{"id":2205,"date":"2019-08-21T08:55:12","date_gmt":"2019-08-21T08:55:12","guid":{"rendered":"https:\/\/www.binah.ai\/?p=2205"},"modified":"2021-07-11T15:59:49","modified_gmt":"2021-07-11T15:59:49","slug":"the-commoditization-of-ai-the-logical-next-step","status":"publish","type":"post","link":"https:\/\/www.binah.ai\/ja\/the-commoditization-of-ai-the-logical-next-step\/","title":{"rendered":"The Commoditization of AI: The Logical Next Step"},"content":{"rendered":"\n

From Details to Disinterest<\/em>:<\/p>\n\n\n\n

Before the dawn of AWS and the official branding of the \u201ccloud,\u201d when you wanted to expand your data storage, you needed to determine which servers, routers, UPS, switches, hard drives, applications, and storage system management solutions you needed to buy. You had to choose a hosting facility and source and test every element within the system.
Now \u2013 log into your cloud console, make a few choices, and then automatically allocate another TB or petabyte of storage \u2013 without needing to know a single fact about the back-end hardware and software.
<\/p>\n\n\n\n

You\u2019ve Seen One Platform\u2026<\/em> <\/p>\n\n\n\n

Gartner\u2019s Magic Quadrant for Data Science platforms lists 16 different options.  First you have to tell them apart. Then, you need to determine which one your team can work best with it. After you\u2019ve spent a few million dollars integrating them into your existing corporate data infrastructure, your data science team can finally get to work.
<\/p>\n\n\n\n

I Can\u2019t Tell Them Apart. Can You?<\/em><\/p>\n\n\n\n

Wikipedia lists almost 275 cloud providers. What are the differences among them? To list everything to figure this out \u2013 if possible \u2013 would involve the spreadsheet from hell. Do you need to fully understand how your electric car\u2019s engine maximizes battery life to ensure that you don\u2019t need to charge it every time you go more than 100 miles\/kilometers?
<\/p>\n\n\n\n

The Bottom Line<\/em>
When making decisions about AI and data science, the mathematical elements are far less important than the measurable results. 
Like with cloud computing, AI is going to become ubiquitous. It ultimately won\u2019t matter what platform you\u2019re going to use.
The highest level of the evolution of AI is simply the application \u2013 the most effective use cases that will deliver the most accurate, stable, and high-performance results \u2013 the results that will most benefit your bottom line.<\/p>\n\n\n\n

You don\u2019t need to care how they got there \u2013 just that they deliver.
<\/p>\n","protected":false},"excerpt":{"rendered":"

From Details to Disi<\/p>\n","protected":false},"author":12,"featured_media":2209,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[45],"tags":[],"class_list":["post-2205","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence"],"acf":[],"yoast_head":"\nThe Commoditization of AI: The Logical Next Step - Binah<\/title>\n<meta name=\"description\" content=\"When making decisions about AI and data science, the mathematical elements are far less important than the measurable results.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.binah.ai\/ja\/the-commoditization-of-ai-the-logical-next-step\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Commoditization of AI: The Logical Next Step - 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