27-Oct MiniRoundTable on WhyAI for B2B SaaS

The MiniRT Agenda

  • Seeding & creating an active discussion on Why AI/ML? What is the higher order value being created?
  • How to identify the value & opportunities to leverage AI?
  • How to get started with an AI playground (if not already running)?
  • How to think of data needs for AI/ML investments,
  • How to address the impact on Product & Business…

This is part of our AI/ML roundtables for B2B SaaS. Insights from these sessions are meant to help refine our approach & readiness to leverage AI/ML for building higher order value products. And in doing so building a vibrant community focused around navigating this shift.

Click to Register for the AI/ML Playbooks Track. (limited invites)

Our Mavens

Adarsh Natarajan

Founder & CEO AIndra

 

Notes

This is a product startup founder/CXO (+1) invite-only events. Venue details will be sent along with the confirmation of your registration.

RoundTables are facilitated by an iSPIRT maven who is an accomplished practitioner of that Round-Table theme. All iSPIRT playbooks are pro-bono, closed roomfounder-level (+1), invite-only sessions. The only thing we require is a strong commitment to attend the sessions completely and to come prepared, to be open to learning & unlearning, and to share your context within a trusted environment. All key learnings are public goods & the sessions are governed by the Chatham House Rule.

18-Oct MiniRoundtable on AI/ML Tools & ML/DL challenges

The MiniRT Agenda

  • The current state of AI/ML tools & frameworks.
  • Share & discuss ML & Deep Learning challenges in your products.

Insights from these sessions are meant to help refine our approach & readiness to leverage AI/ML for building higher order value products. And in doing so building a vibrant community focused around navigating this shift.

Click to Register for the AI/ML Playbooks Track. (limited invites)

Our Maven: Viral Shah
Co-creator of Julia Language,
Co-founder Julia Computing

Notes

This is a product startup founder/CXO (+1) invite-only events. Data scientist leads in a product startup are also welcome to register. On confirmation, the venue details will be sent along with the confirmation of your registration.

RoundTables are facilitated by an iSPIRT maven who is an accomplished practitioner of that Round-Table theme. All iSPIRT playbooks are pro-bono, closed roomfounder-level (+1), invite-only sessions. The only thing we require is a strong commitment to attend the sessions completely and to come prepared, to be open to learning & unlearning, and to share your context within a trusted environment. All key learnings are public goods & the sessions are governed by the Chatham House Rule.

6-Oct MiniRoundTable on WhyAI for B2B SaaS

The MiniRT Agenda

  • Seeding & creating an active discussion on Why AI/ML? What is the higher order value being created?
  • How to identify the value & opportunities to leverage AI?
  • How to get started with an AI playground (if not already running)?
  • How to think of data needs for AI/ML investments,
  • How to address the impact on Product & Business…

Insights from these sessions are meant to help refine our approach & readiness to leverage AI/ML for building higher order value products. And in doing so building a vibrant community focused around navigating this shift.

Click to Register for the AI/ML Playbooks Track.

Notes

This is a product startup founder/CXO (+1) invite-only events. Venue details will be sent along with the confirmation of your registration.

RoundTables are facilitated by an iSPIRT maven who is an accomplished practitioner of that Round-Table theme. All iSPIRT playbooks are pro-bono, closed roomfounder-level (+1), invite-only sessions. The only thing we require is a strong commitment to attend the sessions completely and to come prepared, to be open to learning & unlearning, and to share your context within a trusted environment. All key learnings are public goods & the sessions are governed by the Chatham House Rule.

AI/ML is not Sexy

One would think that the new sexy in the startup capital of the world is self-driving cars, AI/ML… I got news for you! AI/ML (esp. Machine Learning) is not listed in Gartner’s hype cycle for 2018.

Source: https://commons.wikimedia.org/wiki/File:Hype-Cycle-General.png

This was corroborated on my recent trip to the valley and the US east coast, where I met several investors, founders, corp dev and other partners of the startup community. It was evident that the AI/ML hype which peaked in 2016 & 2017 is no longer considered a buzzword. It is assumed to be table stakes. What you do with AI/ML is something everyone is willing to listen to. Using AI/ML to solve a high-value B2B SaaS problem is Sexy! (Gartner trends for 2018).

As the hype with AI/ML settles down, B2B startups across the globe are discovering the realities of working the AI/ML shifts for SaaS. Many AI tools & frameworks in the tech stack are still evolving and early pioneers are discovering constraints in the stack and creatively building workarounds as they build their products.

Many entrepreneurs are watching from the sidelines the unfolding of the AI/ML hype, wondering on many valid questions like these (and more):

Q: Do I have to stop what we are building and jump onto the AI bandwagon? No.
Q: Are the AI/ML resources mature & stable to build better value products? No, they are still evolving.
Q: Do I need expensive investments in constrained resources? No, not until you have a high-value problem to solve.

B2B SaaS startups go through 2 key struggles. How to find market-fit and survive? And how to stay relevant and grow. And if you don’t evolve or reinvent as the market factors change, there are high chances for an upstart to come by and disrupt you. The iSPIRT entrepreneur playbooks look to help entrepreneurs get clarity on such queries and more. Our goal is to help our startups navigate such market shifts, stay relevant and grow. Our mini roundtables Playing with AI/ML are focused on WhyAI for SaaS discussions in multiple cities. If you or a startup you know may benefit do register

The MiniRT Agenda

Seeding & creating an active discussion on Why AI/ML? What is the higher order value being created? How to identify the value & opportunities to leverage AI? How to get started with an AI playground (if not already running)? How to think of data needs for AI/ML investments, How to address the impact on Product & Business… Insights from these sessions are meant to help refine our approach & readiness to leverage AI/ML for building higher order value products. And in doing so building a vibrant community focused around navigating this shift.

Upcoming PlaybookRTs on AI/ML

6-Oct (Chennai) 10 am – 1 pm – MiniRoundTable on WhyAI for B2B SaaS – Shrikanth Jagannathan, PipeCandy Inc
18-Oct (Bangalore) 6 pm – 8 pm MiniRoundTable with Dr Viral Shah on AI/ML Tools & discuss your ML/DeepLearning challenges
27-Oct (Delhi/Gurgaon) 2 pm – 6 pmMiniRoundTable on WhyAI for B2B SaaS, Adarsh Natarajan, CEO & Founder – Aindra Systems
TBD (Bangalore)MiniRoundTable on WhyAI for B2B SaaS, (based on registered interest)
TBD (Mumbai)MiniRoundTable on WhyAI for B2B SaaS, (based on registered interest)

The AI+SaaS game has just begun and it is the right time for our hungry entrepreneurs to Aspire for the Gold, on a reasonable level playing field.

Click to Register for the AI/ML Playbooks Track.

Please note: All iSPIRT playbooks are pro-bono, closed room, founder-level, invite-only sessions. The only thing we require is a strong commitment to attend all sessions completely and to come prepared, to be open to learning & unlearning, and to share your context within a trusted environment. All key learnings are public goods & the sessions are governed by the Chatham House Rule.

Image source: https://commons.wikimedia.org/wiki/File:Hype-Cycle-General.png

Interesting Reads

The slow, light touch of AI in Indian Saas

First AI/ML Playbook Roundtable – Playing With the New Electricity

This is a Guest post by Krupesh Bhat (LegalDesk) and Ujjwal Trivedi (Artoo).

AI is seen as the new electricity that will power the future. How do we make the best of the opportunity that advancements in AI technology brings about? With this thought in mind iSPIRT conducted a symposium roundtable at the Accel Partners premises in Bengaluru on March 10th. Accel’s Sattva room was a comfortable space for 20+ participants from 11 startups. There were deep discussions and a lot of learning happened through subject matter experts as well as peers discussion. Here’s a quick collection of some pearls, that some of us could pick, from the ocean of the deep discussions that happened there.

Products that do not use AI will die soon. Products that use AI without natural intelligence (read common sense) will die sooner.

– Manish Singhal, Pi Ventures

Starting with that pretext, it isn’t hard to gather that AI is not just a promising technology, it is going to be an integral part of our lives in near future. So, what does it mean for existing products? Should everyone start focusing on how they can use AI? Are you an AI-first company? If not, do you need to be one? After all, it does not make sense to build the tech just because it appears to be the next cool thing to do. If you are building AI, can you tell your value proposition without mentioning the word AI or ML? have you figured out your data strategy? Is the need driven by the market or the product?

Before we seek answers we must clarify that there are two types of products/startups in the AI world:

First, an AI-first startup – a startup which cannot exist without AI. Their solution and business model is completely dependent on use of Artificial intelligence (or Machine Learning at least). Some examples of such startups in local ecosystem are Artifacia and Locus.sh.

Second, AI-enabled startup – startups with existing products or new products which can leverage AI to enhance their offering by a significant amount (5x/10x anyone?). Manish has a very nifty way of showing the AI maturity of such companies.

The session was facilitated by several AI experts including Manish Singhal of pi Ventures, Nishith Rastogi of Locus.sh, Shrikanth Jagannathan of PipeCandy, Deepak Vincchi of Julia Computing.

Maturity Levels of AI Startups

After a brief introduction by Chintan to set the direction and general agenda for the afternoon, Manish took over and talked about the various stages of AI based companies. Based on his interactions with many startups in the space, he said there are roughly four growth stages where different companies fall into:

Level 1No Data, No AI: An entity that solves a business problem and is yet to collect sufficient data to build a sustainable AI business. The AI idea will die down if the company fails to move to state 2 quickly. Business may be capturing data but not storing it.
Level 2Dark data, No AI: The company holds data but is yet to build solid AI/ML capabilities to become an AI company. There is a huge upside for such companies but the data strategy needs to be developed and AI capabilities are not mature enough to be considered as an AI/ML company.
Level 3Higher automation driven by data and AI: These are the companies that have built AI to make sense out of data and provide valuable insights into the data using AI/ML, possibly with some kind of human assistance.
Level 4Fully autonomous AI companies: These are the companies at the matured stage where they possess AI products that can run autonomously with no human intervention.

Manish also noted that most companies they meet as a VC are in level 1 and 2, while the ideal level would be 3 and 4. He noted that AI comprises of three important components: Data, Algorithm & the Rest of the System that includes UI, API & other software to support the entire system. While it is important to work on all three components, oftentimes, the data part doesn’t get enough importance.

Do You Really Need Artificial Intelligence?

A whole bunch of solutions are smart because they are able to provide additional value based on past data. These are not AI solutions. They are merely rule based insights. Nishith from Locus added that there is nothing really wrong with rule based systems and in a lot of cases AI is actually an overkill. However, there are two cases where it seems apt for startups to look at AI for their predicament:

  1. Data is incomplete: An example of this is Locus who gets limited mapping for gps coordinates and addresses.
  2. Data is changing constantly: A typical case was of ShieldSquare where bots are continuously evolving and improving and the system deployed to identify them also needs to learn new patterns and evolve with them.

It is important to have clarity on your AI model especially when you communicate with your internal teams. Figure out what is the core component of your product – AI, ML, Deep Learning or Computer Vision.

What’s Driving Your AI Approach?

There are two major driving forces that can help one in deciding whether to AI or not to AI.

  1. PUSH: The internal force when decision can largely be taken if your business is sitting on a lot of useful data, may be as a side effect of your key proposition.
  2. PULL: The external market driven force where clients expect or ask for it e.g chatbots. We are already observing that AI can be a great pricing mechanism.

However, take great caution when using Customer data or Derived data, it depends on legal agreement with clients and can get you into legal troubles if it violates any terms.

Is Your Data Acquisition Strategy in Place?

Anyone interested in AI should have a data acquisition strategy in place. Here are a few points that can help you get one in place:

    • What data do you collect, How do you validate it, Clean it and store it for further analysis?
    • Surveys and chatbots can provide a steady stream of data if built correctly
    • Think of data as a separate entity (has its own lifecycle), it may help to think of it as a currency and plan how you would earn, store and utilise it
    • Capturing location, user interaction data can be insightful. This may include the interactions user has committed and the ones they have not committed (deleted/skipped/hidden)
    • It makes sense to invest time, resources and people to gather data properly
    • Have a unified warehouse (can start with economical options like Google Analytics and AWS)

It is also important to give some thoughts on how you are using aggregate data across the platform. In case, if your AI model uses a combination of customer specific data and the sanitised aggregate data available in the platform (“Derived Work”), then you should make sure that you have the permission to use such data. Without such clarity, you may run into legal issues.

Deepak Vincchi explained how Julia Computing is emerging as the programming language of choice for data scientists. The platform can process 1.3 million threads in parallel and is used by large organizations to crunch data problems.

In all this was an extremely engaging 3 hours without break. Guiding the session with real examples by Nishith, Shrikanth and also shared learnings from Navneet and others really helped bring to life Why AI and How AI. This symposium is part of an AI playbooks track was aimed at kickstarting cohorts of startups ready to jump with AI and help them get traction with AI, more will emerge on this shortly.

10 startups attended this mini-roundtable session – Acebot, Artifacia, Artoo, FusionCharts, InstaSafe, Klove, LegalDesk, Rocketium, Rubique, ShieldSquare.

Thanks to volunteers Rinka Singh and Adam Walker for their notes from the session and Ankit Singh (Mypoolin/Wibmo) for helping coordinate the blog post & note

* All iSPIRT playbooks are pro-bono, closed room, founder-level, invite-only sessions. The only thing we require is a strong commitment to attend all sessions completely, to come prepared, to be open to learning & unlearning, and to share your context within a trusted environment. All key learnings are public goods & the sessions are governed by the Chatham House Rule.

Featured photo by Matan Segev from Pexels https://www.pexels.com/photo/action-android-device-electronics-595804/

Playing with the new Electricity – AI/ML Playbook Sessions [March Update]

[Update 29-Mar] New April Session Dates – Symposium RT is being scheduled for Bangalore & Chennai (21st & 28th April). 

“Tectonic” market shifts happen every few years creating a change in landscape, market and opportunity. The most recent “tectonic” shift is the emergence of the Artificial Intelligence era. In just the same way electrification in the early 1900s transformed major industries globally, AI, Machine Learning & Deep Learning are poised to transform a multitude of industries, services & products.

It took 100 years from the discovery of electrical generator to electrification of industries. AI is doing this in a span of 70 years (from the time of the Turing Test).

AI/ML has gone through many winters and is now in its eternal spring. It portents a new framework for startups to navigate and evolve from an internet era startup into an AI era startup.


Every new era shift begins with a lot of smoke and hype before it is well understood. iSPIRT ProductNation & Julia are launching a set of AI/ML playbook roundtable & workshop sessions to dispel the hype around AI, and help bring a pragmatic mindset & process change necessary for product startups to leverage AI/ML. We believe AI is not just a technology shift. It is a combination of product, business, and technology shift. Adapting to it requires a new paradigm of thinking to build a viable value strategy. This needs to be done mindfully and in context of the value you offer to the customer, do not rush in with the AI hype.

These multi-step playbooks are for all categories of startups regardless whether they are AI-First or SaaS, and MarTech, FinTech, HealthTech or any other <Domain>Tech category, startups who are looking to deliver a higher order value to their customers by leveraging and applying AI models with their data.

Since AI/ML is still in its early years there aren’t any proven success playbooks. Hence these deep sessions will bring together AI experts, AI Mavens (entrepreneurs who are more ahead in their AI journey), iSPIRT Mavens, and selected startups, to discuss & share their insights, challenges & learnings on the mindset shifts outlined above and best practices adopted. The 2-step playbook roundtable sessions focused on founders (+1 typically CXO) and a hands-on lab workshop are a sequence of:

    • AI/ML Symposium RT (step 1) – An invite-only 3 hour mini-symposium playbook with AI/ML experts, first mover AI leaders & Mavens from our startup community and 10-15 invited startups, focusing on Why AI/ML? What was the higher order value being created? How to identify the opportunities to leverage AI? What do you need to get started with AI (if not already running)? Data needs for AI/ML investments… The shared awareness created in this session, combined with the commitment by startups to articulate their AI/ML opportunity, and detail their approach will lead to the next AI/ML roundtable.
    • AI/ML Playbook RT (step 2) – Startups at similar AI readiness from the Symposium will be invited for a 5-hour deep-dive roundtable discussion on the AI/ML challenges in the context of the startup domain, effectively going through their AI/ML readiness & approach (a review & teardown). Topics would emerge from the Symposium RT and could cover data collection & modeling strategy, AI transformation algorithms, Business model innovation, Success metrics… This session is restricted to 5-6 startups (having similar AI needs) per roundtable and an AI Maven to facilitate the topics & discussion. Possible outcomes for each startup would be to develop an action plan/checklist for next few months of execution. Additionally, startups can identify a tiger tech team to go to the AI/ML Training Lab to get traction for their checklist…
    • AI/ML Training Lab with Julia Sandbox (optional) – A 3+ day workshop intended for the 3-4 person tiger tech teams (CTO, Engg, Data guy, PM…) from each startup. The workshop will help focus on building competency, getting traction & executing implementations related to the checklist developed at the roundtable.

For the first set of these playbooks, we are inviting nominations/applications for startup founders (+CXOs) who are either directly focusing on AI-based opportunity or have started integrating AI/ML as a core strategy for their product growth/success. Please provide your nomination for startups you believe should be part of the first series of the AI/ML playbooks. If you are a startup and interested to be part of this please register below. On final approval, an invite confirmation will be sent via email.

Please submit your nominations here. A registration link will be sent to your nominee.

Dates & Venue for the first of the series:

AI/ML Symposium RT #1 – 10th Mar (Sat) 2p – 5p Done
AI/ML Symposium RT #2 – 21st Apr (Sat) 11a – 2p @ Bangalore TBD
AI/ML Symposium RT #328th Apr (Sat) 10a – 1p @ Chennai TBD
AI/ML Playbook RTApr-TBD (Sat) 11a – 5pm @ Bangalore TBD
AI/ML Training Lab w/ JuliaApr-TBD @ TBD (Bangalore)

While the sessions are in Chennai/Bangalore, we believe this topic is of emergent interest to startups across the country and would invite all to register.

AI Mavens

Ashwin Ramasamy – PipeCandy
Manish Singhal – pi Ventures
Nishith Rastogi – Locus.sh
Shrikanth Jagannathan – PipeCandy

Cost

All iSPIRT roundtables are pro-bono (read below for how that works)

This series of playbooks is being setup by active support from our Mavens & Volunteers – Ankit Singh, Deepak Vinchhi, Karthik KS, Praveen Hari, Ravindra Krishnappa, Sandeep Todi.

P.S. Some great material for pre-reading

I strongly recommend all to go through many of these.

* All iSPIRT playbooks are pro-bono, closed room, founder-level, invite-only sessions. The only thing we require is a strong commitment to attend all sessions completely and to come prepared, to be open to learning & unlearning, and to share your context within a trusted environment. All key learnings are public goods & the sessions are governed by the Chatham House Rule.

* The Julia team is on a social mission to train a large number of people in India to develop grassroot skills and competency with AI & ML.

+Feature image from https://www.flickr.com/photos/gleonhard/34046647175/

Deep Learning Session with Julia Computing

robot-2167836_640

An evening with Julia

iSPIRT, in association with Julia Computing, is proud to announce an open-session with Prof. Alan Edelman and Dr. Viral Shah, co-creators of Julia, an open source programming language, and co-founders of Julia Computing Inc.

The event will be hosted in Koramangala, Bangalore, on the 22nd of January 2018, from 5 – 7pm. Register now for an invite to the session or to join the live cast (venue details will be shared along with the invite).

What is Julia?

Julia is a modern, high-level, high-performance programming language for numerical computing, data science and AI. With syntax that is familiar to users of other technical computing environments, Julia solves the eternal two language problem, by providing productivity similar to Matlab or R, and performance similar to C for writing mathematical and statistical software. Julia is open source, its research is anchored at MIT since 2009 and is growing very rapidly in its adoption across industries, from Finance to Life Sciences.

Julia … can even be used by those who aren’t programmers by training

Why Should You Care?

Julia’s deep mathematical roots and comprehensive customizability make it very friendly to work with for data scientists, who are generally limited with popular Machine Learning approaches due to their issues with customizability and efficiency.

This 90 minute session will cover a quick introduction to Julia, showcase a few challenging and compute-intensive case studies that Julia has helped solve across domains, and demonstrate how Julia as a framework is used to enable nextgen AI & ML modeling & computing with the AI tools of your choice, including popular libraries like Mocha, MXNet and TensorFlow. This will be a great opportunity to interact with Prof Alan and Dr. Viral on best ways to approach an AI/ML strategy.

About the Speakers:

Prof. Alan Edelman is a Professor of Applied Mathematics, Computer Science and AI at MIT. He is a co-creator of Julia language, and a Co-founder and Chief Scientific Officer of Julia Computing, Inc.

Dr. Viral Shah is a co-creator of Julia language, and a Co-founder and CEO of of Julia Computing, Inc. He has been an important part of Aadhaar team from 2009 to 2014, and has co-authored a book called Rebooting India with Nandan Nilekani.

Julia Computing was founded in 2015 by the creators of the open source Julia language to develop products and provide support for businesses and researchers who use Julia.

Register now for an invite to the session or join the live cast.

Also, Workshop will be streamed on Youtube live for those who can join us virtually. The Invite will be shared on 21st Jan 2018 with the registered participants.

Are AI and Automation dirty words for some?

Man being replaced by machines has been a topic very well documented in our academic and social history. While, designing machines that can replicate human intelligence is ‘the dream’ for many, the idea has seen its fair share of resistance from anxious workers afraid to lose their livelihood. It would be a mistake to think that the phenomenon is only very recent. The Luddite movement, which began in Nottingham in 1811, was named after a disgruntled weaver who broke two stocking frames in a fit of rage. Destruction of machinery, as a form of protest, was carried out throughout England by groups of English textile workers and self-employed weavers. Since then, the term ‘Luddite’ has become a reference to someone opposed to industrialisation, automation, computerisation or new technologies in general.

Back to the 21st Century, Infosys’s human resources head Krishnamurthy Shankar has revealed that the company had “released” 8,000-9,000 employees in the last 12 months due to automation of lower-end jobs. The employees are not necessarily jobless and have been retrained and absorbed to carry out ‘more advanced projects’. The company also reduced its hiring in the Jan to December 2016 period to 5,700 compared to 17,000 in the first nine months of previous fiscal year. Infosys is not alone in their journey towards automation. Most Indian and global IT services companies are investing in automation of processes in their core businesses such as Application Management, Infrastructure Management and Business Process Management (BPM).

India’s IT giants are leaving no stones unturned to fill the gaps in their digital portfolio of products and services. The subjects of Internet of Things, Cloud, Artificial Intelligence and Automation figure high on each company’s organic strategy and also in their shopping list for inorganic growth (Table 1).

Table 1: Select Digital Acquisitions by Indian IT majors

Acquirer Target Value

(USD mn)

Brief
Infosys Panaya 200 Provider of automation technology for large scale enterprise software management
Wipro Healthplan Services 460 A technology and Business Process as a Service (BPaaS) provider in the U.S. Health Insurance market
Wipro Appiro 500 A services company that helps customers create next-generation Worker and Customer Experience using the latest cloud technologies
Infosys Skava 120 A provider of digital experience solutions, including mobile commerce and in-store shopping experiences to large retail clients
Tech Mahindra The BIO Agency 52 UK-based digital transformation firm
Tech Mahindra Target Group 164 A provider of business process outsourcing and software solutions

Automation is heralding the age of Industry 4.0 which is characterised by a diminishing boundary between the cyber and physical systems. In October 2016, World Bank research announced that Automation threatens 69 % of the jobs in India, while 77% in China. Google’s AI research lab, Google Brain is working on building AI software that can build more AI software. I wouldn’t blame anyone if they started thinking about the Skynet from Terminator or the writings of James Barrat – Our Final Invention: Artificial Intelligence and the End of the Human Era.

As per research by Gartner, IT process automation (ITPA) is very underpenetrated (only 15-20%) and will move towards maturity over the next 5-10 years. Most leading vendors in the IT services space have launched an automation platform to boost delivery efficiency.

Table 2: Automation/ AI Platforms of Indian IT Players

Company Platform Offerings
Wipro Holmes An artificial-intelligence platform built on opensource computing aimed at optimising resource utilisation and reducing costs
Infosys Aikido Enables creation of intelligent robots that can resolve incident related to customer orders
TCS Ignio An Artificial intelligence-based automation platform which automates and optimizes IT processes within an organisation.
Tech Mahindra Carexa Uno Customer care, with agent virtualisation, analytics, assisted

interactions and digital channels.

HCL Technologies DryIce A digital service exchange platform enabled by ServiceNOW

Source: NASSCOM, Edelweiss

Platforms based on novel technologies will minimise the human effort required. Are the coders coding away their jobs then? Thankfully, there are learned people who believe otherwise. As per NASSCOM, the future may not be as dire. There is a distinct possibility that repetitive and labour intensive jobs such as data entry and testing may get completely automated, but there will be augmentation of cognitive jobs. New roles will emerge which will focus on training, learning and maintenance requirements of AI systems. Indian companies will also need to invest in re-training its employees or importing talent in the short term. In the long term, a joint effort with technology schools such as IITs and IISc will be needed to build a supply chain of talent. 65% of Google DeepMind’s hires were directly from academia.

The Indian IT services sector is worth approximately USD 150 billion, and it is largely export dependent. The Indian players need to enhance their digital capabilities to compete globally. Automation is a key area of this digital growth and so is the evolution of skilled workforce and their job profiles. The fear of technology destroying all the jobs is as unreasonable now as it was in the 18th century. Also, it is evident from history that technology has always led to creation of more jobs than it has destroyed.

The workforce engaged in IT services by nature is flexible and open to evolving work profiles. Workers in some other sectors may not have that option, especially at the jobs requiring less complexity. HDFC bank just announced that it has witnessed a head count reduction of 4,500 due to efficiency improvements and attritions in the last quarter alone. The Bank is planning to install up to 20 humanoids named “Íra” at its branches in the two years to assist customers. Ira has been developed by Kochi-based Asimov Robotics and the company has already received queries from airports, hospitality industry and retail chains to deploy similar humanoids. It would be a good move for all professionals in all sectors to ask themselves – “Can a Robot do my job?”, and upgrade their professional skills accordingly.

arvind-yadav

 

This is a guest post by Arvind Yadav,

Principal at Aurum Equity Partners LLP.

 

 

 

 

 

Industry 4.0: The New Normal

In case you are a manufacturing company beginning to explore how investment into Artificial Intelligence and Internet of Things could help your top and bottom lines, you may already have fallen behind. The fourth industrial revolution or the ‘Industry 4.0’ is already upon us and the opportunities to completely transform the way we carry out production are limitless. Industry 4.0 may be broadly defined as a collective term for a number of contemporary automation, data exchange and manufacturing technologies. It is characterised by a diminishing boundary between the cyber and physical systems to enhance productivity and reduce costs. ‘Smart’ and ‘Connected’ are two of the most important keywords in the new industry universe. Smart takes us into the domain of Artificial Intelligence (AI) while ‘Connected’ is more a purview of ‘Internet of Things’ (IoT).

screen-shot-2016-12-08-at-4-26-39-pm

‘Smart’ – A detour into Artificial Intelligence

AI finds its roots way back in 1956 when the name ‘Artificial Intelligence’ was adopted or even further back with Alan Turing in 1950 or in 1943 when McCulloch & Pitts introduced the Boolean circuit model of brain. It’s still however, a little difficult to settle on one universal definition of AI. For our purpose we may define AI as the development of computer systems able to perform tasks normally requiring human intelligence. These may include (but are not limited to) visual perception, speech recognition, decision-making, and translation between languages. More passionate people define AI as the ability to ‘solve new problems’.

The lack of one single definition has not detracted investors from recognizing the potential of AI and they have been pouring in money like never before. As per Zinnov Consulting, in the last 5 years alone, investments in AI have grown ten-fold from USD 94 million in 2011 to USD 1billion in 2016. As per CB Insights, the equity investments in AI were North of USD 2 billion in both 2014 and 2015. We may attribute different ways of defining AI to different investment figures, however we can agree that investments have sky rocketed. While, Venture capital firms have obviously been at the forefront in backing early stage companies, the high corporate interest in acquiring AI start-ups has also led to a buzz in the M&A markets. Some of the biggest acquirers in AI include Google, Apple, Salesforce, Amazon, Microsoft, Intel and IBM.

India is holding its own in terms of AI related action. As per Zinnov, India has emerged as the 3rd largest AI ecosystem in the world with 170 start-ups. Niki.ai, SnapShopr, YANA, HealthNextGen, Aindra Systems, Hire Alchemy are some of the notable firms trying to disrupt the value chain across sectors. Global technology companies have acquired more than half-a-dozen India based AI start-ups in the last 18 months. It’s not all one way traffic. Indian IT services firms like Infosys (UNSILO, Cloudyn, TidalScale) and Wipro (Vicarious, Vectra Ventures) have been looking for targets abroad to augment their AI capabilities.

Table 1: AI use cases across sectors

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‘Connected’ – the Industrial IoT

The Industrial Internet of Things refers to the network of equipment which includes a very large volume of sensors, devices and “things” that produce information and add value to the manufacturing processes. This information or data acts a feed to the AI systems. As per Cisco, 50 billion devices will be connected by 2020 and 500 billion by 2030. McKinsey projects that IoT will generate 11% of global GDP by 2025. This is driven by optimising industry performance and cost efficiencies.

 

IIoT on the Factory Floor

The global IIoT spending is estimated at USD 250 billion and is expected to reach USD 575 billion by 2020. The key components of the IIoT ecosystem include sensors/modules, connectivity, customisation, and platform/IoT cloud/applications.

As per NASSCOM, The Indian IoT market is expected to reach USD 15 billion with 2.7 billion units by 2020 from the current USD 5.6 billion and 200 million connected units. This is expected to be largely driven by applications in manufacturing, automotive and transportation and logistics.

In India, the IIoT segment has caught the attention of the largest manufacturers. In November 2016, Reliance and GE announced a partnership to work together to build applications for GE’s Predix platform. The partnership will provide industrial IoT solutions to customers in industries such as oil and gas, fertilizers, power, healthcare and telecom. Mahindra & Mahindra’s uses bots to build car body frames at its Nashik plant. Plants operated by Godrej and Welspun use the Intelligent Plant Framework provided by Covacis Technologies to run their factory floors.

Industry 4.0 is an exciting phase and the possibilities seem limitless. The Indian government is trying to play its part through the Digital India mission. It is positively driving various government projects such as smart cities, smart transportation, smart grids, etc. which are also expected to further propel the use of IoT technology. It is imperative for the promoters and companies in the manufacturing segment to find their place in the new digital world order through organic or inorganic investment.

arvind-yadav

 

 

 

This is a guest post by Arvind Yadav,

Principal at Aurum Equity Partners LLP.