Databricks AI calls in $1bn investment
Databricks has secured a $1 billion investment to further its rapid growth in the AI market.
The cash will shore up the San Francisco-based company’s heady rise in unified data. Investors in this round of funding were led by newcomer Franklin Templeton, with Canada Pension Plan Investment Board, Fidelity Management and Research and Whale Rock also in the pool.
Databricks has also secured strategic partnerships with AWS, CapitalG and Salesforce.
Existing investors including Microsoft, Andreessen Horowitz, Alkeon Capital Management, funds and accounts managed by BlackRock, Coatue Management, funds and accounts advised by T Rowe Price Associates and Tiger Global Management were also on board for the deal.
Ali Ghodsi, CEO and co-founder of Databricks, said, “We see this investment and our continued rapid growth as further validation of our vision for a simple, open and unified data platform that can support all data-driven use cases, from BI to AI.
“Built on a modern lakehouse architecture in the cloud, Databricks helps organizations eliminate the cost and complexity that is inherent in legacy data architectures so that data teams can collaborate and innovate faster. This lakehouse paradigm is what’s fuelling our growth, and it’s great to see how excited our investors are to be a part of it.”
Jonathan Curtis, senior vice president, research analyst and portfolio manager at Franklin Templeton said, “Franklin Templeton is excited to work with Databricks as they enter this next stage of their impressive journey. We’ve seen first hand their ability to help enterprises leverage data to better understand customer journeys, operationalise business processes and, ultimately, build competitive advantage rooted in data. We believe they have a strong, accomplished team and visionary platform, and believe that the future for Databricks is bright, with a clear leadership position and open-ended growth opportunity.”
‘Scalable data and AI’
Scott Guthrie, executive vice president, cloud and AI at Microsoft, said, “Azure Databricks continues to be an impressive solution that brings the latest advances in open, flexible and scalable data and AI capabilities to our customers. Our investment underscores the vision we share with Databricks of simplifying data and AI for our customers. Together, we will continue to build on the success of Azure Databricks and seamless integrations across Azure data services to enable cloud-scale analytics and AI on Azure.”
The investment takes Databricks market value to $28 billion.
Chinese Firm Taigusys Launches Emotion-Recognition System
In a detailed investigative report, the Guardian reported that Chinese tech company Taigusys can now monitor facial expressions. The company claims that it can track fake smiles, chart genuine emotions, and help police curtail security threats. ‘Ordinary people here in China aren’t happy about this technology, but they have no choice. If the police say there have to be cameras in a community, people will just have to live with it’, said Chen Wei, company founder and chairman. ‘There’s always that demand, and we’re here to fulfil it’.
Who Will Use the Data?
As of right now, the emotion-recognition market is supposed to be worth US$36bn by 2023—which hints at rapid global adoption. Taigusys counts Huawei, China Mobile, China Unicom, and PetroChina among its 36 clients, but none of them has yet revealed if they’ve purchased the new AI. In addition, Taigusys will likely implement the technology in Chinese prisons, schools, and nursing homes.
It’s not likely that emotion-recognition AI will stay within the realm of private enterprise. President Xi Jinping has promoted ‘positive energy’ among citizens and intimated that negative expressions are no good for a healthy society. If the Chinese central government continues to gain control over private companies’ tech data, national officials could use emotional data for ideological purposes—and target ‘unhappy’ or ‘suspicious’ citizens.
How Does It Work?
Taigusys’s AI will track facial muscle movements, body motions, and other biometric data to infer how a person is feeling, collecting massive amounts of personal data for machine learning purposes. If an individual displays too much negative emotion, the platform can recommend him or her for what’s termed ‘emotional support’—and what may end up being much worse.
Can We Really Detect Human Emotions?
This is still up for debate, but many critics say no. Psychologists still debate whether human emotions can be separated into basic emotions such as fear, joy, and surprise across cultures or whether something more complex is at stake. Many claim that AI emotion-reading technology is not only unethical but inaccurate since facial expressions don’t necessarily indicate someone’s true emotional state.
In addition, Taigusys’s facial tracking system could promote racial bias. One of the company’s systems classes faces as ‘yellow, white, or black’; another distinguishes between Uyghur and Han Chinese; and sometimes, the technology picks up certain ethnic features better than others.
Is China the Only One?
Not a chance. Other countries have also tried to decode and use emotions. In 2007, the U.S. Transportation Security Administration (TSA) launched a heavily contested training programme (SPOT) that taught airport personnel to monitor passengers for signs of stress, deception, and fear. But China as a nation rarely discusses bias, and as a result, its AI-based discrimination could be more dangerous.
‘That Chinese conceptions of race are going to be built into technology and exported to other parts of the world is troubling, particularly since there isn’t the kind of critical discourse [about racism and ethnicity in China] that we’re having in the United States’, said Shazeda Ahmed, an AI researcher at New York University (NYU).
Taigusys’s founder points out, on the other hand, that its system can help prevent tragic violence, citing a 2020 stabbing of 41 people in Guangxi Province. Yet top academics remain unconvinced. As Sandra Wachter, associate professor and senior research fellow at the University of Oxford’s Internet Institute, said: ‘[If this continues], we will see a clash with fundamental human rights, such as free expression and the right to privacy’.