Intel and Mila collaborated on FAENet, a new data-centric model paradigm that improves both modeling and compute efficiency across different types of materials modeling datasets.
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Neural networks news
Intel NN News
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Intel and Mila collaborated on FAENet, a new data-centric model paradigm that improves both modeling and compute efficiency across different types of materials modeling datasets.
Intel Innovation 2023 at the San Jose Convention Center is a global tech gathering focusing on AI, future-proof platforms, and startups, including six promising ones from the Intel Liftoff for Startups program. It’s a must-attend event for tech enthusiasts and industry leaders.
Terrain Analytics, a finalist in Intel Liftoff’s AI startup Hackathon, offers HR leaders valuable insights into talent management. Their platform enhances hiring precision and cost-effectiveness for businesses.
Krittika Kanjilal proposed solution for single-cell RNA analysis using Intel® AI Analytics Toolkit
Intel® Liftoff members showcase applications powered by the largest LLMs yet fine-tuned on Intel GPUs running on Intel’s new Developer Cloud.
Intel and Mila collaborate on MatSci-NLP, the first broad benchmark for assessing the capabilities of language models on understanding materials science language and performing useful tasks for materials scientists.
Intel Labs and collaborators from the University of Pennsylvania, Carnegie Mellon University, and IS4S have been selected by DARPA to perform in the H6 program to develop a GPS-independent tactical-grade clock with microsecond timing precision.
Intel® Liftoff startup SiteMana uses advanced machine learning to engage with anonymous traffic, respecting privacy while identifying high-intent visitors. With a focus on personalization, SiteMana helps clients enhance conversion rates, turning anonymous visitors into loyal customers, in line with Intel Liftoff’s innovative approach.
Learn what new optimizations and features have been added to your AI software tools and frameworks.
TensorFlow* developers can benefit from Intel® Advanced Matrix Extension (AMX) with TensorFlow 2.12