I'm curious about audio models like this — I know there's a lot of excitement about them, but I don't get it yet. Do you find in practice it frequently gives you benefits over doing speech recognition and a text model?
RESEARCH
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Training Large Language Models with 1000 H100 GPUs
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GitHub – srush/LLM-Training-Puzzles: What would you do with 1000 H100s… https://
bit.ly/4bCz4yb
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Data Quality Critical for AI Effectiveness and Accuracy
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Skills and Data Quality: AI's effectiveness depends on quality data. Poor data = inaccurate AI outputs. Collaboration between firms and clients is essential for AI-ready datasets. How can we ensure data quality? A challenge for both UK and US!
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Reducing Object Hallucination in Multimodal Language Models
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Multimodal LLMs (MLLMs) excel at many tasks, but object hallucination (generated descriptions of non-existent objects) hinders widespread use. Learn about a method to reduce hallucinations in existing MLLMs and maintain their vision-language capabilities →… pic.twitter.com/jFlLvN9g3D
— Google AI (@GoogleAI) 9 août 2024Multimodal LLMs (MLLMs) excel at many tasks, but object hallucination (generated descriptions of non-existent objects) hinders widespread use. Learn about a method to reduce hallucinations in existing MLLMs and maintain their vision-language capabilities →
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Cerebras MediSwift: 2.5x Faster Biomedical LLM Training
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Cerebras is presenting MediSwift at #ACL 2024: Training unstructured sparse LLMs for BioMedicine 2.5x faster Join us at the Association for Computational Linguistics (ACL 2024) in Bangkok, Thailand, where @vithursant19 will present our accepted paper, "MediSwift: Efficient
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Meta Announces LLM Evaluation Research Grant Program
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LLM Evaluations are an important area of work — today we're announcing a new LLM Evaluation Research Grant to foster further innovation in this area. Recipients will get $200K in funding to support this work. We're accepting proposals until September 6 https://
go.fb.me/eym3xq -
MIT researchers advance AI through novel approach
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Featured authors in article: Nishanth Kumar (
@nishanthkumar23
), Tom Silver (
@tomssilver
), Tomás Lozano-Pérez, and Leslie Pack Kaelbling
Paper: https://
ees.csail.mit.edu
MIT research group: @MITLIS_Lab -
EES Enables Boston Dynamics Spot to Learn Complex Task in Hours
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EES's knack for efficient learning was evident when implemented on Boston Dynamics’ Spot quadruped during research trials at The AI Institute.
— MIT CSAIL (@MIT_CSAIL) 9 août 2024
In one demo, the robot learned how to securely place a ball and ring on a slanted table in ~3 hours. pic.twitter.com/EgQO5EwLAOEES's knack for efficient learning was evident when implemented on Boston Dynamics’ Spot quadruped during research trials at The AI Institute. In one demo, the robot learned how to securely place a ball and ring on a slanted table in ~3 hours.
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Algorithm Trains Robot to Sweep Toys Twice as Fast
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In another, the algorithm guided the machine to improve at sweeping toys into a bin w/i about 2 hours.
— MIT CSAIL (@MIT_CSAIL) 9 août 2024
Both results appear to be an upgrade from previous methods, which would have likely taken >10 hours per task. pic.twitter.com/GAC6hrS8DVIn another, the algorithm guided the machine to improve at sweeping toys into a bin w/i about 2 hours. Both results appear to be an upgrade from previous methods, which would have likely taken >10 hours per task.
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Robot Vision System Learns Task Execution Through Practice
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EES first works w/a vision system that locates & tracks the machine’s surroundings. Then, the algorithm estimates how reliably the robot executes an action & if it should practice more.