1) Language AI will take center stage, with more startups getting funded in NLP than in any other category of AI.
Language is humanity’s most important invention. More than any other attribute, it is the defining hallmark of our species’ intelligence.
Naturally, language pervades every facet of every business activity across every sector. The ability to accurately automate language therefore opens up virtually unbounded opportunities for value creation.
2) Databricks, DataRobot and Scale AI will all go public.
These three companies are among the first wave of big winners in the modern AI economy. They each provide tools and infrastructure to help other companies build AI, reflecting the common theme across technology cycles that infrastructure precedes applications.
3) At least three climate AI startups will become unicorns.
Climate tech has rapidly become one of the hottest categories in the world of startups, with record amounts of venture capital pouring into the sector this year. As previously explored in this column, opportunities abound for startups at the intersection of climate and artificial intelligence.
4) Powerful new AI tools will be built for video.
Video has become the dominant medium for our digital lives. Over 80% of all Internet data in 2022 will be video, according to Cisco. Every day, 7 billion videos are watched on YouTube and 100 million videos are uploaded to TikTok. From Netflix to Amazon Prime Video to Disney+ to Hulu to HBO Max and beyond, Internet streaming services’ user bases and content libraries continue to balloon.
5) An NLP model with over 10 trillion parameters will be built.
The field of natural language processing (NLP) today is defined by the development of ever-larger transformer-based models. This arms race will continue in 2022 (notwithstanding intriguing recent work from DeepMind on the power of smaller models).
6) Collaboration and investment will all but cease between American and Chinese actors in the field of AI.
It is no secret that geopolitical tensions between the United States and China are ratcheting up, with cutting-edge technologies like artificial intelligence representing a particularly contentious touchpoint in the conflict. This will get worse—much worse—in 2022.
In just the past few weeks, the U.S. government added AI startup SenseTime, drone company DJI, and several other leading Chinese AI organizations to an investment blacklist. These are among the most important AI companies in China.
These three companies are among the first wave of big winners in the modern AI economy. They each provide tools and infrastructure to help other companies build AI, reflecting the common theme across technology cycles that infrastructure precedes applications.
3) At least three climate AI startups will become unicorns.
Climate tech has rapidly become one of the hottest categories in the world of startups, with record amounts of venture capital pouring into the sector this year. As previously explored in this column, opportunities abound for startups at the intersection of climate and artificial intelligence.
4) Powerful new AI tools will be built for video.
Video has become the dominant medium for our digital lives. Over 80% of all Internet data in 2022 will be video, according to Cisco. Every day, 7 billion videos are watched on YouTube and 100 million videos are uploaded to TikTok. From Netflix to Amazon Prime Video to Disney+ to Hulu to HBO Max and beyond, Internet streaming services’ user bases and content libraries continue to balloon.
5) An NLP model with over 10 trillion parameters will be built.
The field of natural language processing (NLP) today is defined by the development of ever-larger transformer-based models. This arms race will continue in 2022 (notwithstanding intriguing recent work from DeepMind on the power of smaller models).
6) Collaboration and investment will all but cease between American and Chinese actors in the field of AI.
It is no secret that geopolitical tensions between the United States and China are ratcheting up, with cutting-edge technologies like artificial intelligence representing a particularly contentious touchpoint in the conflict. This will get worse—much worse—in 2022.
In just the past few weeks, the U.S. government added AI startup SenseTime, drone company DJI, and several other leading Chinese AI organizations to an investment blacklist. These are among the most important AI companies in China.
.7) Multiple large cloud/data platforms will announce new synthetic data initiatives.
Getting the right data is the most important and the most challenging part of building AI products today. Synthetic data offers compelling advantages over the status-quo approach of collecting and labeling real-world datasets.
Gartner has predicted that by 2024, synthetic data will account for 60% of all data used in AI development. Facebook’s acquisition of synthetic data startup AI.Reverie two months ago is a canary in the coalmine.
8) Toronto will establish itself as the most important AI hub in the world outside of Silicon Valley and China.
It is not an exaggeration to say that modern artificial intelligence was invented in Toronto, thanks to the work of deep learning pioneers like Geoff Hinton. Though it generates less buzz than other geographies, Toronto remains one of the most important AI hubs in the world.
Getting the right data is the most important and the most challenging part of building AI products today. Synthetic data offers compelling advantages over the status-quo approach of collecting and labeling real-world datasets.
Gartner has predicted that by 2024, synthetic data will account for 60% of all data used in AI development. Facebook’s acquisition of synthetic data startup AI.Reverie two months ago is a canary in the coalmine.
8) Toronto will establish itself as the most important AI hub in the world outside of Silicon Valley and China.
It is not an exaggeration to say that modern artificial intelligence was invented in Toronto, thanks to the work of deep learning pioneers like Geoff Hinton. Though it generates less buzz than other geographies, Toronto remains one of the most important AI hubs in the world.
9) “Responsible AI” will begin to shift from a vague catch-all term to an operationalized set of enterprise practices.
AI technology is improving faster than is our ability to deploy it responsibly, ethically and equitably.
AI technology is improving faster than is our ability to deploy it responsibly, ethically and equitably.
A growing movement has emerged to advocate for the responsible use of AI, led by researchers like Timnit Gebru, Joy Buolamwini and Cathy O’Neill. This push for more responsible AI spans a broad set of issues including AI bias, data provenance, model explanability and model auditability.
10) Reinforcement learning will become an increasingly important and influential AI paradigm.
The dominant approach to AI today is supervised learning, which entails collecting a lot of data, labeling it, and feeding it into an AI model so that the AI learns useful patterns about the world. Unsupervised learning, a similar approach but without the need for human-generated labels, has also begun to gain traction in recent years.
The dominant approach to AI today is supervised learning, which entails collecting a lot of data, labeling it, and feeding it into an AI model so that the AI learns useful patterns about the world. Unsupervised learning, a similar approach but without the need for human-generated labels, has also begun to gain traction in recent years.
