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HR Tech AI Tech

From Science Fiction to Talent Reality – How Tech, AI, and Cutting Edge Recruitment Collide

Written by Dipansh Bhatt on Digilah (Tech Thought Leadership)

The advent of technology and artificial intelligence (AI) has revolutionized numerous industries, and recruitment is no exception.

 

With the help of advanced tools and algorithms, recruiters have found new ways to streamline their processes and identify the best-fit candidates efficiently.

However, as with any technological advancement, there are potential pitfalls to consider. 

In this thought leadership article, we will explore how tech and AI have made life easier for recruiters, while also discussing the precautions they need to take.

We’ll walkthrough the importance of Talent Intelligence (TI) and how it can shape the future of recruitment.

Streamlining Recruitment Processes:

Technology and AI have significantly enhanced the recruitment process, one are the days of manually sifting through stacks of resumes and conducting countless interviews.

AI-powered algorithms can now analyze large volumes of applicant data and shortlist candidates who possess the desired qualifications and skills.

Automated resume screening tools have emerged as a game-changer, allowing recruiters to filter applications based on specific keywords and qualifications.

This helps save valuable time and resources, allowing recruiters to focus on engaging with high-potential candidates. 

Additionally, AI-powered chatbots and virtual assistants have simplified candidate interactions by providing quick responses and handling basic queries, enhancing the overall candidate experience.

However, it is essential for recruiters to approach these advancements with caution as discussed below. Engagement remains just as important.

 

Potential Pitfalls and Precautions:

While technology and AI have undeniable benefits, there are potential risks that recruiters must be mindful of. One significant concern is the potential for algorithmic bias.

Some algorithms are trained using historical data, which may inadvertently incorporate biased hiring practices or prejudices. This can result in unfair outcomes, perpetuating existing inequalities.

Recruiters must be vigilant in reviewing and auditing the data used to train algorithms to prevent bias and ensure fair and inclusive hiring practices.

Another challenge is the loss of personal connection, undermining the human touch. While automation speeds up the process, it can also lead to a lack of human interaction, making candidates feel detached and unimportant.

Recruiters need to strike a balance by incorporating personalized communication and leveraging technology as a tool to enhance, not replace, human interaction.

Maintaining data privacy and security is yet another critical concern. With the vast amounts of personal and sensitive information being collected during the recruitment process, it is essential to implement robust data protection measures.

Recruiters must ensure compliance with relevant data protection regulations and invest in secure systems to safeguard applicant data.

Solutions and the Way Forward:

To address these potential pitfalls, recruiters should prioritize ethical AI practices. This involves regularly auditing algorithms for bias, fostering diversity within recruitment teams, and involving human oversight in decision-making processes.

Transparency is key, and candidates should be informed about the use of AI and the criteria it evaluates.

Recruiters should also invest in training and upskilling their teams to effectively utilize AI tools and strike the right balance between automation and human touch.

By combining the efficiency of AI with the empathetic skills of recruiters, a powerful synergy can be achieved, ultimately enhancing the candidate experience.

Boiled down to its core, recruitment is very similar to a sales function, selling the job to candidates and selling candidates to your hiring managers.

An example of something I’ve done myself to utilise AI in sales – when facing writer’s block or a lack of great idea, tools like ChatGPT or Copy.ai work well to help structure your engagement.

Not to say you should copy and paste these templates but rather use them as a skeleton for your own customized correspondence.

 We’ve seen a decrease in time taken to follow up and at the same time, a decrease in response times as well!

When utilized correctly, talent intelligence emerges as the way forward. It involves harnessing the power of data and AI to gain insights into candidate behaviour, preferences, and skillsets.

By leveraging talent intelligence, recruiters can make more informed decisions, tailor their recruitment strategies, and build stronger talent pipelines.

Technology and AI have undoubtedly made recruitment processes more efficient, enabling recruiters to focus on higher-value tasks. 

However, caution is necessary to mitigate potential pitfalls such as bias and loss of personal connection.

By prioritizing ethical practices and embracing talent intelligence, recruiters can leverage technology to create a more inclusive and effective recruitment landscape.

Solutions like Vita’s Talent Intelligence CRM do exactly this.

As a quick introduction, Vita’s TI helps reactivate past applicants for current hiring, identifying relevant talent from within your database and guiding engagement, within seconds. 

Not only does this streamline sourcing, reducing candidate acquisition costs, this can also be applied to screening active applicants!

Larger enterprises get hundreds of applicants per role and it’s a hassle narrowing this list down and sieving out irrelevant profiles.

Learn how to cross-reference candidates across positions as well to ensure candidates are matched to roles that suit them best, moving away from a candidate to job match but more of a candidate to company match! Get in touch to explore or check us out!

Most asked questions

Can AI be used to recruit humans?

What is an algorithm?

Most asked queries

Algorithm

ChatGPT

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AI Tech

The Magic Tricks of our Common Future! Quantum Computing

Written by Marcus Parade on Digilah (Tech Thought Leadership)

Picture this: You’re a magician on a stage. You place a rabbit in a hat, and suddenly, with a flick of your hand, there’s not 1 rabbit, but 2! Now, imagine if you could do that with your computer – making it not only do one calculation, but millions at the same time. Welcome to the mystical world of quantum computing (QC)! 🐇⚡🐇

The Quantum Mystery:

In our everyday world, things seem pretty straightforward. Your cup of coffee sits on your desk and not floating in the air, right? Things exist in one place at a time, and we’re used to that. But in the quantum reality, things get a bit… wacky. Here, particles can exist in multiple places at the same time!

How is that even possible, you may ask? Well, buckle up, because we’re about to dive together into the crazy world of quantum physics!

🎪 The Deep Atomic Circus – A Magician’s Best Friend:

Quantum mechanics deals with the universe’s tiniest particles: Atoms, electrons, and even quarks. In this microscopic circus, the rules of the game are different from the world we know. Just like how a regular computer uses bits (either a 0 or a 1) to perform calculations, a quantum computer uses quantum bits.

A qubit can be a 0, a 1, or both at the same time! This peculiar principle known as superposition.

Imagine you’re playing a game of hide and seek. In our regular world, you’re either hiding or seeking. But in the quantum world, you could be both hiding and seeking at the same time! That’s superposition for you. It’s as if the quantum particles are the ultimate multi-taskers!

I know it is still confusing – let me give you one more example

🔴 Imagine we have a coin. When you flip it, it can either land heads up or tails up. But while it’s in the air, before you see the result, it can be thought of as being both heads and tails at the same time, because we don’t know the outcome until it lands.

Superposition in quantum physics is somewhat like that, but much more complex. It’s the idea that a particle, like an electron or a photon, can exist in multiple states at once.

For example, an electron in a quantum superposition could be both spinning clockwise and counter clockwise at the same time, or a photon could be in multiple places at once.

💡 Some QC already today claim to be a trillion times faster than a standard supercomputer of today. This means in turn a QC can do calculations in less than 1 minute for which our supercomputer needs 10,000 years to finish it.

Quantum Entanglement: The Ultimate Magic Trick

Another trick up the QC’s magic sleeve is a phenomenon called entanglement. If two quantum particles become entangled, they become like a pair of magical twins. Change the state of one, and the other changes automatically, no matter how far apart they are!

Imagine if you had a pair of entangled dice. You roll one in New York and the other in London. No matter what, they always show the same number. That’s quantum entanglement, and it’s one of the key ingredients in the QC “soup”. 🍜

🌤🌻 Our Quantum Leap into our Future:

QC is still in its early stages, but the possibilities are and will be simply amazing.

When the software of artificial intelligence and the hardware of quantum computers become best friends eventually, one scientist said: “Watch out!”. While this can be interpreted in at least two ways, let’s be curious and investigate the positive aspects, while at the same time watching out.

🐇 🎩 🐇 So, the next time you see a magician pull 1 rabbit out of a hat and then 2, remember that in the world of QC, doing many amazing things at once is just the new normal. Welcome to the future of computers, where everything seems like magic with endless possibilities!

If you find this article somewhat inspiring, please place a like or a  comment.

Love, Marcus

Most asked questions

What is quantum computing?

What is superposition?

Most asked queries

Quantum physics

Superposition

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AI Tech

Do you believe that AI will eventually replace humans altogether?

Written by : Shweta (SOHAM) R on Digilah (Tech Thought Leadership)

Let’s try to understand the term first:

💡What Is Artificial Intelligence?

Artificial Intelligence is a new and exciting field that is quickly gaining popularity. It is a method of making a computer, a computer-controlled robot, or a software think intelligently like the human mind. AI is accomplished by studying the patterns of the human brain and by analyzing the cognitive process. 

It can be considered a tool to assist us to rise above our circumstances.

Before getting threatened and believing in speculations take a moment and register this, AI is a replica we have created to make our lives better.

It is made of code not cells!

Having said that, we must strive for creative sense because it’s just the beginning, we have only touched the surface of what Artificial Intelligence can accomplish. Our thinking capabilities and problem solving abilities are endless.

💡The four A.I. types are:

🧩Reactive Machines

🧩Limited Memory

🧩Theory of Mind(Exits only in theory)

🧩Self Aware(Exits only in theory)

We are currently well past the first type and actively perfecting the second. At the moment, the third and fourth types exist only in theory. 

Most of the recent or past developments are data driven. I am looking forward to the theory of mind and self care developments because their AI will have to deal with thoughts and emotions.

How on earth a machine is going to handle that?? 

According to Forbes AI is expected to see an annual growth rate of 37.3% from 2023 to 2030. AI continues to revolutionize various industries, with an expected annual growth rate of 37.3% between 2023 and 2030, as reported by Grand View Research. This rapid growth emphasizes the increasing impact of AI technologies in the coming years.

A quarter of companies are adopting AI because of labor shortages as labor shortages become a pressing concern, 25% of companies are turning to AI adoption to address this issue, according to an IBM report. AI helps businesses optimize operations and compensate for the lack of human resources.

Software engineers and data engineers are being recruited for AI support

As AI becomes more integrated into businesses, there is a growing demand for AI support roles. In 2022, 39% of businesses reported hiring software engineers, and 35% hired data engineers for AI-related positions, according to a McKinsey report.

97% of business owners believe ChatGPT will help their business

According to Forbes Advisor, a staggering 97% of business owners believe that ChatGPT will benefit their businesses. One in three businesses plan to use ChatGPT to create website content, while 44% aim to generate content in multiple languages. More than half believe AI will improve written content. 

Over half of respondents, 54%, believe that AI can improve written content, suggesting that AI-driven solutions such as ChatGPT have the potential to enhance text quality, creativity and efficiency in various content creation contexts.

💡What can we do to adapt the process?

In the emergence of AI technology, we may need to accept and reassess ourselves. We will need to be equipped skills-wise and knowledge-wise on how to handle and prosper in a world that is continuously changing and improving as days move on.

Conclusively, I will say it is important to get the hang of AI but again try to acquire a balance while you are turning into a robot with AI advancements to keep your natural stupidity alive to be creative. YES, AI is the present, but will it be the future?!

That’s a question mark for me, I believe quantum computing will take over.

Most asked questions

What are the pros and cons of AI?

 Can AI take over the world?

 

Most searched queries

Generative AI 

Machine learning

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AI Tech

Redefining Computing, The Quantum Revolution – A New Era Changing Our World

Written by Marcus Parade on Digilah (Tech Thought Leadership)

Envision yourself reading a book in a library in London while simultaneously sipping coffee at a Parisian café. Unbelievable, right? But with the marvels of quantum computing (QC), this simultaneous presence becomes a metaphorical reality!

Our current computers, in comparison, are like paddleboats trying to keep up with supersonic jets. Welcome to the future of computing, where impossibilities become possibilities.

Regular computers use “bits” like tiny on/off switches to do math. “On” is 1 and “off” is 0. By using many bits of these, our computer can solve many challenges.

QC are COMPLETELY different. Instead of bits, it uses qubits. It’s like comparing a candle to a light bulb – similar goals, but yet very very different.

This is a quantum computer (QC). Just like many inventions we’ve seen in our life before, these machines will get smaller and smaller over time. Also, there are already many different ways to build a quantum computer today.

Qubits are unique because they can be both on and off simultaneously. This strange thing happens because of quantum physics, which is the science that explains how super small things like atoms interact together.

😲 So, a qubit can be a 1, a 0, or both at the same time! This amazing state is named “Superposition” 😉💘. When we have many qubits, they can perform lots of math tasks all at once.

⚡ A QC is today about 158 million times faster than our most sophisticated supercomputer. Some have claimed to have reached even over about a trillion (1,000,158,000,000) times being faster.

Its computing is so powerful, that it could do calculations in at least just 4 minutes what it would take our supercomputer 10,000 years to accomplish.

Nobody in our world knows why these atomic realities exist, but we know that they exist. 💦 Similar as with water. We don’t know why water really exists, BUT we can use it to our advantage and insights … 🌞

So, as I think you and me are doing quite fine with using standard computers, what can these QC be used for our common good?

🔥 Artificial Intelligence (AI): Many scientists believe that quantum computing will be used to accelerate machine learning – a major component of AI.

💊 Drug Discovery: QC will help the pharma industry to discover new drugs or analyse different combinations of molecules interacting for drug effectiveness. Finding the best vaccines could be much much faster.

💡 Finding the Best Answers: Sometimes, we face a challenge with so many possible solutions that it’s hard to find the best one. Such as with logistics, banking and so many more challenges we all face, QC can help us find the best solution much quicker.

🌞 Forecasting: Weather and climate change predictions will become more precise and perhaps even the stock market could become more predictable 😁📈

🕵 Secret Codes: QC will be really good at solving tough codes or making new ones that are almost impossible to crack.

Much like art 🎨, QC invites us to see the world in a whole new light, offering completely new perspectives. It will create new interpretations of our reality and finding new wisdoms for a better sustainable world. 

🚀 Think of QC as a fleet of futuristic rocket ships. Companies and countries are in a race to have the fastest one. But having the fastest rocket shouldn’t be the only goal.

We need to pilot these rockets with care, respect the space laws of ethics, share insights and aim for a galaxy where we all thrive, and our planet is preserved.

So, rather than just trying to out-zoom each other in the space race, let’s exchange star maps, share cosmic insights, and brainstorm better pathways to the stars.

By doing so, we can ensure a better journey for all humankind in this vast universe of possibilities.

💛🌹🌞

𝐈 𝐡𝐨𝐩𝐞 𝐯𝐞𝐫𝐲 much you find my article somewhat inspiring – if – you would make me certainly happy to place a Like 👍 or so? 🌞

Love, Marcus

Most asked questions

What is quantum computing?

Will quantum computers be faster than supercomputers?

Most asked queries

Quantum

Supercomputer

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AI Tech

AI, Bias and Society

Written by Aman Bandvi on Digilah (Tech Thought Leadership)

Artificial intelligence (AI) is rapidly transforming the way we live, work, and interact with each other. As AI becomes more pervasive, it has the potential to influence collective thoughts and actions, shaping the future of our society. However, as with any technology, AI is not immune to bias. Biases in AI systems can skew insights and form a base for ill-conceived actions, ultimately impacting our society in negative ways.

According to Cathy O’Neil, mathematician and author of “Weapons of Math Destruction,” “Algorithms are opinions embedded in code.” This means that the way AI systems are developed and the data they are trained on can reflect the biases and assumptions of their creators. As a result, AI systems can perpetuate biases and discrimination, often unintentionally.

As AI systems become more pervasive, they can reinforce existing biases and stereotypes, leading to a self-perpetuating cycle. Joy Buolamwini, computer scientist and founder of the Algorithmic Justice League, notes that “We are coding the future and we have the opportunity to create a world that is fair, equitable, and just. But, if we don’t take proactive steps, AI has the potential to exacerbate and perpetuate inequalities.”

In society, biases in AI systems can result in discriminatory practices in areas such as employment, criminal justice, and healthcare. For example, AI algorithms used in hiring processes have been shown to discriminate against certain groups, such as women and people of color. Similarly, AI algorithms used in the criminal justice system have been shown to be biased against people of color, resulting in harsher sentences and wrongful convictions.

The concerns of biased AI systems are not just theoretical but are already impacting our society in real ways.

The increasing use of AI in decision-making processes, from hiring to loan approvals, means that biases in AI systems can have real-world consequences for individuals and communities.

AI bias can have a significant impact on sensitive societies in developing nations. In many cases, these societies may be vulnerable to discrimination and marginalization due to factors such as race, ethnicity, religion, or caste. If AI systems are not developed with sensitivity to these factors, they may perpetuate biases and reinforce existing inequalities. For example, in healthcare, biased AI systems may result in certain communities receiving inadequate or inferior care, leading to negative health outcomes. Similarly, in employment and education, biased AI systems may limit opportunities for certain groups, perpetuating cycles of poverty and marginalization. It’s important that AI developers and policymakers in developing nations prioritize ethical AI development and work to ensure that AI systems do not perpetuate discrimination or exacerbate existing inequalities.

It’s crucial that we take proactive steps to address AI bias. This includes auditing AI systems for potential biases, increasing diversity and representation in AI development teams, and creating transparency in AI systems. As Timnit Gebru, computer scientist and AI ethics researcher, notes, “If we want AI to be ethical, it has to be transparent, and it has to be accountable.”

As individuals, we can also play a role in promoting ethical AI development. By being discerning and alert, we can identify potential biases in AI systems and hold developers accountable. As Buolamwini notes, “We need to ask questions about the data and the algorithms that underpin AI systems, and we need to hold those who create these systems accountable for their impact.”

AI has the potential to be a transformative force for good in our society, but only if we take proactive steps to ensure that it is developed and used ethically. By removing biases, auditing AI systems, and being discerning and alert as individuals, we can help create a more equitable and just future. As Gebru notes, “AI is not neutral, it’s not unbiased. It’s the responsibility of those who create these systems to ensure that they are developed and used ethically.”

There are several steps that citizens can take to address AI bias during their online interactions. One of the most important steps is to be aware of the potential for bias in AI systems and to question the information presented to them. Citizens can also actively seek out diverse sources of information and engage with a variety of perspectives to avoid the echo chamber effect. Additionally, citizens can report instances of biased AI to relevant authorities or advocacy groups to raise awareness and promote change. Finally, citizens can advocate for greater transparency and accountability in AI development and use, pushing for ethical standards to be enforced to prevent biases and discrimination. By taking these steps, citizens can play an important role in promoting fairness and equity in AI systems and helping to build a more just and equitable society.

AI bias poses a significant challenge for societies worldwide, particularly in the developing world. Addressing these biases is a complex task that requires the involvement of stakeholders from diverse backgrounds, including policymakers, developers, and citizens. Only through collaborative efforts can we build AI systems that are ethical, unbiased, and truly serve the needs of all members of society.

Aman Bandvi

Co-founder Ais Possible

India Blockchain Alliance

Emerging Technology Council

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Most asked questions

Can AI systems be biased?

How to distinguish if an AI system is biased or not?

 

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Web 3.0 Tech AI Tech

Collaboration and Web3

 

Written by Aman Bandvi on Digilah (Tech Thought Leadership)

“Alone we can do so little, together we can do so much.” – Helen Keller

Helen Keller emphasizes the importance of collaboration in achieving great things. Collaboration has been an integral part of human society since the beginning of time. We collaborate to achieve a common goal, to learn from each other, and to make progress. In the digital age, collaboration has taken on a new meaning with the advent of Web3.

Web3 is the next evolution of the internet, where decentralization, transparency, and community-driven efforts are the norm. Web3 technologies, such as blockchain and smart contracts, have the potential to reshape how we collaborate and create value. In this article, we’ll explore how collaboration and Web3 are interconnected and how this synergy is shaping the future.

Decentralized Collaboration

One of the most significant benefits of Web3 is its decentralized nature. Traditional collaboration relies on centralized entities to facilitate communication, project management, and decision-making. However, Web3 offers a new paradigm where collaboration can happen in a decentralized manner, without the need for intermediaries.

For example, decentralized autonomous organizations (DAOs) are emerging as a new form of collaboration. DAOs are decentralized entities that operate on the blockchain, where members can propose, vote, and execute decisions. DAOs are self-governed, transparent, and open to anyone who wants to join. This new form of collaboration enables community driven efforts that are not possible in traditional organizations.

Trust and Transparency

Another benefit of Web3 is trust and  transparency. Collaboration often requires trust among members, which can be challenging to establish in traditional settings. However, Web3 technologies enable trust through cryptography, consensus mechanisms, and smart contracts.

For example, smart contracts are self-executing contracts that are programmed to execute automatically when specific conditions are met. Smart contracts eliminate the need for intermediaries and provide transparency and trust between parties. This level of trust and transparency can enable more efficient and effective collaboration.

Value Creation

Collaboration and Web3 can create new forms of value. In Web3, value can be created through decentralized applications (dApps) and decentralized finance (DeFi) protocols. dApps enable collaboration between developers, users, and other stakeholders to create new services and products. DeFi protocols enable collaboration between different financial services and create new financial products that are accessible to anyone.

Web3 also enables new forms of incentivization through tokens and cryptocurrencies. These tokens can be used to incentivize collaboration and reward contributors for their efforts. This Aman Bandvi, v1 March 2023 new form of value creation can create more inclusive and equitable collaboration where everyone can participate and benefit.

Case: Collaboration, Web3 and impact on the last-mile

Collaboration and Web3 have the potential to create a significant impact on the last mile and offer value to government stakeholders. Web3’s decentralized nature, transparency, and community-driven efforts can provide an efficient and effective way to collaborate and create value for the last mile.

The last mile is the final leg of the supply chain that delivers goods and services to consumers in remote or underdeveloped areas. Collaborative efforts can help bridge the gap and provide essential services to these areas. For example, DAOs can enable community-driven efforts that address local needs, such as water supply, healthcare, or education. These efforts can create new value for the last mile and improve the quality of life for people in these areas.

Government stakeholders can also benefit from Web3’s collaborative efforts. Web3 technologies can provide transparency, accountability, and trust in government operations. For example, smart contracts can automate government processes, eliminate corruption, and provide transparency in government procurement. Additionally, DeFi protocols can provide a more inclusive and accessible financial system that enables government stakeholders to access financial services and create new financial products that serve their constituents better.

Case: Web3, collaboration and education sector

“Collaboration allows teachers to capture each other’s fund of collective intelligence.” – Mike Schmoker

One example of how Web3 and collaboration have impacted education is the Open Learning Initiative (OLI) at Carnegie Mellon University. OLI is a Web3-based learning platform that leverages blockchain technology and smart contracts to create a more decentralized and community-driven approach to education. The platform enables students to learn at their own pace, with personalized learning paths that are tailored to their individual needs and preferences.

OLI uses Web3’s token economy to incentivize collaboration and participation. Students are rewarded with tokens for their contributions to the platform, such as completing exercises or providing feedback on course content. These tokens can be exchanged for rewards such as access to premium content or discounts on future courses.

OLI also leverages Web3’s decentralized governance model to give students a say in the direction of the platform. The platform is governed by a DAO that is owned and controlled by its members, giving students a voice in decision-making and ensuring that the platform is always evolving to meet their needs.

The impact of OLI has been significant, with students reporting higher levels of engagement and satisfaction with the platform compared to traditional learning methods. By leveraging Web3’s collaboration and decentralized governance models, OLI has created a more personalized and engaging learning experience that is tailored to the needs of individual learners. This has the potential to revolutionize the education sector by providing a more equitable, inclusive, and effective approach to learning that is accessible to all

Summary

Collaboration and Web3 are transforming how we work and create value. Web3’s decentralized nature, trust and transparency, and value creation potential enable new forms of collaboration that were not possible before. This new paradigm offers exciting opportunities for innovation and progress. As we continue to explore the potential of Web3, it’s clear that collaboration will be at the heart of its success.

Aman Bandvi

Co-founder Ais Possible

India Blockchain Alliance

Emerging Technology Council

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Most searched questions

What is the impact of web3 on internet?

Can trust and transparency completely achieved in web3?

Most searched queries

Collaboration

Web3

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AI Tech Climate Tech

From Dirt to Dish: Rethinking Food Production and Consumption 🍽🔥

Written by Marcus Parade on Digilah (Tech Thought Leadership)

𝐋𝐞𝐭 𝐮𝐬 𝐢𝐦𝐚𝐠𝐢𝐧𝐞 𝐰𝐞 have over 8 billion gorilla’s 🦍🦍 living on our planet – would you say we have an overpopulation of gorillas?

As I find overpopulation very visible on our planet, the question arises, how can we feed all our people more sustainable, if our population worldwide is estimated by the UNO to be around 10 billion by the year 2050?

𝐃𝐞𝐟𝐨𝐫𝐞𝐬𝐭𝐚𝐭𝐢𝐨𝐧 𝐟𝐨𝐫 𝐟𝐨𝐨𝐝:

𝐈 𝐰𝐚𝐬 𝐰𝐚𝐥𝐤𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐚 dear 𝐟𝐫𝐢𝐞𝐧𝐝 strolling through endless acres of golden cornfields stretching as far as the eye can see 🌽🌽

He said: “Oh Marcus, it feels so nice to be outside here in lovely nature?!”

I also love walking along golden cornfields and yet the fields feel to me only partly being in nature. Putting it baldly, we were also walking in simple production fields for farming products. We didn’t see animals nor insects.

🌲🌴 𝐃𝐞𝐟𝐨𝐫𝐞𝐬𝐭𝐚𝐭𝐢𝐨𝐧 𝐡𝐚𝐬 𝐛𝐞𝐞𝐧 going on steadily since the last 10.000 years and an end is not in sight. The crazy race for more farmland, driven by climate change and an ever-growing population, is a ticking time bomb that is likely to trigger ecological collapse on a global scale.

1st. circle is from 10.000 years ago. 2nd. circle from 300 years ago. 3rd. circle from 5 years ago.

The question is, how do we feed all people, as further deforestation for more farmlands can in my opinion not be the solution.

In turn, around 1/3 of all food produced for human consumption in the world is lost or wasted every year. Where does it all go?

It is lost during production or wasted at the consumer level. At the same time around 10 % of our world population are starving.

𝐖𝐡𝐚𝐭 𝐜𝐚𝐧 𝐰𝐞 𝐝𝐨 𝐛𝐞𝐭𝐭𝐞𝐫?

We can change our consumer behaviour, as the production such as for meat needs 𝐄𝐍𝐎𝐑𝐌𝐎𝐔𝐒 amounts of more energy, water, space as well as emissions into our atmosphere. AND, less than only 20% of our worldwide farmlands are used for the direct consumption by us humans.

A staggering 80% of our planet’s farmland is devoted to livestock feed, biofuels, and other non-food crops, leaving precious little for direct human consumption.

𝐖𝐞 𝐧𝐞𝐞𝐝 𝐛𝐞𝐭𝐭𝐞𝐫 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐢𝐞𝐬 𝐢𝐧 𝐨𝐮𝐫 𝐟𝐨𝐨𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐚𝐭 𝐚𝐥𝐥 𝐥𝐞𝐯𝐞𝐥𝐬.

New agricultural technologies can be game changers such as:

1.💦💧 More precise watering solutions directly reaching the roots

2. 🚜🛰 Better efficient machines with more precision farming

3. 🌱☣ Biotechnology with genetic modification of plants to protect them better and produce more. 𝐈𝐧 𝐚𝐝𝐝𝐢𝐭𝐢𝐨𝐧 bacteria can be created producing nutrients like proteins.

4. 💡🎲 Use of AI (artificial intelligence):

AI-powered 𝐝𝐫𝐨𝐧𝐞𝐬 𝐚𝐧𝐝 𝐫𝐨𝐛𝐨𝐭𝐬 🤖 𝐜𝐚𝐧 𝐛𝐞 your farm’s new best friends – they collect real-time data on crop yields, plant health, and soil moisture levels. It’s like having a personal assistant who knows everything about your plants.

Self-driving tractors 🚜 and drones can be equipped with 𝐀𝐈-𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐬𝐞𝐧𝐬𝐨𝐫𝐬 𝐭𝐨 optimize crop planting, fertilizing, and harvesting. With their precision and efficiency, they can help reduce labour costs and increase productivity.

AI can be like the ultimate 𝐬𝐮𝐩𝐩𝐥𝐲 𝐜𝐡𝐚𝐢𝐧 𝐝𝐞𝐭𝐞𝐜𝐭𝐢𝐯𝐞 🕵. It can analyse all data from the very beginning up to table to help optimize logistics and reduce waste. It’s like having a personal assistant who knows everything about your plants and how they travel to us.

When it comes to crop monitoring, AI has a 𝐞𝐚𝐠𝐥𝐞 𝐞𝐲𝐞 👁👁 that even most farmers can’t beat.. AI peering deep into the heart 💚 of crops to detect even the slightest signs of disease or pests, empowering farmers to take proactive measures and safeguard their precious yields.

Around 70% of our freshwater is frozen, around 29% is groundwater and the rest is surface water. Source of chart: Netafim

𝐀𝐧𝐝 𝐰𝐢𝐥𝐥 𝐭𝐡𝐢𝐬 𝐛𝐞 𝐞𝐧𝐨𝐮𝐠𝐡?

Improving the production of food on our planet Earth 🌏 is a complex issue that involves various stakeholders including farmers, governments, researchers, and consumers.

While overpopulation remains one of our main challenges is the production of our food a central challenges for our common future of our climate and us humans.

Let’s embrace our future and change for better sustainability and life. 💛🌹🌞

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Art Tech AI Tech

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

ChatGPT and Generative AI’s – A Digilah view

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.

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AI Tech

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

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. 

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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

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AI Tech

5 Levels of Autonomy in Vehicles

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 

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

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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