Skip to Content

Machine Learning and Market for Intelligence Conference Recap

On October 26th 2017, the Toronto Creative Destruction Lab hosted the third annual ‘Machine Learning and the Market for Intelligence’ event.

The Prime Minister of Canada, Justin Trudeau, spoke about the federal government’s current initiatives to support the growth of Artificial Intelligence (AI) within Canada specifically highlighting the benefits that diversity of backgrounds and education can have towards both developing cutting edge technology and applying the technology to innovative business scenarios.

Prime Minister Trudeau receiving an honorary 'coders' sweater

The conference had over 25 industry and academic leaders in AI, with talks ranging from ‘Quantum Machine Learning and its Discontents’ to ‘The World after Capital’. To learn about each speaker and the topics they covered select the article below.

Overall the talks can be consolidated into 4 themes:

1. The growth of AI is exponential

2. Communication and Natural Language Processing (NLP) will be the key towards changing the human-machine relationship

3. The end goal of AI is Artificial General Intelligence (AGI)

The Growth of AI is Exponential

Russ Salakhutdinov, the director of AI research at Apple, spoke about the rational on why AI will continue to grow within the industry,

“As the cost of AI prediction continues to decrease the value of AI adoption will increase. Subsequently the value of human prediction will decrease.”

Companies are recognizing this shift as even Google has noted that it is changing from a mobile first company to an AI first company

Communication and NLP will be the key towards changing the human-machine relationship

While AI has become better than humans at image recognition, the current relationship between consumers and AI is one of distrust due to a lack of transparency on how AI works. Brad Hoover, the CEO of Grammarly, argues that AI should be used as a communication system to augment human behavior rather than disrupt it.

This argument pairs well with Suzanne Gilderts speech about AGI embodiment. Suzanne argues that robotics will help AI ‘look and feel’ like a human. Human-like robotics with NLP and natural langue generation will allow consumers to personify rather than alienate AI.

This is good news as recently Saudi Arabia granted citizenship to a robot.

The end goal of AI is AGI

Scott Phoenix spoke about the growth of AI. Currently AI is just providing the illusion of intelligence as machines do not comprehend information, but simply read it and follow established processes. This makes it very hard to generalize its training or complete abstract thought. True AGI will be achieved when machines are able read, write and create data as well as their own thought process.

A glimpse of this future can be seen in how AlphaGo Zero was able to learn the game of Go from scratch and beat the previous version of AlphaGo which had been manually taught.

Estimates on when AGIs will be realized vary but all speakers agreed it was within the next 20 years as the law of accelerating returns will cause AI growth to innovate exponentially.

AI Startups

There was also a large number of AI companies at the conference who were showcasing how they were using AI to solve business problems:

URU - Uru automatically generates robust data blueprints of inputted videos: their objects and themes, their brand safety level —even the best moments and spaces inside them for brands to occupy.

Cerebri – Cerebri uses AI to identify, generate and action customer insights for businesses.

Iris.AI - Iris.AI will analyze the abstract of your research paper, present the key concepts, and link those with research papers.

Black.AI – Black.AI provides the hardware / sensors needed to measure data that one can use to machine learning and AI

Nama – Nama is a chatbot that helps communicate with customers and automate basic processes.


Join in on the conversation with Calvin Tennakoon when you subscribe to Exponentials.