Artificial Intelligence: Underpinnings of a Disruptive Wave – Vancouver

Artificial Intelligence: Underpinnings of a Disruptive Wave – Vancouver

We are having a blast taking our AI roadshow to different cities. After hosting a wonderful panel in Seattle, our caravan moved up north for our 3rd annual Mobile Breakfast Series event in Vancouver. It was TED week so the city was buzzing with AI and Robotics talk and provided a perfect platform for us to chat about AI and its implications.

Thanks to Optimus Information for sponsoring the series in Vancouver. It is good to work with my friend Pankaj Agarwal, CEO to plan and execute on the event.


The panelists were:

Prof. Mark Schmidt, Department of Computer Science, University of British Columbia

Pankaj Kedia, Senior Director – Smart Wearables, Qualcomm

Lev Mass, Venture Partner, XSeed Capital

Chetan Sharma, CEO, Chetan Sharma Consulting (moderator)






Mark Schmidt has been an assistant professor in the Department of Computer Science at the University of British Columbia since 2014, and is a Canada Research Chair and Alfred P. Sloan Fellow. His research focuses on developing faster algorithms for large-scale machine learning, with an emphasis on methods with provable convergence rates and that can be applied to structured prediction problems.

Pankaj Kedia is Senior Director, Product Management and business Lead for the Wearables Segment at Qualcomm Technologies. In this role, Pankaj is responsible for leading Qualcomm’s efforts to establish and grow its presence across the wearables segments including smart eyewear, smart watches, kid/elderly watches, smart bands, smart headsets, smart clothing, and wearable accessories. Under Pankaj’s leadership, Qualcomm has enabled its customers to ship 100+ products in 30+ countries over the last 2 years.

Lev Mass is a Venture Partner at XSeed Capital, with expertise in cloud computing, mobile, and business development. Prior to joining XSeed, Lev ran operations and business development for the Cloud Group at Yahoo!. While at Yahoo!, Lev helped to facilitate the spin-off of the Hadoop Group into what is now Hortonworks, a leading big data company. In addition, he held a number of executive roles at Yahoo! helping to define strategy for mobile, social, cloud and big data.

We have talked about AI in the context of the “Connected Intelligence” technology Wave. It is a key building block of the industry architecture.

The salient points discussed during the panel were:

  • For academics, the whole AI hype is pretty amusing as they have been at it for a long time and all of a sudden AI becomes the thing. It has gotten so bad that they are receiving offers daily to join the likes of Google and Microsoft. Same for some of the students and it is just getting hard to retain because the offers are insane but not everyone is biting and would rather focus on research work.
  • One of the biggest breakthroughs of the last decade in AI has been in Computer Vision. The fact that we can identify objects reliably has opened up new application areas. 10 years ago, it was thought that if we can solve computer vision, AI would effectively be solved but of course, there is so much yet to explore.
  • The next big frontier in AI is language which is much more complex than computer vision. However, given the recent forays of Microsoft and Google into real-time translation, I am optimistic that we will be cracking the nut for mass market in short order.
  • There a number of application areas for AI some we are close to mastering while others are work in progress such as Motion Capture, OCR, Speech Recognition, Object Recognition, Face detection, Emotion detection, Sports analysis, Personal Assistant, Medical Imaging, Self-Driving Cars, Scene Completion, Image Annotation, Cancer analysis, Deep data analysis, etc.
  • There are two school of thoughts around AI – Intelligence Augmentation (IA) which is where most of things are today vs. pure AI.
  • Qualcomm is building AI right into the chipset with a neural processing engine which is being used for photography, AR/VR, voice detection, security, etc.
  • Bots is where a lot of attention is being put right now. Customer service is an area where some success is being experienced.
  • 60% of the Fortune 100 are doing something with Google Glasses or something similar which indicates that there is a lot of traction and we are likely to see more coming despite a hasty retreat from the consumer market. There are a number of other companies who are doing some cool work on glasses. Snap’s spectacles also look promising. Doctors are using glasses for transcription saving time and money
  • Sensors and wearables have become eyes and ears of the AI world. There is so much data being generated – it is of course being harnessed for individualized training and wellness regimens but also detecting patterns in populations.
  • We explored the interaction of adjacent technologies and what is happening at the edges. For example – AI and blockchain, AI and Quantum Computing,
  • AI and Robotics were hot topics at TED as well. The main message coming out was that since humans are creating AI, we will have control or rather we should control how we build AI. This matter is of significant consternation in the industry. The likes of Gates and Musk have been warning about the impending disaster of AI while others feel that AI can be tamed. The truth lies somewhere in the middle. The law of unintended consequences will surface time and time again as poor design and policies will invariably impact how AI proliferates. Then, there is the question of nefarious actors but that is a separate discussion all by itself.
  • Some at TED raised the notion of regulation of algorithms to better manage what’s coming. Others have raised the notion of regulating data. This is an unknown territory for humanity. Regulators are generally unprepared to deal with AI.
  • So, where does the value lie in AI – algorithms, models, data, ecosystem? There was a consensus that it is data that drives the competitive advantage. Some of the bigger players are giving away algorithms, models, tools to the ecosystem but guarding the data. Google, Facebook, Amazon with their vast repository of consumer data are probably best placed to dominate but each cycles brings new surprises and new winners and losers. We will be deep diving into the AI discussion at our annual summit in September.
  • Qualcomm has more Android engineers than Google.
  • Given that so much Qualcomm technology in cell phone, it makes them the largest camera company, the largest memory company, the largest modem company, largest GPS company, etc. A lot of the technology that enters in the chipsets enables new ecosystems and platforms.
  • Biggest opportunities for startups might be in building on top of existing platforms.
  • Moore’s law to continue as engineers figure out ways to do things better all the time though we might be reaching the limits of physics.
  • Northface is using AI in commerce on website in directing consumers to specific things that they are likely to be interested in.
  • UBC recently got a grant to use AI to detect and work on the fake news problem.
  • United is using bots to provide high-end service to its Global Services customers.
  • Mining industry is using object recognition based AI for safety and exploration.
  • Autonomous vehicles are obviously the use case that is gaining the most traction and every OEM is on it in one way or another.
  • The primary reason AI is hot again is that this time it is better prepared. The enabling technologies for AI – the hardware that enables tremendous amount of processing in ms, the software algorithms that have been refined over decades have been good at using the data, and then finally the data itself is becoming plentiful. There is more data being generated every day that can be used by algorithms to better understand and more importantly train the algorithms to address a specific problem or the opportunity.
  • While the goal of AI is to do unsupervised learning, the reality today is that AI needs supervised learning to get going. One of the biggest and more expense areas
  • The processing power available at the ambient edge is allowing new and interesting use cases.
  • While current AI is good at detecting patterns, and reporting back the probabilities, it is missing context awareness as an input. By understanding the context in which the question is being asked, AI can fine tune the responses.
  • Many a times, the dataset just doesn’t represent the real world so we have to resort to compensating for the holes and it is a very delicate process for if you end up training the engine wrong, it will give spurious results back.
  • There is a severe disconnect between the tech world that is going full in on AI vs. the political class that seems so oblivious to the changes that are coming. Treasury secretary’s ill-informed opinion that AI is not going to be something to worry about for the next 50-100 years is a classic example of the indifference and lack of understanding at the highest levels of the government. The last administration started to broach the subject of automation and AI late into the game but at least some opinions were striating to form on the “ground truth” which is essential before any policy work can start.
  • Automation will keep marching ahead and WILL replace routine jobs and major economies are just not ready. It might hurt US and developed economies more in the short-term but countries like China and India are not immune to the impacts – it is likely to have an even more devastating impact on the economy and politics in the long-term in the emerging markets.
  • We had a lot of discussion around automation and the impact it will have on jobs and that the Education system is not ready for the fallout. Even high-end jobs like radiologists are likely to be eliminated. For example, a radiologist might see 50K images over his/her career which a computer can do in a matter of minutes and the performance will be better. Will we create enough new jobs to compensate for the losses as we have done every year and in every other tech cycle.
  • Canada is putting a lot of emphasis on AI. A number of recent acquisitions have taken place of companies based out of Canada. Toronto and Vancouver have a number of new startups germinating however government and the local VC community needs to step up to compete with VCs down south else companies just move to Silicon Valley for bigger exits.
  • Because of AI, there are some fascinating uses cases to ponder on – for e.g. what happens when there is all this free time in the car cabin – how will that change society? How will AV redefine how we have structured cities? Employment? All these will have enormous implications on how we live and work.
  • There are several issues around ethics and diversity that one needs to work diligently towards.
  • Gates, Musk, and Hawkings have sounded the alarm on the perils of AI, Automation, and Robots. While I perhaps have a bit more faith in human ingenuity in dealing with threats, their warnings shouldn’t be taken lightly because of profound implications.
  • Privacy is a big concern in the age of AI. With all the data being produced by individuals, the opportunity for abuse is enormous. How will the industry rise to be the stewards on consumer privacy rather than just the opportunists to exploit the vulnerable. Of course, the valley point of view is that privacy is dead and it is a waste of time to worry about such matters.
  • One of the most interesting question from the audience was around protection of wisdom gained from applying AI. It is a challenging issue and we just don’t know that yet but IP in the AI era will be an interesting proposition.
  • Obviously, the holy grail of AI is mimicking human brain but we are still far away from reaching that goal.
  • Eventually, AI will become the underlying layer of the Connected Intelligence framework as we envisioned in our Connected Intelligence series of papers.

My thanks to all panelists and the attendees who made it lively. Vancouver is one of my favorite cities and we enjoy bringing MBS to the city. 90 minutes flew by and we had scores of questions still to address. We know it is a deep topic with broad implications so we are continuing our journey into the AI world with our Evening with AI at Google Launchpad in San Francisco on 5/8.

Our annual Mobile Future Forward will tackle many of these themes in much detail. Hope to see you then.