Sai Rajeswar’s Post

Exciting Discovery: Chameleon - The Future of Open-Source Multimodal LLMs 🎯 The Challenge: 🔹 Multimodal models struggle to integrate text and images seamlessly. 🚀 The Hero: Chameleon Model 🔹 Unified Approach: Combines images and text from the start using early-fusion token-based architecture. 🔹 Architectural Innovations: Features query-key normalization and revised layer norms for stability. 🔹 Comprehensive Training: Trained on 5x more tokens than Llama-2 for robust performance. 🌟 Key Benefits: 🔹 Top Performance: Excels in visual question answering, image captioning, and text-only tasks. 🔹 Mixed-Modal Excellence: Outperforms large models like Gemini-Pro and GPT-4V in human evaluations. 🔹 Seamless Integration: Naturally generates interleaved image-text content. 🌐 The Future: Chameleon sets a new benchmark for open multimodal models, promising exciting advancements in AI. More information here: https://lnkd.in/e9H97wmW #AI #MachineLearning #OpenSource #LLM #Multimodality #AI #Innovation

I am excited to have a talk at Artificial Intelligence/Operations Research (AI/OR) workshop III sponsored by Computing Research Association's Computing Community Consortium (CCC) in collaboration with INFORMS to be held in Washington, DC on March 21-22, 2024. Link: https://lnkd.in/gN6YJHdk Title: Trade-off between Optimality and Explainability in AI Summary: From the Constrained Optimization lens in OR, Counterfactual Explainability (how small and plausible perturbations of the input modify the output) in fact refers to ‘sensitivity analysis’ or ‘post optimality’ practice in OR. Using post optimality, we should focus on those learning coefficients that have a narrow range of optimality and coefficients near the endpoints of the range. However, the key limitation in post optimality is: the optimization (learning) algorithms cannot guarantee the ‘global’ or 'near-global' optimum for the majority of the real-world applications due to a complex loss surface. #operationsresearch #optimization #artificialintelligence #machinelearning #explainableai #explainability #XAI #clustering #sensitivityanalysis #mathematicalmodeling

Announcing the GenAINet Research Library! https://lnkd.in/eQcgDbh6 Whether you're deeply exploring the integration of Generative AI in telecommunications or simply curious about the direction of this technology, our research library offers a wide array of resources, from visionary articles to technical contributions, to enrich your understanding of the ongoing research in this exciting field! Our library is continuously updated, be sure to keep an eye on it for the newest insights and developments! #GenAINet IEEE Communications Society #GenerativeAI

Machine Learning 2.0 ? This recent paper "KAN: Kolmogorov-Arnold Networks" is exactly what researchers have to work on . I won't be talking about its advantages (parameter-efficiency etc...) . We have to emphasis on its limitations , for example , it is not GPU-efficient so it is much slower to train than MLPs . Read the paper : https://lnkd.in/dzPNpzpj I am so excited to see such an architecture in a fusion with Transformers and BOOM much smaller LLMs 😄 . #ai #machinelearning #research #gpu #llm

AI CERTs continues to push the pace and set a high bar in the industry. The ever-growing list of solutions integrates easily with the demands of today and innovations of tomorrow. We are excited about the 3 new solutions for teams – AI + Architect – AI + Healthcare – AI + Quantum. 1. AI+ Architect™ - https://lnkd.in/eCTdfv-j This course empowers you to: Master neural network principles and optimization techniques. Apply AI to domains like NLP and computer vision through hands-on projects. Evaluate and enhance model performance with advanced strategies. Deploy AI models in real-world scenarios and understand the necessary infrastructure. Implement responsible AI practices and explore the latest in generative AI. 2. AI+ Healthcare - https://lnkd.in/eFQQKWN8 Transform healthcare with AI+ Healthcare. This course offers an in-depth look at how AI revolutionizes the medical field: Enhance diagnostics, treatment planning, and patient monitoring. Navigate the challenges of data integrity, privacy, and ethical concerns. Leverage AI for predictive analytics and improved healthcare systems efficiency. Prepare for future advancements in patient care and operational optimization. 3. AI+ Quantum - https://lnkd.in/eJJ4jkiu Dive into the intersection of AI and Quantum Computing with AI+ Quantum. This course provides: A solid foundation in AI and Quantum Computing fundamentals. Insight into Quantum Computing Gates, Circuits, and Algorithms. Exploration of Quantum Machine Learning and Quantum Deep Learning. Knowledge of ethical considerations and responsible implementation. Exposure to current trends, future outlooks, and real-world applications. By adopting a vendor-agnostic perspective, our solutions allow you to explore a variety of AI models, helping your team make the most informed investment for integrating AI into your workforce. Stay ahead of the curve with practical insights, hands-on workshops, and expert guidance.   Engage with us to shape the future of AI together! "Never stop learning because life never stops teaching." - Kirill Korshikov #AITraining #HealthcareAI #QuantumComputing #Innovation #ContinuousLearning #ai #artificialintelligence #architecture #healthcare #quantumcomputing #training #certification #futureofwork #netcomlearning

🚀 𝐌𝐋 𝐏𝐚𝐫𝐚𝐝𝐢𝐠𝐦 𝐒𝐡𝐢𝐟𝐭: 𝐊𝐀𝐍 - 𝐊𝐨𝐥𝐦𝐨𝐠𝐨𝐫𝐨𝐯–𝐀𝐫𝐧𝐨𝐥𝐝 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬! ⛳ MIT's groundbreaking architecture, "𝐊𝐀𝐍 - 𝐓𝐡𝐞 𝐊𝐨𝐥𝐦𝐨𝐠𝐨𝐫𝐨𝐯-𝐀𝐫𝐧𝐨𝐥𝐝 𝐍𝐞𝐭𝐰𝐨𝐫𝐤," promises to redefine neural networks, ushering in a new era of AI innovation. ⛳ Let's revisit 𝐌𝐮𝐥𝐭𝐢-𝐋𝐚𝐲𝐞𝐫 𝐏𝐞𝐫𝐜𝐞𝐩𝐭𝐫𝐨𝐧𝐬 (𝐌𝐋𝐏𝐬), the backbone of AI. MLPs organize computations through layered transformations, processing inputs by multiplying them with weights, adding bias, and applying activation functions to optimize task performance. ⛳ 𝐄𝐧𝐭𝐞𝐫 𝐊𝐀𝐍: a breakthrough in AI architecture. Unlike traditional MLPs, KAN revolutionizes activation functions by using adaptive univariate functions, redefining how inputs are processed and enhancing learning dynamics. ⛳ KAN revolutionizes neural network architecture by 𝐫𝐞𝐥𝐨𝐜𝐚𝐭𝐢𝐧𝐠 𝐚𝐜𝐭𝐢𝐯𝐚𝐭𝐢𝐨𝐧 𝐟𝐮𝐧𝐜𝐭𝐢𝐨𝐧𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐞𝐝𝐠𝐞𝐬 and 𝐢𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐢𝐧𝐠 𝐦𝐨𝐝𝐮𝐥𝐚𝐫 𝐧𝐨𝐧-𝐥𝐢𝐧𝐞𝐚𝐫𝐢𝐭𝐲, promising networks capable of handling dynamic tasks with greater precision and efficiency. This innovative approach signifies a paradigm shift towards fundamentally enhanced AI capabilities. ⛳ 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬:   🌟 Paper: https://lnkd.in/geZKVMer   🌟 Github: https://lnkd.in/gDV4w2eQ   🌟 Documantation: https://lnkd.in/gdKTxBYp Don't miss out on daily updates and insights by joining me on this exciting journey. 🔔 #NeuralNetworks #MLParadigmShift #KAN #AI #AIRevolution #MLP #DeepLearning #AIResearch #SRBlog

Introducing Ansys 2024 R1! Discover how Ansys is introducing an elevated user experience designed to increase digital engineering productivity with #AI.

Introducing Ansys 2024 R1! Discover how Ansys is introducing an elevated user experience designed to increase digital engineering productivity with #AI.

Introducing Ansys 2024 R1! Discover how Ansys is introducing an elevated user experience designed to increase digital engineering productivity with #AI.