Umbo CV has raised a 2.8 million seed round for its security cameras, which use artificial intelligence to identify suspicious activity and prevent crimes before they happen. The Taipei- and San Francisco-based startup's funding was led by AppWorks Ventures, with participation from Mesh Ventures, Wistron Corporation, and Phison Electronics. The two-year-old startup has already shipped its system--including cameras and a cloud-based management platform--to clients in Dubai, the United States, and Europe, and will begin mass manufacturing next month. Co-founder and chief executive officer Shawn Guan says Umbo CV has also received 1.4 million in pre-orders and letters of intent from other customers. Its funding will be used for research and hiring.
Artificial intelligence is already in use across surveillance networks around the world. At high security sites like prisons, nuclear facilities or government agencies, it's commonplace for security systems to set up a number of rules-based alerts for their video analytics. So if an object on the screen (a person, or a car, for instance) crosses a designated part of the scene, an alert is passed on to the human operator. The operator surveys the footage, and works out if further action needs to be taken... BRS Labs' AISight is different because it doesn't rely on a human programmer to tell it what behaviour is suspicious. It learns that all by itself.
New York City transit officials are exploring a controversial plan to use artificial intelligence software to track how many subway riders are wearing face masks, and where. The technology, which is currently being used in Paris, was among a host of ideas presented in a consultant's report released to the public on Monday that could help transit authorities measure the level of face mask compliance at specific subway stations. The list includes several high-tech tools like thermal-scanner temperature checks, which has been adopted in Canada and Singapore, as well as UV lamps and robots that China has deployed on buses to kill the viruses on surfaces. "We're exploring the feasibility of a wide range of tools and approaches for helping keep our employees and customers safe," said Andrei Berman, a spokesman for the MTA, in a statement. "AI is one of those tools and we'll continue to research whether it might be effective, and if so, how it might be deployed in an appropriate manner to continue ensuring best public health practices are followed for the safety of our customers and employees."
In July 2019, Guillermo Federico Ibarrola was heading home on the subway when he was stopped by Buenos Aires police. The authorities told Ibarrola that he was being detained for an armed robbery that had happened three years ago in a city about 400 miles away. He said he had never even been to the city where he was accused of committing the crime. On the sixth day in police custody, he was suddenly released. The police officers offered Ibarrola coffee and dinner, and a bus ticket back home. As it turned out, a "Guillermo Ibarrola" had potentially committed a crime, but it wasn't this Guillermo Ibarrola.
Companies and cities all over world are experimenting with using artificial intelligence to reduce and prevent crime, and to more quickly respond to crimes in progress. The ideas behind many of these projects is that crimes are relatively predictable; it just requires being able to sort through a massive volume of data to find patterns that are useful to law enforcement. This kind of data analysis was technologically impossible a few decades ago, but the hope is that recent developments in machine learning are up to the task. There is good reason why companies and government are both interested in trying to use AI in this manner. As of 2010, the United States spent over $80 billion a year on incarations at the state, local, and federal levels. Estimates put the United States' total spending on law enforcement at over $100 billion a year.