In 2022 I would have accepted $10 per sq ft if it ticked all the boxes. There's been a few spaces I kicked myself over not signing soon enough ($6 per sq ft, 3200 sq ft, large with ample power 480v with 600 amp service, concrete roof, dock door)
253 karma · joined November 3, 2015
I've been looking for 1500-3000 sq ft for a light manufacturing space for around two years. In my area warehouse $/sqft is $5-7 a year. Office space is $13 for old and dated layouts. I have no use for that dotcom era conference room. I need 10 ft dock doors, tall ceilings, and reliable 3 phase power.
Buying land outside my metro area and building new is becoming the only option for me until this crash actually happens. Sprawling out of the metro would only bite me down the line because the labor market is even tighter in rural areas.
I work with a company that recycles older hybrid batteries from Toyota, Honda, Ford. Most of these are NiMH and pay $0.40-$0.80 per pound for the Nickel value alone.
So a NiMH hybrid battery is worth $50 for the core from a Prius, but a lithium battery from a Nissan Leaf would cost you ~$700 to recycle.
If the mesh was every Digital TV tuner inside a municipality, then maybe the mesh could triangulate position.
I've been setting up old GPUs for folding@home and recently acquired a Nvidia Jetson AGX Xavier for machine vision.
Currently I'm building a 6 camera rig using Raspberry Pi IMX219 or IMX477 cameras to create an ultra high FPS rolling shutter.
Warning, her writing style is closer to rambling than academic/professional.
That's a strange way to exclude sex workers.
I'm thinking specifically about the DOD/ITAR material traceability market. They would eat this product up at $1 per label.
* 2.4GHz 8‑core 9th‑generation Intel Core i9 processor, Turbo Boost up to 5.0GHz
* 64GB 2666MHz DDR4 memory
* AMD Radeon Pro 5500M with 8GB of GDDR6 memory
* 8TB SSD storage
for $6099USD. I wonder how it will handle the thermals.
So 3.297 cents per kwh. That's on par with large hydro like Tacoma Power Park. I'm getting 11 cents per kwh for my solar currently in the midwest.
• We designed a pipeline for automatically discovering vulnerabilities in the Android permissions system through a combination of dynamic and static analysis, in effect creating a scalable honeypot environment.
• We tested our pipeline on more than 88,000 apps and discovered a number of vulnerabilities, which we responsibly disclosed. These apps were downloaded from the U.S. Google Play Store and include popular apps from all categories. We further describe the vulnerabilities in detail, and measure the degree to which they are in active use, and thus pose a threat to users. We discovered covert and side channels used in the wild that compromise both users’ location data and persistent identifers.
• We discovered companies getting the MAC addresses of the connected WiFi base stations from the ARP cache. This can be used as a surrogate for location data. We found 5 apps exploiting this vulnerability and 5 with the pertinent code to do so.
• We discovered Unity obtaining the device MAC address using ioctl system calls. The MAC address can be used to uniquely identify the device. We found 42 apps exploiting this vulnerability and 12,408 apps with the pertinent code to do so.
• We also discovered that third-party libraries provided by two Chinese companies—Baidu and Salmonads— independently make use of the SD card as a covert channel, so that when an app can read the phone’s IMEI, it stores it for other apps that cannot. We found 159 apps with the potential to exploit this covert channel and empirically found 13 apps doing so.
• We found one app that used picture metadata as a side channel to access precise location information despite not holding location permissions.
[0] https://www.ftc.gov/system/files/documents/public_events/141...
• We designed a pipeline for automatically discovering vulnerabilities in the Android permissions system through a combination of dynamic and static analysis, in effect creating a scalable honeypot environment.
• We tested our pipeline on more than 88,000 apps and discovered a number of vulnerabilities, which we responsibly disclosed. These apps were downloaded from the U.S. Google Play Store and include popular apps from all categories. We further describe the vulnerabilities in detail, and measure the degree to which they are in active use, and thus pose a threat to users. We discovered covert and side channels used in the wild that compromise both users’ location data and persistent identifers.
• We discovered companies getting the MAC addresses of the connected WiFi base stations from the ARP cache. This can be used as a surrogate for location data. We found 5 apps exploiting this vulnerability and 5 with the pertinent code to do so.
• We discovered Unity obtaining the device MAC address using ioctl system calls. The MAC address can be used to uniquely identify the device. We found 42 apps exploiting this vulnerability and 12,408 apps with the pertinent code to do so.
• We also discovered that third-party libraries provided by two Chinese companies—Baidu and Salmonads— independently make use of the SD card as a covert channel, so that when an app can read the phone’s IMEI, it stores it for other apps that cannot. We found 159 apps with the potential to exploit this covert channel and empirically found 13 apps doing so.
• We found one app that used picture metadata as a side channel to access precise location information despite not holding location permissions.
I recommend the odroid [1] XU4 (desktop) or [2] HC1 (nas) if you have anything that requires constant read writes. Pi SD cards do go bad over time unless you set it to run the OS from memory. Odroid made a smarter choice going with eMMC early on. The con of odroid is you have to hack everything that was already done on a pi to work.
[1] https://www.hardkernel.com/shop/odroid-xu4-special-price/
[2] https://www.hardkernel.com/shop/odroid-hc1-home-cloud-one/
I wonder how this will integrate with Einstein and other AI products salesforce already has. Pardot is the first to come to mind. They already own Heroku, Mulesoft, and Quip.
Exciting times to be a data geek. Hopefully this adds more money to the AI race.
The one benefit would be if you were using or developing generative design in 3d printed molds, this would be a great test bed.
source - I work in the injection molding, 3dp, and CNC industry.
EDIT: it appears the Livpi uses a K30 chip. The K33 [1] is the version sold on industrial sites.
[0] http://www.livpi.com/ [1] https://www.co2meter.com/products/k-33-icb-co2-sensor
This already exists in the North American market, I.E. Protolabs