At the time of Artificial Intelligence taking over the world rapidly, does engineering have any future?

Back then engineering was all about blueprints, sketches, and physical models. But today it is intensively about software tools and computer designs. The demand for artificial intelligence and digital technology has been gaining momentum. Advancements in the AI sector are transforming smart systems and supervised machine learning to a great extent.

Artificial intelligence systems will ease the laborious tasks that engineers do such as finding relevant content, fixing errors, and determining solutions. Smart systems can help finish their job quickly. AI and digital tech can also assist the system engineer in creating sophisticated designs along with incorporating sensor-based design procedures and delivering the designs to intelligent manufacturing facilities.

But AI may not approach the project the way a human designer would. Sometimes this can go off the grid too. Because today’s machines are usually made of expert systems that have software-enabled decision-making. Since the engine of this software is based on if-then rules, it is acquired through experience.

When new knowledge is registered in the library, the software uses if-then rules to expand new facts or ifs and comes out suggesting various solutions or then what occurs.

This process serves as the basis of AI and machine learning. As people are connected with the help of the internet, this opens the doors for smart machines to bring in new services and opportunities.

The largest fraction of smart systems is currently made of expert systems and this will be soon taken over by autonomous robots through technology transformation by 2024. There are critics as well as supporters for this trend. Since the number of robotic appliances continues to increase automatically, the cost of the sensors will decrease this becomes the simple reason for artificial intelligence robots to multiply within no time.

The robotic sensors market is estimated to undergo a CAGR of nearly 8% over the forecast period of (2021-2026). Currently, most of the industries like automotive, transportation, industrial manufacturing, logistics, and defense have started to adopt autonomous robotics and digital technology as their main mode of the production process.

As a result, due to this rapid growth of smart technologies with its roots, interconnected artificial intelligence can lead to uncertainty. Though computers can take intelligently-based action, they are not capable of replicating the cognition processes of the human brain. Algorithms of artificial intelligence tech can only deal with known data and cannot predict and formulate rational decisions during uncertain situations.

New technologies using the most advanced AI and machine learning have been coming up due to their widespread connectivity and inexpensive sensors. These technologies are primitive and still are not capable of mimicking the human brain.

It becomes clear that AI algorithms relate facts to solutions that are dependent on experiential learning without any acknowledgment of physics. AI has evolved from scientific advancement to an engineering tool. Latest innovations in digital tech require engineers from various domains to learn and integrate AI tools into their engineering designs.

Many open-source tools such as Microsoft’s DMLT, Google’s TensorFlow, and Amazon’s DSSTNE possess software libraries that empower machine learning. The DeepVariant open AI software of Google can depict a person’s genome from sequencing data more accurately than other methods are helping engineers to seek help from.

Personal productivity assistants like Amazon’s Alexa, Apple’s Siri, and Windows Cortana use natural language processing to make decisions. IBM Watson has been trained by Oncologists to help them treat and diagnose lung cancer. Tesla is getting closer to self-driving autonomous vehicles. Zebra Medical Systems, an Israeli company is developing tools for radiology having greater than human accuracy. All this is possible with the help of different types of engineers who are responsible for training smart systems.

At this point in time, the role of a human engineer may be that of a director shortly rather than producing and manufacturing the products. Though humans may not be executing the task, they are definitely the ones who are choosing the direction the machine should work. Once the machine knows how to design things, the system of engineering will change but engineers will still be highly skilled and relevant.

The uncertain future of technologies demands resilient and versatile engineers who can design robust technologies using artificial intelligence with different skill sets, including teaching AI systems how to innovate and become part of future human-AI organizations.

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AI in art is giving birth to many artificial intelligence artists

Artificially intelligent systems are gradually taking control of errands recently done by people, and numerous processes including redundant, simple developments have effectively been completely automated. Meanwhile, people keep on being better when it comes to abstract and creative tasks. Over a recent couple of years, we’ve seen the rise of AI in art giving birth to many artificial intelligence artists.

These unpredictable algorithms are making interesting (and in some cases frightful) works of art. They’re producing dazzling visuals, significant poetry, extraordinary music, and surprisingly practical film scripts. However, work by these AI artists are bringing up issues about the idea of artificial intelligence in art and the job of human creativity in future societies.

Creativity appears to be baffling because when we have innovative thoughts it is hard to clarify how we got them and we frequently talk about obscure ideas like “motivation” and “instinct” when we try to explain creativity. The fact that we are not aware of how a creative thought shows itself doesn’t really suggest that a scientific explanation cannot exist. In actuality, we don’t know about how we perform different activities, for example, pattern recognition, language understanding, etc., yet we have better art created by AI ready to duplicate such activities.

In March 2019, an AI artist called AICAN and its maker Ahmed Elgammal took control over a New York exhibition. The exhibition at HG Commentary showed two series of canvas works depicting nerve racking, dream-like faceless pictures.

The gallery was not just credited to a machine, yet rather ascribed to the joint effort of a human and machine. Ahmed Elgammal is the Founder and Head of the Art and Artificial Intelligence Laboratory at Rutgers University. He considers AICAN to not exclusively be an autonomous AI artist, yet in addition a collaborator for artistic endeavors promoting artificial intelligence art.

How did AICAN make these scary faceless portraits? The framework was given 100,000 photographs of Western art from more than five centuries, permitting it to become familiar with the style of art via machine learning. It at that point drew from this historical knowledge and the order to make something new to make a work of art with AI without human mediation.

Recently, Hanson Robotics’ female AI robot named Sophia became the world’s first machine artist to sell her Non-Fungible Token (NFT) digital paintings named ‘Sophia Instantiation’ at an auction on premier marketplace Nifty Gateway. Her AI art pieces, which were bought utilizing Ethereum blockchain exchange, were made in collaboration with the UK-based Italian art specialist Andrea Bonaceto, who sold Beeple’s Everyday at Christie’s for $69 million. NFTs, in the resemblance of the digital money, comprise unique codes and can be stored in records or digi wallets. Artificial intelligence robot Sophia’s auction of NFT AI art pieces denoted the first breakthrough between a human and a robot trading.

Sophia is internationally known for being a worldwide celebrity doing a lot of TV appearances across the world including the Jimmy Fallon Show in the US and the Ivan Urgant show in Russia. Sophia is likewise an Innovation Champion for the United Nations Development Program (UNDP) and the first robot to get citizenship of a country. Recently, her computational works were introduced at the Neurips AI conference in the neural inventiveness workshop, and in the poster session at the AAAS yearly gathering. This will be the first series of AI artworks promoted by Sophia and her maker Dr. David Hanson.

Dr. Hanson says, “We made Sophia herself as a work of art as well as an AI development platform. Her intelligence is a group of algorithms and people working together like a hive. For this show, Sophia made the art totally utilizing neural networks and symbolic AI, responding to her impression of Andrea Bonaceto’s works as well as to information from her “life” experiences, under direction from the Sophia team’s designers and programmers. How she reacted to Andrea’s art just excites me. I’m one pleased dad.”

Sophia digitally made her own picture utilizing artificial intelligence art and did what the roboticist David Hanson portrays as ‘an artistic revolution.’ “The experience of teaming up with Sophia and Hansen on the project at Nifty Gateway has been stunning.  Grown so much as an artist since we began this undertaking”, Bonaceto tweeted. Then, humanoid Sophia plans to “study the most noteworthy bidder’s face” who will buy her work and will add one final emphasis to her AI artwork.

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