I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing ...
I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing
We all interact with artificial intelligence every day: It builds our Google searches, our Facebook feeds, and predicts the next word we'll type. In this way we're consumers of AI, rather than using it ourselves.
But many of us use Excel. In an attempt to make it easier to work with machine learning on a daily basis, which Microsoft has repeatedly claimed will improve our lives rather than kill jobs, the company is adding a slew of machine learning tools to its Excel spreadsheet software, according to TechCrunch.
Spreadsheet jockeys will be able to import machine learning models to analyze data within Excel, and the program will automatically recognize items such as company names and locations, and pull in additional data.
The models could predict future sales numbers given different scenarios, or stand in for any number of software-as-a-service analytics tools that have become popular in sales and marketing.
This also means Excel will try to understand the connections between your data as you enter it (like whether the words represent companies or people) rather than just determining if they're numbers or text.
"Historically, Excel has always been good at numbers and you can enter in text and use conditional formatting and things like that, Jared Spataro, general manager for Microsoft Office, told TechCrunch. " We are adding the idea that Excel can now recognize data types that are richer than those two.
All of this is undeniably boring, but sets up the easy-to-use and amazingly pervasive Excel to be an even more powerful tool for organizing and analyzing data.