Digital Revolutions

DR

Markets have been constantly evolving from pre-internet era of viscous state through fluid state over last decade with internet democratized access to information, reducing buyer-seller information asymmetry. Digital Revolutions with the advent of AI, Blockchain, Robotics, AR/VR, and hyper connected driven IoT technologies are forcing companies to functioning in a state of super fluidity in recent times.

Fortune 1000 organizations and VC backed startups are applying AI, ML, AR/VR, Blockchain and IoT to empower enterprises to make intelligent decisions, prioritizing and driving next-gen innovations improving the success rates. As an enthusiast envisioning the success of superfluid markets and with know-how of recent technology developments, I would like to summarize below the driving forces of Digital Revolutions

  • Key characteristics of Digital Revolutions: As businesses are trying to become intelligent enterprises with real times responses, there is an increasing demand for dematerializing their physical assets with digital touchpoints. In these times, business operations, supply chain, supporting infrastructure and technology, and enormous volumes of data becomes software driven making enterprises become hyper connected seamlessly and derive proactive insights. This is leading to Digital Revolutions offering a rich user/consumer experiences.
  • Blockchain and IoT are expediting the pace of Digital Revolutions: We have now entered the age of superfluid markets, which represents the convergence of multiple forces. While many transaction costs were reduced during the fluid market period, costs around contracting, trust and the policing and enforcing of contracts remained high. The maturation of blockchain technology as a transaction engine in which trust is “built in” will reduce even these costs. With the Internet of Things, physical goods are being sensed, tagged and linked to the Internet, with the promise to better match supply and demand. Intelligent agents will soon anticipate buyer preferences before buyers themselves. The intersection of blockchain and IoT will create autonomous markets that run themselves cheaply and efficiently. The gig economy implies increasingly superfluid labor markets. And these developments may just represent the tip of the iceberg. Examples include,
    • Blockchain potentiality to offer intrinsic business value in integrated utilities management with a reliable, low-cost way for recording validating financial or operational transactions across a distributed network with no central point of authority. Peer-to-peer energy trading, Billing of AV charging stations, Power Ledger and Smart grid management systems are few use cases.
    • Visa’s IoT platform designed to bring the point-of-sale everywhere by allowing businesses to introduce secure payment experiences quickly to any device connected to the IoT. Visa’s vision and belief is to securely embed payments and commerce into any device—from a watch to a ring to an appliance or a car.
  • Robotics and Bots are first steps of organization in taking advantages of Digital Revolutions: Robotics are emerging to pick up precision heavy activities and “bots” leveraging AI is taking customer service and experience to the next level. Take a look at inVia that is introducing “robotics-as-a-service” to the new economy with first “goods-to-box” warehouse packing system. This new robotics system that put goods directly into shipping boxes. Instead of investing in a fleet of robots, customers pay a monthly service fee.
  • Artificial Intelligence and Machine Learning are big boost to Digital Revolutions: AI combine with machine learning is paving ways to new business models. AI technologies already pervade human lives progressing beyond simply building systems that are intelligent to building intelligent systems that are human-aware and trustworthy.
  • AR/VR is becoming a driving force of Digital Revolutions. Let us take examples of retail industry transformation. Virtual reality (VR), along with its sister technology augmented reality (AR), offers retailers the opportunity to transform how people shop. One customer might try on shirts without having to travel to the store. Another might order furniture on the spot, confident that it’s right for the house. Applications using either technology stand to eliminate customer pain points, elevate customer service, and create a differentiated, personalized customer experience. The successful incorporation of VR and AR into retail models also has the potential to vastly change the way retailers are thinking about stores of the future

Digital Revolutions are leading to superfluid markets which will continue to evolve differently across different industries and companies. These transformations are what we continue to explore into future. There is a pressing need for companies to collaborate exchanging ideas, trend spotting, and tap innovations to succeed in  future frictionless markets.

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Healthcare Simplified with AI

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Healthcare industry is a front runner in creating business value applying AI followed by Automotive and Financial Services industries.

In simple and direct interpretation, Artificial Intelligence fundamentally helps either completing tasks at a basic level to making decisions at advanced level. AI help in completing tasks is twofold, either totally automate the tasks without human intervention or help humans in completing the tasks in faster and effective ways. Similarly AI can enable decision making in fully autonomous ways with NO to very little human involvement or amplify the human decision making. Let us examine these scenarios in context of Healthcare industry encompassing the four dimensions of applied AI in healthcare.

  1. AI completing healthcare tasks without humans: Chatbot to connect scheduling Electronic health record systems and automate the confirmation and scheduling of patients
  2. AI aiding humans in completing tasks: AI powered diagnostics which helps humans/users in analyzing patient’s unique history as a baseline against which trigger a possible health condition that is in necessity of future investigation and potential treatment.
  3. AI augmenting decision making in healthcare: AI is able to provide clinicians evidence-based treatment options which is kind of a data driven diagnosis. AI as well is aiding in virtual drug development process.
  4. AI autonomously making decisions in healthcare: Will humans let an AI’led robot perform your surgery by itself? As AI proves dealing with complication, it can aid intelligent implantation with improved health benefits and lives.

AI reach in healthcare is everywhere from answering specific patient queries to intelligent implantation. It is evident from recent developments including,

  • Google’s DeepMind platform: Detecting certain health risks thro’ data collected via a mobile app or analysis of medical images to develop computer vision algorithms to detect cancerous tissues
  • Intel’s Lumiata: Using AI to identify at-risk patients and develop care options
  • IBM’s Watson: AI enabled Oncology alongside Cleveland Clinic or work with CVS Health on AI applications in chronic disease treatment, etc.
  • Microsoft’s Hanover project: Medical research to predict the most effective cancer drug treatment options or medical image analysis of tumor progression and development of programmable cells
  • Refer for other examples @ https://www.cbinsights.com/blog/artificial-intelligence-startups-healthcare/

There are a number of startups entering the healthcare AI space has increased in recent years. AI systems are getting involved in full spectrum across Healthcare industry encompassing providers, consumers, payers and pharma and PBM players. The future seems to be very promising as the potential of commercial benefit of applying AI in healthcare will be substantial.

With the earlier posts in this space, I have been discussing on various topics pinpointing the application of AI in healthcare and listing below details for reference.

  1. Intelligent Algorithms in Healthcare https://akshinthalakk.com/2017/06/12/intelligent-algorithms-healthcare/
  2. AI in Pharma https://akshinthalakk.com/2017/03/10/ai-in-pharma/
  3. New age Healthcare evolution fueled by Digital reality https://akshinthalakk.com/2016/06/05/new-age-healthcare-evolution-fueled-by-digital-reality/

Next-Gen Education System

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In gig-economy there is a tremendous opportunity to leverage the full potential of digital disruption including AI, Gamification, and Automation paving path to next-gen educational methods and job reorientation. Firstly, finding ways on how AI technologies could aid education methods, augment human skills in professional jobs and there by the challenges posed by AI. We commonly hear news like – an artificially intelligent computer system built by Google has just beaten the world’s best human, Lee Sedol of South Korea, at an ancient strategy game called Go. The Google program Alpha Go, actually learned the game without much human help. It started by studying a database of about 100,000 human matches, and then continued by playing against itself millions of times. As it evolved, it reprogrammed itself and improved. This self-learning program is based on a neural network, and theories of how the human brain works. Another classic example is Pearson – the world’s leading Education Company tapping IBM’s Watson as a virtual tutor for college students. With continued impact of AI on education and gig-economy, analysts are estimating a net reductions in jobs/workforce between 4% and 7% across various industries. It is simultaneously creating demand for high skilled digital workforce. Likewise AI and advance machine learning is paving new paths to education methods and future focus areas to complement and supersede machines to take full advantage of AI.

Second focus area is Gamification that has become the frontier of training, capitalizing on a new generation born into a computerized world. The idea behind the concept is to take elements of game design and logic and apply it to a work situation. One of the biggest companies to utilize gamification is McDonald’s, which introduced a new till system using a simulation game. Employees were asked to engage customers and use the till while under time restraints. Air Cargo Netherlands also used gamification when they needed to train employees on a specific utility. They created a game version of a new logistic system called Smartgate. They used the game to develop employees’ “chain thinking” and help them realize the consequences of their decisions in a risk-free environment.

Lastly, driving the automation agenda leveraging advances in robotics, artificial intelligence, and machine learning as machines match or outperform human performance in a range of work activities, including ones requiring cognitive capabilities. Examples include guiding customer service representatives to more quickly resolve customer problems and anticipate future purchases, quickly and securely reconciling mass overnight transactions for financial institutions, or giving time back to HR professionals by managing the time consuming on-boarding processes for new hires. Technical, economic, and social factors will determine the pace and extent of automation. Continued technical progress, for example in areas such as natural language processing, is a key factor. Beyond technical feasibility, the cost of technology, competition with labor including skills and supply and demand dynamics, performance benefits including and beyond labor cost savings, and social and regulatory acceptance will affect the pace and scope of automation. Hence the next-gen education should focus on learning futuristic competencies with an aim to complement realizing full potential of automation.

New IT enabling Superfluid Markets

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Digital forces like AI, Machine Learning, IoT, Robotics, VR/AR, Blockchain etc. are reimagining business models transforming goods, services and labor markets at unprecedented pace enabling the superfluidity of the markets. Two fundamental characteristics of superfluid markets are shrinking lead times making the interactions seamless and near realtime, and second is extreme focus on cost-to-value ratio. I will discuss the evolving nature of markets with few use cases below.

1) Goods and Services in Superfluid Markets:

i) Artificial Intelligence and Machine Learning: AI combine with machine learning is paving ways to new business models for example, changing the landscape of online ads by connecting shoppers to goods using images. Take a look at an AI platform called The Discover Machine, created by the startup Z Advanced Computing (ZAC). This new machine learning backed platform is changing the landscape of online ads. ZAC claims to offer something unique by producing online ads generated through images, not text. The machine-learning platform can be applied to searches from shoppers that will lead to the product on a merchant’s website, or to serve merchants by generating targeted visual ads based on a customer’s browsing history. The intended users of the platform include shoppers, merchants, and bloggers or other publishers.

ii) Internet of Things (IoT): As the Internet of Things (IoT) continues to grow and drive a more connected world, it is changing the way we live, shop and pay by moving data and the point-of-sale to wherever the consumer wants it to be. Take a peek at Visa’s IoT platform designed to bring the point-of-sale everywhere by allowing businesses to introduce secure payment experiences quickly to any device connected to the IoT. Visa’s vision and belief is to securely embed payments and commerce into any device—from a watch to a ring to an appliance or a car. Experts estimate there will be 380 million connected cars by 2021. Visa is working with a number of car manufacturers (and other companies from across the car ecosystem) to build and test prototypes for car-based payments. By connecting the car ecosystem to the Watson IoT Platform and enabling the car with secure payment functionality, imagining the many possibilities becomes easy. Drivers could be alerted when their smog certification is about to expire or if a specific car part needs replacing, responding by either scheduling a service appointment or ordering the part that has the combined lowest cost and fastest shipping time. The range of other options is virtually limitless, extending to insurance offerings, paying for gas without a physical card or zipping through the drive-thru that much faster because the payment part of the transaction no longer exists.

iii) Robotics are emerging to pick up precision heavy activities and “bots” leveraging AI is taking customer service and experience to the next level. Take a look at inVia that is introducing “robotics-as-a-service” to the new economy with first “goods-to-box” warehouse packing system. This new robotics system that put goods directly into shipping boxes. Instead of investing in a fleet of robots, customers pay a monthly service fee.

iv) AR/VR in a classic example driving superfluidity is transforming the retail industry. Virtual reality (VR), along with its sister technology augmented reality (AR), offers retailers the opportunity to transform how people shop. One customer might try on shirts without having to travel to the store. Another might order furniture on the spot, confident that it’s right for the house. Applications using either technology stand to eliminate customer pain points, elevate customer service, and create a differentiated, personalized customer experience. The successful incorporation of VR and AR into retail models also has the potential to vastly change the way retailers are thinking about stores of the future

2) Labor Markets:
“On-demand and online talent platform” is a new labor model in the connected digital age. As per multiple surveys 1B+ people are unemployed in Developed & BRIC nations. According to McKinsey, online talent platforms serve as clearinghouses that can inject new momentum into job markets. By 2025, they could add $2.7 trillion, or 2.0 percent, to global GDP and increase employment by 72 million full-time-equivalent positions. Global companies are rethinking their talent strategies to tap Connected Transparent Talent Pool.

AI in Pharma

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Artificial Intelligence is leapfrogging in healthcare and pharma field with enabling technologies spanning across research and drug development, clinical trials, pharmacovigilance, supply chain, health records, compliance, data privacy and security.

AI is a study acknowledged to imitate human knowledge into PC innovation that could help both specialists and patients in the accompanying way, by giving a research facility to the examination, representation, and classification of restorative data, by concocting novel devices to bolster choice making and research, by incorporating exercises in medicinal, programming and psychological sciences lastly, by offering a substance rich order for future logical restorative group.

To convey a medication from introductory revelation to the hands of patients takes more than a decade time and billions of dollars. AI can significantly reduce the lead times, and also cut the costs significantly by 30% to 50%+. Early adopters like MedRespond is offering initial uses case by consolidating AI and streaming media showcasing how the company permits clients to sort in their inquiries, in their own words, and the framework chooses the pre-recorded video that best answers their inquiries. This process is helping MedRespond in both patient recruitment and retention.

Precision remedy is an area where AI is making inroads in getting the right treatment to the right patient at the ideal time. Examination of illness cells routinely takes years – yet the advent of AI’s fake awareness is that it works speedier than any human could. Today there are diverse associations who are leveraging AI, for example “Berg” a fast growing biotech, lies at the nexus of artificial intelligence, precision medicine and big data. Its AI-based drug discovery platform roots through reams of patient data to find and validate disease-causing biomarkers and efficiently craft therapies based on the newly found data.

In another example, AI is bolstering pharmaceutical adherence. AI Cure is a start-up that uses AI on patient’s cell phones to affirm solution ingestion support in clinical trials and high-chance populaces. AI Cure’s HIPAA-agreeable programming catches and dissects proof of drug ingestion. A cell phone’s camera is utilized to comprehend whether patients took the medicine effectively.

AI is also predicating the patience drug resistance, and enabling patients to become dynamic members of clinical trials. A year ago, IBM declared that the pharmaceutical mammoth Johnson and Johnson and contender Sanofi would participate in a joint effort with IBM Watson’s Discovery Advisor group. J&J will likely educate the supercomputer to peruse and comprehend experimental papers that contain clinical trial results, and afterward create and assess medicines and different medications. While this may not sound excessively energizing, it could have inconceivable outcomes on how pharmaceutical organizations do similar viability examines.

Moving to Healthcare, with most of today’s U.S. adolescents, adults and seniors owning a smartphone, they are likely to have access to an intelligent personal virtual assistant on their device. The likes of Cortana and Siri are backed by powerful systems with robust AI capabilities. These systems have the potential to provide tremendous value when combined with healthcare apps. Also, one of the new areas of AI that is beginning to gain adoption is in the field of customer service, and healthcare bots are likely to be available soon as part of what healthcare providers offer.

From the patient privacy and compliance perspective, the advent of AI is demanding technologists to ensure preventing cyber-security attacks, and develop advanced AI security monitoring solutions. AI could revolutionize compliance by offering software platforms that promise to automate otherwise routine tasks and improve upon fraud detection audits, anti-money laundering protocols, and know-your-customer screening. Keep in mind that tools and technologies are enablers and are not the foundation of a robust monitoring program. As pharma industry move toward the use of compliance intelligence, behavioral analytics, and Big Data, first we need to ask if more data feeds will lead to more alerts or even more noise, and whether analysts are just going to get buried in this noise. AI definitely promising a helping hand to humans to manage data noise.

Being technology watch dog closely following the progression of AI in pharma transformation, combined with experience around developments in this area, I welcome valuable inputs in collaborating and triggering thought provoking discussions to trend-spotting and lead the path to strike a common ground in crystalizing positive impacts of AI in future of pharm and healthcare.

Can enterprises jump directly to AI bandwagon?

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What is an enterprise’s path to Artificial Intelligence? Can companies jump on to AI hype bandwagon? Sharing a perspective to trigger a dialogue and seek your inputs.

The following journey seems to be a logical path to AI.

Step 1: Enterprise has to start with basic levels of automation

Step2: Define the path for robotics play. With basic levels of automation, leverage RPA with still human dominance.

Step3: Next pave path to robotics dominance with human assistance making it autonomics

Step4: Elevate to cognitive automation with pure robotics play having human oversight. Ingrain cognitive intelligence as a logic step to AI.

Step5: Land on Artificial Intelligence arena. Can companies jump here directly, we need to think creative.

Artificial Intelligence – Techniques & Use Cases

The artificial intelligence (AI) market is estimated to grow from $0.42bn in 2014 to $5bn by 2020, at a CAGR of 54%. In another report, BofA Merrill reckons the market will blossom to $153bn over the next five years – $70bn for artificial intelligence-based systems, and $83bn for robots. That compares to roughly $58bn in 2014. This growth can be attributed to the factors such as diversified application areas, improved productivity, and increased customer satisfaction.

With recent advances, AI is gaining confidence to drive business growth. In this blog, I have taken a close look at inventory of AI Techniques / Technologies and applicable use cases. The following chart provide “Artificial Intelligence – Techniques & Use Cases” snapshot.

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