Industry executives and experts share their predictions for 2023. Read them in this 15th annual VMblog.com series exclusive.
Trends in innovation-driven technology, generative AI and data-driven solutions
By Scott
Stephenson, CEO and co-founder of Deepgram
In the current financial
downturn, many tech companies are finding themselves at a crossroads between
cutting costs and investing in innovation. The reality, however, is that they
don't have to choose one strategy over the other. Although some parts of the
economy are indeed cooling off, demand for technology solutions to business
problems will remain strong in 2023.
As the CEO and co-founder of Deepgram, an industry-leading speech technology company, I've got
a front seat to the technical trends and innovators that are reshaping the
business landscape with artificial intelligence. The following are a few of my
predictions for 2023, including why AI is recession proof, key tech trends to
follow in the new year and why I think that end-to-end deep learning needs
data-driven solutions.
AI is Recession Proof
Despite the economic
uncertainties that consumers and companies are facing, I predict that demand
for AI-enabled products and services will remain not only resilient but
recession-proof.
Over the past five or so years,
business leaders enjoyed a permissive financial environment. "Growth at all
costs" was the mandate, made affordable by all the cheap, plentiful capital
flying around the market at the time. Well, we all know what happened next:
inflation picked up and the Federal Reserve took away the punchbowl. Party
over, for now.
The U.S. economy is not in a
recession, yet, but business leaders must deal with a new set of financial
constraints while still managing to eke out some business growth while they
still can. Since a company can no longer spend its way out of a business
problem, innovation and automation is now the name of the game.
Simply put, AI will help us do
more with less. Artificial intelligence in the workplace has come a long way
from the little animated paper clip in the corner of your word processor. AI
solutions save teams hundreds or even thousands of hours by automating tedious
processes, and they enable companies to access and use their data in new ways
that weren't feasible without large-scale computation and predictive modeling.
Working with AI is not the far-out science fiction future; it's happening at
basically every large company today. I predict that AI will continue to be
central to business in 2023 by cutting costs and enabling innovation.
All signs point to continued
deterioration of macroeconomic conditions as the effects of mid-to-late 2022's
interest rate hikes start to come online, so 2023 may bring a serious test of
this hypothesis.
The Next AI Wave is
Generative
In 2023, one of the biggest
focuses will be on generative AI technologies. This really does feel like something new, and the rate of
progress is nothing short of amazing.
At this point you've almost
certainly heard about AI programs-like OpenAI's DALL-E 2 model, Google's Imagen model, or the open source image synthesis toolkit Stable
Diffusion-that take a written description of an
image and turn it into an actual image, with some models also supporting video
generation. By that same token, you might've had a conversation with ChatGPT, a chatbot from OpenAI that relies on a large language
model to produce eerily human-sounding responses to basically whatever question
or challenge you throw at it.
It's kind of hard to believe that
these tools were only released in 2022. It's taken years of fundamental
research and development work to get to this point, and if 2022 was the year
that a lot of folks started talking about generative AI, I predict that
2023 will be the year when even more folks start using generative
AI.
Although the technology seems
relatively siloed off in the world of art or content creation, for now,
generative AI has applications throughout the economy-from banking and
industrial design to data security and personalized marketing, and beyond! It
will be exciting to see which new use cases are discovered in the next year,
and I wouldn't be at all surprised if generative AI plays a role in making some
of those discoveries.
End-to-End Deep Learning
Needs Data-Driven Solutions
2023 will be the year of
end-to-end deep learning in the enterprise. No longer a speculative area of
academic computer science research, the stuff of skunkworks projects that will
never see the light of day, or a mere component in a complex data processing
pipeline, most companies today have enough data to build powerful models that
can handle all the steps of a given business process. The pace of progress in
applied deep learning is accelerating, so what may be on the cusp of
possibility today will be table stakes in a couple of years. Deep learning
models have proven to be a remarkably robust part of the new business
stack.
Overall, it is clear that
technology is resilient despite economic circumstances, and it is crucial that
technology leaders can identify where change and creativity can happen in order
to rise above these challenges. In 2023, AI will continue to help companies
drive growth, innovatively disrupt the way we work, and adapt to the ebbs and
flows of the way humans interact and work.
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ABOUT THE AUTHOR
Scott Stephenson is a dark matter physicist turned Deep Learning
entrepreneur. He earned a PhD in particle physics from University of Michigan
where his research involved building a lab two miles underground to detect dark
matter. Scott left his physics post-doc research position to found Deepgram.