Artificial Intelligence Is a Must, Not a Need

WHAT DOES ARTIFICIAL INTELLIGENCE MEAN?

Artificial Intelligence refers to the vicinity of science and engineering focusing on developing the machines as intelligent as the humans. They are created to be fitted into place on behaviors that human regard as intelligent i.e. simulation of human behaviors which they consider as intelligent via the use of machines.

It is all concerned with developing the intelligent computer programs. The main objective behind the adoption of AI is to enable a machine to discover, analyze and crack the problems in parallel.

It is not essential that the computer programs developed are as intelligent as humans in all aspects. But in some aspects, the machine fitted with artificial intelligence can be even more intelligent than humans.

The future of artificial intelligence will change everything in our lives.

WHY DO WE NEED ARTIFICIAL INTELLIGENCE?

The integration of artificial intelligence into the computer programs, assists to create more efficient and effective systems. The opportunity in the form of AI is challenging and efficient at the same time.

The glaring pitfall to be kept in mind while talking about the efficiencies and the opportunities offered by this hi-tech world is that the amount of data being generated on a daily basis is rapidly increasing and it is becoming impossible to mine and analyze the data fully. The amount of data generation has made it impossible for the humans to deal with i.e. it has exceeded the capabilities of humans that they can extract the valuable information out of it.

The skilled professionals in the field of data science with the expertise and their skill sets try to create correlations between various inputs in order to draw out a specific output. But with the sheer volume of data, it has become relatively impossible to correlate every possible input.

This is where Artificial Intelligence can help. Incorporating AI into the systems lets you purify the raw facts into useful and palatable information.

The driver seat in the field of artificial intelligence is handled by the fresh and innovative codes generally referred to as algorithms.

Let us consider an example to understand how the AI works:

Facebook is a very popular social media platform. Facebook deciphers the user’s likes, the activities etc. and then determine what all content is to be placed on his/her news feed. The longer the time you remain active on Facebook, the more and more data is being generated and stored in the warehouse.

The systems incorporated with AI uses the deep learning to get the incessant feedbacks on its algorithms as the users interact. This way the algorithms generally referred to as coding assist the Facebook to analyze the interactions of the users to determine the content to be mentioned on the news feed.

Not only Facebook, even Twitter uses the concept of AI to position the tweets based on the users’ relevance and interests and also suggest them the tweets as per their interests.

Why Image Masking Is Necessary

In Post-processing, it is nearly impossible for a designer to avoid using the image masking features and methods. Image masking opens up a new window of endless editing effects and a dedicated designer is bent on taking every single opportunity.

Sound knowledge about these options and functions will ensure a satisfying end result. Now to address the question at hand:

Non-Destructive: As opposed to erasing a background using the Eraser Tool, masking technique does not obliterate the image details. They are cleverly hidden below various layers so that they can help us out in case we need to make changes. On the contrary, the Eraser tool permanently deletes these pixels and it is close to impossible to bring those back in case a tweaking is required.

Transitions: The basic or simplest function of image masking technique is to have a “hide and seek” effect in some areas of the photo. This transitioning effect can be created using brushes and gradients for soft masking. This requires delicate strokes and soft brushes. This transparency of pictures can be controlled. The opacity level can be adjusted to suit the photo and its background. This is not the only technique for achieving this effect, but it is the simplest.

Editing Specific Areas: Many times we are faced with projects where we need to edit a small portion of the photo; such as, changing the color of someone’s clothes in a photo and fixing shadow/light issues. You can use masking techniques to highlight the portion and edit it as you wish e.g. color correction, brightness, contrast, exposure, shadows etc.

Removing / Replacing Background of Translucent Objects: Masking is an easy option when it comes to removing backgrounds of translucent objects. Any object with any level of transparency can be isolated from its background by careful masking. Even in cases of semi-transparent clothes’ photos, this technique can be applied.

Single Advantage of Clipping Mask: Clipping mask, when compared to Layer Mask, has the advantage of making different areas visible by simply moving the clipped image. It can be determined by the user which part of the background they want to be visible and which part they don’t by using clipping mask. Other than this one advantage, regular layer masking is more than good enough for most masking work.

Creating Collage Photos: Collage images are fun and it is even more interesting when you play with the masking tools while making a collage. Interesting and cool effects can be made by using a number of pictures and masking them. Soft brushes in varying gradients and hues of gray will definitely make these blending smooth.

Harvest Is Over – Better Get the Ladder

When business is good and customers are eager to buy, it sure is a great time. Business seems bountiful and everlasting. You’re hot. The phone is ringing, orders come through a cornucopia of the internet, customers stand in line… easy pickings… like harvest time in an orchard and all you have to do is just walk over to a tree and pluck another apple… one customer after another… you feel that you are a business genius. Here’s some advice from someone who has been there: better enjoy it while it lasts.

Because, after a while, the orchard is picked over. Sometimes there is a drought. Insects or disease or a frost attacks the crop. Customers now are standing in line somewhere else for the next shiny thing. The market swings in other directions away from you. The easy pickings are long gone. Customers have dwindled. You are no longer a genius, what oh what to do? Wringing your hands doesn’t help.

In the orchard, some starve because they can’t get to the harder-to-reach fruit, even standing on your tippy-toes, sigh, and give up; survivors build ladders to climb higher. In business, some give up and close shop. Those who have the resources and the gumption to survive evolve by changing product, marketing harder and smarter, perhaps even changing their business model. They change their offerings and bring out new, improved colors or sizes or capacities or groupings. They take groups of products or services into and put them into different combinations or bundles with new pricing.

Survivors have a way of going after an increasingly more elusive harvest. They have larger crops in good times when the picking is easy and can sustain themselves when there is a drought or other calamities. Whether the tool of survival is a ladder, a marketing plan, a customer retention plan, customer service training, sowing, fertilizing, weeding, pruning, and harvesting… it all needs to get done year after year.

Increase your reach now, plan your evolution when business is good, before the drought, before customers defect for the latest fashion, before the next shiny thing comes and replaces you in the marketplace, before something else gains favor. Always be aware of events that arise and affect your market and circumstances beyond your control. Keep your eyes and ears tuned to the changes happening around you and your business. Do that and you will survive and prosper in good times and bad.

5 Tips for Typography Best Practices

This was my first year at Typographics 2018. Typographics 2018 is a conference for typography enthusiasts around the world, that’s held at Cooper Union. There were panelists from San Francisco, Berlin, Buenos Aires, and Japan; it really felt like a truly international experience.

I had the chance to sit in on both the conference and TypeLab parts of Typographics. Here are a few highlights from the panels/breakout sessions that I really enjoyed:

1. Emojis = Pictures + Character (Jennifer Daniel, Google Emoji)
Emojis are images that may translate into different meanings across different devices. Jennifer gave an example about how the “dumpling” emoji looks different across different chat platforms -every culture has a dumpling!
I found an interesting tension in this statement -emojis should have a consistent user experience (across platforms), yet still be personalized to their users.

2. Ubiquitous type is can cause user confusion (Mr. Keedy)
Mr. Keedy created Keedy Sans, a popular font in the 90’s. The font was considered “uncool” 10 years later and used everywhere. Keedy sans is used on teenage girl makeup packaging, as well as winebars. This could create a bad user experience for people because of lack of branding. Last year, Mr. Keedy refreshed his font -to create greater customization and allow Keedy fans to layer the font for interesting visual effects.

3. Braille is a form of typography (Ellen Lupton, Cooper Hewitt)
Ellen talked about how blind individuals read Braille in a unique way -holding it across their body. She also demonstrated a blind person’s experience watching music videos by showing the accessibility voiceover.

4. Brand holds content together with design (Gale Bichler, NYTimes)
Gale foused on how the New York Times(NYT) has branded itself as a publication that experiments with many types of fonts. NYT can play around with different types and massive fonts as illustration. If someone picks up a page from the floor, they can usually tell that it’s from the New York Times because of branding.

5. Picking fonts is like eating ice cream. (Veronika Burian and Jose Scaglione, Type Together)
When combining fonts, look at mechanic and organic feels. Veronika and Jose talked about how people like humanist fonts, with a hint of a calligrapher’s hand. Ideally, you should find a balance typefaces share a common language.

The overarching theme is that typography is wide-ranging and crosses various mediums. Visual languages include symbols, braille, and audio caption. The challenge now lies in how to design the best experiences for these new forms of language.

The Future of Data Science

If you have a question in mind regarding the future of data science then you are definitely concerned with whether the techniques and tools such as Python, Hadoop or SAS will become outdated or whether investing in a data science course will be beneficial for your career in the long-run. But there is no need for worry. Businesses have only recently begun to realize the worth of their data and have just begun to make significant investment in these areas. So data science careers will be around for quite some time.

HISTORY OF DATA SCIENCE

The history of data as well as statistics is proof of the fact that the transformation of data into useful insights is something which has been happening for a long, long time.

The high-tech data-driven world has forced companies to develop cheaper and more reliable sources of data storage so as to store lots and lots of business data. The extraction of useful insights from this mass of data requires the skills and knowledge base of statistician and programmers. This combination of statistic skills and programming skills can be seen only in the DATA SCIENTIST. The job of data scientists is not only extracting useful insights but extends to designing new tools and techniques for processing and storage of data.

A SECURE AND LUCRATIVE CAREER AS A DATA SCIENTIST

The individuals with right mix of skills necessary for jobs as data scientists will have a challenging career. The job and salary prospects of DATA SCIENTISTS make it an even more worthwhile educational investment for new entrants and professionals in the near term. Data scientists will have a wonderful career in the future as well. The field of data science (machine learning in particular) is not going to disappear but rather outshine other fields. So the future of data science looks promising.

The market for data is regarded as highly competitive. Standing out from the crowd and having an edge over the competition are the two important traits to keep in mind when pursuing your career in the field of data science.

HOW CAN THIS BE ACHIEVED?

A lot has been discussed about the use and benefits of data. But now the question arises regarding how to accomplish training in this field. Professionals can advance their skills and knowledge base by taking classes in data as it is always said that upgrading one’s skillset (by way of training, education or any other mode) is the key to a successful career and a bright future. It is always beneficial to be in sync with the latest technology and trends.

THE FUTURE OF DATA SCIENCE IS DEFINITELY GOING TO BE BRIGHTER THAN EVER

But remember, getting into this field is not easy. You will need to have an in-depth and thorough knowledge of all the techniques and methodologies utilized in the field of data science.