market cap


Decentralized Machine Learning Market Cap Tops $23874.00 (DML)

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Decentralized Machine Learning (CURRENCY:DML) traded 3.8% higher against the U.S. dollar during the 1-day period ending at 12:00 PM Eastern …


Will AI Be Fashion Forward--or a Fashion Flop?

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The narrative that often accompanies most stories about artificial intelligence these days is how machines will disrupt any number of industries, from healthcare to transportation. After all, technology already drives many of the innovations in these sectors of the economy. The definitively low-tech fashion industry would seem to be one of the last to turn over its creative direction to data scientists and machine learning algorithms. However, big brands, e-commerce giants, and numerous startups are betting that AI can ingest data and spit out Chanel. Maybe it's not surprising, given that fashion is partly about buzz and trends--and there's nothing more buzzy and trendy in the world of tech today than AI.



Improved Forecasting of Cryptocurrency Price using Social Signals

arXiv.org Machine Learning

Social media signals have been successfully used to develop large-scale predictive and anticipatory analytics. For example, forecasting stock market prices and influenza outbreaks. Recently, social data has been explored to forecast price fluctuations of cryptocurrencies, which are a novel disruptive technology with significant political and economic implications. In this paper we leverage and contrast the predictive power of social signals, specifically user behavior and communication patterns, from multiple social platforms GitHub and Reddit to forecast prices for three cyptocurrencies with high developer and community interest - Bitcoin, Ethereum, and Monero. We evaluate the performance of neural network models that rely on long short-term memory units (LSTMs) trained on historical price data and social data against price only LSTMs and baseline autoregressive integrated moving average (ARIMA) models, commonly used to predict stock prices. Our results not only demonstrate that social signals reduce error when forecasting daily coin price, but also show that the language used in comments within the official communities on Reddit (r/Bitcoin, r/Ethereum, and r/Monero) are the best predictors overall. We observe that models are more accurate in forecasting price one day ahead for Bitcoin (4% root mean squared percent error) compared to Ethereum (7%) and Monero (8%).


Artificial Intelligence: Industry Report and Investment Case

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Artificial Intelligence (AI) is the augmentation and imitation of human activity and behavior to increase output or efficiency. Driven in large by technological advancements and an increase in implementation and demand, this burgeoning field has gained a lot of attention in the last few years. However, its underlying sciences have been in development for decades. By the 1950's, a generation of scientists discussed the concept of an artificial brain. In 1956, John McCarthy coined the term AI when he, along with other researchers, claimed in their proposal for the Dartmouth Research Project on AI that "every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it".


Decentralized Machine Learning Hits Market Cap of $229,511.00 (CRYPTO:DML)

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Decentralized Machine Learning (CURRENCY:DML) traded 2.4% lower against the U.S. dollar during the 1-day period ending at 7:00 AM Eastern on February 23rd. One Decentralized Machine Learning token can now be purchased for about $0.0036 or 0.00000094 BTC on cryptocurrency exchanges including DDEX and IDEX. Over the last seven days, Decentralized Machine Learning has traded down 10.6% against the U.S. dollar. Decentralized Machine Learning has a total market cap of $229,511.00 Here's how similar cryptocurrencies have performed over the last 24 hours: Decentralized Machine Learning's launch date was March 9th, 2018.


What might humanity do in 30 years?

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At the start of the 20th Century, the majority of Americans were farmers, today that number is less than 2%.We've created new jobs. Most jobs that exist today didn't exist 100 years ago. In fact, in 1910 service jobs and agriculture together accounted for 70% of the US labor market. Today, service jobs account for almost 80% of jobs with industry making up the remaining 20%.


5 Artificial Intelligence Stocks

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Blockchain isn't the only new wave of technology that's transforming the world we live in: artificial intelligence (AI) is also taking charge as a revolutionary industry in a big, big way.


Time Series Analysis in Python: An Introduction – Towards Data Science

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Time series are one of the most common data types encountered in daily life. Financial prices, weather, home energy usage, and even weight are all examples of data that can be collected at regular intervals. Almost every data scientist will encounter time series in their daily work and learning how to model them is an important skill in the data science toolbox. One powerful yet simple method for analyzing and predicting periodic data is the additive model. The idea is straightforward: represent a time-series as a combination of patterns at different scales such as daily, weekly, seasonally, and yearly, along with an overall trend.


Time Series Analysis in Python: An Introduction – Towards Data Science

#artificialintelligence

Time series are one of the most common data types encountered in daily life. Financial prices, weather, home energy usage, and even weight are all examples of data that can be collected at regular intervals. Almost every data scientist will encounter time series in their daily work and learning how to model them is an important skill in the data science toolbox. One powerful yet simple method for analyzing and predicting periodic data is the additive model. The idea is straightforward: represent a time-series as a combination of patterns at different scales such as daily, weekly, seasonally, and yearly, along with an overall trend.