Thursday, November 30, 2017

How CXOs are Learning to Tackle the Challenges of Multiple Clouds

Five years ago, when messaging and voice communication services provider Solutions Infini Inc. moved its entire information technology (IT) infrastructure to the cloud, the company’s executives believed they would save on operational costs. Chief technology officer (CTO) Ashish Agarwal soon realized that such was not the case. Just two years after the company moved to the cloud, he discovered that “the amount of money we were paying to the cloud providers was quite high for us, as we operate on very slim margins”.

This called for remedial action, following which the company decided to invest in a hyper-converged infrastructure (HCI) system and host these machines at independent data centres.

While a converged infrastructure integrates the computing, storage, networking and server virtualization aspects of a data centre, HCI integrates some additional technologies with the help of software. Agarwal chose Nutanix as the HCI vendor. Other companies that offer HCI systems include Dell Technologies Inc., Hewlett Packard Enterprise Co. and Oracle Corp.

Agarwal reasoned that, “using the front-end of Nutanix’s HCI solution, which is quite simple, we could replicate or mirror our cloud environment with simple clicks”. Solutions Infini now uses a blend of cloud services and the HCI systems hosted at third-party data centres for its application delivery needs.

Solutions Infini’s example is simply a case in point. The fact is that chief information officers (CIOs), CTOs, and other technology decision makers in India are facing challenges related to dealing with multiple cloud computing facilities of companies such as Amazon Web Services, Inc. (AWS), Microsoft Corp., International Business Machines Corp. (IBM) and Google Inc.

Industry experts and analysts are of the view that as more investments pour into cloud data centres, which provide computing, storage and other information technology (IT) infrastructure and services on a pay-per-use basis, CIOs will have to learn how to manage what they say is an “increasingly hybrid” set-up.

There are three models under cloud computing: in public cloud, business applications run completely in a third-party data centre; in private cloud, individual companies operate their own data centres; and in hybrid cloud, they use a mix of the two. Research firm Gartner, Inc. estimates that the public cloud services market in India, which stood at $1.35 billion in 2016, will grow to $1.93 billion by 2017 and further to $4.28 billion by the end of 2020.

According to the firm, hybrid cloud solutions are driving overall cloud adoption in India.

“Cloud adoption is growing strongly in the region, albeit from a low base. Enterprises are adopting both cloud-enabled managed hosting and public cloud services, such as AWS and Microsoft Azure, typically for different use cases,” said D.D. Mishra, research director, Gartner India. “It is getting increasingly common for enterprises to have multiple cloud environments, often operated and supported separately.”

The main issues faced by companies and CIOs, according to Mishra, include “lack of expertise around key areas of hybrid cloud enablement—virtualization, standardization, automation and instrumentation.”

According to Mishra, there is a “lack of guidance” on the technology prerequisites needed to “fully leverage hybrid cloud capabilities”.

He added that the capabilities required typically involve use of “automation and monitoring tools... to not only detect user-impacting problems, but also proactively identify when the service is degrading”.

The growth of virtualization—one of the building blocks of cloud computing—has also given rise to the phrase “software-defined” (software-defined storage, software-defined networking, even software-defined data centre). Virtualization allows a computer to be split into multiple virtual machines (VMs) for running different applications through the use of a sophisticated software called ‘hypervisor’. Companies that provide hypervisor solutions include VMware Inc., Microsoft, Red Hat, Inc., Citrix Systems, Inc. and Nutanix.

“Gradually, it has to be software-defined everything and one operating system (OS) will subsume everything else,” said Dheeraj Pandey, co-founder and CEO, Nutanix, in an interview recently.

“You can get rid of a lot of people in the data centre and optimize your costs when software starts to do a lot of things automatically,” he explained.

He added that the concept that everything is an app is “being replicated into the bowels of the data centre”.

The service delivery model in cloud computing has evolved from companies having their own data centres to hosting their servers in outside facilities, to plain-vanilla or bare-metal infrastructure-as-a-service (IaaS) to software-as-a-service (SaaS), according to Sunil Gupta, executive director and president of Netmagic—an NTT Communications Corp. company that operates a number of cloud data centres across India.

Netmagic, according to Gupta, has integrated multiple cloud offerings from different companies into “a unified managed cloud service”. Towards this purpose, it has developed an “orchestration layer or a cloud management platform” internally over the past couple of years. Moving to the cloud, Gupta said, is not a “zero-to-one story”. It is a “gradual, lengthy journey” and CIOs must keep that in mind.

“The challenge for them is how to migrate their applications smoothly to the cloud with zero or negligible downtime. Then, they also have to tackle what is called ‘shadow IT’ wherein departments other than IT purchased certain cloud applications without even informing the CIO,” Gupta cautioned.

CIOs, according to Gupta, are increasingly moving applications to the cloud—not just email and productivity apps that they began with but also critical ones such as payroll and human resource management apps. Hence, they should plan their cloud migration well in advance. And while planning must be done in a comprehensive way—taking into account storage and other infrastructure requirements—execution should be “gradual”.

According to Gupta, IT heads should also invest in skills for cloud computing such as how to configure and manage hypervisors and hire people who have experience in procuring cloud. “One challenge CIOs face is that different cloud computing companies have different parameters and models for pricing cloud resources, so it makes sense to have technically savvy people in the infrastructure procurement or purchase department who can understand the complexities involved,” he explained.

Mishra of Gartner believes that taking a “consultative approach” is often “a good way to go about implementing one’s cloud strategy.”

CIOs should also look at developing or hiring talent in the areas of automation tools, agile development and cognitive domains, he said.

(This article first appeared on www.livemint.com. 
Image Credit: Pixabay.com)

Friday, October 27, 2017

A Rendezvous with Top Artificial Intelligence Expert, Google's Fei-Fei Li

"We are very far from what is possible in AI": Fei-Fei Li

Google Cloud chief scientist and Stanford prof Fei-Fei Li at a TED talk
Image: Google 
The field of artificial intelligence (AI) has evolved from academic research to one of the biggest drivers of business today, said Fei-Fei Li, chief scientist of Google Cloud and an associate professor in the computer science department at Stanford University. So big, in fact, that she called AI “one of the biggest technologies of the twenty-first century”, while acknowledging her possible “bias as an AI technologist”.

Li should know: one of the top AI experts in the world, especially in the AI sub-domain of computer vision, she and a few other researchers at Stanford are credited with giving the trigger to the “big explosion of AI today.” (http://bit.ly/2uwyb8R) Among other things, she and her associates worked on ImageNet, a huge dataset that now contains over 13 million images of animals, people, products and other ‘objects’ all over the world. The collective effort put up by AI researchers in developing and improving deep learning algorithms over the years has recently made it possible for an AI-powered system to correctly identify and label images with an accuracies of 97% and above--better than the human eye. (Deep learning is a specialty in AI which is based loosely on how neural networks in the brain work.)

“But we are very, very far from all that is possible,” said Li when asked about the problems that still need to be cracked in computer vision. While machines have used the brute computing power and large datasets to solve the issue of “naming objects”, she said that AI would be no match to someone getting up early in the morning and trying to find their car keys, for instance. Describing the properties of objects and figuring out their relationships with each other are still “very difficult” for AI to handle. Elaborating it further, she said that while AI systems have to be trained thousands of times on the same data to “learn something”, children can learn to do that same task easily with just one or two demonstrations—for instance, looking at a tool, they would know where to hold it and can grab it properly whereas AI-based robots would struggle for long.

Nevertheless, Li believes that AI is putting pressure on a lot of repetitive tasks and impacting “the landscape of labour”—something that is only going to accelerate in the next few years as AI capabilities and access to AI tools improve.

“The smart CEOs should be thinking about AI and its impact on their respective business,” she said. They should also be looking at how AI can be adopted or adapted for their industries.

Li was speaking to mediapersons in India through a webcast at Google offices in Delhi, Mumbai and Bengaluru.

She likened the current and future job losses feared from wider applications of AI across industries to similar technological advancements in the past. For instance, she said that while a tool such as spreadsheets made a lot of book keepers redundant (while making them available for other analytical and accounting work), it was “curious” that the human tellers in banks continued to grow in number despite automated teller machines (ATMs). Li said that there has always been interplay between technology and the labour market and it needs the “whole society” to ponder over the question of job shifts in an AI-powered world. “As for me, I’m an optimist,” she said.

Google—like its peers such as International Business Machines Corp. (IBM) and Microsoft Corp.—has of late been opening up application programming interfaces (APIs) that allow coders to use the AI capabilities of the company for developing commercial applications in healthcare, travel, entertainment and media, and several other industry segments.

Li shared a few examples of how the AI interfaces are being used in the real world. For instance, Shazam, a UK-based music service with over 40 million songs in its database uses AI for “audio fingerprinting” which enables it to update its index of popular songs every hour instead of once a day earlier. Some Indian examples include publisher DB Corp, which uses Google Cloud for real-time publishing and uses the speech APIs to capture and document interviews; real estate portal NoBroker.in, which uses Google Vision API to identify rooms and figure out the condition of properties listed on the site; and software solution provider Searce, which has developed an intelligent software called HappierHR for converting paper-based processes into paperless ones.

While the AI technology is improving, Li believes that more and more companies and people need to have access to the AI tools and datasets to be able to get their own projects off the ground—something that Google is evangelizing through what is often termed “the democratization of AI”. Essentially, it involves opening up datasets and machine learning libraries (such as Google’s TensorFlow) to more programmers so that AI-based applications can be built and implemented as quickly as businesses need.


(Note: an edited version of this post first appeared on Livemint.com.)

Sunday, July 9, 2017

How to sit down in meditation

Not happy with how you meditate? Maybe a change in how you sit down could make a difference... 

Image: Pixabay
The thought of writing this post has crossed my mind a few times even as I sat meditating, in the middle of my own attempts to let go of all thought and distraction—but somehow I couldn’t bring myself round to jotting it down.

Today is Guru Purnima, and what better day than the ‘Teacher’s Full Moon’ to give shape to a noble thought! Guru is a Sanskrit word that means one who removes darkness or ignorance, thus allowing the light of knowledge to shine through the disciple’s intellect.

This post assumes that you are convinced of the value of meditation in your life, and perhaps have even had a go or two at it, but are unable to find the peace and tranquillity that meditation entails (If you are curious about what meditation really is, maybe you can find some clues here).

So let’s get on with it, without further ado.

At a very basic level, when you sit down to meditate, all you need is comfortable clothing, a relaxed posture and a decent, quiet place. After all, what could be there to really learn about “sitting down to meditate”?

But, believe me, at a deeper level, there’s a lot to it. And I’m not saying it for the sake of it but drawing upon my close to three years of regular practice (which, by the way, doesn’t make me an expert—though it should lend a bit of credibility to what I’m going to say).

The first thing I would suggest is to review your approach to the whole process of meditation. Are you meditating just because of peer pressure or some vow you want to get over with? Or is it some deeply felt need that has been pulling you close to setting aside some time regularly for being at peace with yourself and your environment? Do you consider meditation more of a physical act or a fad? Or do you realize the involvement of your whole being in its ‘practice’?

As they say of an arduous journey, “Well begun is half done,” so it is with meditation. If you are able to start it on the right note—which essentially means being able to “sit down” in the right frame of mind—you are more likely to get up peaceful, rested or even feeling blessed at the end of your session rather than find yourself wondering what went wrong.

What to do? Let’s do a mock-up. Suppose it is time for you to meditate (while one can meditate any time of the day, I find setting aside a regular time-frame to be of help in developing the practice). Typically, what do you do? Do you sit down hurriedly, put on some music and close your eyes quickly? Start telling beads or chanting some mantra, while shaking your body with each repetition?

Instead, give some time to the process of sitting down. Make sure your surroundings are quiet and comfortable (to the extent possible), you have set your mental clock to the time available for the current session (I vary mine depending on the other tasks and schedule of the day). And last but not the least, sit down in peace, noticing your whereabouts and closing your eyes gradually. (Before you sit, you can play some soothing music if it works for you; it’s fine otherwise too.)

If you need to cough, regulate your unruly breathing or do any fidgety thing to enhance your comfort, do it now. Do not jump headlong into the process of chanting—nor should you worry too much about the flood of thoughts that continues to lap at the shores of your mind even after you shut your eyes.

On the contrary, after slowly closing your external eyes, turn your attention to your mind’s eye and to all the thoughts coming to your mind. Breathe deeply but simply a few times and gradually bring that same attention to the act of inhaling, holding and exhaling of breath. While you do that, pay attention to your spine and try to make it as straight as you can (but hey, straight doesn’t mean rigid or taut like a bowstring!)

Once your breathing has stabilized, the tide of your thoughts has turned to a slow ebb (or almost disappeared) and you are more or less reconciled to your posture, you are ready.

Now, bow mentally before someone or something you highly regard—anything you revere or respect or hold dear to your heart—and be grateful for a moment. Be forgiving, too—of your own self and of the actions right or wrong of others. Sit like this for a while, suspended in thought, space and time—mindful of your breath and thankful of the moment.

Keep still like this, breathe simply, with your back straight and attention relaxed on breathing.

Now you are ready: go on, meditate...


Thursday, May 25, 2017

Artificial Intelligence has long way to go but it's already creating much value: Neil Jacobstein


Neil Jacobstein chairs the artificial intelligence (AI) and robotics track at Singularity University on the National Aeronautics and Space Administration (Nasa) Research Park campus in Mountain View, California. A former CEO of Teknowledge Corp., an early AI company, Jacobstein was in India recently to speak at the two-day SingularityU India Summit (held recently in association with INK, which hosts events such as INKtalks for the exchange of cutting-edge ideas). In an interview, Jacobstein talks about the confusion around AI, how job losses from AI should be tackled and the possibilities of a brighter future for humanity. Edited excerpts:
There are several definitions of AI. Which one is your favourite?
Artificial intelligence allows us to create pattern-recognition and problem-solving capability in a computer, using software algorithms. AI allows us to tackle practical business and technical problems, and it presents an opportunity for us to allow computers to do things that previously only humans did.
There seems to be a lot of confusion about what AI can or cannot do. What is your reading of the prevailing situation?
I think part of the confusion in the market might be that science-fiction movies have given people very vivid and sometimes incorrect view of what AI is capable of doing. Today, we have AI that is already at human levels of problem-solving in very narrow domains such as chess or go (a Japanese board game) or certain kinds of medical diagnostics. But we don’t have human-level AI that is general across the board. So we don’t have AI with natural language understanding at human level, and we don’t have AI that has humour or empathy at human levels. So it’s a kind of mixed landscape.
When do you think will we achieve “true AI”, so to say? What are the challenges to be overcome?
We have already achieved true AI in the sense of creating problem-solvers that add billions of dollars of value every year to various industries. That’s happening now. But if you are referring to artificial general intelligence that is at human levels, I think that probably won’t happen for several years: it could be as early as mid-2020s or as late as 2030s. The critical thing is not the time frame but the consequences of having AI at a human level and what that means for jobs, for global security, and for opportunity to solve problems.
While there are those who believe in the potential of AI and its applications, a sizeable number— including Stephen Hawking, Bill Gates and Elon Musk—have expressed fears that AI-powered machines could rule over humans. What’s your take on this?
To his credit, Elon has changed his views on this over time. He has invested over $1 billion in an entity called OpenAI to democratize access to AI and to create new AI test beds and capabilities that will allow us to build layers of control into AI software. He has also participated in creating conferences on the future of AI and sponsored Future of Life Institute’s conferences around developing new principles of AI safety, the so-called Asilomar 23 principles (futureoflife.org/ai-principles). So he’s interested in capturing the benefits of AI and wants to help us work systematically to reduce the downside risk.
There may be an alarmist element to job losses resulting from AI, but robots are indeed replacing humans. How do you think should the situation be handled?
I think there is a need to anticipate things and to have some empathy and foresightedness for people who will be affected by job losses. For one, the quality of life for the rich people goes down when there are a lot of angry and alienated and armed people around. So it makes sense to think ahead as to how we can educate people doing routine jobs now and, in anticipation of problems downstream, provide access to free, high-quality education. Not everyone will take advantage of that and not everyone will achieve high levels of skill in some new job. So it makes sense to have some kind of basic minimum income and there are different potential schemes for doing that—but nobody knows the exact answer to this.
While Peter Diamandis talks optimistically about the future in his book Abundance, there’s a widening gap between the rich and the poor? Do you think a technology like AI can bridge this gap?
I think rather than focus on the gap, it would be better to focus on the quality of life metrics: do people have access to high-quality, nutritious food? Do they have access to first-rate education or clean water? If you look at the evidence for abundance on Peter’s website or read Steven Pinker’s book, The Better Nature of Our Angels, what’s clear is that in some respects, we are living in the best times for humanity. The challenge is to create a world where, instead of having a world of haves and have-nots, we have a world of haves and super-haves. Now, the gap between haves and super-haves might still be very big, but the haves will at least have things they never had before.
You have spoken about the huge impact of atomically precise manufacturing in nanotechnology. When will it be achieved?
The kind of nanotech we have today is mostly materials science; it’s not molecular machines or atomically precise manufacturing. But I do think we will eventually have atomically precise manufacturing, as we know it’s possible and researchers have demonstrated in the lab the ability to manipulate atoms and molecules with precision. What’s missing is to do it at industrial scale; that may take years.
(Note: This interview first appeared on www.livemint.com.)

Sunday, February 19, 2017

Time: A Poem Written in Prose


There's a time in your life when you are poised on the precipice of eternity. When you have come as far as you have to go.

There is a time when everything seems all right yet all seems so wrong. When you think it doesn't matter as well as it matters the most. There is a time when you waft along effortlessly, balanced between compulsion and free will. When the people around you smile and frown at the same time.

What do you call such times?

There is a time when the light from the Sun seems neither too harsh nor too gentle but just about right to soak up its warmth. A time when you forgive yourself before you set out to forgive others. When you don't hold anything against anyone.

There's a time when you do not want to go too slow or too fast but just walk on without any thoughts of time, space or greed for speed. There is a taste in your mouth some call bittersweet, but which can perhaps better be described as divine. For it's a taste not only on your tongue; it is felt also on your skin and in your ears and perceived in your gaze and percolated right into the core of your being...That's when you know you have arrived somewhere you always wanted to be, where you know you always should have been living.


That time, that place, that wonderful moment can only be described in one word. And that single powerful word, my dear friend, is what gives the utmost meaning to our life: Now.

(Image credit: http://getrefe.tumblr.com/)