What really excites me about data science and by extension machine learning is the sheer number of possibilities! You can think of so many applications off the top of your head: robo-advisors, computerized lawyers, digital medicine, even automating VC decisions when they invest in startups. You can even venture into automation of art and music, algorithms writing papers which are indistinguishable from human-written papers. It’s like solving a puzzle, but a puzzle that’s meaningful and that has real world implications.
The things that we can do today weren’t possible 5 years ago, and this is largely thanks to growth in computational power, data availability, and the adoption of the cloud that made accessing these resources economical for everyone, all key enabling factors for the advancement of Machine learning and AI. Having witnessed the growth of data science as discipline, industries like finance, health-care, education, media & entertainment, insurance, retail as well as energy has left no stone unturned to harness this opportunity.
Data science has the capability to offer even more; and we will see the wide range of applications in the future in places haven’t even been explored. In the years to come, we will increasingly see data powered/ AI enabled products and services take on roles traditionally handled by humans as they required innately human qualities to successfully perform. In this article we have covered some use cases of Data Science being used differently and start-ups who have practically implemented it:
The Nurturer: For elder care
The world is aging rather rapidly. According to the World Health Organization, nearly two billion people across the world are expected to be over 60 years old by 2050, a figure that’s more than triple what it was in 2000. In order to adapt to their increasingly aging population, many countries have raised the retirement age, reducing pension benefits, and have started spending more on elderly care. Research institutions in countries like Japan, home to a large elderly population, are focusing their R&D efforts on robots that can perform tasks like lifting and moving chronically ill patients, many startups are working on automating hospital logistics and bringing in virtual assistance. They also offer AI-based virtual assistants to serve as middlemen between nurses and patients, reducing the need for frequent in-hospital visits.
Dr Ben Maruthappu, a practising doctor, has brought a change to the world of geriatric care with an AI based app Cera. It is an on-demand platform to aid the elderly in need. The Cera app firmly puts itself in the category of Uber & Amazon, whereby it connects elderly people in need of care with a caregiver in a matter of few hours. The team behind this innovation also plans to use AI to track patients’ health conditions and reduce the number of emergency patients admitted in hospitals.
A social companion technology – Elliq created by Intuition Robotics helps older adults stay active and engaged with a proactive social robot that overcomes the digital divide. AliveCor, a leading FDA-cleared mobile heart solution helps save lives, money, and has brought modern healthcare alive into the 21st century.
The Teacher: Personalized education platform for lifelong learning
With children increasingly using smartphones and tablets and coding becoming a part of national curricula around the world, technology has become an integral part of classrooms. We have already witnessed the rise and impact of education technology especially through a multitude of adaptive learning platforms that allow learners to strengthen their skills and knowledge – CBTs, LMSes, MOOCs and more.
And now virtual reality ( VR) and artificial intelligence (AI) are gaining traction to provide us with lifelong learning companion that can accompany and support individuals throughout their studies – in and beyond school . An AI based educational platform learns the amount of potential held by each particular student. Based on this data, tailored guidance is provided to fix mistakes and improvise on the weaker areas. A detailed report can be generated by the teachers to help them customise lesson plans to best suit the needs of the student.
Take Gruff Davies’ Kwiziq for example. Gruff with his team leverage AI to provide a personalised learning experience for students based on their individual needs. Students registered on the platform get an advantage of an AI based language coach which asks them to solve various micro quizzes. Quiz solutions provided by students are then turned into detailed “brain maps”. These brain maps are further used to provide tailored instructions and feedback for improvement.
Other startup firms like Blippar specialize in Augmented reality for visual and experiential learning. Unelma Platforms, a software platform development company provides state-of-the-art software for higher-education, healthcare and business markets.
The Provider: Farming to be more productive, sustainable and advanced
Though farming is considered the backbone of many national economies especially in the developing world, there is often an outdated view of it involving a small, family-owned lands where crops are hand harvested. The reality of modern-day farms have had to overhaul operations to meet demand and remain competitively priced while adapting to the ever-changing ways technology is infiltrating all parts of life. Climate change is a serious environmental threat farmers must deal with every season: Strong storms and severe droughts have made farming even more challenging. Additionally lack of agricultural input, water scarcity, over-chemicalization in fertilizers, water & soil pollution or shortage of storage systems has made survival for farmers all the more difficult.
To overcome these challenges, smart farming techniques are the need of an hour for farmers in order to manage resources and sustain in the market. For instance, in a paper published by arXiv, the team explains how they used a technique known as transfer learning to teach the AI how to recognize crop diseases and pest damage.They utilized TensorFlow, to build and train a neural network of their own, which involved showing the AI 2,756 images of cassava leaves from plants in Tanzania. Their efforts were a success, as the AI was able to correctly identify brown leaf spot disease with 98 percent accuracy.
WeFarm, SaaS based agritech firm, headquartered in London, aims to bridge the connectivity gap amongst the farmer community. It allows them to send queries related to farming via text message which is then shared online into several languages. The farmer then receives a crowdsourced response from other farmers around the world. In this way, a particular farmer in Kenya can get a solution from someone sitting in Uganda, without having to leave his farm, spend additional money or without accessing the internet.
Benson Hill Bio-systems, by Matthew B. Crisp, former President of Agricultural Biotechnology Division, has differentiated itself by bringing the power of Cloud Biology™ to agriculture. It combines cloud computing, big data analytics, and plant biology to inspire innovation in agriculture. At the heart of Benson Hill is CropOS™, a cognitive engine that integrates crop data and analytics with the biological expertise and experience of the Benson Hill scientists. CropOS™ continuously advances and improves with every new dataset, resulting in the strengthening of the system’s predictive power.
Firms like Plenty Inc and Bowery Farming Inc are nowhere behind in offering smart farming solutions. Plenty Inc is an agriculture technology company that develops plant sciences for crops to flourish in a pesticide and GMO-free environment. While Bowery Farming uses high-tech approaches such as robotics, LED lighting and data analytics to grow leafy greens indoors.
The Saviour: For sustainability and waste management
The global energy landscape continues to evolve, sometimes by the nanosecond, sometimes by the day. The sector finds itself pulled to economize and pushed to innovate due to a surge in demand for new power and utilities offerings. Innovations in power-sector technology, such as new storage battery options and smartphone-based thermostat apps, AI enabled sensors etc; are advancing at a pace that has surprised developers and adopters alike. Consumer’s demands for such products have increased. To meet this, industry leaders are integrating those innovations into their operations and infrastructure as rapidly as they can. On the other hand, companies pursuing energy efficiency have two long-standing goals — gaining a competitive advantage and boosting the bottom line — and a relatively new one: environmental sustainability.
Realising the importance of such impending situations in the industry, we have startups like SmartTrace offering an innovative cloud-based platform to quickly manage waste at multiple levels. This includes bridging rough data from waste contractors, extrapolating to volume, EWC, finance and Co2 statistics. Data extracted acts as a guide to improve methodology, educate, strengthen oversight and direct improvements to the bottom line, as well as environmental outcomes.
One Concern provides damage estimates using artificial intelligence on natural phenomena sciences. Autogrid organizes energy data and employs big data analytics to generate real-time predictions to create actionable data.
The Dreamer: For lifestyle and creative product development and design
Consumers in our modern world continually make multiple decisions with regard to product choice due to many competing products in the market.Often those choices boil down to whether it provides better value than others either in terms of product quality, price or by aligning with their personal beliefs and values.Lifestyle products and brands operate off ideologies, hoping to attract a relatively high number of people and ultimately becoming a recognized social phenomenon. While ecommerce has leveraged data science to master the price dimension, here are some examples of startups trying to deconstruct the other two dimensions: product development and branding.
I wonder if you have ever imagined your beer to be brewed by AI? Well, now you can with IntelligentX. The Intelligent X team claim to have invented the world’s first beer brewed by Artificial intelligence. They also plan to craft a premium beer using complex machine learning algorithms which can improve itself from the feedback given by its customers. Customers are given to try one of their four bottled conditioned beers, after the trial they are asked by their AI what they think of the beer, via an online feedback messenger. The data then collected is used by an algorithm to brew the next batch. Because their AI is constantly reacting to user feedback, they can brew beer that matches what customers want, more quickly than anyone else can. What this actually means that the company gets more data and customers get a customized fresh beer!
In the lifestyle domain, we have Stitch Fix which has brought a personal touch to the online shopping journey. They are no regular other apparel e-commerce company. They have created a perfect formula for blending human expertise with the right amount of Data Science to serve their customers. According to Katrina Lake, Founder, and CEO, “You can look at every product on the planet, but trying to figure out which one is best for you is really the challenge” and that’s where Stitch Fix has come into the picture. The company is disrupting traditional retail by bridging the gap of personalized shopping, that the former could not achieve. To know how StitchFix uses Full Stack Data Science read our detailed article.
The Writer: From content creation to curation to promotion
In the publishing industry, we have seen a digital revolution coming in too. Echobox are one of the pioneers in building AI for the publishing industry. Antoine Amann, founder of Echobox, wrote in a blog post that they have “developed an AI platform that takes large quantity of variables into account and analyses them in real time to determine optimum post performance“. Echobox pride itself to currently work with Facebook and Twitter for optimizing social media content, perform advanced analytics with A/B testing and also curate content for desired CTRs. With global client base like The Le Monde, The Telegraph, The Guardian etc. they have conveniently ripped social media editors.
New York-based startup Agolo uses AI to create real-time summaries of information. It initially use to curate Twitter feeds in order to focus on conversations, tweets and hashtags that were most relevant to its user’s preferences. Using natural language processing, Agolo scans content, identifies relationships among the information sources, and picks out the most relevant information, all leading to a comprehensive summary of the original piece of information.
Other websites like Grammarly, offers AI-powered solutions to help people write, edit and formulate mistake-free content. Textio came up with augmented writing which means every time you wrote something and you would come to know ahead of time exactly who is going to respond. It basically means writing which is supported by outcomes in real time. Automated Insights, Creator of Wordsmith, the natural language generation platform enables you to produce human-sounding narratives from data.
The Matchmaker: Connecting people, skills and other entities
AI will make networking at B2B events more fun and highly productive for business professionals. Grip, a London based startup, formerly known as Network, rebranded itself in the month of April, 2016. Grip is using AI as a platform to make networking at events more constructive and fruitful. It acts as a B2B matchmaking engine that accumulates data from social accounts (LinkedIn, Twitter) and smartly matches the event registration data. Synonymous to Tinder for networking, Grip uses advanced algorithms to recommend the right people and presents them with an easy to use swiping interface feature. It also delivers a detailed report to the event organizer on the success of the event for every user or a social Segment.
We are well aware of the data scientist being the sexiest job of the 21st century. JamieAi harnessing this fact connects technical talent with data-oriented jobs organizations of all types and sizes. The start-up firm has combined AI insights and human oversight to reduce hiring costs and eliminate bias. Also, third party recruitment agencies are removed from the process to boost transparency and efficiency in the path to employment. Another example is Woo.io, a marketplace for matching tech professionals and companies.
The Manager: Virtual assistants of a different kind
Artificial Intelligence can also predict how much your household appliance will cost on your electricity bill. Verv, a producer of clever home energy assistance provides intelligent information on your household appliances. It helps its customers with a significant reduction on their electricity bills and carbon footprints. The technology uses machine learning algorithms to provide real-time information by learning how much power and money each device is using. Not only this, it can also suggest eco-friendly alternatives, alert homeowners of appliances in use for a longer duration and warn them of any dangerous activity when they aren’t present at home.
Other examples include firms like Maana which manages machines and improves operational efficiencies in order to make fast data driven decisions. Gong.io, acts as a sales representative’s assistant to understand sales conversations resulting into actionable insights. ObEN, creates complete virtual identities for consumers and celebrities in the emerging digital world.
The Motivator: For personal and business productivity and growth
A super cross-functional company Perkbox, came up with an employee engagement platform. Saurav Chopra founder of Perkbox believes teams perform their best when they are happy and engaged! Hence, Perkbox helps companies boost employee motivation and create a more inspirational atmosphere to work. The platform offers gym services, dental discounts and rewards for top achievers in the team to firms in UK. Perkbox offers a wide range of perks, discounts and tools to help organizations retain and motivate their employees. Technologies like AWS and Kubernetes allow to closely knit themselves with their development team. In order to build, scale and support Perkbox application for the growing number of user base.
So, these are some use cases where we found startups using data science and machine learning differently. Do you know of others? Please share them in the comments below.