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Blockchain’s basic features and characteristics such as being secure, transparent, autonomous, open, decentralized, immutable, permanent and democratic, lend it to be used for many applications and solutions across industry verticals, outside of banking and finance. Photo: iStock
Blockchain’s basic features and characteristics such as being secure, transparent, autonomous, open, decentralized, immutable, permanent and democratic, lend it to be used for many applications and solutions across industry verticals, outside of banking and finance. Photo: iStock

Emerging tech to get a boost in 2018

Artificial intelligence, blockchain and internet of things hit an inflection point in 2017; innovations based on them are expected to scale next year

Deep tech, a term increasingly quoted by investors, is used to describe start-ups or companies whose business is built around unique, differentiated—often protected or hard to reproduce—technological or scientific advances. For instance, a start-up that uses a public or semi-public machine learning (ML) application programming interface (API) would be a technology start-up; and a start-up building a real-time three-dimensional (3D) artificial vision system for autonomous vehicles using its own research and development (R&D), building on advanced math, would be a ‘deep technology’ start-up. This distinction does matter significantly to investors as the business potential of the latter start-up can only be assessed starting with a deep scrutiny of the underlying technology.

The growth dynamics and advanced developments of a trio of emerging technologies—artificial intelligence (AI)/ML, blockchain and internet of things (IoT)—in 2017 have hit an inflection point, enabling deep tech start-ups to go mainstream.

There’s an AI for that: In 2017, AI was used for any and all kinds of applications, including transcribing conversations, writing a movie script from the scratch, writing a chapter of a Harry Potter book by learning from the previous seven books and creating a heavy metal music album—apart from helping companies in their marketing and customer support activities. We are entering the AI version of the popular “There’s an app for that" adage (from the mobile apps era).

The competition between US and Chinese technology giants—Google, Amazon, Baidu, etc.—in the AI space; the focus of semiconductor companies (Nvidia, Intel, etc.) to build AI chipsets; the focus on talent acquisition and increased acqui-hiring in the AI space; and the evolution of ‘conversational user interface’ and voice apps have made AI the most trending tech buzzword of 2017.

Bitcoin’s rise brought blockchain into the spotlight: In 2017, bitcoin evolved from an obscure curiosity to a household name, with its value rising from $1,000 at the beginning of the year to over $19,000 (and counting) by mid-December. While bitcoin’s future is still highly speculative, its exponential rise has put the focus on blockchain, the technology behind bitcoin.

Although blockchain so far has been synonymous with mining crypto-currencies, its basic features and characteristics such as being secure, transparent, autonomous, open, decentralized, immutable, permanent and democratic, lend it to be used for many applications and solutions across industry verticals, outside of banking and finance. In the music industry, we are witnessing the use of blockchain not just for artists’ royalty payments, but also for them to connect and engage with fans. In digital retail, blockchain is enabling easier and faster purchase and transaction of merchandise in peer-to-peer (P2P) marketplaces. Blockchain is also being used in urban transport for ride-sharing applications and traffic decongestion, and in town planning for secure management and monitoring of property records and contracts.

IoT went mainstream in industrial and enterprise sectors: Industrial and enterprise IoT solutions are primarily in smart manufacturing, Industry 4.0, smart grids, oil rigs and refineries, wind farms, retail, logistics, etc. Consumer IoT solutions are being developed in home automation, healthcare, quantified self, sports, automotive, entertainment, etc. In 2017, with lack of standards, interoperability issues, fragmented platforms and scarce funding, consumer IoT companies found it difficult to evolve and scale. Over three quarters of investor funding was directed towards industrial IoT (IIoT) solution providers.

The Indian tech innovation engine was in cleanup mode: In 2017, India has been transitioning through to the second phase of technology start-ups based innovation and investment cycles. Most of the technology innovation (at least at the start-up level) is venture capital (VC) investments-led in India. And there has been continuous consolidation of the first phase consumer internet and mobile start-ups (primarily to cash out the early backers of the ecosystem), and emergence of first-generation, VC investments-backed technology giants—Flipkart, Paytm and Ola. These three companies have not only rapidly influenced and changed the digital consumer dynamics in India but also attracted majority share of VC investments in the country. India, unlike Japan, the US or China, lacks big-name domestic investors, and the technology start-ups in the country are dependent on US-based VCs—and, in the recent past, on China’s Alibaba and Tencent, and Japan’s SoftBank.

As for the innovation in emerging technologies and deep tech, India is lagging behind the rest of the world when it comes to the quantum of innovative products and solutions, primarily due to the lack of requisite expertise and talent, investor risk appetite and founders’ need for early revenue generation.

As for the innovation in emerging technologies and deep tech, India is lagging behind the rest of the world when it comes to the quantum of innovative products and solutions, primarily due to the lack of requisite expertise and talent, investor risk appetite and founders’ need for early revenue generation. Most Indian companies working in emerging tech, especially in AI/ML and blockchain, are service providers or data aggregators (in case of AI start-ups), and only a handful are developing innovative, globally scalable products. Most of the innovation in emerging technologies, especially AI, is happening in-house in the large and well-funded companies—be it Reliance Jio’s investment and focus on advanced analytics, Paytm’s ML-based recommendations and fraud detection, Flipkart’s predictive analytics engine, or IDFC Mutual Fund’s AI-based fund that picks stocks for a portfolio, manages it and suggests exit opportunities.

In 2018, Indian tech companies will primarily innovate for domestic market: Globally, young companies in the emerging technologies space are innovating and developing intellectual property with wide, global adoption potential.

Be it Bite.ai’s two-member team that used advanced clustering algorithms and proprietary support vector machines to vectorize and classify over a million photographs in just two weeks, or Underwrite.ai’s use of AI advancements in genomics and particle physics to provide lenders with non-linear, dynamic models of credit risk that radically outperform traditional approaches in the banking sector, or SingularityNET’s (a decentralized marketplace for AI) aim to solve interoperability issue of AI leading the way for data collaboration, especially for IoT products and solutions—there are rapid advancements and innovation by small teams in various areas of emerging technologies. Indian companies currently lack the requisite vision, expertise, talent and investor confidence to develop such generic solutions in the emerging tech space.

However, in India, in 2018 technology-led innovation and entrepreneurship is expected to solve domestic issues and shift towards middle-India to tap the potential 300-500 million mobile-first consumer segment.

Be it India Stack’s Unified Payments Interface (UPI) and further ‘API-sation’ of banking and payments infrastructure, Metro Bikes’ (a Bengaluru-based start-up) customization of the global success of dockless bicycle sharing through scooter sharing in India, Reverie Technologies’ language-as-a-service platform—for transliteration, input, localization and multi-lingual search—developed for Indic languages—all these initiatives and companies are using emerging technologies such as AI/ML and IoT to solve India-specific problems. And such innovations are expected to scale, capitalizing on the early-mover advantage and capturing market share in India in 2018, before scaling globally. The year 2018 is going to be the year of cautious experimentation for Indian companies.

Jayanth Kolla is a partner with Convergence Catalyst. Disclaimer: He is an advisor and mentor to Metro Bikes in India, and works closely with Underwrite.ai and Bite.ai teams in the US.

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