Data Analysis: Artificial Intelligence

Data Analysis: Artificial Intelligence

Introduction

 Artificial Intelligence is a collection of technologies that excel at extracting insights and patterns from large sets of data, then making predictions based on that information. That includes your analytics data from places like Google Analytics, automation platforms, content management systems, CRMs, and more.

5 Buisnesses using Artificial Intelligence in 2020

With a large number of organizations showing interest in obtaining analytics and artificial intelligence (AL) products and services, a host of companies have hustled to fill the need. According to Forrester, “53% of global data and analytics decision makers say they have implemented, are in the process of implementing, or are expanding or upgrading their implementation of some form of artificial intelligence.”

1. Alibaba
Alibaba is china’s ecommerce company which sells more than Amazon and eBay combined. Alibaba is the world’s largest e-commerce platform that uses Artificial Intelligence every day to predict what its audience wants to buy but also using AI to automate the product description using natural language generation. Alibaba also have Alibaba City Brain where they are offering there AI services to china’s cities to help create smart cities.

2. Alphabet
Alphabet is a parent company of Google that are focusing a large share of their attention to self-driving cars with Waymo the company’s self-driving technology division. Waymo was created to help reduce the number of crashes which is currently being trailed in California for self-driving taxies. Another AI development from google is Google Duplex with AI voice interface can make phone calls and schedule appointments using natural language processing.

3. Amazon
Amazon is America’s largest e-trailer company that thrives using AI with its well known digital voice assistant, Alexa. Amazon also use AI to ship things to you before you even think about buying it using what they call anticipatory shipping. With Amazons level of confidence, they are able to predict what a person is going to buy from data about a person’s buying habits with predictive analytics. The e-retailer also offers Amazon go a new convenience store concept where there is no checkout required. The stores use AI technology to track what items you pick up and charge for them automatically.

4. Facebook
Facebook is a well known social networking site that has invested a huge amount of money into AI and deep learning technology and have developed a tool called Deep Text which now automatically understands the words you type and the meaning behind them. Also, Deep face which is a utility used to help Facebook recognise faces anywhere on the internet. Facebook’s Deep face is now in fact better then human face recognition capability with creating 3-D images of a persons face from an uploaded photograph and then looking where else it is on Facebook to help make new friend suggestions.

5. Microsoft
Microsoft use AI with smart machines and focus on the machines now being central to everything they do as they strongly believe it to be the future of software. From computer software such as office with spell checker to using AI in machines to detect disseises early on transforming not only human healthcare but also animal healthcare with helping prevent the extinction of endangered animals such as the snow leopard as well as collecting data of their numbers and their where abouts.

 

How can Estio Training help with your Data Analytics

To learn more about how Estio can support your business with developing Cyber Security skills, please take a look at our Data Analyst apprenticeship. To read more industry insights please take a closer look at our articles relating to the Data Analyst industry

How to Prepare Data for Machine Leaarning and A.I

Artificial Intelligence is only as powerful as the quality of the data collection, so it’s important to prepare data for Machine learning correctly to ensure no data bias in the prediction models.

Artificial Intelligence reveals unexpected insights and good data collection is driven by knowing we’re all subject to bias. So instead of only feeding a subset of your data to a machine learning model, dump it all in. Even the stuff you think is irrelevant. If it’s irrelevant, the algorithm will ignore it.

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