Industry analysis and opinion
Smartphones play a vital role in our life; it is sort of panacea for us. It has achieved massive growth in the last decade. With such demand of the end product, it is obvious that the supply side has worked in overdrive. Semiconductor industry has seen massive growth due to smartphones. The number of OEMs increased to fulfil the volume demands, pulling more vendors into semiconductor industry to suffice the OEMs’ supply chain requirements.
A few OEMs made fortune in smartphone sales, with revenue exceeding billions cumulatively. Such capital inflow encouraged them to invest more money on product development, to fulfil the end users’ paradoxical requirement of more performance with more battery life (less power consumption) at a lower price. With cumulative silicon sales going into billions, the semiconductor industry responded positively, and focused on stretching the innovation into leading process nodes and other techniques to enhance performance.
If there's one thing that's unique about being human, we can't deny that it's speech. Sure, animals have a way of communicating but that's not in any way as refined as we humans do. The key lies in the way we are able modulate sound waves with the rolls and wags of our tongue. Perhaps, it's for this reason we have phrases such as "mother tongue". Aural communication in the rest of the animal kingdom is limited to coarse sounds that we simply name as moos, grunts and hee-haws. But it's not going to be long before we lose our monopoly of speech.
The best machines could do in the past were beeps and alarms. Those of us who have lived through the times of early fixed line modems can recall the staccato of beeps as they tried to handshake and establish a connection to a server somewhere on the internet. Of course, machines also talk among themselves silently, by parsing bits and bytes. But now the time has come for machines to talk directly to humans via human speech.
Ever watched the Ted talk by Simon Sinek, How great leaders inspire actions? Not yet? Then I encourage you watch this 20-minute talk. This video covers the most fundamental thing that most companies fail to address: connecting with customers! Often companies focus on their products, going into details about the technical features, price, engineering innovation, etc. However, they fail to address the basic thing that is needed for a successful sale: Why they are offering the product? Answering this question bridges the gap between product and market. Revenue is an outcome, not the sole purpose of a company’s existence.
Let us take an example of a conventional sales pitch for the embedded computing platform: System on Module (SoM).
“We offer SoM that has a SoC, memory, power circuitry, Operating System, and BSPs, all integrated on a small form-factor board that offers you a platform for building your next embedded product”.
Sounds exciting? Well, it depends. However, it does not generate a great interest. Now, how about the following as a sales pitch?
The new kid on the block
The emerging IoT industry is an aggregation of products and services, complementing each other to enable efficiency and cost optimization in multiple industries. It does not have a vertically oriented value chain. IoT end nodes will be scattered in billions in various industries.
As mentioned in my earlier post ARM vs Intel: The new war frontiers, COTS processors will not be ideal for building these end nodes, as the latter are application specific. Companies would be inclined to adopt custom processors as they offer flexibility to assemble only required parts. These parts can include analogue sensor, DSP, proprietary IP, etc. Further, custom processors substantially reduce BoM cost and die size, which will minimize power dissipation. It also helps companies to differentiate their product from those of their competitors. In view of failing Moore’s Law, customization is the answer as it can reduce the BoM cost significantly.
Takeaways from Intel AI Developer Workshop @ Bangalore
Images in this article are copyright of Intel.
I just returned from a full-day developer workshop organized by Intel. The focus was on Artificial Intelligence (AI) and how Intel is contributing in mankind's best efforts to teach machines to sense, reason and decide. The event was a useful peek into what Intel is bringing to the table in terms of both hardware and software. Beyond that, it was not an event that I would call a developer workshop since there were no hands-on sessions, demos or even tips and tricks that developers can use. The event was structured as a line of talks in order to bring awareness of Intel's involvement in AI and where the market is headed.
AI originated in the 1950s but it was only in the 1980s when Machine Learning (ML) came about that people started to think it might be possible to realize AI. Machines can be trained and then asked to solve problems. Their algorithms could be tweaked as they learn and relearn with more sets of data. Deep Learning (DL) came about as a sub-branch of ML, where neural networks became the basis of learning. DL has brought us closer to the dream of realizing AI but DL alone did not achieve this.
Measure, analyze and optimize app experience
I come mostly from a web app background. I haven't done much work in the mobile apps except for dabbling with some sample code in React Native. Mobile has come a long way. Yes, it's built on the foundations of web app development but today it has a life and roadmap of its own. I was therefore glad to attend today's event organized by Flurry, which is a platform for mobile analytics. Flurry was founded in 2005 and acquired by Yahoo in 2014. The event this afternoon was attended by entrepreneurs, developers and marketing executives. There was so much information packed into one afternoon that I'm sure everyone took away something useful from it, even if they were experienced in the mobile space.
The format was a mix of panel discussions and focused talks. It was nice to see representation from a spectrum of Indian start-ups. It happens sometimes that events organized by US or European companies feature speakers who know quite well their US or European markets but nothing much about the Indian market. Today's event was quite different. With speakers and moderators from Paytm, Flipkart, CouponDunia, Wooplr, Bounty, YourStory and more, it was clearly and rightly focused on the Indian market. There were of course guys from Flurry, Truecaller and Branch Metrics who gave lot of additional insights.
Author: Paul Allen
Publisher: Portfolio/Penguin, 2011
In this autobiography, Paul Allen talks about the early years when he joined with Bill Gates and co-founded Microsoft in 1975. While both Bill and Microsoft are fairly well known to the public, Paul has not had that much of a public presence, at least not outside of the US. This may have something to do with the fact that he left Microsoft in 1982, when the personal computer revolution had just begun to accelerate. This book tells us a lot about his contribution towards building Microsoft what it is today. It's also lays bare the complex relationship that Paul had with Bill. The book is also a quick overview of how technology has progressed through the 1970s and 1980s, which is something that will interest today's engineers.
It's true that sometimes success is being in the right place at the right time. If you're too early, the market is not ready or the technology is unavailable. If you're too late, you end up trying to catch up with others. Either way, this book makes one thing clear: it's equally important to be adventurous, be confident in your abilities and have a vision for the future. Quite often Paul mentions that many of the ideas he contributed were pivotal to the success of Microsoft, which explains the title of this book.
How good ideas evolve
The four quadrants that you see here are adapted from Steven Johnson's book titled Where Good Ideas Come From. We have in fact done a review of this book many months ago on IEDF but I thought there's one aspect of innovation that deserves more attention and explanation. Johnson tries to analyze innovations with respect to the surrounding ecosystem and the models in which individuals and companies operate. The result is the four quadrants.
Broadly, someone who invents or innovates is either doing it individually in the proverbial garage or attic; or she is part of a bigger research group that has access to funds and resources. The other axis of analysis is about the motive: are the inventors interested in profiting from their creations or are they open to sharing them with everyone else in the ecosystem. This is what the four quadrants are all about. Let's now look at some specifics.