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Computers can now create art! But is it the same as human creations? 

Written by Science Centre Singapore on Digilah (Tech Thought Leadership)

For those of us mere mortals, aka not art inclined, we may think of art as the sole bastion of talented creative masters. These individuals epitomise the very best of human creativity

On the fundamental level, art is really not just limited to the masters, everyone of us can indulge in a spot of artistic creativity.

We’ve been using art as an intrinsic way of expressing ourselves; our emotions, and our knowledge to other people.

If we think of art in this way, it can be seen as a form of communication that is unique to us humans. However, recent events have shown that Artificial Intelligence (A.I.) has begun to intrude into the art scene. 

An example would be the painting, Edmond de Belamy that was sold for $432,500 – nearly 45 times its highest estimate. This begs us to question if A.I. has begun to eat into this realm that once belonged only to humans.

The present

Currently, A.I. hasn’t had too much influence over the art industry. With people still producing paintings and music albums, we can still believe that art is something that’s made by humans.

However, like the example above, we’re already starting to see signs of A.I. creating paintings. ‘Edmond de Belamy’ is an A.I.-generated painting by a Paris-based collective called Obvious.

Hugo Caselles-Dupré, a member of Obvious, said that “We found that portraits provided the best way to illustrate our point, which is that algorithms are able to emulate creativity”.

Just like Edmond de Belamy, A.I. is also taking its baby steps into the music industry. One example of this is a program called ‘OpenAI’. 

As Jon Porter from TheVerge says, “OpenAI’s MuseNet is a new online tool that uses A.I. to generate songs with as many as 10 different instruments”. 

Not only that, but it can create music in as many as 15 different styles, imitating classical composers like Mozart, contemporary artists like Lady Gaga, or genres like bluegrass or even video game music”. Soon enough, there’s likely to be A.I.-generated songs and art forms.

Now, the question here is – 

If artificial intelligence were to be able to emulate creativity, would that be beneficial or disadvantageous to us? 

Would artists still be able to create inspiring artworks? Would musicians still be able to create soothing pieces? 

Or would all these be taken away from us, and be dominated by A.I.?

We’re already over-reliant on technology in many parts of our lives, and that reliance on technology might rub off with the art scene, and lead us into losing the ability to differentiate human-created art and A.I.-created art.

We might also be wholly dependent on technology in the future to be creative. This might sound a bit far stretched, but it is definitely something that could happen.

AI and Machine Learning

With these questions in mind, we have to plan out the risks that we might take by letting A.I. into the art and music industries.

It might be like letting babies into a playground, or it might be like letting a pack of wolves into a herd of sheep. 

As of right now, A.I. definitely isn’t able to create art with the same quality as humans. 

They’re only able to create art from taking the data provided to them and piecing them together, making them seem unique, but in fact they are still replicated from human creativity.

This is because “art” is a complex thing. It’s not simple for A.I to just learn how to make art out of nowhere. Ken Weiner, a blogger on Scientific American, says that

“Even though the Cloudpainter machine (an artificially intelligent painting robot) has evolved over time to become a highly intelligent system capable of making creative decisions of its own accord, the final piece of work could only be described as a collaboration between human and machine”.

What this means is that with our current set of technologies, the artwork of any A.I still involves a human touch. But what about the future?

There is something called ‘machine learning’, and it is an application of artificial intelligence that provides the system with an ability to take in data and learn and improve from its past experiences and uses.

This is extremely important since machine learning could allow A.I. to create distinctive forms of art and music that may not even closely resemble the input data, opening the concepts of originality and creativity to A.I.-generated art and music.

The future

In the future, with the development of machine learning and A.I., the question is: Is this handmade, or is this made by A.I.?

A.I.-generated images already lurk around in our daily lives, and we might not even notice it until we look more closely. 

A.I.-generated faces, where they take 2 different photos and merge them together; or Snapchat filters, where they locate different spots on your face, such as your nose or your eyes, and put a mask on it, are both examples of A.I.-generated images and videos that have become part of our daily lives.

Sooner or later, A.I., along with the help of machine learning, will be able to adapt to our current world and will eventually create everything for us.

Art would be made by taking previous paintings in order to make a new one, while music would be made by taking previous songs of a specific genre and re-produce beats, patterns, and rhythms all on its own.

A.I. might even emulate human creativity and produce never-before-seen pieces of art.

It feels like we are on the verge of an A.I. revolution in the art and music scene. Just like how jobs were changed, for better or worse during the industrial revolution, A.I. may change the way we view and appreciate music. 

New, different art and music styles could be produced, styles of the past like Mozart’s music could be recreated, resurrected, revamped.

The question here is, in what way will A.I. change the art and music world, and how would we, being creatures able to emulate creativity and the people who gave life to these machines in the first place, deal with it?

Illustrations by Toh Bee Suan

Sources cited:

“Why Is Art so Important to Mankind?” Artistartist-strange-work.com/why-is-art-so-important-to-mankind/.

“Is Artificial Intelligence Set to Become Art’s Next Medium?: Christie’s.” The First Piece of AI-Generated Art to Come to Auction | Christie’s, Christies, 12 Dec. 2018, www.christies.com/features/A-collaboration-between-two-artists-one-human-one-a-machine-9332-1.aspx.

Porter, Jon. “OpenAI’s MuseNet Generates AI Music at the Push of a Button.” The Verge, The Verge, 26 Apr. 2019, www.theverge.com/2019/4/26/18517803/openai-musenet-artificial-intelligence-ai-music-generation-lady-gaga-harry-potter-mozart.

Weiner, Ken. “Can AI Create True Art?” Scientific American Blog Network, Scientific American, 12 Nov. 2018, blogs.scientificamerican.com/observations/can-ai-create-true-art/.

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AI Tech

Driving intelligence solution for the automotive industry

Written by : Vivek Gouda  on Digilah (Tech Thought Leadership)

The automotive industry is rapidly adapting to the demands of connected mobility. The rise of autonomous and electric vehicles will create new challenges for manufacturers, who must implement solutions that will help them meet changing consumer needs. These vehicles are expected to require more computing power than traditional cars, which leads us to ask: What does this mean for aftermarket solutions?

What does this mean for aftermarket solutions?

As both traditional and autonomous cars become more automated, and more intelligent, the use of geospatial technology is proliferating.Geospatial intelligence (GEOINT) is the use of data and technology to improve the way we make decisions. It’s a key component of connected mobility, which refers to how vehicles communicate with each other or with infrastructure.

In autonomous vehicles, geospatial intelligence can be used to collect real-time information about road conditions as well as traffic patterns—which can help a vehicle avoid hazards that could otherwise cause an accident or delay. This type of information can also be useful for collecting data on weather conditions, or even hazards like ice on the roads during winter months.

Connected cars are another place where geospatial intelligence is being applied: they collect both driver behavior data and location information via onboard sensors that provide insights into driver quality control and safety measures such as speeding or harsh braking incidents.

But what exactly does that mean for the future of cars?

Geospatial intelligence (GEOINT) is a broad term that refers to information gathered from satellite data and other sources in order to identify people, places, and objects.

Using GEOINT, we can determine the location of a person or object within a specific area. This allows us to collect data on the location of vehicles on roads at any given time—information which is then used by car manufacturers and other companies to improve their products and services. For example, knowing where cars are parked may help you find your way into an underground parking lot before you run out of battery power in your electric vehicle; it can also be used by municipalities when designing new roads so they can plan how many lanes will be needed for traffic flow.

And how does it work?

Driving intelligence solutions allow manufacturers and OEMs to identify and engage with their customers based on their driving behavior. The solution is designed to be used by the driver, who can also access it from an app on their phone or tablet. Using this technology, car manufacturers can:

  • Monitor vehicle location & speed
  • Identify where drivers spend most of their time in the vehicle
  • Collect data on when they start and stop using the car, how long they use it for and where they go during those times

What does this mean for traditional vehicles?

Geospatial intelligence is a software solution that integrates data from multiple sources to help personnel make better decisions. In the automotive industry, it has been applied to several areas, including navigation and fleet management.

In this article, we’ll explore how geospatial intelligence can improve driver safety and efficiency in traditional vehicles.

How does it all come together?

Here’s how it all comes together:

  • Data from connected vehicles – This is the raw data collected by autonomous vehicles and other vehicle systems. It offers an on-demand picture of traffic patterns, road conditions and driver behavior.
  • Data from the cloud – The cloud allows you to store and analyze large amounts of data in real time. In this way, you can quickly identify patterns that indicate a problem with one or more sensors or systems on your vehicle.
  • Data from the edge – Edge computing uses advanced analytics at the edge of a network (a local area) rather than in a centralized location such as a cloud server center or data hub. This approach enables faster decision making because only relevant information is sent over high-bandwidth networks instead of sending all available information for analysis in another location—a process that can take hours or even days depending on bandwidth capacity limitations

Harnessing the power of geospatial intelligence will help you create better experiences for every aspect of your customer journey.

Geospatial intelligence is a powerful tool that can help you create a more personalized and engaging experience for your customers.

Heliware’s HeliAI uses location data to give you insights into how people are moving around the world, what they are doing at any given time and whether there are opportunities to engage with them at specific locations. Automotive service providers or manufacturers can use this information to understand customer behavior and improve the experiences your products offer.

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