How Anaconda’s data science platform will help IBM speed up enterprise machine learning adoption
IBM announced that it will offer open data science platform Anaconda on IBM Cognitive Systems. Here’s how it could help your business.
On Monday, IBM announced that it has partnered with Continuum Analytics to offer open data science platform Anaconda on IBM Cognitive Systems. Anaconda, which is powered by Python, will also integrate with IBM’s PowerAI software for machine learning and deep learning, making it easier and faster for businesses to analyze and gain insights from data-intensive cognitive workloads.
“Anaconda is an important capability for developers building cognitive solutions, and now it’s available on IBM’s high performance deep learning platform,” said Bob Picciano, senior vice president of Cognitive Systems, in a press release. “Anaconda on IBM Cognitive Systems empowers developers and data scientists to build and deploy deep learning applications that are ready to scale.”
Software Engineering Has Become Way More than Coding
Software engineering firm Cambridge Consultants notes that among their hundreds of engineers, most are involved in design. Few actually do coding.
In spite of common misperceptions, software engineers are not strapped to workstations slaving over code. Code may have been a central facet of software activity in past years, but that is changing as companies incorporate more software into their products to improve and differentiate them. Software engineers are moving from coding to design and from design to management.
‘The engine of change’: SAS Institute says it wants to bring its analytics everywhere
At the company’s annual user conference in Orlando, Dr. Jim Goodnight, CEO of analytics giant SAS Institute, told the over 5,600 users in attendance and more than 30,000 joining via live stream that SAS is on a mission to bring analytics everywhere.
“And if analytics is the engine of change, data is the fuel,” he said. “The opportunity is enormous.”
The company’s growth illustrates that. When Goodnight co-founded the SAS Institute in 1976, analytics was a niche technology. That first year the company made US$138,000. But along with the explosion of data came the need to do something with it, and analytics finally took off. In 2016, SAS made US$3.2 billion, had over 83,000 customers and over 14,000 employees (almost 350 in Canada).