6 Predictions for AI, ML and NLP for 2021

  2 m, 30 s

Every year, we like to consider what happened in the last year in AI, ML and NLP, and prognosticate on what might happen in the next 12 months. And while 2020 was a doozy of a year, from the pandemic to the recession to social justice movements and political unrest, there were important developments in technology we work in, like the advancements in deep learning models like GPT-3, and the growing importance of using NLP in VoC programs as businesses work to understand customers’ needs in a world in tremendous flux.

With that in mind, below are predictions for this year, provided by our CEO Jeff Catlin, and Chief Scientist Paul Barba.

  • Data Annotation will become the next big “side hustle” in 2021. It’s already a common way to make an extra buck or two, but there’s been a race to the bottom in pricing, where annotations are largely sourced well below minimum wage in industrialized nations. However, as AI sees successes in industries requiring expertise, like health care or law, the demand for specialist knowledge will see the development of infrastructure for matching more lucrative annotation contracts to professionals.
  • A slew of industry-disrupting startups are on the way. High unemployment and general uncertainty resulting from the pandemic give some people the push needed to set out on their own. We’ll see increased collaboration between technologists and experienced professionals in starting new businesses to bring the latest advances in AI to all sorts of industries.
  • There will be more consolidation in the ML platform space. As AI became the “it” technology over the last few years, a bunch of AI infrastructure companies popped up and began peddling AI platforms to ease the task of building models for companies looking to leverage AI. While it sounds good on the surface, there is no identified business task being solved here; it’s simply more efficient use of technology, and that’s hard to sell. It’s likely that the VC’s who backed these plays will begin to sever the cash lifelines in 2021 which will lead to some consolidation, but that doesn’t mean we might not see one of these companies evolve into the next Oracle in the coming years.
  • The improvements in deep learning models over the last 18 months mean that NLP features that have been desired but unfulfilled will start showing results. These include better entity recognition which drives better normalization, which in turn drives generic relationship extraction. The advances in deep learning models make all of these possible.
  • AI platforms will consolidate, but AI services will pick up the slack here. Companies are becoming more accepting of third party expertise in machine learning, and this is driving an increase in consulting services for ML.  This trend will continue and accelerate in 2021.
  • Fake news detection will start showing dividends. Fake news detection is an incredibly hard problem, but a lot of very smart people are spending a lot of time working on it. The spread of misinformation will be notably lower by late 2021.
Categories: Lexalytics

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