝗻𝗧𝗼𝗪𝗼𝗿𝗸 #𝗗𝗮𝘁𝗮𝗦𝗰𝗶𝗲𝗻𝗰𝗲 #𝗠𝗮𝗰𝗵𝗶𝗻𝗲𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 #𝗔𝗜 #𝗦𝗜𝗴𝗻𝗮𝗹𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 #𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 #𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 #𝗜𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 #𝗧𝗲𝗰𝗵𝗝𝗼𝗯𝘀

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🧠 🚨 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫-𝐛𝐚𝐬𝐞𝐝 𝐃𝐨𝐠 𝐁𝐞𝐡𝐚𝐯𝐢𝐨𝐫 𝐂𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐌𝐨𝐭𝐢𝐨𝐧 𝐒𝐞𝐧𝐬𝐨𝐫𝐬 ⚡ 🔥 - a new solo-authored paper by Dr. Barak Or 💥 💥 With a great pleasure I am sharing a new and a very cool paper of my dear friend Dr. Barak Or. ✅ This paper deals with classifying dog behavior using motion sensors, leveraging a transformer-based #deepneuralnetwork model. ✅ Understanding dog behavior is essential for fostering positive relationships between dogs and humans and ensuring their well-being. ✅ Traditional methods often fall short i capturing temporal dependencies and efficiently processing high-dimensional sensor data. ✅ Our proposed architecture, inspired by its success in #nlp, utilizes the self-attention mechanism of the transformer to effectively identify relevant features across various time scales, making it ideal for real-time applications. 😎 This research is done by MetaOr Artificial Intelligence's aiming at pushing AI to a new level, where it can be anywhere, even in pet care! #pets #transformers #ai

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𝗜𝗻 𝟮𝟬𝟮𝟰, 𝗔𝗜 𝘄𝗿𝗼𝘁𝗲 𝟰𝟬% 𝗼𝗳 𝗮𝗹𝗹 𝗰𝗼𝗱𝗲, 𝗰𝗿𝗲𝗮𝘁𝗲𝗱 𝟱𝟬 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝘃𝗶𝗱𝗲𝗼𝘀, 𝗮𝗻𝗱 𝗿𝗲𝗽𝗹𝗮𝗰𝗲𝗱 𝟭𝟬𝟬,𝟬𝟬𝟬+ 𝗷𝗼𝗯𝘀 Let me break down how AI changed our world this year in simple terms 👇 AI Wrapped 2024: The year that made the impossible possible   𝟭. OpenAI 𝗟𝗲𝗮𝗱𝗶𝗻𝗴 𝘁𝗵𝗲 𝗪𝗮𝘆 They showed us what AI can do: • Made GPT-4 much faster and better at everything • Created Sora, an AI that makes videos from text • Became worth $157B (that's more than Nike! btw) • Launched o1 that can literally think & understand problems • Put out all their ammunition for Christmas • Set new standards for what AI can achieve 𝟮. Google's 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗖𝗼𝗺𝗲𝗯𝗮𝗰𝗸 Remember when Google's AI was a joke? Look at them now: • Built Gemini 2.0 that can understand text, images, and voice • Created Project Astra - an AI that remembers conversations • Released free AI tools for developers • Have you folks tried Google's deep research? It is mind-blowing!! • Went from being laughed at to leading the pack 𝟯. Microsoft 𝗚𝗲𝘁𝘁𝗶𝗻𝗴 𝗧𝗵𝗶𝗻𝗴𝘀 𝗗𝗼𝗻𝗲 While others made noise, Microsoft made progress: • Made Copilot better at helping with daily tasks • Added live translation to video calls • Working on their own AI (MAI-1) • Made Office apps smarter with AI 𝟰. 𝗚𝗿𝗼𝗸 𝗝𝗼𝗶𝗻𝗶𝗻𝗴 𝘁𝗵𝗲 𝗥𝗮𝗰𝗲 The new player with big dreams: • Raised $6B in funding • Worth $24B already • Built AI that explains its decisions • Putting to research where Grok is powering the health sector in   making prescriptions. • Making AI more trustworthy 𝟱. NVIDIA: 𝗧𝗵𝗲 𝗦𝗶𝗹𝗲𝗻𝘁 𝗛𝗲𝗿𝗼 Making it all possible: • Created faster AI chips • Built super powerful computers • Worth $3 TRILLION now • Powering everyone's AI dreams But here's what's really important... 2025 will be even bigger: • AI agents will become more like colleagues • AGI RAGs will power businesses & disrupt them. • AI + Automation intersection will reach new levels • AI will think and work more independently Here's the truth: While most companies are still learning basic AI tools, the world is moving towards AI that can work independently! What do you think will happen in 2025? Are you excited or worried? Share your thoughts 👇 Let's talk about the future! #AIWrapped2024 #AI #Technology #Future

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0059: Mapping Molecular Hamiltonians To Qubit Operators with Jordan-Wigner Transformation In quantum computing, the efficient mapping of molecular Hamiltonians to qubit operators is a critical step in solving electronic structure problems, especially in quantum chemistry. One of the most established methods for achieving this is the Jordan-Wigner Transformation (JWT). The JWT translates fermionic operators, which describe the behavior of electrons in molecules, into qubit operators that can be used in quantum algorithms. The central challenge in electronic structure calculations is the fermionic nature of electrons, which obey the Pauli exclusion principle and anti-commutation relations. Fermionic operators are used to create and annihilate electrons in specific quantum states, but these operators do not directly translate to qubit-based quantum computing. This is where JWT comes in: it provides a systematic way to represent these fermionic operators as qubit operators that obey the commutation relations of quantum gates. The Jordan-Wigner Transformation maps each fermionic operator to a string of Pauli matrices on qubits. Specifically, each fermionic creation or annihilation operator is mapped to a combination of Pauli-Z, Pauli-X, and Pauli-Y operators that span the qubits, ensuring that the anti-commutation properties of fermions are preserved in the qubit space. By mapping molecular Hamiltonians using the Jordan-Wigner Transformation, we can represent the electronic interactions and energy of a molecule in a form that quantum computers can process. Once this mapping is complete, variational algorithms like the Variational Quantum Eigensolver (VQE) or Quantum Phase Estimation (QPE) can be employed to estimate the ground-state energy of the molecule. These algorithms aim to find the eigenvalues of the molecular Hamiltonian, which directly correspond to the molecular energy levels. The benefit of using JWT is that it scales linearly with the number of qubits, making it an efficient method for near-term quantum devices. However, it has some limitations, such as the need for long-range qubit interactions, which may pose a challenge for hardware implementations. Other transformations, like the Bravyi-Kitaev Transformation, offer alternatives with different trade-offs in qubit connectivity and operator complexity. The Jordan-Wigner Transformation is foundational in quantum chemistry simulations on quantum computers. It bridges the gap between the fermionic nature of molecules and the qubit-based framework of quantum computing. As the field progresses, leveraging such transformations is essential for advancing quantum simulations of complex molecular systems, which could lead to breakthroughs in fields like drug discovery, material science, and energy research. Check comment for links to code repository and resources in Quantum Chemistry.

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Congratulations to my student Chengzeng You for winning the best paper award at the IEEE/ACM Workshop on the Internet of Safe Things! In this work we show that it is possible for an adversary to construct digital adversarial patches for 3D point clouds to evade 3D object detection. 3D point clouds is how measurements taken by depth sensors are stored and processed and find applications in autonomous driving, environment mapping and land surveying. We leveraged an explainability aware approach called integrated gradients to identify critical points in a point cloud which allowed us to develop a method to concentrate the attack on a small area in a region of interest. This demonstrates that these attacks can be performed more efficiently and more stealthily than previously considered and highlights the need for more effective defenses. This is joint work with Aaron (Zhongyuan) H. and Binbin Xu and is part of our research group’s goal in better understanding the threats in using AI in cyber physical systems and designing efficient and effective defensive AI. Paper title: Adversarial 3D Virtual Patches Using Integrated Gradients. https://lnkd.in/eW7tkB7N

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🌐 𝐆𝐨𝐨𝐠𝐥𝐞 𝐀𝐈’𝐬 𝐓𝐫𝐚𝐧𝐬𝐥𝐚𝐭𝐢𝐨𝐧 𝐏𝐨𝐰𝐞𝐫 𝐔𝐧𝐥𝐨𝐜𝐤𝐞𝐝 𝐛𝐲 𝐚 𝐏𝐫𝐨𝐦𝐩𝐭! 🌐 🌐 𝐏𝐫𝐞-𝐭𝐫𝐚𝐢𝐧𝐞𝐝 𝐨𝐧 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐝𝐚𝐭𝐚, 𝐆𝐨𝐨𝐠𝐥𝐞 𝐀𝐈 𝐜𝐨𝐮𝐥𝐝 𝐛𝐞 𝐩𝐚𝐯𝐢𝐧𝐠 𝐭𝐡𝐞 𝐰𝐚𝐲 𝐭𝐨 𝐦𝐚𝐬𝐭𝐞𝐫𝐢𝐧𝐠 𝐡𝐮𝐧𝐝𝐫𝐞𝐝𝐬 (𝐨𝐫 𝐭𝐡𝐨𝐮𝐬𝐚𝐧𝐝𝐬!) 𝐨𝐟 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬. 𝐓𝐡𝐞 𝐭𝐰𝐢𝐬𝐭? 𝐈𝐭𝐬 𝐢𝐧𝐧𝐞𝐫 𝐰𝐨𝐫𝐤𝐢𝐧𝐠𝐬 𝐫𝐞𝐦𝐚𝐢𝐧 𝐚 𝐦𝐲𝐬𝐭𝐞𝐫𝐲 𝐚𝐬 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐚𝐬 𝐭𝐡𝐞 𝐡𝐮𝐦𝐚𝐧 𝐦𝐢𝐧𝐝. 🤔 ✨ 𝐖𝐡𝐚𝐭’𝐬 𝐈𝐧𝐭𝐫𝐢𝐠𝐮𝐢𝐧𝐠: • 💬 Multilingual Potential – Breaking language barriers • 🧠 AI “Black Box” – Still an enigma, even to its creators • 🌍 Future of Communication – Imagine seamless global interaction 📽️: 𝐔𝐧𝐤𝐧𝐨𝐰𝐧 (𝐃𝐌 𝐟𝐨𝐫 𝐜𝐫𝐞𝐝𝐢𝐭𝐬) #AI #GoogleAI #LanguageAI #AITips #MachineLearning #TranslationTech #TechInnovation #AIandLanguage #BlackBoxAI #FutureOfAI #AITools #TechMysteries #SmartTech #GlobalCommunication #ArtificialIntelligence #DigitalTransformation #TechInLanguage #AIinAction #AITranslation #NextGenTech #TechTrends #TechForGood #Innovation #AIAdvancements #AIResearch #LanguageTech

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🌟 𝐓𝐡𝐞 𝐩𝐨𝐬𝐬𝐢𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬 𝐨𝐟 𝐀𝐈 𝐚𝐫𝐞 𝐞𝐧𝐝𝐥𝐞𝐬𝐬! 𝐍𝐨𝐰, 𝐦𝐚𝐧𝐚𝐠𝐞 𝐲𝐨𝐮𝐫 𝐦𝐚𝐜𝐫𝐨𝐧𝐮𝐭𝐫𝐢𝐞𝐧𝐭𝐬 𝐰𝐢𝐭𝐡 𝐣𝐮𝐬𝐭 𝐚 𝐬𝐢𝐧𝐠𝐥𝐞 𝐩𝐢𝐜𝐭𝐮𝐫𝐞. 🚀 𝐈𝐭’𝐬 𝐧𝐨𝐭 𝐬𝐜𝐢𝐞𝐧𝐜𝐞 𝐟𝐢𝐜𝐭𝐢𝐨𝐧—𝐢𝐭’𝐬 𝐡𝐚𝐩𝐩𝐞𝐧𝐢𝐧𝐠 𝐧𝐨𝐰. 🌐 Day 1 of AI and cutting-edge tech is already reshaping our world. They're not just trends; they’re the new standard, the ultimate solution, the secret weapon, and the game changer we've all been waiting for. 🚀 For professionals, this means unlocking new levels of efficiency and innovation. 🔗 Keep in touch and discover one AI tool a day with our free newsletter at www.wildtools.ai 🌿 Struggling with stress, work-life balance, burnout, or finding your purpose? Make a change today with a free discovery call: https://shorturl.at/blHMr #AI #Innovation #FutureOfWork #BusinessGrowth #TechRevolution Keep innovating and transforming with AI! 🚀

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𝐓𝐨𝐰𝐚𝐫𝐝𝐬 𝐓𝐡𝐞 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐄𝐜𝐨𝐧𝐨𝐦𝐲: Modern AI agents, driven by advances in large foundation models, promise to enhance our productivity and transform our lives by augmenting our knowledge and capabilities. To achieve this vision, 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 𝐦𝐮𝐬𝐭 𝐞𝐟𝐟𝐞𝐜𝐭𝐢𝐯𝐞𝐥𝐲 𝐩𝐥𝐚𝐧, 𝐩𝐞𝐫𝐟𝐨𝐫𝐦 𝐦𝐮𝐥𝐭𝐢-𝐬𝐭𝐞𝐩 𝐫𝐞𝐚𝐬𝐨𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐚𝐜𝐭𝐢𝐨𝐧𝐬, 𝐫𝐞𝐬𝐩𝐨𝐧𝐝 𝐭𝐨 𝐧𝐨𝐯𝐞𝐥 𝐨𝐛𝐬𝐞𝐫𝐯𝐚𝐭𝐢𝐨𝐧𝐬, 𝐚𝐧𝐝 𝐫𝐞𝐜𝐨𝐯𝐞𝐫 𝐟𝐫𝐨𝐦 𝐞𝐫𝐫𝐨𝐫𝐬, 𝐭𝐨 𝐬𝐮𝐜𝐜𝐞𝐬𝐬𝐟𝐮𝐥𝐥𝐲 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐭𝐚𝐬𝐤𝐬 𝐚𝐜𝐫𝐨𝐬𝐬 𝐚 𝐰𝐢𝐝𝐞 𝐫𝐚𝐧𝐠𝐞 𝐨𝐟 𝐬𝐜𝐞𝐧𝐚𝐫𝐢𝐨𝐬. 𝐈𝐧 𝐭𝐡𝐢𝐬 𝐰𝐨𝐫𝐤, 𝐭𝐡𝐞 𝐚𝐮𝐭𝐡𝐨𝐫𝐬 𝐢𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐞 𝐌𝐚𝐠𝐞𝐧𝐭𝐢𝐜-𝐎𝐧𝐞, 𝐚 𝐡𝐢𝐠𝐡-𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐨𝐩𝐞𝐧-𝐬𝐨𝐮𝐫𝐜𝐞 𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐬𝐲𝐬𝐭𝐞𝐦 𝐟𝐨𝐫 𝐬𝐨𝐥𝐯𝐢𝐧𝐠 𝐬𝐮𝐜𝐡 𝐭𝐚𝐬𝐤𝐬. Magentic-One uses a multi-agent architecture where a lead agent, the Orchestrator, plans, tracks progress, and re-plans to recover from errors. Throughout task execution, the Orchestrator directs other specialized agents to perform tasks as needed, such as operating a web browser, navigating local files, or writing and executing Python code. 𝐓𝐡𝐞 𝐚𝐮𝐭𝐡𝐨𝐫𝐬 𝐬𝐡𝐨𝐰 𝐭𝐡𝐚𝐭 𝐌𝐚𝐠𝐞𝐧𝐭𝐢𝐜-𝐎𝐧𝐞 𝐚𝐜𝐡𝐢𝐞𝐯𝐞𝐬 𝐬𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐚𝐥𝐥𝐲 𝐜𝐨𝐦𝐩𝐞𝐭𝐢𝐭𝐢𝐯𝐞 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐭𝐨 𝐭𝐡𝐞 𝐬𝐭𝐚𝐭𝐞-𝐨𝐟-𝐭𝐡𝐞-𝐚𝐫𝐭 𝐨𝐧 𝐭𝐡𝐫𝐞𝐞 𝐝𝐢𝐯𝐞𝐫𝐬𝐞 𝐚𝐧𝐝 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐢𝐧𝐠 𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐛𝐞𝐧𝐜𝐡𝐦𝐚𝐫𝐤𝐬: 𝐆𝐀𝐈𝐀, 𝐀𝐬𝐬𝐢𝐬𝐭𝐚𝐧𝐭𝐁𝐞𝐧𝐜𝐡, 𝐚𝐧𝐝 𝐖𝐞𝐛𝐀𝐫𝐞𝐧𝐚. Magentic-One achieves these results without modification to core agent capabilities or to how they collaborate, 𝐝𝐞𝐦𝐨𝐧𝐬𝐭𝐫𝐚𝐭𝐢𝐧𝐠 𝐩𝐫𝐨𝐠𝐫𝐞𝐬𝐬 𝐭𝐨𝐰𝐚𝐫𝐝𝐬 𝐠𝐞𝐧𝐞𝐫𝐚𝐥𝐢𝐬𝐭 𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐬𝐲𝐬𝐭𝐞𝐦𝐬. Moreover, 𝐌𝐚𝐠𝐞𝐧𝐭𝐢𝐜-𝐎𝐧𝐞'𝐬 𝐦𝐨𝐝𝐮𝐥𝐚𝐫 𝐝𝐞𝐬𝐢𝐠𝐧 𝐚𝐥𝐥𝐨𝐰𝐬 𝐚𝐠𝐞𝐧𝐭𝐬 𝐭𝐨 𝐛𝐞 𝐚𝐝𝐝𝐞𝐝 𝐨𝐫 𝐫𝐞𝐦𝐨𝐯𝐞𝐝 𝐟𝐫𝐨𝐦 𝐭𝐡𝐞 𝐭𝐞𝐚𝐦 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐚𝐝𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐩𝐫𝐨𝐦𝐩𝐭 𝐭𝐮𝐧𝐢𝐧𝐠 𝐨𝐫 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠, 𝐞𝐚𝐬𝐢𝐧𝐠 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐚𝐧𝐝 𝐦𝐚𝐤𝐢𝐧𝐠 𝐢𝐭 𝐞𝐱𝐭𝐞𝐧𝐬𝐢𝐛𝐥𝐞 𝐭𝐨 𝐟𝐮𝐭𝐮𝐫𝐞 𝐬𝐜𝐞𝐧𝐚𝐫𝐢𝐨𝐬. The authors provide an open-source implementation of Magentic-One, and they include AutoGenBench, a standalone tool for agentic evaluation. AutoGenBench provides built-in controls for repetition and isolation to run agentic benchmarks in a rigorous and contained manner -- which is important when agents' actions have side-effects. SOURCE: https://lnkd.in/ga33RY-r CODE: https://lnkd.in/gSgmT36s

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Excited to share my recent interview on "הכל כלכלה" discussing Nvidia's acquisition of Run:ai, an Israeli software company, for a whopping $700 million! This move, along with potential future acquisitions, demonstrates Nvidia's strong belief in Israeli AI innovation. Run:AI's software expertise will enhance Nvidia's hardware offerings, making AI more accessible and efficient. As the global AI race intensifies, Israel's talent and technology are crucial. With strategic partnerships and continued investment, we can ensure Israel remains a leader in shaping the future of AI.

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♟️ 𝐖𝐡𝐞𝐧 𝐀𝐦𝐞𝐜𝐚 𝐏𝐥𝐚𝐲𝐬 𝐂𝐡𝐞𝐬𝐬... ♟️ 📌 𝐌𝐞𝐞𝐭 𝐀𝐦𝐞𝐜𝐚, 𝐚 𝐥𝐢𝐟𝐞𝐥𝐢𝐤𝐞 𝐚𝐧𝐝𝐫𝐨𝐢𝐝 𝐰𝐢𝐭𝐡 𝐢𝐧𝐜𝐫𝐞𝐝𝐢𝐛𝐥𝐞 𝐡𝐮𝐦𝐚𝐧-𝐥𝐢𝐤𝐞 𝐞𝐱𝐩𝐫𝐞𝐬𝐬𝐢𝐨𝐧𝐬—𝐛𝐥𝐢𝐧𝐤𝐢𝐧𝐠 𝐢𝐧 𝐬𝐮𝐫𝐩𝐫𝐢𝐬𝐞, 𝐬𝐦𝐢𝐥𝐢𝐧𝐠 𝐢𝐧 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧, 𝐚𝐧𝐝, 𝐚𝐬 𝐬𝐞𝐞𝐧 𝐡𝐞𝐫𝐞, 𝐩𝐥𝐚𝐲𝐢𝐧𝐠 𝐜𝐡𝐞𝐬𝐬! 𝐓𝐡𝐢𝐬 𝐫𝐨𝐛𝐨𝐭 𝐢𝐬 𝐞𝐪𝐮𝐢𝐩𝐩𝐞𝐝 𝐰𝐢𝐭𝐡 𝐀𝐈 𝐭𝐡𝐚𝐭 𝐚𝐥𝐥𝐨𝐰𝐬 𝐢𝐭 𝐭𝐨 𝐢𝐧𝐭𝐞𝐫𝐚𝐜𝐭 𝐯𝐞𝐫𝐛𝐚𝐥𝐥𝐲 𝐚𝐧𝐝 𝐫𝐞𝐬𝐩𝐨𝐧𝐝 𝐭𝐨 𝐭𝐡𝐨𝐬𝐞 𝐚𝐫𝐨𝐮𝐧𝐝 𝐢𝐭. ✨ 𝐖𝐡𝐲 𝐀𝐦𝐞𝐜𝐚 𝐢𝐬 𝐈𝐦𝐩𝐫𝐞𝐬𝐬𝐢𝐯𝐞: • 👀 Expressive Reactions – Blinks, smiles, and shows human-like gestures • 🗣️ Interactive AI – Engages in verbal conversations seamlessly • ♟️ Chess Skills – Bringing intelligence and personality to the game 𝐒𝐨𝐮𝐫𝐜𝐞: 𝐂𝐡𝐞𝐝𝐝𝐚𝐫 #AI #Ameca #Robotics #Innovation #HumanlikeRobots #TechTrends #ArtificialIntelligence #TopVoice #Robotique #FutureOfTech #ExpressiveRobots #InteractiveAI #GameChanger #InnovationInRobotics #LifelikeAndroids #NextGenTech #FutureOfRobots #HumanRobotInteraction #IntelligentSystems #AdvancedAI #RoboticsInnovation #TechUpdates #SmartTechnology #AIInAction #TechRevolution #DigitalInnovation

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💥 𝐀𝐈-𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐞𝐝 𝐦𝐮𝐬𝐢𝐜 𝐯𝐢𝐝𝐞𝐨𝐬 𝐚𝐫𝐞 𝐫𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐭𝐡𝐞 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐲! 💥 𝐓𝐨𝐨𝐥𝐬 𝐔𝐬𝐞𝐝 ↓ 𝐌𝐮𝐬𝐢𝐜 🎵: 𝐂𝐡𝐚𝐭𝐆𝐏𝐓, 𝐒𝐮𝐧𝐨𝐚𝐢 𝐕𝐢𝐝𝐞𝐨 🎥: 𝐃𝐫𝐞𝐚𝐦 𝐌𝐚𝐜𝐡𝐢𝐧𝐞, 𝐆𝐞𝐧-𝟑, 𝐊𝐥𝐢𝐧𝐠 𝐈𝐦𝐚𝐠𝐞𝐬 🖼️: 𝐌𝐉, 𝐒𝐃 𝐄𝐝𝐢𝐭𝐢𝐧𝐠 ✏️: 𝐏𝐬, 𝐀𝐞 AI is drastically reducing costs while maintaining top-notch quality. What's your prediction for the next big leap in AI-generated videos? Could it be movies or something completely unexpected? 𝐂𝐫𝐞𝐝𝐢𝐭𝐬: @𝐚𝐫𝐚𝐭𝐚_𝐟𝐮𝐤𝐨𝐞✨ 𝐅𝐨𝐥𝐥𝐨𝐰 @𝐀𝐈 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐮𝐩𝐝𝐚𝐭𝐞𝐬! #ai #artificialintelligence #generativeai

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🌟 2024: The Year of Generative AI Deployment! 🌟   If 2022 was the year the world discovered the potential of generative AI (GenAI) and 2023 marked breakthroughs in large-scale training, then 2024 is set to revolutionize how organizations deploy these powerful systems. Companies are now actively testing GenAI in production, unlocking unprecedented benefits. However, this shift isn't without its challenges—managing complexity and ensuring rapid response times are crucial for a seamless, human-like experience.   🚀 Introducing NVIDIA NIM™   NVIDIA has launched NIM™ inference microservices, designed to streamline GenAI deployment and significantly reduce time to market. Learn more about NIMs here https://lnkd.in/dyFkBfbi.   But what if the specific model you need isn't available as a NIM yet? You can still be extremely performant, and we’ll show you how.   📚 Unlocking Potential with Optimized Inferencing   In our latest blog , we explore how to leverage NVIDIA's cutting-edge inferencing technologies—Triton Inference Server and TensorRT-LLM—to enhance large language model (LLM) inferencing in production. We showcase the DictaLM-2.0 model with a custom tokenizer (which has recently led the Hugging Face Open Leaderboard for Hebrew LLMs) and demonstrate how to create optimized engines for both FP16 and quantized INT4 versions, all served through Triton Server. This setup allows for efficient interaction with the LLM, delivering streaming outputs with minimal latency.   🔗 Dive Deeper!   Check out our blog and explore the accompanying Jupyter notebook that details each step of the process. We’d love for you to try it out and share your feedback! Blog - https://lnkd.in/d68QYepb Unofficial Jupyter notebook - https://lnkd.in/digcgqQh   Big shoutout to the incredible team behind this initiative and the guys over at Dicta for the amazing collaboration: Shaltiel Shmidman Amit Bleiweiss Zvi Lapp   #GenerativeAI #MachineLearning #NVIDIA #TritonInferenceServer #TensorRT #LLM

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Happy to announce that I just released a killer, fun-to-read #medium article about #Generative_models, their role, how they generate content, and also, a simple explanation of the #latent_space concept ✔. It contains the summary of well over 3 months of getting my head around such concepts and understanding them to better explain them to the community in 3mins 🦥. Have a read: https://lnkd.in/ejMZGBYY #generativeModels #genAI #AI #latentspace #it #itcommunity #contribute

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#Google has made a groundbreaking leap in #quantum_computing with the unveiling of "#Willow," a revolutionary #quantum_chip that redefines computational capabilities. This breakthrough chip performed a complex computation in under five minutes, a task that would take the world's most advanced supercomputers an unimaginable 10 septillion years to complete. With 105 qubits and cutting-edge error correction techniques, #Willow sets a new standard in #quantum_technology, pushing the boundaries of science and innovation. This achievement positions #Google at the forefront of #quantum_computing, paving the way for transformative applications in artificial intelligence, drug discovery, weather prediction, and beyond. Google's #Willow represents not just a technological milestone, but a glimpse into a future powered by quantum possibilities. https://lnkd.in/drTpUmqv

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Yesterday Sassine Ghazi joined us as the last guest lecturer for my Stanford University cloud computing class. He's CEO of Synopsys Inc, the 14th largest software company in the world. A couple of highlights. 1) Over the past 40 years the industry can now pack 1,000,000x more transistors in the same semiconductor chip area. With this rise in complexity he talked about Re-engineering Engineering and how AI will fundamentally change hardware/chip engineering - soon. 2) His advice to students - it's a learning journey. He himself spends 15% of his personal time - learning. 3) He believes this vast buildout of centralized AI infrastructure will be used for science and engineering applications. Aart de Geus Luis Borgen Marc Casper Janice Durbin Chaffin Bruce Chizen Rob Painter Jeannine Sargent John Schwarz Shankar Krishnamoorthy Joachim Kunkel Ravi Subramanian Ann Minooka ANTONIO VARAS Siva K Yerramilli Pat Gelsinger Antonio Neri Jensen Huang Cristiano R. Amon Lisa Su Andy Jassy Tom Eggemeier Richard Ho Rami Rahim Rene Haas Gamiel Gran Raj Varada Sandeep Mehndiratta

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I’m pleased to share the link to our research paper titled "Breast Cancer Detection and Localizing the Mass Area Using Deep Learning" in Big Data and Cognitive Computing by MDPI [Q2 Journal]! 🎉 Link: https://lnkd.in/guKZFRJ9 #breastcancer detection #deeplearning #convolutionneuralnetwork #machine learning #Research #artificialintelligence

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