Autonomous delivery company Udelv has signed yet another partner to launch a new pilot of its self-driving goods delivery service: Texas-based supermarket chain H-E-B Group. The pilot will provide service to customers in Olmos Park, just outside of downtown San Antonio where the grocery retailer is based.
California-based Udelv will provide H-E-B with one of its Newton second-generation autonomous delivery vehicles, which are already in service in trials in the Bay Area, Arizona and Houston providing deliveries on behalf of some of Udelv’s other clients, which include Walmart among others.
Udelv CEO and founder Daniel Laury explained in an interview that they’re very excited to be partnering with H-E-B, because of the company’s reach in Texas, where it’s the largest grocery chain with approximately 400 stores. This initial phase only covers one car and one store, and during this part of the pilot the vehicle will have a safety driver on board. But the plan includes the option to expand the partnership to cover more vehicles and eventually achieve full driverless operation.
“They’re really at the forefront of technology, in the areas where they need to be,” Laury said. “It’s a very impressive company.”
For its part, H-E-B Group has been in discussion with a number of potential partners for autonomous deliver trials, and according to Paul Tepfenhart, SVP of Omnichannel and Emerging Technologies at H-E-B, but it liked Udelv specifically because of their safety record, and because they didn’t just come in with a set plan and a fully formed off-the-shelf offering – they truly partnered with HEB on what the final deployment of the pilot would look like.
Both Tepfenhart and Laury emphasized the importance of customer experience in providing autonomous solutions, and Laury noted that he thinks Udelv’s unique advantage in the increasingly competitive autonomous curbside delivery business is its attention to the robotics of the actual delivery and storage components of its custom vehicle.
“The reason I think we’re we’ve been so successful, is because we focused a lot on the delivery robotics,” Laury explained. “If you think about it, there’s no autonomous delivery business that works if you don’t have the robotics aspect of it figured out also. You can have an autonomous vehicle, but if you don’t have an automated cargo space where merchants can load [their goods] and consumers can unload the vehicle by themselves, you have no business.”
Udelv also thinks that it has an advantage when it comes to its business model, which aims to generate revenue now, in exchange for providing actual value to paying customers, rather than counting on being supported entirely through funding from a wealthy investor or deep-pocketed corporate partners. Laury likens it to Tesla’s approach, where it actually has over 500,000 vehicles on the road helping it build its autonomous technology – but all of those are operated by paying customers who get all the benefits of owing their cars today.
“We want to be the Tesla of autonomous delivery,” Laury said. “If you think about it, Tesla has got 500,000 vehicles on the road […] if you think about this, for of all the the cars in the world that have some level of automated driver assistance (ADAS) or autonomy, I think Tesla’s 90% of them – and they get the customers to pay a ridiculous amount of money for that. Everybody else in the business is getting funding from something else. Waymo is getting funding from search; Cruise is getting funding from GM and SoftBank and others, Nuro is getting funding from SoftBank. So, pretty much everybody else is getting funding from a source that’s a different source from the actual business they’re supposed to be in.”
Laury says that Udelv’s unique strength is in the ability the company has to provide value to partners like HEB today, through its focus on robotics and solving problems like engineering the robotics of the loading and customer pick-up experience, which puts it in a unique place where it can fund its own research through revenue-generating services that can be offered in-market now, rather than ten years from now.
Google has employed its network of street view vehicles to also measure street-level air quality in recent years, through an initiative it calls ‘Project Air View.’ Today, it’s making more of the resulting data from that ongoing initiative available to scientists and researcher organizations. The company is releasing an updated version of its air quality data set that includes information collected with partner Aclima’s environmental sensors gathered between 2017 and 2018.
The combined data cache new includes info from the SF Bay and San Joaquin valley area originally starting in 2016, along with the additional two years’ worth of data for those areas as well as for other parts of California, and other major cities including Houston, Salt Lake City, Copenhagen, London and Amsterdam.
All told, Google’s mapping data set for air quality now includes info covering over 140,000 miles and 7,000 hours of combined driving time spanning 2016 through 2018. That’s a significant base upon which to build a study of the trajectory of air quality changes over time, and Google plans to not only continue this program, but expand it with additional coverage for more cities globally, including in Asia, Africa and South America.
For the past nineteen years, Ioannis Tarnanas, the founder and chief scientific officer at Altoida, has been developing virtual and augmented reality tools to offer predictions about the onset of mental illness in older patients.
The company, whose tools have been approved by the Food and Drug Administration for predicting Alzheimer’s, claims that it can determine whether someone will present with the disease six-to-ten years before the onset of mild cognitive impairment symptoms with a 94% accuracy.
In 2019, Alzheimer’s and other dementias will cost the U.S. nearly $290 billion and that figure could rise as high as $1.1 trillion by 2050, according to Altoida.
The number of people living with Alzheimer’s disease is rapidly growing. In 2019 alone, Alzheimer’s disease and other dementias will cost the nation $290 billion. By 2050, these costs could rise as high as $1.1 trillion, but Altoida says that these costs can be prevented if the disease is caught early enough.
Altoida uses an iPad or a tablet accelerometer, a gyroscope, and touch screen sensors to detect what the company calls “micro-errors” as patients complete a series of AR and VR challenges. It’s basically a game of hide-and-seek where patients put virtual objects in different physical spaces in a clinical environment and then try to collect them.
Right now, the company’s technology is only available as a clinically supervised test in a doctor’s office, but the company is beginning to look at bringing its diagnostic tools into the home.
“In this field there are two major waves. Passive digital biomarkers and active digital biomarkers. With passive biomarkers you collect data from sensors,” says Tarnanas. “To give you an example of what this means in real life. [With passive digital biomarkers] you wind up collecting huge amounts of data and you see spikes and associate that with more everyday function or not… you are never sure whether this is due to day to day activity.”
Tarnanas started conducting longitudinal clinical trials around cognitive testing in the early 2000s while he was working on his Masters at the University of Sussex. He then moved to San Diego and worked in the Virtual Reality Medical Center before moving on to Bern Switzerland to conduct additional research. Tarnanas finally settled in Houston, where Altoida is now based.
“Developing enhanced methods to objectively evaluate cognitive function is a critical component of the next generation digital medicine — a component that is required to not only advance the basic research in neurodegenerative disease, but also one that is required for the development of improved clinical interventions,” said Dr. Walter Greenleaf, PhD, a neuroscientist and Distinguished Visiting Scholar working at the Stanford University Virtual Human Interaction Lab, in a statement. “Understanding neurodegenerative biotypes will dramatically improve our ability to conduct a differential diagnosis at the primary care level. Improved diagnostics will provide healthcare professionals with the key information necessary to precisely adapt clinical interventions to personalize the patient’s cognitive care. This will ultimately lead to improved outcomes of care and to reduced healthcare costs.”
Some influential healthcare investors are already on board. Altoida has raised $6.3 million in a new round of financing from investors led by M Ventures, the corporate investment arm of the pharmaceutical company Merck, with additional participation from Grey Sky Venture Partners, VI Partners AG, Alpana Ventures, and FYRFLY Venture Partners.
“The beauty of active digital biomarkers is that they can actually expand to more conditions,” says Tarnanas. The company is looking at expanding its prognostic toolkits to determining lasting impacts from traumatic brain injuries, and post-operative cognitive disorder, he says.
“As the world’s effort to introduce meaningful therapies for Alzheimer’s disease inches closer and closer to success, it is clear that the greatest benefit will come to those whose disease is detected at a very early stage,” said Jonathan L. Liss, MD, Director at Columbus Memory Center and Founder of Columbus Memory Project, who has been using Altoida’s technology since September 2018. “The Altoida Neuro-Motor Index (NMI) device offers an ingenious way in which to detect early disease and track progression without prolonged cognitive testing, tissue sampling, or radiologic intervention. The Altoida NMI device is a welcome advancement to the field of cognitive health.”
Altoida isn’t alone in trying to find a way to diagnose Alzheimer’s earlier. Recently, MyndYou, a New York-based company announced a partnership with Mizuho to bring its passive prognostic toolkit to Japan. That company recently secured roughly $2 million to build out its own solution.