Scale AI CEO Alexandr Wang doesn’t need a crystal ball to see where artificial intelligence will be used in the future. He just looks at his customer list.
The four-year-old startup, which recently hit a valuation of more than $3.5 billion, got its start supplying autonomous vehicle companies with the labeled data needed to train machine learning models to develop and eventually commercialize robotaxis, self-driving trucks and automated bots used in warehouses and on-demand delivery.
In 2020, that changed as e-commerce, enterprise automation, government, insurance, real estate and robotics companies turned to Scale’s visual data labeling platform to develop and apply artificial intelligence to their respective businesses. Now, the company is preparing for the customer list to grow and become more varied.
How 2020 shaped up for AI
Scale AI’s customer list has included an array of autonomous vehicle companies including, Voyage, Aptiv, Embark, Nuro and Zoox. While it began to diversify with additions like Airbnb, DoorDash and Pinterest, there were still sectors that had yet to jump on board. That changed in 2020, Wang said.
Scale began to see incredible use cases of AI within the government as well as enterprise automation, according to Wang. Scale AI began working more closely with government agencies this year and added enterprise automation customers like States Title, a residential real estate company.
Wang also saw an increase in uses around conversational AI, in both consumer and enterprise applications as well as growth in e-commerce as companies sought out ways to use AI to provide personalized recommendations for its customers that were on par with Amazon.
Robotics continued to expand as well in 2020, although it spread to use cases beyond robotaxis, autonomous delivery and self-driving trucks, Wang said.
“A lot of the innovations that have happened within the self-driving industry, we’re starting to see trickle out throughout a lot of other robotics problems,” Wang said. “And so it’s been super exciting to see the breadth of AI continue to broaden and serve our ability to support all these use cases.”
The wider adoption of AI across industries has been a bit of a slow burn over the past several years as company founders and executives begin to understand what the technology could do for their businesses, Wang said, adding that advancements in natural language processing of text, improved offerings from cloud companies like AWS, Azure and Google Cloud and greater access to datasets helped sustain this trend.
“We’re finally getting to the point where we can help with computational AI, which has been this thing that’s been pitched for forever,” he said.
That slow burn heated up with the COVID-19 pandemic, said Wang, noting that interest has been particularly strong within government and enterprise automation as these entities looked for ways to operate more efficiently.
“There was this big reckoning,” Wang said of 2020 and the effect that COVID-19 had on traditional business enterprises.
If the future is mostly remote with consumers buying online instead of in-person, companies started to ask, “How do we start building for that?,” according to Wang.
The push for operational efficiency coupled with the capabilities of the technology is only going to accelerate the use of AI for automating processes like mortgage applications or customer loans at banks, Wang said, who noted that outside of the tech world there are industries that still rely on a lot of paper and manual processes.
“I’m super-psyched because I think that the technology is getting to a point where it’s going to meet a lot of the hype that has happened,” he said.
Scale’s 2021
The pursuit of autonomous vehicles was ahead of the curve of a broader adoption of AI, perhaps because it was a use case that caught everyone’s imagination. There has been just this incredible flow of talent and capital into self-driving; it was kind of the belle of the AI ball for a while,” Wang said, explaining why Scale AI initially focused on this field.
Scale AI hits $3.5B valuation as it turns the AI boom into a venture bonanza
Autonomous vehicle development will continue to expand in 2021. However, its place in the AI universe will shift as a diverse mix of industries begin to use artificial intelligence in its own operations, according to Wang.
“As AI makes its way across the whole ecosystem each of these industries are kind of having their own mini self-driving moments,” he said. E-commerce is is learning how to apply AI to shopping preferences, government is understanding how AI can help reduce red tape and enterprises are learning they can use it to converse with customers and modernize “old stodgy processes” that have been around for forever, Wang predicted.
Scale AI plans to scale its business to suit the changing landscape of AI. Perhaps the best example is a product that Scale developed and quietly released this year called nucleus. The product is like Google Photos of machine learning datasets, Wang explained. Customers can use it to organize, curate and manage massive datasets.
The lack of tools to build out machine learning applications is where we see the next biggest bottleneck for customers, Wang said, noting that infrastructure for datasets exists but has been built mostly by and for researchers, not companies. Scale AI plans to continue to build on top of “nucleus” to meet the changing and expanded needs of its customer base.
The startup also plans to hire more employees and has a target of increasing its workforce by 75% to about 350 people. That hiring spree is meant to match the increase in business in 2021, which will be driven by autonomous vehicle technology and other robotics use cases, government, e-commerce and enterprise automation.
How AI will evolve in 2021
Other frontier cases of AI will become more common, Wang said, predicting that Scale will see more customers in 2021 that are working on virtual reality, augmented reality and even drug discovery.
The company is also investing in real-time video datasets, a growing area of interest, Wang said. Scale AI acquired in December computer vision startup Helia to expand its expertise in this area. Real-time video has been used in the development of autonomous vehicles, but it has become increasingly important for VR and AR, he added.
“More and more customers, even beyond just the self-drive folks, were wanting to do AI on real-time video,” he said. “And so it was becoming this expertise that we knew just wasn’t going to go away.”
Wang also is “super excited” about conversational AI and predicts it will be one of the frontiers that will advance over the next year and be adopted by a growing number of enterprise and consumer-facing products.
“The year Scale started in 2016, that was the year of the chatbot, but at that time, the technology was not ready in any way,” Wang said. “Now, fueled by a lot of the advancements in natural language processing, we’ve made some pretty massive advancements with conversational AI.
Wang expects voice assistants like Amazon Alexa and Apple’s Siri will get “a lot smarter,” while enterprise companies will start to rely more on conversational AI for customer interactions.
Tik Tok and personalization
Relevance and personalization — two areas that seemed to be mastered by platforms like Facebook and Instagram — will become more important applications of AI, Wang said.
“Tik Tok took this to a whole new level,” Wang said, noting that the company leapfrogged the competition in part because of how it used AI for video understanding. “It’s like scary good at just knowing the kind of content that you’ll like after very little information from you.”
While personalization isn’t an industry on its own, Wang believes that there will be increased investment and resources dedicated to improving it.
“Tik Tok had this lightning-in-a-bottle-like advancement in AI for personalization,” he said, adding that there’s a lot of interest in figuring out how to replicate that across other major platforms. “Hopefully it gets all the way to e-commerce, where these platforms learn as quickly as possible.”
The growth-consolidation cycle
AI is still in its nascent stages, Wang said. While it is set to grow pretty dramatically, the founder and CEO believes there will continue to be a cycle of new AI-related startups and consolidation in the near term. Cloud-based IT services company ServiceNow’s acquisition in November of Element AI is one example of consolidation that will likely happen in the next year.
“There were a lot of AI companies started over the past few years and not all of them are going to make it,” he said. “But I think there’s still opportunity for new companies to be started.”
Wang admits that for years the hype surrounding AI simply didn’t match with real capabilities. It has caused the tech industry to be dismissive of AI, but Wang predicts that will change in 2021 and 2022.
“We’re going to start to see a lot of real value and ROI generated by AI across more and more businesses,” he said. “Maybe the pithy way to put it is it’s the year to stop dismissing and pay more attention.”
ServiceNow is acquiring Element AI, the Canadian startup building AI services for enterprises
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