Years ago, a mobile app for email launched to immediate fanfare. Simply called Mailbox, its life was woefully cut short -- we'll get to that. Today, its founders are back with their second act: An AI-enabled assistant called Navigator meant to help teams work and communicate more efficiently. With the support of $12 million in Series A funding from CRV, #Angels, Designer Fund, SV Angel, Dropbox's Drew Houston and other angel investors, Aspen, the San Francisco and Seattle-based startup behind Navigator, has quietly been beta testing its tool within 50 organizations across the U.S. "We've had teams and research institutes and churches and academic institutions, places that aren't businesses at all in addition to smaller startups and large four-figure-person organizations using it," Mailbox and Navigator co-founder and chief executive officer Gentry Underwood tells TechCrunch. "Pretty much anywhere you have meetings, there is value for Navigator."
In the lead-up to the 2016 election, very few predicted the degree to which online misinformation would disrupt the democratic process. Now, as we edge closer to 2020, there is a heightened sense of vigilance around new threats to truth in our already fragile information ecosystem. At the top of the list of concerns is no longer Russian bots, but deepfakes, the artifical intelligence-manipulated media that can make people appear to do or say things that they never did or said. The threat is being taken so seriously that last Thursday, the House intelligence committee held Congress's first hearing on the subject. In his opening remarks, Representative Adam Schiff, the committee chairman, talked of society being "on the cusp of a technological revolution" that will qualitatively transform how fake news is made.
Guru Hariharan, chief executive officer of Boomerang Commerce Inc., stands for a photograph after a Bloomberg Technology Television interview in San Francisco, California, July 2018. Boomerang Commerce Inc. provides online retail services by retailing analytics through complex optimization methods, machine learning and real-time data analytics. Machine learning has been one of the top tech new topics in recent months and is now being widely applied to businesses. Briefly, machine learning (ML) is an application of AI (artificial intelligence) that allows systems to learn and improve without being directly programmed. Focussing on the development of computer programs that can access data in order to learn autonomously, machine learning is being used by Google on its AI Platform which is bringing all its services, from data preparation to the training, tuning, deploying, collaborating and sharing of machine learning models.
The healthcare sector has long been an early adopter of and benefited greatly from technological advances. These days, machine learning (a subset of artificial intelligence) plays a key role in many health-related realms, including the development of new medical procedures, the handling of patient data and records and the treatment of chronic diseases. As computer scientist Sebastian Thrum told the New Yorker in a recent article titled "A.I. Versus M.D., "Just as machines made human muscles a thousand times stronger, machines will make the human brain a thousand times more powerful." Despite warnings from some doctors that things are moving too fast, the rate of progress keeps increasing. And for many, that's as it should be. "AI is the future of healthcare," Fatima Paruk, CMO of Chicago-based Allscripts Analytics, said in 2017. She went on to explain how critical it would be in the ensuing few years and beyond -- in the care management of prevalent chronic diseases; in the leveraging of "patient-centered health data with external influences such as pollution exposure, weather factors and economic factors to generate precision medicine solutions customized to individual characteristics"; in the use of genetic information "within care management and precision medicine to uncover the best possible medical treatment plans." "AI will affect physicians and hospitals, as it will play a key role in clinical decision support, enabling earlier identification of disease, and tailored treatment plans to ensure optimal outcomes," Paruk explained. "It can also be used to demonstrate and educate patients on potential disease pathways and outcomes given different treatment options.
We already knew an artificial intelligence could reflect the racial bias of its creator. But San Francisco thinks the tech could potentially do the opposite as well, by identifying and counteracting racial prejudice -- and it plans to put the theory to the test in a way that could change the legal system forever. On Wednesday, San Francisco District Attorney George Gascon announced that city prosecutors will begin using an AI-powered "bias-mitigation tool" created by Stanford University researchers on July 1. This could include their last name, eye color, hair color, or location. It also removes any information that might identify the law enforcement involved in the case, such as their badge number, a DA spokesperson told The Verge.
Last year's Camp Fire in California was devastating. California's hillsides are still green, thanks to a surplus of rain in the past few months, but the state is already exhorting homeowners to build 100 feet of "defensible space" around their homes, an ominous warning of the coming wildfire season. Cape Analytics, a data startup, wants to do one better, using images from the air and data analytics to identify homes most at risk from a fast-moving wildfire. The Mountain View, California-based company said Wednesday that it is releasing a new product that makes use of its machine learning tools for aerial imagery to assess wildfire risks to people's homes. The primary customer for the product is insurance companies, who can use the tools to assess risk and notify homeowners if that risk can be mitigated.
A radical electric passenger drone developed by Airbus has completed its first full transition flight, proving its ability to take off vertically and accelerate to over 100 miles per hour before slowing down for a soft landing. Vahana, the project working to bring the craft to life under Airbus's innovation arm, shared incredible footage of the accomplishment this week. The test marked Vahana's 66th flight, a number it has since surpassed by more than a dozen. In a blog post announcing the milestone, Vahana's Zach Lovering said the test'represents everything we set out to achieve when we began our flight test campaign.' The successful full transition flight was performed on May 3 in Oregon.
On May 14, 2019, the San Francisco government became the first major city in the United States to ban the use of facial-recognition technology (paywall) by the government and law enforcement agencies. This ban comes as a part of a broader anti-surveillance ordinance. As of May 14, the ordinance was set to go into effect in about a month. Local officials and civil advocates seem to fear the repercussions of allowing facial-recognition technology to proliferate throughout San Francisco, while supporters of the software claim that the ban could limit technological progress. In this article, I'll examine the ban that just took place in San Francisco, explore the concerns surrounding facial recognition technology, and explain why an outright ban may not be the best course of action.