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Precision Clustering Made Simple: kscorer’s Guide to Auto-Selecting Optimal K-means Clusters
kscorer is a package that helps with clustering and data analysis through advanced scoring and parallelization. It offers techniques such as dimensionality reduction, cosine similarity, multi-metric assessment, and data sampling to determine the optimal number of clusters. The package also provides evaluation metrics like Silhouette Coefficient, Calinski-Harabasz Index, Davies-Bouldin Index, Dunn Index, and Bayesian Information…
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Meet DISC-FinLLM: A Chinese Financial Large Language Model (LLM) Based On Multiple Experts Fine-Tuning
The introduction of Large Language Models (LLMs) has been a significant advancement in Artificial Intelligence. These models face unique challenges in the finance industry but have seen progress in financial text summarization, stock price predictions, financial report production, news sentiment analysis, and financial event extraction. However, in the Chinese financial market, LLMs lack an in-depth…
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DAI#12 – AI gets into snacks, and Grok tries to be funny
This week’s AI news roundup includes various interesting developments. Pepsico has used AI to silence the crunch of Doritos for gamers. Steak-umm gaslit vegans with fake videos. AI-generated fake nudes caused issues in a New Jersey school. Meta now requires labeling of AI-generated ads due to the ease with which humans are tricked. There is…
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Microsoft Researchers Unveil ‘EmotionPrompt’: Enhancing AI Emotional Intelligence Across Multiple Language Models
New research by CAS, Microsoft, William & Mary, Beijing Normal University, and HKUST explores the relationship between Emotional Intelligence (EQ) and large language models (LLMs). The study investigates whether LLMs can interpret emotional cues and how emotional stimuli can improve their performance. The researchers developed EmotionPrompt, a method for investigating LLMs’ emotional intelligence, and found…
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Intel Researchers Propose a New Artificial Intelligence Approach to Deploy LLMs on CPUs More Efficiently
Large Language Models (LLMs) have gained popularity for their text generation and language understanding capabilities. However, their adoption is challenging due to the large memory requirements. Intel researchers propose using quantization methods to reduce computational power on CPUs. Their approach includes INT-4 weight-only quantization and a specialized LLM runtime for efficient inference. Experimental results show…
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Towards Generative AI for Model Architecture
“Intelligent Model Architecture Design (MAD)” explores the idea of using generative AI to guide researchers in designing more effective and efficient deep learning model architectures. By leveraging techniques like Neural Architecture Search (NAS) and graph-based approaches, MAD aims to accelerate the discovery of new breakthroughs in model architecture design. The potential implications of self-improvement in…
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Comprehensive Guide: Supporting Customers on Social Media
Summary: Supporting customers on social media has become crucial for businesses. Social media platforms provide a convenient and direct way for customers to seek help and voice concerns. It allows for real-time problem-solving and provides opportunities to showcase expertise and personalize interactions. Businesses must identify their target audience, set up a dedicated support team, and…
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Steady the Course: Navigating the Evaluation of LLM-based Applications
LLM-based applications, powered by Large Language Models (LLMs), are becoming increasingly popular. However, as these applications transition from prototypes to mature versions, it’s important to have a robust evaluation framework in place. This framework will ensure optimal performance and consistent results. Evaluating LLM-based applications involves collecting data, building a test set, and measuring performance using…
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Humane, an OpenAI and Apple collaboration, drop the “AI Pin”
Humane, a startup led by former Apple innovators, has unveiled the AI Pin, a wearable projector priced at $699. The device functions as a personal assistant and comes with features like ultrawide camera capabilities, text/email communication, and AI responses. It was developed in collaboration with OpenAI and Microsoft. The AI Pin will start shipping in…
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Meta & GeorgiaTech Researchers Release a New Dataset and Associated AI Models to Help Accelerate Research on Direct Air Capture to Combat Climate Change
The OpenDAC project, a collaboration between Meta and Georgia Tech, aims to reduce the cost of Direct Air Capture (DAC) by identifying novel sorbents that efficiently remove CO2 from the air. They have created the ODAC23 dataset, the largest collection of Metal-Organic Framework (MOF) adsorption calculations, and released it to the research community to facilitate…