Uber recently announced that it will close 45 offices globally, and slashed 3,000 jobs early last week, the Wall Street Journal first reported. This comes two weeks after the tech-disruptor laid off 3,700 Uber employees. Altogether, in less than a month, Uber has laid off 6,700 of its employees, a significant chunk of its workforce.

Uber’s CEO, Dara Khosrowshahi, announced the bad news to the staff via email. The move includes shutting down divisions such as Uber Incubator, job-matching service, Uber Works, and the artificial intelligence (AI) division Uber AI Labs putting a halt to the company’s futuristic dreams as part of Khosrowshahi’s $ 1-billion cost-cutting plans. 

“We are organizing around our core: helping people move, and delivering things…Given the necessary cost cuts and the increased focus on core, we have decided to wind down the Incubator and AI Labs and pursue strategic alternatives for Uber Works,” reads Khosrowshahi’s email the was sent to the staff.

The main aim of Uber’s AI Lab, founded in 2016, was to make everything that the company did, smarter in the future - from ride prediction, logistics, food delivery and autonomous self-driving cars. Uber’s set-up was termed as an almost perfect playground for testing AI technologies. It was a large-scale company with possibilities of creating AI-centric transportation models. However, Uber AI Lab was not only dedicated to finding out better transportation solutions, but it had also ventured beyond that.

Uber’s Paired Open-Ended Trailblazer, aka POET, is an AI algorithm that generates it’s own challenging paths and explores possible solutions through various agents. Uber researchers applied the algorithm to automatically generate a walking obstacle course for a bipedal agent. The bipedal agent learnt to navigate through the environment, ranging from easy to extremely difficult.

 “At a more practical level, it could generate simulated test courses for autonomous driving that both expose unique edge cases and demonstrate solutions to them,” proclaimed an Uber blog post. While POET’s obvious application was to help train autonomous drivers, researchers also stated that POET’s problem-solving capabilities can be applied for “inventing new proteins or chemical processes that perform novel functions that solve problems in a variety of application areas.”

Ludwig, Uber’s open-source toolbox was a breakthrough product which enabled developers to create, train and test AI models without needing to write codes. Uber used Ludwig internally too. 

“We have witnessed its value to several of Uber’s own projects, including our Customer Obsession Ticket Assistant (COTA), information extraction from driver licenses, identification of points of interest during conversations between driver-partners and riders, food delivery time prediction, and much more,” researchers wrote in an Uber blog. 

But outside these applications, Ludwig is capable of training models that can perform tasks like “text classification, object classification, image captioning, sequence tagging, regression, language modelling, machine translation, time series forecasting, and question answering.”

Uber AI Lab produced a new technique that is capable of training deep neural networks (DNNs). Their simple generic algorithm taught deep convolutional networks to play Atari games, an industry benchmark for testing adaptive algorithms, with over 4 million parameters. The DNNs had the potential of being applied to a multitude of areas from operations to creating better, reliable transportation solutions.

Experts in the industry warn that Uber’s steps may put the company’s future in perils by focusing on short-term cost-cutting. 

“With a long-term strategy focused on R&D, Uber’s position as the world’s largest (and best-known) ride-sharing platform puts it in a unique position to take advantage of economies of scale and develop driverless technologies and machine learning algorithms for its platform…Uber does not need to end its cost-cutting approach. It just needs to ensure that it is selective in what is being cut,” stated Danyaal Rashid, Thematic Analyst at GlobalData, a leading data and analytics company.

While for the moment, Uber’s dream of entering the autonomous driving arena have met an impasse with Khosrowshahi’s decision to shut down the Uber’s AI Lab and focus on core business amidst COVID-19 pandemic, handful companies in the industry have actually been progressing further with research and development of autonomous driving technology due to the pandemic.

Waymo, Alphabet Inc’s self-driving unit, announced an additional external investment of $ 750 million, bringing the firm’s total external investment to $3 billion in three months. On the company blog, CEO John Krafcik acknowledged how COVID-19 pandemic has highlighted the need for such technology, stating “COVID-19 has underscored how fully self-driving technology can provide safe and hygienic personal mobility and delivery services. We’re grateful these partners share our mission to make it safe and easy for people and things to get where they’re going.”

The COVID-19 pandemic’s epicentre, China, saw an increased demand for autonomous vehicles as opportunities for driverless deliveries and non-contact services increased. Baidu has released 104 driverless vehicles in China, across 17 cities. These vehicles carry out risk-laden work such as disinfectant operations, security robots to enforce coronavirus prevention guidelines, logistical support such as transporting medical and food supplies to hospitals and transportation support. Baidu has also launched a Robo-taxi service in Changsha region in April.

Meanwhile, Chinese self-driving car start-up AutoX is the first service to be allowed to pick-up and drop services in Jiading, a suburban district in Shanghai. The taxi service is allowed to speed up to the speed limit of 80km an hour, as reported by the Financial Times. The company had signed a deal in March, to launch a 100 Robo-taxis on the roads of Jiading district. Meanwhile, AutoX’s rival, WeRide.com has increased it’s presence in Guangzhou with 100 driverless vehicles.

While once, Uber was Silicon Valley’s blue-eyed tech-disruptor, the recent decisions probably have opened up the ground for newer players to have their chance in the sun.

Image by zombieite via Flickr