When it comes to weather events that may affect operations, today's enterprises have great insights into the future -- thanks to satellites and advanced forecasting systems that continue to advance technologically. The same holds true for sales and revenue forecasting, as companies leverage sophisticated predictive analytics to gain a clearer view of their financial future. Now, enterprises are taking their predictive capabilities to new heights, thanks to the power of artificial intelligence applications driven by high performance computing systems. This new breed of predictive applications is a cornerstone to making better business decisions, keeping systems and equipment in top shape, understanding the movement of markets and much more. In many cases, these forward-looking applications are both predictive and prescriptive, meaning they tell you what's likely to happen and recommend steps you can take to address emerging issues and influence outcomes.
From driver-assisted vehicles on our city streets to self-driving vehicles on our factory floors, robotic and autonomous systems are becoming commonplace. You may even have one in your home, vacuuming the floors for you while you stay busy with more meaningful work. The truth is, these hands-off systems are just about everywhere anymore. In a sign of the growing adoption of robotic systems, the market-advisory firm ABI Research predicts that, by 2025, more than 4 million commercial robots will be on the job in over 50,000 warehouses, up from just under 4,000 robotic warehouses in 2018.1 And that's just warehouses -- that's not the "everywhere else" where these worker bees are found.
If you've shopped in the online world, you've encountered recommendation engines. These artificial intelligence (AI) systems, also known as recommendation systems or recommender systems, leverage algorithms that help users find products and services based on their past buying behaviors, known preferences and more. Through their ability to predict interests and desires at a personalized level, recommendation engines help content and product providers drive people to music, video, books, clothes and just about any other product or service they might be interested in. Services like Amazon, Netflix, Spotify and YouTube make heavy use of recommendation engines in an effort to increase sales and improve customer satisfaction. Best Buy has some recommendations tailored to your tastes.
New integration empowers teams working with the world's fastest time series database to deliver time-aware AI and machine learning initiatives at scale and speed. Milton Keynes, UK: DataRobot, an enterprise AI, has partnered with Kx to offer financial institutions and IoT-driven industries a comprehensive, scalable high-performance solution for applying AI to time series data. By integrating DataRobot's Enterprise AI Platform with the Kx database platform kdb --the world's fastest in-memory time series database--the partnership, which was unveiled during the Kx Innovation Day at Aston Martin Red Bull Racing headquarters, allows consumers of market data to quickly generate actionable insights for agile, strategic business decisions. "AI is rapidly reshaping all industries, but none more than financial institutions," said Rob Hegarty, General Manager of Financial Markets and Fintech at DataRobot. "So much of the world's market data is in kdb due to its powerful time series capabilities and performance. The integration with DataRobot--the world leaders in enterprise AI at scale--will accelerate ROI and separate financial markets institutions' performance from their peers."
Becoming a cloud-centric technology company is a given nowadays for companies that consider themselves future-ready. The question is hence, not whether a company is operating in the cloud, but what level of sophistication they have reached in their cloud endeavors. This is because the cloud is being enriched by incorporating other emerging technologies, especially machine learning. There is no doubt that contemporary cloud networks will be more intelligent than ever. And companies must harness the power of the intelligent cloud to realize value.