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

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?” Artist, artist-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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ChatGPT and Generative AI’s – A Digilah view

ChatGPT and Generative AI’s
ChatGPT and Generative AI’s

Written by Vidya Dhareshwar on Digilah (Tech Thought Leadership)

Chatgpt, Bard AI and all the generative AI seems to be the current flavour. There is an insurmountable buzz around and about it . 

Everyone has an opinion on its impact and the ways that it can change, how we and our future generations engage with and use tech in our daily lives.

Whilst there have been many concerns on its impact on search engines, students, jobs and livelihoods, the fact remains that this evolution has happened and is here to stay.

ChatGPT alone has been the fastest growing consumer internet app ever with over 100 million users two months after launch. This itself shows the vast potential of generative AI.

 Just as life evolves, so does technology and yet this revolutionary technology doesn’t take away from human intelligence instead it is trained to learn what humans mean when they ask a question. 

Many users are awed at its ability to provide human-quality responses, inspiring the feeling that it may eventually have the power to disrupt how humans interact with computers and change how information is retrieved.

In the context of Digilah, where we like to provide a digital platform for every tech enthusiast to learn and contribute their tech journey and thought leadership, we view chatGPT, Bard AI and all other generative AI’s as an enabler and an opportunity for many of our start up and tech founders to share their learnings.

Let’s talk about the tech startup market in South East Asia alone. As per a Forbes article, The digital and tech industries of this region have enjoyed an enormous boom over the last few years. 

According to Jungle Ventures, Southeast Asia’s technology startups had a combined valuation of $340 billion in 2020, and they anticipate this will triple by 2025.

This is a diverse but very strong prospective market with a focus in Vietnam, Thailand, Indonesia, Malaysia, Singapore and the Philippines.

This market is quite complicated. Many entrepreneurs are hindered by concerns over a difference in mentality and a lack of understanding of how to do business there. We @ Digilah look at this as a huge opportunity.

There is a need to get all of the learnings and journeys of these startups and founders so that this rich knowledge repertoire is available to all. 

Many of them would like to share their journeys and provide their insights but sometimes are busy learning and navigating the markets and business challenges and for some it might also mean a constraint in terms of resources and skills to share their journeys be it content creation or communication skills or just time.

We present the combined power of Human Experience with the generative AI’s in the form of articles published by us at Digilah. Our submission is to use the vast reach of the generative AI tools to start the journey.

What this tech will do is provide for a framework, a skeleton, a structure of an article , a startup founders journey as a start point. This can then be brought to life by adding the content  and context of experience, leadership, success, failures and insights by the tech founders.

These articles are extremely valuable and become a  rich database of insight and knowledge for all knowledge seekers today and for the future.

In short, in our view, ChatGPT, Bard AI AND Human Experience is the opportunity to build the knowledge here at Digilah, all at the click of a key.

Hello readers! Hope you liked what you read today. Click the like button at the bottom of this page and share insights with your colleagues and friends!

For more such amazing content follow DigilahVidya Dhareshwar

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AI Tech

𝐇𝐨𝐰 𝐟𝐚𝐫 𝐝𝐨 𝐰𝐞 𝐰𝐚𝐧𝐭 𝐭𝐨 𝐠𝐨?

how far do we want to go

Written by : Marcus Parade on Digilah (Tech Thought Leadership)

… 𝐚𝐧𝐝 𝐡𝐨𝐰 𝐟𝐚𝐫 𝐜𝐚𝐧 𝐰𝐞 𝐠𝐨?

There will be a time sooner than we think, when you will not recognize the difference of a human being and a human robot said an expert of robotics already 10 years ago.

We are still in our early days of AI and robotics and already now, amazing advances have been made in a very short time.

In concern of AI, all kinds of industries are or will be affected, where huge amounts of data are accessible to be processed.

𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐩𝐫𝐨𝐯𝐢𝐝𝐞 𝐢𝐧 many cases better efficiency, insights and incredible time savings and therefore also support an increased competitive advantage. 

AI is one of the most exciting and rapidly advancing technologies of our time.

𝐖𝐡𝐢𝐥𝐞 𝐠𝐨𝐯𝐞𝐫𝐧𝐦𝐞𝐧𝐭𝐬, 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐚𝐧𝐝 𝐩𝐞𝐨𝐩𝐥𝐞 𝐚𝐫𝐞 𝐬𝐭𝐢𝐥𝐥 trying to figure out the legal and ethical implications of a content world increasingly turned on by AI, is the progress of this technology advancing “day by day”.

𝐖𝐞𝐥𝐥, 𝐥𝐞𝐭’𝐬 𝐭𝐚𝐥𝐤 𝐚𝐛𝐨𝐮𝐭 𝐰𝐡𝐚𝐭 𝐀𝐈 𝐜𝐚𝐧 do now for us 🙂💡. We’ve all heard of Alexa, Google and Siri Assistants – these are all examples of AI in the form of virtual assistants. 

But AI is also being used in a far more wide range of industries – from healthcare to finance to retail and much much more.

For example, AI-powered diagnostic tools are being used to help doctors identify diseases like cancer more quickly and accurately. In finance, AI is being used to detect and prevent fraud.

And in retail, AI is being used to personalize shopping experiences and make precise recommendations to customers.

AI is also being used in many other industries such as transportation, manufacturing, law, astronomy, agriculture, energy – basically 𝐲𝐨𝐮 𝐧𝐚𝐦𝐞 𝐢𝐭 and again – the AI is getting better day by day …

𝐁𝐮𝐭 𝐰𝐡𝐚𝐭 𝐚𝐛𝐨𝐮𝐭 𝐨𝐮𝐫 𝐟𝐮𝐭𝐮𝐫𝐞 🌎? 𝐖𝐞𝐥𝐥, 𝐭𝐡𝐚𝐭’𝐬 where I find things get really interesting. Some experts predict that AI will eventually be able to do just about anything a human can do and I personally think even far far beyond in many fields.

For example, AI can be used to perform complex surgeries and improve our mobility and here I do not only mean self-driving cars, but also the overall complexity of traffic and logistics and more.

AI is also expected to play a key role in fields such as natural language processing, image recognition, climate prediction and the bit scary part – military weapons and operations.

What I particularly like is that AI might even find out more about the languages of our whales singing 🐳🎵🐋 as well as other animals 🦅. This will teach us a lot about language structures, communication, emotions of animals and even ourselves.

𝐀𝐈 𝐚𝐥𝐬𝐨 𝐡𝐚𝐬 𝐭𝐡𝐞 𝐩𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥 𝐭𝐨 change the way we consume information, and how we interact with our world 🌏. As AI becomes more advanced, it’s expected that it will be able to “understand ” natural existing and ancient languages, and carry on conversations with humans that are indistinguishable from conversations with other humans.

𝐌𝐚𝐲𝐛𝐞 𝐰𝐞 𝐣𝐮𝐬𝐭 𝐡𝐚𝐯𝐞 𝐭𝐨 𝐥𝐞𝐚𝐫𝐧 𝐭𝐨 𝐚𝐜𝐜𝐞𝐩𝐭 AI as an additional mega tool that helps our lives to make our challenges easier. 

A bit questionable I personally find though, that there are many start-ups now, tapping markets for people, that want to hold conversations with their beloved ones that have passed away 💛.

Whereas it is often a big challenge to cope with a lost life, I think it is also important to strive forward towards our future. But everyone should decide for themselves and I think experiences will solve many questions.

AMAZING 𝐀𝐈 𝐰𝐢𝐥𝐥 𝐚𝐥𝐬𝐨 𝐛𝐞 𝐚𝐛𝐥𝐞 𝐭𝐨 process and understand images and videos, and make predictions, decisions and summaries based on all kinds of data. 

What has been recently released for example is the AI used for texting called chat.openAI.com (COAI). The provided data for this platform here is the complete internet that is open and not secured.

𝐍𝐨𝐭 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐫𝐞𝐚𝐬𝐨𝐧 𝐢𝐬 Google on “red 🚨 alert”, as their business strategy is nowadays being questioned as them not being up to date enough in comparison to the progresses of AI.

Whereas the search engine of Google relies on their algorithms to search for the most relevant results, will AI be able to provide more and more precise SUMMARIES of different sources combined of what you are searching for.

𝐁𝐮𝐭 𝐭𝐚𝐥𝐤𝐢𝐧𝐠 𝐚𝐛𝐨𝐮𝐭 𝐩𝐫𝐞𝐜𝐢𝐬𝐞 results, so far the results of the AI and COAI are amazing, but when I read some of the AI texts, you will be able to detect some limits at the stage of today. So far the texts of COAI sound quite emotionless and yet quite perfect in many cases.

As an example, job applicants have been invited for job interviews by letting AI write ✍📜 them their resume as well as the attached letter. In the end, we humans have to decide, if we want to use the AI proposals, adjust it or leave it out. 

And such as in the example with the job interview, no AI can play your individual role, your character and your true emotions while talking in real life face to face.

𝐀𝐥𝐬𝐨 𝐢𝐟 𝐲𝐨𝐮 ask the AI for jokes on COAI for example, I found them 𝐬𝐨 𝐟𝐚𝐫 a bit middle range. I asked for example 3 times, to tell me jokes about AI:

“Why was the AI sad 😪? Because it had no emotions.”

“Why did the robot 🤖 go on a diet? Because it wanted to reduce its “byte” size!”

“Why was the AI cold ⛄❄? Because it left its algorithms open!”

𝐓𝐡𝐞𝐬𝐞 𝐚𝐫𝐞 𝐨𝐧𝐥𝐲 𝐨𝐧𝐞 some examples, where the AI so far is still hitting its limits. It is also possible that these jokes existed already in the internet and that the jokes were not independently combined.

But as mentioned, AI gets better day by day. The AI will even be able to adapt to your personal writing and speaking style and you will be able to “outsource” many kinds of texting AND research.

In my opinion, ANY industry that is involved with any kind of texting or large data research – even companies such as creating advertising spots and many many more, will be affected “massively” by the progress of AI. The innovative ideas however I will stay in our power 🤜 – if we choose to.

𝐀𝐬 𝐨𝐟 𝐧𝐨𝐰 𝐈 𝐰𝐨𝐮𝐥𝐝 𝐬𝐚𝐲 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐰𝐢𝐥𝐥 need less employees, as any kind of texting can be done much faster. And the AI even at this stage can deliver very good outputs in order for people 🎭 to have a much faster start with the usage of COAI.

In my opinion, “luckily” so far, the human evaluation and creativity is more than absolutely needed, but let’s talk again in let’s say 10 years again – the dice 🎲 might roll on improved adapted ground …

𝐁𝐮𝐭 𝐢𝐭’𝐬 𝐧𝐨𝐭 𝐚𝐥𝐥 𝐫𝐚𝐢𝐧𝐛𝐨𝐰𝐬 🌈 𝐚𝐧𝐝 sunshine 🌞 – some people are worried that as AI becomes more advanced, it could lead as mentioned to widespread job losses and even the rise of a robot 🤖 “rebellion”.

There is also a concern that AI could be used to create autonomous weapons, and to gather data on individuals without their knowledge or consent.

𝐖𝐡𝐚𝐭𝐞𝐯𝐞𝐫 𝐲𝐨𝐮 𝐦𝐢𝐠𝐡𝐭 𝐭𝐡𝐢𝐧𝐤 𝐚𝐛𝐨𝐮𝐭 Elon Musk, but I find his quote about AI very interesting, that AI could be the biggest threat for human kind. 

Logically I think however, it should “easily” be possible to create secure gateways for AI not be able to become independent and to totally restrict opportunistic behaviour in favour of AI so far.

𝐇𝐨𝐰 𝐟𝐚𝐫 𝐝𝐨 𝐰𝐞 𝐰𝐚𝐧𝐭 𝐭𝐨 𝐠𝐨?? I personally believe that most technological advances will be tried out if it is more or less promising for a competitive advantage.

It’s also integrated in our genes for our survival instinct to strive for technological advances. As AI provides competitive advantages and an easier life, this is and will be part of our evolutionary processes of technology surrounding us. 

It will accompany us now and for our common & united future. As the scientist Darwin already stated “Survival of the fittest”.

𝐄𝐭𝐡𝐢𝐜𝐚𝐥 standards will need to be set, as the AI is extracting and combining data from all kinds of previous inputs that is found in our internet. For example the first upload bans for AI artwork have started. 

I can follow these measures and as of now, I think AI inclusion should a t least be identified, but this could also be wishful thinking…

𝐎𝐯𝐞𝐫all, AI has the potential to make our lives better in countless ways. 

AI can helps us be more efficient and productive, it can help us make better decisions, and it can help us to understand and interact with the world in innovative, inspirational and faster ways.

And who knows, maybe in the future we’ll all have robot butlers to do our chores and make us 007-🍸 Martinis or whatever … 😁

𝐒𝐨, 𝐭𝐡𝐞𝐫𝐞 𝐲𝐨𝐮 – we – 𝐡𝐚𝐯𝐞 𝐢𝐭 – 𝐚 brief overview of what AI can do now and what our future might hold. 

It’s an exciting time to be alive and to see how far AI has come, and it is going to be even more exciting to see what our future will reveal.

The possibilities are quite endless and I am most curious to see how AI will shape our world in the coming years ahead to our common advantage.

𝐓𝐨𝐝𝐚𝐲’𝐬 𝐀𝐈 𝐢𝐬 still narrow and often yet not so very intelligent, but it soon will be, as the tech is getting better day by day – like the harnessing of electricity – that has changed the very fabric of our human life. 

Some scientists proclaimed that in 2029, AI will be “smarter” than us humans – others say quite a bit later…

𝐋𝐞𝐭 𝐮𝐬 hopefully only go as far, as where we humans still remain the ultimate decision making power without opportunistic behaviour. AND having unifying sustainable goals supported by AI, to save our lovely planet with humans living on it 🌍

💛🌹🌞

𝐈 𝐡𝐨𝐩𝐞 𝐯𝐞𝐫𝐲 much you like or found my article somewhat inspiring – 𝐈𝐅 – perhaps you might like to comment or place a 👍 or so? 🌞

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AI Tech Art Tech

How Technology can help India’s Traditional Craftspeople

How Technology can help India’s Traditional Craftspeople

Written by : Suki Iyer on  Digilah (Tech Thought Leadership)

A recent conversation with a friend got me thinking of the intersection between technology, design, the preservation and flourishing of traditional handicrafts, and communities. 

The Indian handicraft industry is a highly labor intensive one, with more than 7 million artisans, a majority of whom are women and largely underprivileged.

This industry, which is traditionally a major source of revenue generation in rural India, has been in decline (though there have been several efforts to support it), and has been hit hard by the pandemic as well. 

What are the glaring gaps in the market for traditional craft? (specific to India, but this could apply to the world as well). To my mind the key gaps are in design, and in business building capacities. 

Local artisans lack the ability to meet the needs of new markets and are forced to find low unskilled employment in urban industries. One of the major factors contributing to this is that artisans are not trained to contemporize their designs. 

In this article, I’d like to focus on design and the role technology can play in meeting the current gaps. 

While some work has been done on modernizing design, a lot of craft continues to center around traditional design, often not appealing to modern sensibilities, and thus not being able to build the foundation of a sustainable business. How can technology help? For example, AI techniques have been leveraged for emulating creativity and imagination – for image generation, style-transfer, image-to-image translation; for pattern generation, and color-transfer etc.  

An interesting study (Raviprakash et al., May 2019) describes how AI techniques can be used to contemporize design, while keeping the underlying technique unchanged. It generated colored motifs and patterns that can be manufactured into physical products. This study experimented with using AI on the popular IKAT weave. Unlike other dyeing techniques, in IKAT the yarn is dyed BEFORE it is woven. This is what gives it its unique shading effect. This property was harnessed by the researchers to create a contemporary design. 

A picture containing text Description automatically generated

The researchers first used a black motif using an AI technique trained on a set of 1000 paintings from a famous European painter, Piet Mondrian, and their gray-scale counterparts. The simplicity of these paintings along with the use of only primitive colors made them an ideal choice for our approach, since the model is able to learn primitive colorization of a motif from a relatively small training dataset. 

The model used a generator which colorizes the input and a discriminator that learns to distinguish between the real paintings and the colorized images. The discriminator’s output determines the loss of the generator, which the generator tries to minimize, effectively colorizing images to make them indistinguishable from real paintings. 

These motifs were re-colored with colors of an inspiration image using a statistical approach of global color transformation, and the design was post-processed to a grid that could be readily used for dyeing, as each cell is of a single color. 

Products manufactured with designs generated using the above approach are found to be much more visually appealing than their traditional counterparts in the present market. Local artisans used these designs to manufacture and sell products successfully. A person painting a picture Description automatically generated with medium confidence

There are several such examples of how technology can modernize craft without compromising on the underlying uniqueness of a particular craft technique. 

Investments need to be made in building such design capacity amongst artisans so they can once again take their place as valued centers of their communities. 

Suki Iyer

Most searched question

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5 Levels of Autonomy in Vehicles

automation

Witten by Oliver-Werner K. on Digilah (Tech Thought Leadership)

Levels 0 to 5

Level 0 – No Automation. The human at the wheel steers, brakes, accelerates, and negotiates traffic.

Level 1 – Driver Assistance. …

Level 2 – Partial Automation. …

Level 3 – Conditional Automation. …

Level 4 – High Automation. …

Level 5 – Full Automation.

Researchers forecast that by 2025 we’ll see approximately 8 million autonomous or semi-autonomous vehicles on the road. Before merging onto roadways, self-driving cars will first have to progress through 6 levels of driver assistance technology advancements.

What exactly are these levels? And where are we now? 

The Society of Automotive Engineers (SAE) defines 6 levels of driving automation ranging from 0 (fully manual) to 5 (fully autonomous). These levels have been adopted by the U.S. Department of Transportation. 

Level 0 (No Driving Automation)

Most vehicles on the road today are Level 0: manually controlled. The human provides the “dynamic driving task“ although there may be systems in place to help the driver. An example would be the emergency braking system―since it technically doesn’t “drive” the vehicle, it does not qualify as automation. 

Level 1 (Driver Assistance)

This is the lowest level of automation. The vehicle features a single automated system for driver assistance, such as steering or accelerating (cruise control). Adaptive cruise control, where the vehicle can be kept at a safe distance behind the next car, qualifies as Level 1 because the human driver monitors the other aspects of driving such as steering and braking. 

Level 2 (Partial Driving Automation)

This means advanced driver assistance systems or ADAS. The vehicle can control both steering and accelerating/decelerating. Here the automation falls short of self-driving because a human sits in the driver’s seat and can take control of the car at any time. Tesla Autopilot and Cadillac (General Motors) Super Cruise systems both qualify as Level 2.

Level 3 (Conditional Driving Automation)

The jump from Level 2 to Level 3 is substantial from a technological perspective, but subtle if not negligible from a human perspective.

Level 3 vehicles have “environmental detection” capabilities and can make informed decisions for themselves, such as accelerating past a slow-moving vehicle. But―they still require human override. The driver must remain alert and ready to take control if the system is unable to execute the task.

Almost two years ago, Audi (Volkswagen) announced that the next generation of the A8―their flagship sedan―would be the world’s first production Level 3 vehicle. And they delivered. The 2019 Audi A8L arrives in commercial dealerships this Fall. It features Traffic Jam Pilot, which combines a lidar scanner with advanced sensor fusion and processing power (plus built-in redundancies should a component fail).

However, while Audi was developing their marvel of engineering, the regulatory process in the U.S. shifted from federal guidance to state-by-state mandates for autonomous vehicles. So for the time being, the A8L is still classified as a Level 2 vehicle in the United States and will ship without key hardware and software required to achieve Level 3 functionality. In Europe, however, Audi will roll out the full Level 3 A8L with Traffic Jam Pilot (in Germany first). 

artificial intelligence

Level 4 (High Driving Automation)

The key difference between Level 3 and Level 4 automation is that Level 4 vehicles can intervene if things go wrong or there is a system failure. In this sense, these cars do not require human interaction in most circumstances. However, a human still has the option to manually override.

Level 4 vehicles can operate in self-driving mode. But until legislation and infrastructure evolves, they can only do so within a limited area (usually an urban environment where top speeds reach an average of 30mph). This is known as geofencing. As such, most Level 4 vehicles in existence are geared toward ridesharing. For example:

NAVYA, a French company, is already building and selling Level 4 shuttles and cabs in the U.S. that run fully on electric power and can reach a top speed of 55 mph.

Alphabet’s Waymo recently unveiled a Level 4 self-driving taxi service in Arizona, where they had been testing driverless cars―without a safety driver in the seat―for more than a year and over 10 million miles.

Canadian automotive supplier Magna has developed technology (MAX4) to enable Level 4 capabilities in both urban and highway environments. 

They are working with Lyft to supply high-tech kits that turn vehicles into self-driving cars.Just a few months ago, Volvo and Baidu announced a strategic partnership to jointly develop Level 4 electric vehicles that will serve the robotaxi market in China.

Level 5 (Full Driving Automation)

Level 5 vehicles do not require human attention―the “dynamic driving task” is eliminated. Level 5 cars won’t even have steering wheels or acceleration/braking pedals. They will be free from geofencing, able to go anywhere and do anything that an experienced human driver can do. Fully autonomous cars are undergoing testing in several pockets of the world, but none are yet available to the general public!

 

(Source1: https://www.synopsys.com/automotive/autonomous-driving-levels.html)

(Source2: https://newsroom.intel.com/news/autonomous-driving-hands-wheel-no-wheel-all/)

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AI Tech Web 3.0 Tech

Web3.0:The Real decentralized Internet 

web3.0

Written by Femi Omoshona on Digilah (Tech Thought Leadership)

Decentralized technology is the present and the early we start investing our time, energy and resources trying to understand what future DApp looks like the better for us. 

Blockchain, AI, AR and IOT are amazing technologies we should be wrapping our brain around in this 21st century.

In this article, I lay out how the web has evolved, where it’s going next, and how Africa as a continent can position itself for the future.

Think about how the internet affects your life on a daily basis since it was discovered in early 1990. Internet, a system architecture that has revolutionized communications and methods of commerce by allowing various computer networks around the world to interconnect. Sometimes referred to as a network of networks, the Internet emerged in the United States in the 1970s but did not become visible to the general public until the early 1990s.

By 2020, approximately 4.5 billion people, or more than half of the world’s population, were estimated to have access to the Internet.

The Evolution of the Web

The evolution of the web can be classified into three separate stages: Web 1.0, Web 2.0, and Web 3.0.

Web 1.0  are static web sites and personal sites, the term used for the earliest version of the Internet as it emerged from its origins with Defense Advanced Research Projects Agency (DARPA) and became, for the first time, a global network representing the future of digital communications. Web 1.0  offered little information and was accessible to users across the world; these pages had little or no functionality, flexibility, or user-generated content.

Web 2.0 is called the “read/write” web, which seems to indicate an updated version of the current World Wide Web, which is known as Web 1.0. It’s more accurate to think of Web 2.0 as a shift in thinking and focus on web design. Instead of static HTML pages with little or no interaction between users, Web 2.0 represents a shift to interactive functionality and compatibility through some of the following features: User-generated content, Transparency in data and integrations.

Web 3.0 (…Loading)

Web 3.0 is the next stage of the web evolution that would make the internet more intelligent or process information with near-human-like intelligence through the power of AI systems that could run smart programs to assist users.

Tim Berners-Lee had said that the Semantic Web is meant to “automatically” interface with systems, people and home devices. As such, content creation and decision-making processes will involve both humans and machines. This would enable the intelligent creation and distribution of highly-tailored content straight to every internet consumer.

Key Features of Web 3.0

To really understand the next stage of the internet, we need to take a look at the four key features of Web 3.0:

Semantic Web

Semantic(s) is the study of the relationship between words. Therefore, the Semantic Web, according to Berners-Lee, enables computers to analyze loads of data from the Web, which includes content, transactions and links between persons.

Artificial Intelligence

Web 3.0 machines can read and decipher the meaning and emotions conveyed by a set of data, it brings forth intelligent machines. Although Web 2.0 presents similar capabilities, it is still predominantly human-based, which opens up room for corrupt behaviors such as biased product reviews, rigged ratings, etc.

For instance, online review platforms like Trustpilot provide a way for consumers to review any product or service. Unfortunately, a company can simply gather a large group of people and pay them to create positive reviews for its undeserving products. Therefore, the internet needs AI to learn how to distinguish the genuine from the fake in order to provide reliable data.

Web3.0 future for Africa

Across the world, the new Web3 economy is giving birth to myriad opportunities and the implications for the African continent are massive. Code 247 Foundation is on a mission to raised the next generation of Africa talent who will leverage the latest blockchain technologies to provide real value to billions of unbanked, underbanked and underserved individuals across Africa and other emerging markets, and we’re excited to see various blockchain protocols, startups, investors, grant funders and governments interested in doing the same.

Web3 can open up an intra-African exchange economy, it can be used for purchases and transportation between African nations. It will assist Africans to generate more economic value in a wider market.

In Africa, the evolution of blockchain technology has interested many governments across the Africa countries  to explore blockchain-based solutions, creating Central Bank Digital Currencies (CBDCs) that are likely to develop a more informed approach to the Web3 economy along with policy frameworks in line with the needs of everyday users.

Web 3 can be used to solve some of the challenges in Africa, issues of land ownership:

It is no secret the messy land management in most African countries has made it harder for citizens to acquire genuine land. This has meant that most communities are left poor due to lack of access to manage and develop their lands. Other challenges include faulk drugs, financial transactions and management of traffic etc.

Conclusion

We believe in Africa 100%. Africa can be great, will be great and must be great. Blockchain and Web3 technologies will be revolutionary in Africa. There are a lot of problems with currency and corruption in Africa.

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AI Tech

Driving intelligence solution for the automotive industry

AI technology

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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