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Identification of Hazardous Areas for Priority Landmine Clearance: AI for Humanitarian Mine Action

ML @ CMU

In close collaboration with the UN and local NGOs, we co-develop an interpretable predictive tool for landmine contamination to identify hazardous clusters under geographic and budget constraints, experimentally reducing false alarms and clearance time by half. The major components of RELand are illustrated in Fig.

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Hammerspace Unveils the Fastest File System in the World for Training Enterprise AI Models at Scale

insideBIGDATA

Hammerspace, the company orchestrating the Next Data Cycle, unveiled the high-performance NAS architecture needed to address the requirements of broad-based enterprise AI, machine learning and deep learning (AI/ML/DL) initiatives and the widespread rise of GPU computing both on-premises and in the cloud.

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PEFT fine tuning of Llama 3 on SageMaker HyperPod with AWS Trainium

AWS Machine Learning Blog

To reduce costs while continuing to use the power of AI , many companies have shifted to fine tuning LLMs on their domain-specific data using Parameter-Efficient Fine Tuning (PEFT). Manually managing such complexity can often be counter-productive and take away valuable resources from your businesses AI development.

AWS 106
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How Neurosymbolic AI merges logical reasoning with LLMs

Dataconomy

AI is good at pattern recognition but struggles with reasoning. What if we could combine the best of both worlds the raw processing power of Large Language Models (LLMs) and the structured, rule-based thinking of symbolic AI? Can AI get it right? Meanwhile, human cognition is deeply rooted in logic and coherence. The problem?

AI 121
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Classics Never Fade Away: Decipher Gaussian Mixture Model and Its Variants!

Towards AI

Author(s): Kaitai Dong Originally published on Towards AI. Figure 1: Gaussian mixture model illustration [Image by AI] Introduction In a time where deep learning (DL) and transformers steal the spotlight, its easy to forget about classic algorithms like K-means, DBSCAN, and GMM. Remember this.

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Was ist eine Vektor-Datenbank? Und warum spielt sie für AI eine so große Rolle?

Data Science Blog

Vektor-Datenbanken sind ein weiterer Typ von Datenbank, die unter Einsatz von AI (Deep Learning, n-grams, …) Wissen in Vektoren übersetzen und damit vergleichbarer und wieder auffindbarer machen. der k-Nächste-Nachbarn -Prädiktionsalgorithmus (Regression/Klassifikation) oder K-Means-Clustering. von OpenAI genutzt.

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FPGA vs. GPU: Which is better for deep learning?

IBM Journey to AI blog

Underpinning most artificial intelligence (AI) deep learning is a subset of machine learning that uses multi-layered neural networks to simulate the complex decision-making power of the human brain. Deep learning requires a tremendous amount of computing power.