Article | December 23, 2020
Imagination, creativity, and ambition are what brought us here to this modern high-tech age that we live in today. These characteristics are the reason behind mankind’s innovative creations that started from inventing the wheel in the stone ages, to the development of the first car in 1885.
“Every generation needs a new revolution”
For science, the sky’s the limit when it comes to new creations and inventions that serve mankind in their daily life tasks, or just to entertain. Whether it’s a smartphone that keeps you connected with people, a cleaning robot that keeps your floor shiny and spotless, or even a cup holder that just holds your drink inside your car. As time passes, we notice how technology and science prosper to bring new tools and gadgets to the world to facilitate human tasks. It’s all thanks to humans’ ability to imagine and create.
Now, we have reached a point where Artificial Intelligence has been introduced and is helping us do tasks much easier and faster. This remarkable technology has the ability to do what humans can in a more efficient way. It doesn’t have emotions like us but it sure can think and act like it. Therefore, as you think about it, is it possible for them to reach that point of creating, as humans have?
What Is AI Technology?
Artificial intelligent technology (also known as AI) is the process in which robots and machines, created by man, are able to solve problems, complete motor-related tasks, and think like humans by just learning from the experiences they approach. By using the method of deep learning, machine learning, and natural language processing, robots can process all the data we give them in an algorithmic manner. By doing so, they determine certain patterns and features to produce the ability to act and think like humans.
Although for some scientists and researchers, the definition of AI technology can go beyond the description I just provided you. Moreover, it’s known as robots that think like humans. You can notice all the amazing inventions originated by using AI like self-parking cars, voice-activated lights, and much more. Although does it stop there? Can more come from AI technology rather than just providing help around the house? Or when giving directions on a built-in GPS?
What I want to get at is…
Can AI Technology Create and Write Music?
It has been known across history and for generations that creating an artistic masterpiece requires passion, dedication, and emotions to bring forth a spectacular piece of art.
Great artistic minds like Da Vinci, were able to paint what to be considered today as one of the iconic paintings that symbolize art, known as the Mona Lisa painting. Another poetic artistic mind like Bach was able to create extraordinary and moving pieces of music that set new standards for musicians back in the 18th century. It is because of humans’ ability to imagine and their willingness to express their emotions through art, that they were able to originate outstanding masterpieces.
Although making music, for instance, does require that sense of passion and emotion to generate it. It still relies on basic rules, patterns, and fundamentals that are very important to know, and acquire, to make or write music from scratch. You see, any piece of music is made up of musical notes, certain chords, and a rhythmic bassline. These musical elements create what we call a melody in a song or just a full song. You can’t apply any chord to any bassline without referring to the rules of music first, because making music is all about assembling all of those key factors in a musical pattern. While following the rules at the same time. Of course, some musicians bypass those rules and still are able to create great songs. Even so, that’s just a different story from what I’m trying to explain.
Emotions in Music
When listening to any type of song, you can instantly tell if it’s a sad, happy, motivating, or horrifying song just from the lyrics. The instrumental melody in the background plays a huge factor in determining the mood of the song. Some chords are considered to provide a happy and uplifting feeling when played. Other musical notes and patterns generate that sense of sadness. Music Theory has assigned certain feelings to certain chords. So, when writing a happy or sad song you can easily pick which chord to use for the certain feeling you want to express in your musical piece. Some instruments used in songs are also related to specific feelings as well. That’s how the genre of music is determined most of the time.
Since making and writing music is mostly about knowing the rules and choosing which chord to go with which note. Then it’s possible to create a song relying only on the fundamentals of Music Theory. Also, if we consider these chords and notes as patterns and data, can’t it be implemented and processed by AI technology?
AI Technology Seen Today
A lot of modern age gadgets have been introduced to the market that uses AI technology to serve our wants and needs. Even music tech. Musical gadgets have been invented like automatic tuners that can tune your guitar hands-free, metronome watches, portable guitars, and many more. What’s truly fascinating is the implementation of this technology into next-level music inventions.
You might not know this but AI technology has been implemented on most of the music platforms you use today. Platforms like Pandora, Spotify, Amazon Music, and others use mathematical algorithms in their operating system that enable them to predict and suggest songs that might seem appealing to you. It’s all according to the thumbs-up feedback you provide for each song you listen to. It’s also associated with the constant clicks and searches you conduct for certain types of artists and songs.
It’s simply remarkable how these music platforms are able to provide the user with song suggestions and playlists that suit their music taste. This is all possible through AI technology’s ability to process the patterns in the music being played, the tempo, and the instruments used. With that data processed, it can predict the next song that will meet the user’s desire. Since AI can identify the type of music being played, then it’s safe to say that there’s a possibility it can write music as well. Actually, it already has.
Music Platforms That Create Music
Throughout history, many great musical artists have used technology and machines to make writing music an easier task. While for some it was just a source of inspiration. AI technology had been used by musicians for a long time to assist them in originating their masterpieces. Alan Turing, the godfather of computer science, built a machine in 1951 that generated three simple melodies. David Bowie used the lyric randomizer in the ’90s for inspiration. In addition, a music theory professor was able to create a computer program that was able to write new music in the style of Bach. These few examples make it clear that AI was able to assist artists in their music careers.
After a few thorough tests and analyses, AI has become a part of the songwriting process. The research has led to the development of songwriting platforms like Watson Beat, Amper, and Google Magenta NSynth Super. These platforms use the essence of AI in deep learning by processing the data given. They search for patterns in the styles, chords, and other musical elements between songs to produce new material in the end.
Songwriting platforms, like Amper, allow anyone without the musical knowledge or experience to create a full song instantly. The process is quite easy. All you have to do is pick a genre, mood, and tempo while Amper takes care of the rest. This program has been used to create music for podcasts, commercials, and videos for companies. Still, it hasn’t been able to produce a hit song that will reach the top spot in the music billboards. My guess is because it lacks passion and emotion when creating a song.
Will AI Technology Take Over the Music Industry?
While a lot believe that someday AI Technology is going to backfire on us and take over our jobs. Some say that if they do take over everything then more jobs will emerge from it in the process. It’s a conflicting discussion.
What has been made clear though, is that today’s modern age technology has been able to create and write music just like humans can. It’s faster and efficient. Even though it might seem that AI will take over the music industry. It still doesn’t have that emotional side of making music. Furthermore, it’s been proven that even music writing platforms, like Amper, don’t have the ability to create a hit number one song. Or one that will catch the attention of millions. Although they can create music for marketing, promotional, and commercial purposes easily.
In conclusion, Artificial Intelligence is truly a mind-blowing invention. Having it helps us with our everyday life tasks and daily routines. Nevertheless, making it write music is also remarkable and sets high standards for technology nowadays. We don’t know what technology has installed for us but it’s no doubt making the world a better place.
Article | August 13, 2020
The coronavirus outbreak in China has grown to a pandemic and is affecting the global health & social and economic dynamics. An ever increasing velocity and scale of analysis — in terms of both processing and access is required to succeed in the face of unimaginable shifts of market; health and social paradigms. The COVID-19 pandemic is accompanied by an Infodemic. With the global Novel Coronavirus pandemic filling headlines, TV news space and social media it can seem as if we are drowning in information and data about the virus. With so much data being pushed at us and shared it can be hard for the general public to know what is correct, what is useful and (unfortunately) what is dangerous. In general, levels of trust in scientists are quite high albeit with differences across countries and regions. A 2019 survey conducted across 140 countries showed that, globally, 72% of the respondents trusted scientists at “high” or “medium” levels. However, the proportion expressing “high” or “medium” levels of trust in science ranged from about 90% in Northern and Western Europe to 68% in South America and 48% in Central Africa (Rabesandratana, 2020).
In times of crisis, like the ongoing spread of COVID-19, both scientific & non-scientific data should be a trusted source for information, analysis and decision making. While global sharing and collaboration of research data has reached unprecedented levels, challenges remain. Trust in at least some of the data is relatively low, and outstanding issues include the lack of specific standards, co-ordination and interoperability, as well as data quality and interpretation. To strengthen the contribution of open science to the COVID-19 response, policy makers need to ensure adequate data governance models, interoperable standards, sustainable data sharing agreements involving public sector, private sector and civil society, incentives for researchers, sustainable infrastructures, human and institutional capabilities and mechanisms for access to data across borders.
The COVID19 data is cited critical for vaccine discovery; planning and forecasting for healthcare set up; emergency systems set up and expected to contribute to policy objectives like higher transparency and accountability, more informed policy debates, better public services, greater citizen engagement, and new business development. This is precisely why the need to have “open data” access to COVID-19 information is critical for humanity to succeed. In global emergencies like the coronavirus (COVID-19) pandemic, open science policies can remove obstacles to the free flow of research data and ideas, and thus accelerate the pace of research critical to combating the disease. UNESCO have set up open access to few data is leading a major role in this direction. Thankfully though, scientists around the world working on COVID-19 are able to work together, share data and findings and hopefully make a difference to the containment, treatment and eventually vaccines for COVID-19.
Science and technology are essential to humanity’s collective response to the COVID-19 pandemic. Yet the extent to which policymaking is shaped by scientific evidence and by technological possibilities varies across governments and societies, and can often be limited. At the same time, collaborations across science and technology communities have grown in response to the current crisis, holding promise for enhanced cooperation in the future as well.
A prominent example of this is the Coalition for Epidemic Preparedness Innovations (CEPI), launched in 2017 as a partnership between public, private, philanthropic and civil society organizations to accelerate the development of epidemic vaccines. Its ongoing work has cut the expected development time for a COVID-19 vaccine to 12–18 months, and its grants are providing quick funding for some promising early candidates. It is estimated that an investment of USD 2 billion will be needed, with resources being made available from a variety of sources (Yamey, et al., 2020).
The Open COVID Pledge was launched in April 2020 by an international coalition of scientists, lawyers, and technology companies, and calls on authors to make all intellectual property (IP) under their control available, free of charge, and without encumbrances to help end the COVID-19 pandemic, and reduce the impact of the disease. Some notable signatories include Intel, Facebook, Amazon, IBM, Sandia National Laboratories, Hewlett Packard, Microsoft, Uber, Open Knowledge Foundation, the Massachusetts Institute of Technology, and AT&T. The signatories will offer a specific non-exclusive royalty-free Open COVID license to use IP for the purpose of diagnosing, preventing and treating COVID-19.
Also illustrating the power of open science, online platforms are increasingly facilitating collaborative work of COVID-19 researchers around the world. A few examples include:
1. Research on treatments and vaccines is supported by Elixir, REACTing, CEPI and others.
2. WHO funded research and data organization.
3. London School of Hygiene and Tropical Medicine releases a dataset about the environments that have led to significant clusters of COVID-19 cases,containing more than 250 records with date, location, if the event was indoors or outdoors, and how many individuals became infected. (7/24/20)
4. The European Union Science Hub publishes a report on the concept of data-driven Mobility Functional Areas (MFAs). They demonstrate how mobile data calculated at a European regional scale can be useful for informing policies related to COVID-19 and future outbreaks. (7/16/20)
While clinical, epidemiological and laboratory data about COVID-19 is widely available, including genomic sequencing of the pathogen, a number of challenges remain:
1. All data is not sufficiently findable, accessible, interoperable and reusable (FAIR), or not yet FAIR data.
2. Sources of data tend to be dispersed, even though many pooling initiatives are under way, curation needs to be operated “on the fly”.
3. In addition, many issues arise around the interpretation of data – this can be illustrated by the widely followed epidemiological statistics. Typically, the statistics concern “confirmed cases”, “deaths” and “recoveries”. Each of these items seem to be treated differently in different countries, and are sometimes subject to methodological changes within the same country.
4. Specific standards for COVID-19 data therefore need to be established, and this is one of the priorities of the UK COVID-19 Strategy. A working group within Research Data Alliance has been set up to propose such standards at an international level.
Given the achievements and challenges of open science in the current crisis, lessons from prior experience & from SARS and MARS outbreaks globally can be drawn to assist the design of open science initiatives to address the COVID-19 crisis. The following actions can help to further strengthen open science in support of responses to the COVID-19 crisis:
1. Providing regulatory frameworks that would enable interoperability within the networks of large electronic health records providers, patient mediated exchanges, and peer-to-peer direct exchanges. Data standards need to ensure that data is findable, accessible, interoperable and reusable, including general data standards, as well as specific standards for the pandemic.
2. Working together by public actors, private actors, and civil society to develop and/or clarify a governance framework for the trusted reuse of privately-held research data toward the public interest. This framework should include governance principles, open data policies, trusted data reuse agreements, transparency requirements and safeguards, and accountability mechanisms, including ethical councils, that clearly define duties of care for data accessed in emergency contexts.
3. Securing adequate infrastructure (including data and software repositories, computational infrastructure, and digital collaboration platforms) to allow for recurrent occurrences of emergency situations. This includes a global network of certified trustworthy and interlinked repositories with compatible standards to guarantee the long-term preservation of FAIR COVID-19 data, as well as the preparedness for any future emergencies.
4. Ensuring that adequate human capital and institutional capabilities are in place to manage, create, curate and reuse research data – both in individual institutions and in institutions that act as data aggregators, whose role is real-time curation of data from different sources.
In increasingly knowledge-based societies and economies, data are a key resource. Enhanced access to publicly funded data enables research and innovation, and has far-reaching effects on resource efficiency, productivity and competitiveness, creating benefits for society at large. Yet these benefits must also be balanced against associated risks to privacy, intellectual property, national security and the public interest.
Entities such as UNESCO are helping the open science movement to progress towards establishing norms and standards that will facilitate greater, and more timely, access to scientific research across the world. Independent scientific assessments that inform the work of many United Nations bodies are indicating areas needing urgent action, and international cooperation can help with national capacities to implement them. At the same time, actively engaging with different stakeholders in countries around the dissemination of the findings of such assessments can help in building public trust in science.
Article | November 20, 2020
As smart machines, data, and algorithms usher in dramatic technological transformation, its global impact spans from cautious optimism to doomsday scenarios. Widespread transformation, displacement, and disaggregation of world labor markets is speculated in countries like India, with an estimated 600 million workforce by 2022, as well as the global labor market. Even today, we are witnessing the resurgence of 'hybrid' jobs where distinctive human abilities are paired with data and algorithms, and 'super' jobs that involve deep tech. Our historical response to such tectonic shifts and upheavals has been predictable so far - responding with trepidation and uncertainty in the beginning followed by a period of painful transition. Communities and nations that can sense and respond will be able to shape social, economic, and political order decisively. However, with general AI predictably coming of age by 2050-60, governments will need to frame effective policies to respond to their obligations to their citizens. This involves the creation of a new social contract between the individual, enterprise, and state for an inclusive and equitable society.
The present age is marked by automation, augmentation, and amplification of human talent by transformative technologies. A typical career may go through 15-20 transitions. And given the gig economy, the shelf-life of skills is rapidly shrinking. Many agree that for the next 30 years, the nature and the volume of jobs will get significantly redefined. So even as it is nearly impossible to gaze into the crystal ball 100 years later, one can take a shot at what jobs may emerge in the next 20-30 years given the present state. So here is a glimpse into the kind of technological changes the next generation might witness that will change the employment scenario:
RESTORATION OF BIODIVERSITY
Our biodiversity is shrinking frighteningly fast - for both flora and fauna. Extinct species revivalists may be challenged with restoring and reintegrating pertinent elements back into the natural environment. Without biodiversity, humanity will perish.
Medicine is rapidly getting personalized as genome sequencing becomes commonplace. Even today, Elon Musk's Neuralink is working on brain-machine interfaces. So you may soon be able to upload your brain onto a computer where it can be edited, transformed, and re-uploaded back into you. Anti-aging practitioners will be tasked with enhancing human life-spans to ensure we stay productive late into our twilight years. Gene sequencers will help personalize treatments and epigenetic therapists will manipulate gene expression to overcome disease and decay. Brain neurostimulation experts and augmentationists may be commonplace to ensure we are happier, healthier, and disease-free. In fact, happiness itself may get redefined as it shifts from the quality of our relationships to that between man-machine integration.
THE QUANTIFIED SELF
As more of the populace interact and engage with a digitized world, digital rehabilitators will help you detox and regain your sense of self, which may get inseparably intertwined with smart machines and interfaces.
DATA-LED VALUE CREATION
Data is exploding at a torrid pace and becoming a source of value-creation. While today's organizations are scrambling to create data lakes, future data-centers will be entrusted with sourcing high-value data, securing rights to it, and even licensing it to others. Data will increasingly create competitive asymmetries amongst organizations and nations. Data brokers will be the new intermediaries and data detectives, analysts, monitors or watchers, auditors, and frackers will emerge as new-age roles. Since data and privacy issues are entwined together, data regulators, ethicists, and trust professionals will thrive. Many new cyber laws will come into existence.
HEALING THE PLANET
As the world grapples with the specter of climate change, our focus on sustainability and clean energy will intensify. Our landfills are choked with both toxic and non-toxic waste. Plastic alone takes almost 1000 years to degrade, so landfill operators will use earthworm-like robots to help decompose waste and recoup precious recyclable waste. Nuclear fusion will emerge as the new source of clean energy, creating a broad gamut of engineers, designers, integrators, architects, and planners around it. We may even generate power in space. Since our oceans are infested with waste, a lot of initiatives and roles will emerge around cleaning the marine environment to ensure natural habitat and food security.
TAMING THE GENOME
As technologies like CRISPR and Prime-editing mature, we may see a resurgence of biohackers and programmable healthcare. Our health and nutrition may be algorithmically managed. CRISPR-like advancements will need a swathe of engineers, technicians, auditors, and regulators for genetically engineered health that may overcome a wide variety of diseases for longer life-expectancy.
THE RISE OF BOTS
Humanoid and non-humanoid robots will need entire workforce ecosystems around them spanning from suppliers, programmers, operators, and maintenance experts to ethicists and UI-designers. Smart robot psychologists will have to counsel them and ensure they are safe and friendly. Regulators may grant varying levels of autonomy to robots.
DATA LOADS THE GUN, CREATIVITY FIRES THE TRIGGER
Today's deep-learning Generative Adversarial Networks (GANs) can create music like Mozart and paintings like Picasso. Such advancements will give birth to a wide array of AI-enhanced professionals, like musicians, painters, authors, quantum programmers, cybersecurity experts, educators, etc.
FROM AUGMENTATION TO AUTONOMY
Autonomous driving is about to mature in the next few years and will extend to air and space travel. Safety will exceed human capabilities and we may soon reach a state of diminishing returns where we will employ fewer humans to prevent mishaps and unforeseen occurrences. This industry will need supportive command center managers, traffic analyzers, fleet managers, and people to ensure onboarding experience.
BLOCKCHAIN BECOMES PERVASIVE
Blockchain will create a lot of jobs for its mainstream and derivative applications. Even though most of its present applications are in Financial Services, Supply Chain, and Asset Management industries, very soon its adoption and integration will be a lot more expansive. Engineers, designers, UI/UX experts, analysts, auditors, and regulators will be required to manage blockchain-related applications. With Crypto being one of its better-known applications, a lot of transaction specialists, miners, insurers, wealth managers, and regulators will be needed. Crypto exchanges will come under the purview of the regulatory framework.
3D PRINTING TURNS GAME-CHANGER
Additive manufacturing, also popularly called 3D printing, will mature in its precision, capabilities, and market potential. Lab-grown, 3D-printed food will be part of our regular diet. Transplantable organs will be generated using stem cell research and 3D printing. Amputees and the disabled will adopt 3D-printed limbs and prosthetics. Its applications for high-precision reconstructive surgery are already commonplace. Pills are being 3D printed as we speak. So again, we are looking at 3D printers, operators, material scientists, pharmacists, construction experts, etc.
THE COLONIZATION OF OUTER SPACE
Amazon's Blue Origin and Elon Musk's SpaceX signal a new horizon. As space tech gets into a new trajectory, a new breed of commercial space pilots, mission planners, launch managers, cargo experts, ground crew, experience designers, etc. will be required. Since we have ravaged the limited resources of our planet already, mankind will need to venture into asteroid mining for rare and precious metals. This will need scouts and surveyors, meteorologists, remote bot operators, remotely managed factories, and whatnot.
THE HYPER-CONNECTED WORLD
By 2020, we already have anywhere between 50-75 billion connected devices. By 2040, this will likely swell to more than 100 trillion sensors that will spew out a dizzying volume of real-time data ready for analytics and AI. A complete IoT system as we know it is aware, autonomous, and actionable, just like a self-driving car. Imagine the number of data modelers, sensor designers and installers, signal architects and engineers that will be needed. Home automation will be pervasive and smart medicines, implants, and wearables will be the norms of the day.
DRONES USHER IN DISRUPTION
Unmanned aerial and underwater drones are already becoming ubiquitous for applications in aerial surveillance, delivery, and security. Countries are awakening to their potential as well as possibilities of misuse. Command centers, just like that for space travel, will manage them as countries rush to put in a regulatory framework around them. An army of designers, programmers, security experts, traffic flow optimizers will harness their true potential.
SHIELDING YOUR DATA
With data come cyber threats, data breaches, cyber warfare, cyber espionage, and a host of other issues. The more data-dependent and connected the world is, the bigger the problem of cybersecurity will be. The severity of the problem will increase manifold from the current issues like phishing, spyware, malware, viruses and worms, ransomware, DoS/ DDoS attacks, hacktivism, and cybersecurity will indeed be big business. The problem is that threats are increasing 10X faster than investments in this space and the interesting thing is that it is a lot more about audits, governance, policies, and compliance than technology alone.
FOOD-TECH COMES OF AGE
As the world population grows to 9.7 billion people in 2050, cultured food and lab-grown meat will hit our tables to ensure food security. Entire food chains and value delivery networks will see an unprecedented change. Agriculture will be transformed with robotics, IoT, drones, and the food-tech sector will take off in a big way.
QUANTUM COMPUTING SOLVES INTRACTABLE PROBLEMS
Finally, while the list is very long, let’s touch upon the advent of qubits, or Quantum computing. With its ability to break the best encryption on the planet, the traditional asymmetric encryption, public key infrastructure, digital envelopes, and digital certificates in use today will be rendered useless. Bring in the quantum programmers, analysts, privacy and trust managers, health monitors, etc.
As we brace for the world that looms large ahead of us, the biggest enabler that will be transformed itself will be Education 4.0. Education will cease to be a phase in your life. Life-long interventions will be needed to adapt, impart, and shape the skills of individuals that are ready for the future of work. More power to the people!
Article | March 26, 2020
Search and AI-driven analytics provider ThoughtSpot recently announced a collaboration with Google Cloud to launch Embrace for Google Cloud Platform that will enable enterprises to perform search and AI-driven analytics directly in Google BigQuery. The launch of Embrace will help enterprises leverage the dual power of Google BigQuery and ThoughtSpot’s augmented analytics. The combined delivery will enable organizations to derive proper insights and help them in taking appropriate actions. “Enterprises have more data at their disposal than ever before. The problem arises, however, when they look to turn that data into insights that can transform how their business operates. The old analytics stack is too slow and cumbersome to deliver the value they need from their data,” said Seann Gardiner, SVP of Business Development & GM of Embrace, ThoughtSpot. “Embrace for Google Cloud exemplifies the new, cloud-native, AI-powered analytics stack required to rewrite this equation and drive true transformation for our customers.”