Artificial Intelligence, or AI, is easily one of the biggest technology developments in the past few decades. Both exciting and limitless in its possibilities, it is opening the doors to all kinds of creative applications. What started out as a high-tech and seemingly unapproachable technology has now become mainstream, with people using it in one way or another often without even realizing it.

One area that AI has managed to have a real impact on is design. In fact, design has been completely shaken up thanks to this technology and the doors it has opened. But how exactly is AI being used in the design? Let’s peel back the layers and look a little closer.

Use AI for the Monotonous Jobs

There are plenty of jobs that designers have to do that feel monotonous, time-consuming, and frankly not all that creative. This is where AI could really step in and fill a void, freeing up the designers’ time and energy so they can direct it elsewhere.

Some examples of these types of tasks include color correction on various photos, cropping photos, and even resizing images. A fair amount of time can be spent on these types of simple tasks, and AI has the ability to learn what to do and do it for designers.

It Allows for Custom Designs

Then there is the fact that AI can aid in custom designs. So many businesses, clients, and individuals prefer that custom touch to their particular design, as it helps to add a unique feature and makes the finished design more functional.

A really intriguing example is custom stage design, meant for professional stage productions like concerts, plays, and so forth. Because these shows have such specific needs, a custom design from companies like Staging Concepts makes sense, and AI along with other technology makes the design concept that much easier to put together and showcase to the client.

he Opportunity to Co-Create Designs

Here’s a really innovative concept but imagine being able to co-create with AI and/or robot technology? That is quickly becoming the reality, as AI isn’t intended to take the place of a designer in a company rather it is meant to help them.

It can spark creativity, help make the job go smoother and faster, and offer solutions that the designer may not have thought of. Again, the AI is meant to enhance the process not take it over.

Use Voice Commands for Your Designs

Now imagine being able to put together designs via voice commands. It sounds incredibly high-tech, but again it is the reality of where things are today. If you can use voice commands to create designs, then you can expect a much faster design process overall. Think of it AI as your digital assistant.

AI is Transforming the Industry

Sure, it’s a bold statement to say that AI is transforming the design industry, but it’s not an understatement. Artificial technology and innovative technology, in general, are truly shaping the design industry adding more functionality and promise than ever before.

The post HOW AI IS BEING USED IN DESIGN appeared first on Artificial Intelligence.

The world is drooling over Artificial Intelligence. From research institutions to corporate houses, every organization aims to create AI-driven systems to build their enterprise. Machine Learning, or more commonly known as ML, is a sub-array of AI. With ML, you can teach the machines to behave like humans, i.e. develop brains in a machine. The result is automated machines that know-how and what is to be done. One commonly used place for AI & ML is Maps. Have you noticed that it shows you the route with the least traffic and the best route? That happens through ML along with other technologies.

Another hot thing in the technological sphere is Big Data and its management. Big data is a terminology utilized for data of all types. It incorporates structured, semi-structured, and unstructured data. Be it any type of organization, you will always have a lot of data related to operations, finance, marketing, manufacturing, sales, etc.

How you utilize and manage this data is the work of data scientists. Machines absorb the information that is further utilized and adopted in AI is all related to Big Data. Hence, to dive into AI, you will have to be accustomed to ML and Big data. Data science, ML, big data, and AI are all interlinked and synchronized.

If you are talking about turning a machine like a human, it requires you to feed it in the language that it understands. Yes, we are talking, i.e. programming languages. Some of the commonly practiced languages for ML and Decision science are Python, Java, etc. But Java is a language that one must never forget. If you know Java Outsourcing Company, you can hop on the bandwagon of ML with great ease. How will it happen? Read along to learn more.

Top Expertise to Develop For Machine Learning & Data Science

If you want to excel in any field, you first need to develop the skills. Here’s a list of all the skills required if you’re going to learn ML & data science.

Math: It is all about permutations and combination complemented with your calculation ability to be able to link yourself with machines.

Data Architecture: To be able to reach the core of any technology, you must have a broad idea of the data formats.

Software Structures: There is no ML without software, and a data engineer should be clear with concepts related to software and their working.

Programming & Languages: If you do not know anything about this, there is no ML for you. Programming languages are the essential requirement for one to be able to build a career in ML.

Differencing and Data Mining: If you have no clue about data, you are a zero. To be able to learn ML, data mining, and the ability to infer the information is crucial.

Java: Machine Learning & Data Science’s Future

Java is a technology that proves beneficial in varied arrays of development and ML. One of the critical things in ML & Data Science is algorithms. With Java’s available resources, one can efficiently work in various algorithms and even develop them.

It is a scalable language with many frameworks and libraries. In the current scenario, Java is amongst the most prominent languages in AI and ML. Some of the reasons why Java is an excellent alternative for a future in Data Science, Machine Learning, and finally, Artificial Intelligence are:

Pace of Execution

If you are arguing about the speed of coding and execution, Java takes the lead in it, which means faster ML & DS technologies. Its features of statically typing and compilation are what makes it super in execution. With a lesser run time than any other language, knowing Java means you are good to go in the ML industry.

Coding

Indentation in Java is not a must which makes it easier than Python or R. Also, coding in Java may require more lines, but it is easier than in other languages. If you are well-versed with coding, Java will be beneficial in ML and DS.

Learning Curve

Java has a lot of areas where one must work hard. The learning curve for Java and allied language is quicker and more comfortable than other languages in totality. Suppose you know a language better and efficiently. In that case, it means that you can enter the domain at a more accelerated pace than through any other language whose learning curve is typical of Java.

Salary Packages

Java has been in use for 30+ years. The future salaries of people who know Java are perceived to be higher than through any other language. We are not saying that you might not have a handsome amount in your hand if one knows Python. Instead, we are just focusing that with Java’s legacy in place, the salaries you get in your growth years are expected to be more for people who know Java.

Community

Java will complete three decades of existence and is still one of the most prevalent and popularized languages. It means that numerous people in the enterprise know the language and will provide you with support in requirements. Several people in DS and ML are working through Java. It is an additional benefit that you can avail of if you learn ML and DS with Java.

Varied Libraries

With Java, you have access to various libraries in Java for learning ML. To name a few, there are ADAMS, Mahaut, JavaML, WEKA, Deeplearning4j, etc.

We hope that now you know why one must learn Machine Learning and Data Science in Java. With its scalability, versatility, and balanced demand, you will always have to work with Java.

The post CAN JAVA BE USED FOR MACHINE LEARNING AND DATA SCIENCE? appeared first on Artificial Intelligence.

JetBrains and the Python Software Foundation have released the results of its latest survey to reveal the current state of the language, the ecosystem around it, including insights into who uses Python and for what purposes. 

The Python Developers Survey, conducted jointly by the Python Software Foundation and JetBrains, was inaugurated in 2017 so now we have the results of its fourth iteration. The number of respondents has increased year on year and over 28,000 Python developers and enthusiasts from almost 200 countries/regions took part in the latest, conducted in October 2020.

Back in 2017 the proportion of respondents for whom Python was the main language was 79%, by 2018 it had risen to 84%, see Survey Results From More Python Developers, where it remained in 2019, see Python Developer Survey and in 2020 it had edged up to 85%.

With regard to the other languages used with Python there are few changes from last year. JavaScript, which has been in the lead in every survey, starting with 50%, is still top, but has again shortened its lead:

Obviously the percentages here far exceed one hundred – this is because respondents could choose as many as applied. However, the number that said that they only use Python had increased since the previous surveys – 15% this year compared to 12% last year and 6% before that.

In response to the question about whether Python was being used for work or other reasons there was an increase, from 21% to 26% in the option “For personal, educational or side projects” reduction in the other two – down 4% for “Both work and personal” and 2% “For work” which fell to less than 1 in 5. This is largely explained by the fact that the proportion of students included in the survey rose from 10% to 13% and a further 7% choosing “Work student” for Employment status. The sizable proportion of students influenced the age distribution of respondents  which peaked with 40% in the 21-29 age band and a total of 50% under 30 years, and their experience. Over a third, 34%, claimed less than 1 year of coding experience and 68% fell into the up to and including 5 years of coding experience. Conversely in terms of Python experience, the most popular response was 3-5 years (28%) even though 74% were in the up to and including 5 years of coding experience. 

When respondents were asked “What do you use Python for” and allowed to nominate multiple purposes, the mean number of choices was 3.9% and Data analysis topped the chart with 54% of respondents including this use. Web development camme next, 48% with DevOps and Machine learning tying for 3rd place with 38%.

However, when asked “What do you use Python for most?”, Web development came top with 25% and Data Analysis, still in second place, was well behind in terms of its share at 17%. Machine learning was still in third place at 13% leaving Dev Ops with 10% in fourth place.

The post What is Python Used For? appeared first on Artificial Intelligence.