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Exploring Rocks on Mars using Laser-Induced Breakdown Spectroscopy


Image Credit: Vadim Sadovski/Shutterstock.com
Laser-induced breakdown spectroscopy (LIBS) instruments built into the latest generation of Martian rovers will provide planetary scientists with a wealth of new data on Martian geology – but to learn from it, they will need to overcome a critical challenge with their machine learning models.
Because scientists do not have real Martian rock samples to work with in the lab, there is no training data to calibrate the machine learning models usually used to analyze LIBS spectra. Though scientists have improvised make-shift training sets using Earth rocks, results are still skewed by ‘physical matrix effects’. ....

Andrew Messiosmar , Vadim Sadovski Shutterstock , Shanghai Jiao Tong University , School Of Physics , Matrix Effects , Mars Sample Return , From Machine Learning , Transfer Learning , Laser Induced Breakdown Spectroscopy , Rock Analysis , ஷாங்காய் ஜியாவோ நாக்கு பல்கலைக்கழகம் , பள்ளி ஆஃப் இயற்பியல் , அணி விளைவுகள் , செவ்வாய் கிரகம் மாதிரி திரும்ப , இருந்து இயந்திரம் கற்றல் , பரிமாற்றம் கற்றல் , பாறை பகுப்பாய்வு ,

Blaize Delivers First Open and Code-free AI Software Platform Spanning the Entire Edge AI Application Lifecycle


Industry Articles
Transforms productivity for faster ROI of AI edge deployments
El DORADO HILLS, CA December 14, 2020 Blaize today fully unveiled the Blaize AI Studio offering, the industry’s first open and code-free software platform to span the complete edge AI operational workflow from idea to development, deployment and management. AI Studio dramatically reduces edge AI application deployment complexity, time, and cost by breaking the barriers within existing application development and machine learning operations (MLOps) infrastructure that hinder edge AI deployments. Eliminating the complexities of integrating disparate tools and workflows, along with the introduction of multiple ease-of-use and intelligence features, AI Studio reduces from months to days the time required to go from models to deployed production applications. ....

United Kingdom , Dmitry Zakharchenko , Dinakar Munagala , Tim Ensor , Mlops Devops , Data Center , Capgemini Group , Vp Research Development , Transfer Learning , Early Adopter Customers , ஒன்றுபட்டது கிஂக்டம் , நேரம் உறுதிப்படுத்தல் , தகவல்கள் மையம் , ஸாபிஜெமினி குழு , வ்ப் ஆராய்ச்சி வளர்ச்சி , பரிமாற்றம் கற்றல் ,