Application of Artificial intelligence in business

pcbuck April 22, 2021 0 Comments

1. Artificial Intelligence and Deep Learning

AI has exploded across industry lines, thanks to the widespread GPUs that makeparallel processing possible. While AI-geared algorithms are prevailing in topapps and services, many organizations are still learning to adapt machinelearning in a way that enhances company production. Even though manybusinesses are still in the stages of gathering data and testing betatechnologies, it is a common prediction that eventually enterprise leaderswill see intelligent and automated processes as a crucial element of typicalbusiness management.Artificial intelligence has been met with a variety of responses. However,now, with the introduction of deep learning, even those new to AI concepts cansee that it is less about installing robotics to replace human hands than itis about creating assistive tools that accomplish tasks and processinformation at a scale that human effort can not.In 2018, the practical uses of AI in everything from manufacturing tohealthcare and beyond are reaching ever-increasing heights of potential. It’sall about figuring out how to put artificial thinking into practice to createhelpful systems, especially regarding cybersecurity and intelligent Things.

Machine Learning will Shape AI

In 2019, Machine Learning and Artificial Intelligence will be implanted in thebusiness platform creating and empowering savvy business operations. In theArtificial Intelligence space, China is going to leave the US behind, risingas an innovator in AI advancements and applications. Advances in MachineLearning innovation and algorithm training will result in new and furtherdeveloped AI. Autonomous vehicles and robotics technology are the two venturesthat will see the most rapid improvements during 2019.

Machine Learning

Machine learning is the art of study of algorithms that learn from examplesand experiences.Machine learning is based on the idea that there exist some patterns in thedata that were identified and used for future predictions.The difference from hardcoding rules is that the machine learns on its own tofind such rules.

AI vs. Machine Learning

Most of our smartphone, daily device or even the internet uses Artificialintelligence. Very often, AI and machine learning are used interchangeably bybig companies that want to announce their latest innovation. However, Machinelearning and AI are different in some ways.AI- artificial intelligence- is the science of training machines to performhuman tasks. The term was invented in the 1950s when scientists beganexploring how computers could solve problems on their own.Artificial Intelligence vs Machine LearningArtificial Intelligence is a computer that is given human-like properties.Take our brain; it works effortlessly and seamlessly to calculate the worldaround us. Artificial Intelligence is the concept that a computer can do thesame. It can be said that AI is the large science that mimics human aptitudes.Machine learning is a distinct subset of AI that trains a machine how tolearn. Machine learning models look for patterns in data and try to conclude.In a nutshell, the machine does not need to be explicitly programmed bypeople. The programmers give some examples, and the computer is going to learnwhat to do from those samples.

Artificial Intelligence Applications: Marketing

Marketing is a way to sugar coat your products to attract more customers. We,humans, are pretty good at sugar coating, but what if an algorithm or a bot isthere solely for the purpose of marketing a brand or a company? It would do apretty awesome job!In the early 2000s, if we searched an online store to find a product withoutknowing it’s exact name, it would become a nightmare to find the product. Butnow when we search for an item on any e-commerce store, we get all possibleresults related to the item. It’s like these search engines are reading ourminds! In a matter of seconds, we get a list of all relevant items. An exampleof this is finding the right movies on Netflix.Artificial Intelligence Applications – AI in MarketingOne reason why we’re all obsessed with Netflix and chill is because, Netflixprovides highly accurate predictive technology based on customer’s reactionsto films. It examines millions of records to suggest shows and films that youmight like based on your previous actions and choices of films. As the dataset grows, this technology is getting smarter and smarter every day.With the growing advancement in AI, in the near future, it may be possible forconsumers on the web to buy products by snapping a photo of it. Companies likeCamFind and their competitors are experimenting this already.

Artificial Intelligence Applications: Social Media

Ever since social media has become our identity, we’ve been generating animmeasurable amount of data through chats, tweets, posts and so on. Andwherever there is an abundance of data, AI and Machine Learning are alwayspresent.In social media platforms like Facebook, AI is used for face verificationwherein machine learning and deep learning concepts are used to detect facialfeatures and tag your friends. Deep Learning is used to extract every minutedetail from an image by using a bunch of deep neural networks. On the otherhand, Machine learning algorithms are used to design your feed based on yourinterests.Another such example is Twitter’s AI, which is being used to identify hatespeech and terroristic language in tweets. It makes use of Machine Learning,Deep Learning, and Natural language processing to filter out offensivecontent. The company discovered and banned 300,000 terrorist-linked accounts,95% of which were found by non-human, artificially intelligent machines.

Artificial Intelligence in Business

There are many types of AI technology, such as machine learning, deeplearning, natural language processing, and cognitive computing, AI can be usedfor image and speech recognition, predictive analytics, AI is not used bybusinesses only, but also the government, education, science and otherresearchers, and others.Artificial intelligence (AI) in business becomes a commonly-used competitivetool, It is used in better chatbots for customer service, data analytics,making predictive recommendations, watching your company’s activities, AI canhelp businesses predict a wide array of activities, With ArtificialIntelligence, you can do three main things for any business, You can optimizebusiness processes, You can minimize costs and you can maximize revenues.Deep learning & artificial intelligence in their many forms are seen bybusiness leaders as an essential tool, Your company should join leadingemerging technologies like Machine Learning, cloud computing & Big Data,Vendors have added AI capabilities to their offerings, such as Amazon, Appleand Google to IBM, Intel, and SalesForce, so, you’ll decide whether you areplanning to do this with hardware you own/buy, or cloud resources (or both).Artificial intelligence in businessArtificial intelligence is beginning to replace many of the workplace rolesthat men dominate, AI will optimize the flows in an E-Commerce warehouse, Moreadvanced AI will minimize the costs in energy consumption of a data center,and AI will maximize the revenue of an Online Retail Business.Businesses can use Artificial intelligence as a tool to improve customerservice and processes, not just to imitate humans, Businesses learn how toleverage AI to optimize their Business, maximize profitability and efficiency,Artificial intelligence is affecting many industries, AI can be used tostreamline their professional routines through practices like automated dataentry and reporting.AI can be used in collaboration solutions, security, services & networkinfrastructure, AI platform can be used to build conversational interfaces topower the next generation of chat and voice assistants, AI can be used in ITservices and security, as well as hyper-converged infrastructure to balancethe workloads of computing systems.AI can be used to assist with cybersecurity defense, The AI system constantlyanalyzes network packets and maps out what is normal traffic, It is aware ofover 102,000 patterns on the network, The AI wins over traditional firewallrules or AV data in that it works automatically without prior signatureknowledge to find anomalies.

Application of Artificial intelligence in business

There are many applications of AI in business management such as spam filters,smart email categorisation, voice to text features, smart personal assistants,such as Siri, Cortana & Google Now, automated responders and online customersupport, process automation, sales and business forecasting, securitysurveillance, smart devices that adjust according to behaviour, automatedinsights, especially for data-driven industries (eg financial services ore-commerce).There are many applications of artificial intelligence in the consumer &business spaces, from Apple’s Siri to Google’s DeepMind, Siri uses naturallanguage processing (NLP) to interpret voice commands and respond accordingly,Google’s DeepMind uses deep learning, It can make connections and reachmeanings without relying on predefined behavioral algorithms, instead learningfrom experience and using raw data as its inputs, by applying findings fromDeepMind, Google can improve the efficiency of its own power centers, reducingthe energy used for cooling by 40%.

Artificial intelligence in marketing

Examples of AI in marketing include: recommendations and content curation,personalisation of news feeds, pattern and image recognition, languagerecognition – to digest unstructured data from customers and sales prospects,ad targeting and optimised, real-time bidding, data analysis and customersegmentation, social semantics and sentiment analysis, automated web design,and predictive customer service.Applications of Artificial intelligence & Machine Learning in business Artificial intelligence (AI) definition, advantages, disadvantages, features &applicationsArtificial intelligence (AI) in writing articles, Robot writing softwareadvantages & disadvantagesTop Artificial Intelligence Salaries in India in August 2020

Machine Learning Engineer

Machine Learning Engineers are the one who responsible for creating machinelearning models and retraining systems. Their ultimate goal is to shape andbuild efficient self-learning applications. A machine learning engineertypically requires to have proven experience as a Machine Learning Engineer orsimilar role; understanding of data structures, data modeling and softwarearchitecture; knowledge of math, probability, statistics and algorithms, alongwith programming languages like Python, Java and R. He/she also must befamiliar with machine learning frameworks such as Keras or PyTorch andlibraries like scikit-learn. The national average salary of a Machine LearningEngineer in India is INR 7,61,552.Average salary: INR 7,61,552Salary range (per year): INR 3,44,000 – INR 1,567,000

Artificial Intelligence Software Engineer

The roles of Artificial Intelligence Software Engineers span the entire AIstack. They will need to demonstrate software skills and broaden theirexpertise by using or creating new tools, techniques, and processes. They willrequire to set up and manage AI development and production infrastructure;assist AI product managers and business stakeholders to understand thepotential and limitations of AI when planning new products; build data ingestand data transformation infrastructure, and identify transfer learningopportunities and new training datasets, and more. AI Software Engineers musthave demonstrated proficiency in multiple programming languages with a strongfoundation in a statistical platform such as Python, R, SAS, or MatLab. Theaverage salary of an Artificial Intelligent Software Engineer is INR 360,319.Average salary: INR 360,319Salary range (per year): INR 343,000 – INR 825,000

Difference between AI and Machine Learning

These two terms are correlated to each other and use interchangeably. For thisreason, it creates lots of confusion in many of us brain.But, they are not the same term. Let’s understand with an example to clear ourwrong perception.If AI is – tree then ML is – one of the main Branch of treeAs we know, Artificial Intelligence is ‘Smart’ then who makes it smart? Offcourse the ‘Data’ and who feeds that data to AI? Yes, you are absolutely rightMachine Learning provide the data to AI.Machine Learning is a subset of Artificial Intelligence. We can say that thebackbone of AI is Machine Learning.Without Machine Learning machine can’t able to perform any task on its own.Therefore you have to get some knowledge of ML if you opt for ArtificialIntelligence as a career option.If you want to learn about Machine Learning and want to know various ML careerpaths check out this article; Machine Learning Career Path [Things You ShouldKnow]To become successful in the Artificial Intelligence career path you must havea clear understanding of how machine learns from scratch.Without ML AI is completely zero i.e. without ML there is a point of AI

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