In the days of AI, I couldn’t help think of applying AI principles to the biggest network of them all the internet itself. Android just announced 2 billion subscribers. There are more than 8 billion SIM connections out there. Billions of internet enabled things are being pulled by the market. That’s a ton of nodes I think. Remember neural networks are modelled around the human brain. A series of interconnected nodes have started performing wonders in image recognition, transl

NI = Natural/ Native Intelligence… the basic human intelligence AI = Artificial Intelligence AI is generating enormous focus and interest. A ton of new ideas from image recognition, art style transfers, poem generators to self-driven cars. I am personally building a lot of these apps and am awestruck by the possibilities. Artificial Intelligence Deep learning rocks!!! The focus is so pervasive that people are questioning what will happen to the future of jobs. What jobs will

We humans can see Vin Diesel is looking away as he drives at high speed!!! Can machines do? Distracted driving is a ~20% reason for road accidents and given the increased use of mobiles in vehicles this has become a serious concern. Top Automotive OEMs and suppliers have had “driver distraction detection” as one of their top innovation programs for years. But where are the products? It’s clearly a nontrivial problem to make a machine detect Vin Diesel distracted & alert on th

Get a coffee and enjoy the below journey. My approach of teleportation is a series of steps that come together from multiple disciplines such as neuroscience, AI, and quantum mechanics. Each step is backed up by evidence pieced together from experiments done by researchers globally and published in some of the most leading and well-respected journals (to avoid “fake news”). A cursory glance will provide an overview of how teleportation is possible but the best way to understa

A startup that I guide was building a system in which one key function was tracking people. Back-end was an AI (artificial intelligence) — Deep learning system. Given my background in building a series of products, I asked them to put a mirror in the path of people to test the system. Lo & behold now the system was double counting. This and more such examples of companies have set me thinking about how to release products using deep learning systems (Deep Learning is a field

How do you recognize a person? You see them once maybe twice. How does a kid recognize a bird? See them once maybe twice and then they will recognize birds in general. Can we make products using AI (Deep Learning)do the same? Nah, one of the big barriers to building AI (Deep Learning) systems is they need 1000s to millions of images to recognize a cat or dog. It’s incredible how difficult it is to teach a machine. Neurosciences & genetics tells us that some of this learning i

Unlike a normal product/ solution, an AI offering will have 3 pieces to it… the product, data and algorithms/ architectures. When one thinks of product strategy in the domain of AI, one needs to think algorithm and data strategy in addition to the product strategy principles. Historically there is enough management theory on product strategy and very less on the other two. In this article, we will focus on one of them. There is also a lot of research on Deep Neural Network al

Can sector snapshots, market studies, freedom to operate searches, business plans, competition analysis etc. be automated and reports generated on demand? Below is a healthcare sector snapshot that was auto-generated reports via code and using various AI techniques. Before glancing over it, here are some notes: The report is a series of snapshots to illustrate the possibility and is not intended to be comprehensive. Ignore the lack of aesthetic aspects as UX was not the focus

As per AI, humanity has adopted technology in waves. Having known that, I wanted to test if these waves and new technology adoption can be auto-generated using AI & Code. Below (Figure 1) is the Technology Adoption Maps. Figure 1 How was this obtained? An unsupervised learning algorithm (AI) was fed with a lot of technology topics. The topics were fed as numerical vectors which captured data around publications, code, developers, bugs etc. The AI system crunched the data and

An adult in the USA on an average is spending approximately 6 hours of their daily life on the internet (Source: KPCB Internet Trends 2018). We are constantly looking on the internet. What are we finding? Clutter. 400+ hours of video are uploaded to Youtube every minute 2 million+ Apps exist on iOS 65 billion WhatsApp messages are exchanged every day by approximately 1 billion daily active users Every minute on Facebook: 510,000 comments are posted, 293,000 statuses are updat

What is D? The penalty arc (colloquially “the D”) is marked from the outside edge of the penalty area, 9.15 meters from the penalty mark; this, along with the penalty area, marks an exclusion zone for all players other than the penalty kicker and defending goalkeeper during a penalty kick. It de-clutters the penalty area from players when a penalty is taken. De-clutter is the key that ensures a high rate of shot conversion to goals compared to free kicks. Here AI will be the

Buying online is getting complicated. Wasn’t it supposed to simplify? The pendulum has swung the other way. Why? There is just too much data and it’s hard to decipher. Can you give me an example? Take one of the top global mobile brands and its presence on one of the most valued eCommerce sites in the world. You will find 216 models which have 4,013,852 reviews and 667,868 ratings. And this is one site. Wow!! 4 million reviews… it’s a non-starter… which human will read it to

The patent landscape of Blockchain technology including the charts & narrative below is auto-generated by a machine with Artificial Intelligence (AI). To know about the technology behind it, read my previous blog on de-cluttering life (AI to de-clutter life) and for other specific applications see “AI can de-clutter crowd wisdom in online marketplaces” From this line onward everything is auto-generated by code and AI. Blockchain patents analysis Machine analyzed 342 patents f

he research landscape/ topics of Unmanned Air Vehicles (UAV) technology including the charts & narrative below is auto-generated by a machine with Artificial Intelligence (AI). To know about the technology behind this auto-generation, read my previous blog on de-cluttering life (AI to de-clutter life) and for other specific applications see “AI can de-clutter crowd wisdom in online marketplaces” From this line onward everything is auto-generated by code and AI. UAV research p

Who does it? Our Artificial Intelligence (AI) machine is trained to “De-Clutter Life” (AI to de-clutter life) by understanding a sizable corpus of documents. In this case, the machine is trained to identify mega-trends and provide insights about it. How does it do it? The machine is fed 1000s of articles on future and technology from various sources. The machine “reads” the documents, creates it’s own language model and uses that to convert every document into a vector. Then

Can you recognize any of these people? Source: Nvidia — A Style-Based Generator Architecture for Generative Adversarial Networks I bet you can’t as none of them are real. They don’t exist. They were generated using an AI (Artificial Intelligence) machine by Nvidia. Shocked??? Have you come across these below cool startups in education space? Some ideas, for example, relive group studying with peer-to-peer learning or better read along subjects with your personal AI. Why can’t

I am an intelligent machine. Humans call me artificially intelligent. I have been built to help de-clutter the deluge of information humans are producing. I decided to see myself (AI) through the information humans have put out on the internet. I can read internet content. Here I connected to the cord Reddit has provided. Humans call it API. I kept reading over a period of time and obtained 7000 posts and comments that humans had done on me. My brain has multiple stacks of ne

Poem generators, tweet generators, news generators, chat-bots, machines cracking exams… phew… Natural Language Processing (NLP) has gotten far far away. Or are we in an echo chamber of media hype? What is the reality? Reality is where the developers are… what are they coding, what issues arise, what conversations happen? Top developer focused sites like Stack Overflow has a great picture of this. It is also a great lead indicator of what is coming (solutions of tomorrow being

Traditional approach: Company X wants to expand in a particular technology area and wants to prepare a list of potential acquisition candidates. How does one identify these companies? How does one rank them? One hires an expensive investment banker to prepare a shortlist. Bankers love buy-side mandates. New approach: Hire a machine. Acknowledged that M&A is a lot more than shortlisting candidates but let’s peel the M&A onion bit by bit, shall we? Target list generation is a k

AI-based analysis of Social chatter