Question

NO COPIED ANSWER PLEASE, I WILL UPVOTE YOURS!!

YOUR TOPIC IS Artificial Intelligence, WRITE A RESEARCH PAPER

following SLOs: The student will analyze the impact of specific practices, programs, and benchmarks (qualitative / quantitative) used by organizations to support valuing diversity. The student will analyze the impact of tools, methods, and significant barriers, for effective Internal organizational communication. The student will explore or analyze the impact of Change Management on profitability. The student will analyze the impact of key HR drivers for organizational innovation and sustainability -

Answer 1

Artificial Intelligence is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence.

AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data. The following major subfields:

• Machine learning automates analytical model building. It uses methods from neural networks, statistics, operations research and physics to find hidden insights in data without explicitly being programmed for where to look or what to conclude.
• A neural network is a type of machine learning that is made up of interconnected units (like neurons) that processes information by responding to external inputs, relaying information between each unit. The process requires multiple passes at the data to find connections and derive meaning from undefined data.
• Deep learning uses huge neural networks with many layers of processing units, taking advantage of advances in computing power and improved training techniques to learn complex patterns in large amounts of data. Common applications include image and speech recognition.
• Cognitive computing is a subfield of AI that strives for a natural, human-like interaction with machines. Using AI and cognitive computing, the ultimate goal is for a machine to simulate human processes through the ability to interpret images and speech – and then speak coherently in response.  
• Computer vision relies on pattern recognition and deep learning to recognize what’s in a picture or video. When machines can process, analyze and understand images, they can capture images or videos in real time and interpret their surroundings.
• Natural language processing (NLP) is the ability of computers to analyze, understand and generate human language, including speech.

Additionally, several technologies enable and support AI:

• Graphical processing units are key to AI because they provide the heavy compute power that’s required for iterative processing. Training neural networks requires big data plus compute power.
• The Internet of Things generates massive amounts of data from connected devices, most of it unanalyzed. Automating models with AI will allow us to use more of it.
• Advanced algorithms are being developed and combined in new ways to analyze more data faster and at multiple levels.
• APIs, or application programming interfaces, are portable packages of code that make it possible to add AI functionality to existing products and software packages.

Change managers face a problem that's very similar to the challenge invested billions in machine learning and other forms of artificial Intelligence to solve which gives you the predicted probability of failure for the new changes in queue. How various combinations of risk factors impact the overall failure rate.

As such, AI plays a big role today in transforming HR and the workforce; reducing human bias, increasing efficiency in candidate assessment, improving relationships with employees, improving compliance, increasing adoption of metrics, and improving workplace learning are some of the benefits organizations are experiencing today.

AI helping to solve five global problems that machine learning could help us solve.

• Healthcare. One of the biggest benefits of AI is its ability to trawl through massive amounts of data in record time.
• Making driving safer.Despite the crashes involving self-driving cars that have hit the headlines this year, this area of AI could dramatically reduce deaths and injuries on our roads.
• Transforming how we learn.Earlier this year, students at Georgia Tech university in the US were startled to discover that their helpful teaching assistant had in fact been a robot all along.
• Help us be smarter about energy. Artificial intelligence could help us be smarter about our energy consumption. Google and other tech giants have enormous data centres that require a massive amount of energy to run the servers and keep them cool.
• Helping wildlife by tracking animal movements, we can see where they go, and what habitats we need to protect. This study uses computing power to figure out the best places to create wildlife corridors for wolverines and grizzly bears in Montana. Wildlife corridors are continuous areas of protected land that link zones of biological significance that the animals can use to move safely through the wilderness.

In summary, the goal of AI is to provide software that can reason on input and explain on output. AI will provide human-like interactions with software and offer decision support for specific tasks, but it’s not a replacement for humans – and won’t be anytime soon.