My dad’s 1978 house fell-through when he tried to use this weatherization\effeciency\free repair program back in 2005. The local overseer company could only “gift” one single family house per month. The applicant list was +5,000 homes long. Funds were exhausted in less than 1 year… so that’s like 11 or 12 homes that got what they needed.

Everyone else got: weather stripping, faucet areators, 2 smoke alarms, window repair glue, 5 (max) compact florescent bulbs, 1 “air filter” for your ac\furnace (it was garbage fishing troller net precut filter floss), an attic inspection, a house pressure air leak test, and one tree removal referral (never happened).

The team that came to the house was professional though. Protective gear, professional testing equipment, They mentioned half received minimum wage, half volunteers.

In the end, the bad roof and single-pane windows remained.

They’re not separating data throughly. Researcher Yifang Zhu, over many publishings, mainly gathers and publishes raw findings. Such as… (summarizing) “Children are at risk due to immature respiratory systems and faster breathing rates… by traveling in diesel powered school buses in my South Texas study.”
Source- https://scholar.google.com/citations?view_op=view_citation&hl=en&user=kvSIKM8AAAAJ&cstart=20&pagesize=80&citation_for_view=kvSIKM8AAAAJ%3A5nxA0vEk-isC

A research participant, Yifang Zhu, is tied to a thing called Mobility Justice Frameworks. It’s pushing for greenspaces in urban areas, including making existing infrastructures look bad for its cause(s).

The research team has more A.I. tools than proper researching. It’s odd.

My bottom-of-the-rabbit-hole best guess. Create premature science data media for campaigns for lawmakers to push for more greenspaces in urban areas.

I just web searched the names of this research team… The last one on the list is a teeth-puller, folks.

Yuan Yao, teacher of sustainable systems.

Muchuan Niu, UCLA student, MS in Environmental Sciences.

Haoxuan Chen, Stanford student, machine learning.

Qiao Yu, Shanghai A.I. Laboratory.

Qingyang Wu, private A.I. developer.

Yuhang Li, student, Art History, A.I. cloud data processor.

Yijie Zhang, UCLA student, A.I. machine learning.

Aydogan Ozcan, UCLA, computational imaging and deep learning optics.

Michael Jerrett, teacher at UCLA, geographic information systems science, spatial exposure science.

Yifang Zhu, student in Environmental Sciences, associate of UCLA Fielding School project group, funds and\or law underwriter for Mobility Justice Frameworks (Mobility Justice is an almost eco-extremist entity that also uses racial cause to gather USDOT public funding).

“…creation of motion graphics designer Tom Coben…” https://mashable.com/video/bowling-robot-video-computer-generated

I imagine they will scale back robot design and just throw from the truck.

They said it’s rolling out in beta. Spam Protection is already in the Messages app. Scam Protection is coming soon. But to listen to telephone audio that means they want to add it into the native dialer\phone app. Google has a dialer app named “Phone” with a Spam filter feature currently.

I assume that’s what is coming – a.i. into the dialer\phone app.

Similar to cellphone a-gps (assisted gps) with a supplemental unified NLP (network location provider) addon feature found on recent phones… but beefed-up on a large-scale. This should provide more emitter sources, whitelisting and blacklisting, and dedicated software to help discover bad or rogue emitters.

I’m going off the graphic guessing the “detectors” continuous scanning contributes into a database that users will then subscribe on to; instead of the cellphone makeing the self-processing decisions in NLP software.