Iran has warned global markets to prepare for oil at US$200 per barrel , escalating rhetoric as attacks intensify and shipping through the Strait of Hormuz remains effectively frozen. While oil prices have retreated from recent highs near US$120, Tehran’s message underscores the growing risk of a prolonged energy shock. Key Takeaways Iran warns oil could surge to US$200 per barrel Strait of Hormuz remains blocked, disrupting 20% of global oil flows 14 merchant ships reportedly struck since conflict began IEA expected to propose record 400 million-barrel reserve release Markets currently betting conflict may be contained Oil Market on Edge Iran’s military command said oil prices depend on regional security — warning the world to prepare for US$200 crude if instability persists. The Strait of Hormuz, a narrow chokepoint along Iran’s coast, normally handles: About 20% of global oil shipments A significant share of global LNG trade So far: At least 14 ships have reportedly been struck...
If you think Microsoft's new CEO is making another bold statement without action, think again. Microsoft's new CEO, Satya Nadella is serious about cloud computing and he has a strategy.
A supposedly comprehensive predictive analysis service — and all you have to do is store your data in Azure, the Microsoft cloud.
The service will be known as Microsoft Azure Machine Learning (ML) was announced on Monday but will only be available in June. This is the first time where Microsoft combines their very own software with publicly available open source software, so that it's much more easier for usage than most of the available arcane strategies that are available now.
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| Machine Learning - fixing today's problem yesterday |
The VP for ML at Microsoft proudly said, "This is drag-and-drop software."
This is a big step forward in popularizing what is currently a difficult process in increasingly high demand. It would also further the ambitions of Satya Nadella, Microsoft’s chief executive, of making Azure the center of Microsoft’s future.
Machine learning computers examine historical data through different algorithms and programming languages to make predictions. The process is commonly used in Internet search, fraud detection, product recommendations and digital personal assistants, among other things.
As more data is automatically stored online, there are opportunities to use machine learning for performing maintenance, scheduling hospital services, and anticipating disease outbreaks and crime, among other things. The methods have to become easier and cheaper to be popular, however.
That is the goal of Azure Machine Learning.
Here is a video posted by Microsoft on Youtube:
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