Remove price quant-network
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Portfolio optimization through multidimensional action optimization using Amazon SageMaker RL

AWS Machine Learning Blog

The market price of each asset is assumed to vary across time. The prices are sampled randomly but modeled to show distinct behavior with different levels of volatility. The price ranges for the three asset classes are shown in the following figure. The agent uses the available cash balance to finance any asset purchases.

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Professional Opportunities for Data Science Students & Early Grads: Information Sessions with CVS…

NYU Center for Data Science

The presentation focused on the function of Markets Quantitative Analysis (MOA) at Citi, which designs models and analytics to assist clients in pricing, hedging, and structuring securities. In the session, the presenters particularly discussed the role of a junior quant.

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Beyond ‘Data-Driven’: How Energy-Efficient Computing for AI Is Propelling Innovation and Savings Across Industries

NVIDIA

Telecommunications providers are building more energy-efficient networks. Telcos Scale Network Capacity To connect their subscribers, telecommunications companies send data across sprawling networks of cell towers, fiber-optic cables and wireless signals. Biomedical researchers are bringing novel drugs to market faster.

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Reducing the cost of LLMs with quantization and efficient fine-tuning: how can businesses benefit from Generative AI with limited hardware?

deepsense.ai

LLMs are machine learning models based on deep neural networks, capable of generating text by autoregressively predicting the next word (or the next token , to be more precise). It is worth mentioning one more data type, designed specifically with deep neural networks in mind – bfloat16 (brain floating point).