How LightGBM improves pathloss prediction

10 Strategies to Reduce LLM Inference Costs Quantization Lower the precision of model weights and activations for efficiency. Pruning Eliminate less critical weights to streamline the model. Knowledge Distillation Train a smaller model to replicate the performance of a larger one. Batching Handle multiple requests simultaneously to improve throughput. Model Compression Utilize techniques like factorization and tensor decomposition to reduce size. Early Exiting Halt computation when a confident answer is reached to save resources. Optimized Hardware Leverage specialized hardware designed for AI workloads. Caching Reuse previously computed results to avoid redundant processing. Prompt Engineering Craft precise, clear instructions to optimize model performance. Distributed Inference Distribute tasks across multiple machines to share the workload. #AI #MachineLearning #LLM #AICostOptimization #InferenceOptimization #DeepLearning #ArtificialIntelligence #TechInnovation #DataScience #GenerativeAI #AIEfficiency #MLModelOptimization #AIInfrastructure #TechTips

🚀 Excited to share a presentation on GrafCompounder! Discover how advanced AI is transforming rubber compound development with multi-criteria analysis, real-time simulation, and smart data integration. See how GrafCompounder works for you to streamline formulation processes, enhances data management, and accelerates decision-making—all without the need for extensive lab trials. Perfect for anyone in rubber processing and material science! Insights that could change your approach to compound development. 💡 #Innovation #AI #RubberProcessing #MaterialScience #GrafCompounder

Discover how MIT's CSAIL is revolutionizing simulations through innovative AI sampling techniques. By enhancing data efficiency and modeling accuracy, these breakthroughs have the potential to significantly speed up complex simulations across various fields, paving the way for more precise engineering and scientific exploration. Read more here: [MIT News](https://lnkd.in/eEQGVCzJ) #ArtificialIntelligence #MachineLearning #Innovation #Simulation #MIT #TechForGood #DataScience

Check out our latest video on YouTube showcasing the revolutionary Zebra Technologies Aurora™ Deep Learning technology for machine vision applications! 🌟 In this video, you'll discover how our advanced deep learning tools are transforming the capabilities of Aurora™ Vision Studio and Library software. Learn about: - Optical character recognition (OCR) - Anomaly and feature detection - Real-world applications across various industries - Innovative tools like ModelFinder3D, Box Finder, and CNNObjectDetect - Comprehensive measurement solutions for quality assurance Whether you're tackling complex visual inspections, capturing accurate parcel dimensions on the go, or ensuring the highest quality in manufacturing, Zebra Aurora™ Deep Learning has you covered. Don't miss out on seeing these cutting-edge tools in action and understanding how they can revolutionize your machine vision applications. 📈 Click the link to watch the full video and unlock the future of vision technology today! 🎥👇 #DeepLearning #MachineVision #Innovation #Technology #AI #Automation #ZebraTechnologies #VisionSolutions #IndustrialAutomation #QualityAssurance https://lnkd.in/ejs8xzXp

Bert Labs adds another US patent to its growing portfolio! 🎉 Exciting times ahead as Bert Labs secures another patent title as SELF-SERVICE ARTIFICIAL INTELLIGENCE PLATFORM LEVERAGING DATA-BASED AND PHYSICS-BASED MODELS FOR PROVIDING REAL-TIME CONTROLSAND RECOMMENDATIONS. This innovative technology, co-created by our brilliant inventor/Founder Rohit Kochar, leverages both data-based and physics-based models to provide real-time controls and recommendations. As the Lead Research Scientist for Physics-Based Modelling at Bert Labs, I am proud to highlight the importance of physics-based models in this breakthrough. When combined with data-based models, physics-based models enhance the accuracy and reliability of predictions and control actions. They offer a deep, fundamental understanding of physical laws and processes, which is critical for industries that demand precision and real-time decision-making. This patent is part of our growing portfolio of 40+ patents filed during the first three quarters of FY 24-25, showcasing our commitment to continuous innovation and pushing the boundaries of what’s possible in AI and industrial automation. By integrating these models, we create hybrid systems that continuously adapt and optimize, empowering industries to make smarter, more informed, and proactive decisions. #AI #BertLabs #PhysicsBasedModeling #DataScience #Innovation #IndustrialAutomation #RealTimeRecommendations #PatentedTechnology

INTELLITECH [intelligent technologies] and its #XTRACTIS “General AI Reasoning for Trusted Decisions” will be present at #EUROSATORY on our partner Eviden booth (5A J126). We will present live demos of XTRACTIS® in different Use Cases dealing with Defense/Cyber/Security issues.   For critical high-risk decisions, new regulations require the use of high-performance AND transparent models explaining complex behaviors. This type of models can be audited by the field experts and certified by the regulator. Since 2003, XTRACTIS has been able to discover and reveal such intelligible models composed of an optimal number of IF…THEN rules (with continuous logics), thanks to its decremental holistic evolving and adaptive fuzzy inductive reasoning, applied to a multidimensional reference dataset. And the accuracy of its models is at least equal to that of the opaque models produced by its main nonlinear challengers (random forest, boosted tree, neural network) https://lnkd.in/ghJiGM8Y . Direct benefit, the human operator can access knowledge that clearly describes complex processes and phenomena which would have remained completely hidden without the use of XTRACTIS: 🔹 Malicious human behaviors or physicochemical behaviors (enemy attacks, cyberattacks, terrorism, criminality, predictive maintenance of turbines, properties of composite materials, identification of drugs / toxic chemical compounds, detection of explosives) 🔹 Sensory perceptive decision-making strategies developed by our unconscious human brain (golden ear in a submarine or a warship, identification of drones or aircrafts, identification of vehicles in satellite images). Thanks to its fuzzy abductive reasoning, XTRACTIS can also help solving complex operational research issues: optimal allocation of military resources in the battlefield, logistics planning, supply chain management, optimal formulations and specifications. The outcome is reliable, rapid, precise, and deterministic automated decisions. Pose your complex decision-making problem and let your army of reasoning robots find the solution for you 24/7/365! And above all, abandon opaque “black box” models if you have to make critical, high-risk decisions! Prof. Dr. @Zyed ZALILA will be present on the EVIDEN booth on Wednesday June 19, 2024. You can still book a meeting with him and EVIDEN’s XTRACTIS expert Stéphane Delaye here http://spr.ly/6041ecip1 📅 June 17-21, 2024 | Stand 5A J126 | Paris #ai #augmentedfuzzysymbolicai #trustworthyai #trustedai #reasoningai #induction #deduction #abduction #exobrain #XTRACTIS #intelligibleai #xai #explainableai #intelligibility #transparency #explainability #decisionmakingsystem #predictiveai #predictivemodeling #Defense #Security #Cyber #Eurosatory

Government can provide better services and become more efficient through thoughtful use of A.I. That's the conclusion of a major report released by Congress this week. And that's what our public sector customers are getting when they hire Advanced Robot Solutions to develop their custom self-service system.

How can we solve #InverseProblems (IPs), especially in science/engineering settings, with limited data and compute for simulations? PIED 🥧 is an #ExperimentalDesign (ED) framework for #PDE-based inverse problems that efficiently optimizes for the best sensor placements. Using #PINNs and other techniques, PIED selects the optimal design parameters for one-shot deployment, allows exploitation of parallel computation, and outperforms existing ED benchmarks in IPs for both finite-dimensional and function-values inverse parameters given limited budget. Visit our poster at #ICML2024 Workshop on AI for Science (26 Jul, https://lnkd.in/gjMstSKx).

When it comes to using AI on hardware, smaller is often better for performance. Check out this session at #MATLABEXPO to learn more about an end-to-end #EdgeComputing workflow by MathWorks and ST to boost productivity and innovation. https://spr.ly/6040UoV3k

Unlock the power of Sequence-to-Sequence (Seq2Seq) and Vision Transformer (ViT) models with this comprehensive guide! Explore the foundations of Seq2Seq for machine translation, including encoder-decoder architectures, attention mechanisms, and practical use cases. Dive into ViT's revolutionary approach for image segmentation, leveraging self-attention and patch embeddings to achieve state-of-the-art results. This document covers key innovations like multi-head attention, positional encoding, and advanced decoding techniques such as beam search. Perfect for AI enthusiasts and professionals, it provides actionable insights into transforming sequential and visual data. Elevate your AI knowledge today! #Seq2Seq #VisionTransformers #DeepLearning #AIInnovation #MachineTranslation"