Radical Reads: 10 AI predictions for 2022

Editorial Team

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Radical Ventures Partner Rob Toews published his predictions for AI in 2022 this week in Forbes. In his 2021 predictions retrospective there are some misses and significant wins including foreseeing AI’s jump to the forefront of Washington’s policy agenda and researchers successfully building an natural language processing (NLP) model with over one trillion parameters. This year brings another ten predictions including a deepening of the east-west technology divide, the next steps in language AI, and climate change becoming a spotlight for innovation. 

 

We have pulled excerpts from Rob’s 10 AI predictions for 2022 below: 

 

1) Language AI will take center stage, with more startups getting funded in NLP than in any other category of AI.


“The field of NLP has been upended and turbocharged in the past few years by a foundational new technology known as transformers, first introduced by Google researchers in a 2017 paper. We are only now reaching the point at which this dazzlingly powerful technology is mature enough to be productized and commercialized at scale. A revolution in language AI, and thus in business, is around the corner… Leading NLP startups Hugging Face (last valued at $440M) and Cohere (last valued at $200M) will both become unicorns next year.”

 

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… Companies often make a high-profile CFO hire in preparation for an upcoming IPO. DataRobot announced this April that it had hired Damon Fletcher (formerly Tableau CFO) for the role. Databricks CFO Dave Conte, meanwhile, previously served as CFO of Splunk, where he took the company public in 2012. Don’t be surprised to see Scale AI make a high-profile CFO hire early in the new year.”

 

3) At least three climate AI startups will become unicorns.

“A number of climate AI startups have recently burst onto the scene with big funding rounds (despite limited commercial traction to date). Next year, a few of these players will ride the intensifying climate tech fervour to billion-dollar-plus valuations.”

 

Editor’s note: Radical Ventures is an investor in ClimateAi – a climate resilience platform for enterprises. ClimateAI’s industry-leading modelling products are capable of delivering accurate weather and climate predictions beyond current capabilities.

4) Powerful new AI tools will be built for video.

Video has become the dominant medium for our digital lives… And yet, compared to other data modalities like image and text, there has been relatively little focus to date on building deep learning-based products and capabilities specifically for video. This represents a massive market opportunity. Expect to see a blossoming of AI tools for video in 2022, from video search to video editing to video generation.”

 

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)… Expect this hockey-stick growth in the size of large language models to continue next year.” 

 

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.”

 

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… Next year, multiple major computing platforms will launch new synthetic data efforts as they recognize the importance of this technology to tomorrow’s AI stack and seek to attract more builders to their ecosystems.”

 

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… Historically, Toronto has had a reputation as a top-notch AI research hub but a comparatively underdeveloped startup ecosystem. This is changing fast. Ada (chatbot platform), Cohere (NLP), Deep Genomics (AI for drug discovery) and Waabi (autonomous vehicles) are just a few examples of Toronto-based AI startups that have raised monster funding rounds in recent months. Expect more world-class AI startups to emerge from Toronto in the coming year.”

 

9) “Responsible AI” will begin to shift from a vague catch-all term to an operationalized set of enterprise practices.

“While awareness of these issues is growing, the topic remains sufficiently abstract that, by and large, AI practitioners do not build “responsible AI” practices into their day-to-day workflows. 2022 is the year that this will begin to change, as responsible AI practices and toolkits become productized and operationalized.” 

 

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. But there is another paradigm in AI, which has been around for decades but whose vast real-world potential is only starting to become clear: reinforcement learning… Reinforcement learning may offer a path to a more sophisticated, flexible form of machine intelligence.” 

 

Read Rob’s 2022 predictions in full. Rob writes a regular column for Forbes about artificial intelligence.

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