At the strategy conference of Baidu cloud computing on Wednesday, Baidu launched three intelligent cloud platforms. They will integrate with pre-existing cloud services for its open cloud platforms to help enterprises increase working efficiency. Baidu founder and CEO Robin Li said that Baidu has been a de facto search engine company from the very beginning, but that the company was bound to move into cloud technology, as efficient web searching is made possible via the cloud. Li said that Baidu used to consider cloud computing as too simple a technology and would rather focus on building its web search engine, but then some recent changes happened: On the one hand, the days are gone when economic development is accelerated by a cheap labor force, and companies today must survive using technological innovations and higher efficiency. On the other hand, cloud technology has been making breakthroughs, and it is no longer merely about storage and computing.
Apple is looking to broaden Siri's footprint and usefulness with help from third party app developers and a software development kit. The big question is whether the move will be able to thwart rivals such as Google Assistant and Amazon's Alexa. From connected light bulbs, to plant sensors, to smart locks, and beyond, smart home tech is growing and evolving rapidly. Here you'll find the latest product reviews, news, and how-tos to help you connect your surroundings to the internet in the smartest way possible. The Information is reporting that Apple is opening up Siri to third-party applications.
The concept of machine learning has been around for decades, primarily in academia. Along the way it has taken various forms and adopted various terminologies, including pattern recognition, artificial intelligence, knowledge management, computational statistics, etc. Regardless of terminology, machine learning enables computers to learn on their own without being explicitly programmed for specific tasks. Through the use of algorithms, computers are able to read sample input data, build models and make predictions and decisions based on new data. This concept is particularly powerful when the set of input data is highly variable and static programming instructions cannot handle such scenarios. In recent years, the proliferation of digital information through social media, the Internet of Things (IoT) and e-commerce, combined with accessibility to economical compute power, has enabled machine learning to move into the mainstream.
Microsoft has infused Office 365 with machine learning. Tableau is putting data visualization control back in IT hands. GE is supplying an IoT developer kit for its Predix offering. Snowflake Computing has updated its cloud-based data warehouse, and Teradata has acquired Big Data Partnership. This data visualization company's platform has been embraced by business users over the past several years because it was simple enough for them to use and understand without involving the IT department.
Industry experts estimate that data volumes are doubling in size every two years. Managing all of this is a challenge for any enterprise, but it's not just the volume of data as much as the variety of data that presents a problems. With SaaS and on-premises applications, machine data, and mobile apps all proliferating, we are seeing the rise of an increasingly complicated value-chain ecosystem. IT leaders need to incorporate a portfolio-based approach and combine cloud and on-premises deployment models to sustain competitive advantage. Improving the scale and flexibility of data integration across both environments to deliver a hybrid offering is necessary to provide the right data to the right people at the right time.