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Apple had to use iPad components in the iPhone 12 Pro. All due to the lack of components

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Apple had to use iPad components in the iPhone 12 Pro. All due to the lack of components

Today we reported that Apple is facing a serious shortage of power components required for the production of new flagship smartphones of the iPhone 12 series. It is now known that in order to solve the problem, the company has decided to redistribute parts for the production of iPad in order to avoid a shortage of smartphones.

iPhone 12
iPhone 12

The demand for the iPhone 12 Pro was higher than expected. Apple was unprepared for such a development and faced an acute shortage of certain components,  such as power management chips and components for LiDAR modules. And the company found an ambiguous way out of this situation.

According to Nikkei Asia sources, the California-based company is redistributing iPad-grade components for the iPhone 12 Pro in an attempt to prioritize supply shortages. This decision has reportedly disrupted Apple’s tablet production plans for this year. According to some reports, the company has put on the iPhone the components needed to produce about two million iPads.

In addition, Apple has reportedly asked its suppliers to prepare over 20 million more affordable iPhone models, namely the iPhone 11, SE, and XR, for the holiday shopping season. As for the iPhone 12, according to reports, the total number of orders for the production of smartphones in this series by the end of the year is between 75 and 80 million units.

Source: https://phonemantra.com/apple-had-to-use-ipad-components-in-the-iphone-12-pro-all-due-to-the-lack-of-components/

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Research

Researchers hacked a robotic vacuum cleaner to record speech and music remotely

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A team of researchers demonstrated that popular robotic household vacuum cleaners can be remotely hacked to act as microphones.

The researchers—including Nirupam Roy, an assistant professor in the University of Maryland’s Department of Computer Science—collected information from the laser-based  in a popular vacuum robot and applied  and deep learning techniques to recover speech and identify  playing in the same room as the device.

The research demonstrates the potential for any device that uses light detection and ranging (Lidar) technology to be manipulated for collecting , despite not having a microphone. This work, which is a collaboration with assistant professor Jun Han at the University of Singapore was presented at the Association for Computing Machinery’s Conference on Embedded Networked Sensor Systems (SenSys 2020) on November 18, 2020.

“We welcome these devices into our homes, and we don’t think anything about it,” said Roy, who holds a joint appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS). “But we have shown that even though these devices don’t have microphones, we can repurpose the systems they use for navigation to spy on conversations and potentially reveal .”

The Lidar navigation systems in household vacuum bots shine a laser beam around a room and sense the reflection of the laser as it bounces off nearby objects. The robot uses the reflected signals to map the room and avoid collisions as it moves through the house.

Privacy experts have suggested that the maps made by vacuum bots, which are often stored in the cloud, pose potential privacy breaches that could give advertisers access to information about such things as home size, which suggests income level, and other lifestyle-related information. Roy and his team wondered if the Lidar in these robots could also pose potential security risks as sound recording devices in users’ homes or businesses.

Sound waves cause objects to vibrate, and these vibrations cause slight variations in the light bouncing off an object. Laser microphones, used in espionage since the 1940s, are capable of converting those variations back into sound waves. But laser microphones rely on a targeted laser beam reflecting off very smooth surfaces, such as glass windows.

Could your vacuum be listening to you?
Deep learning algorithms were able to interpret scattered sound waves, such those above that were captured by a robot vacuum, to identify numbers and musical sequences. Credit: Sriram Sami

A vacuum Lidar, on the other hand, scans the environment with a laser and senses the light scattered back by objects that are irregular in shape and density. The scattered signal received by the vacuum’s sensor provides only a fraction of the information needed to recover sound waves. The researchers were unsure if a vacuum bot’s Lidar system could be manipulated to function as a microphone and if the signal could be interpreted into meaningful sound signals.

First, the researchers hacked a robot vacuum to show they could control the position of the  and send the sensed data to their laptops through Wi-Fi without interfering with the device’s navigation.

Next, they conducted experiments with two sound sources. One source was a human voice reciting numbers played over computer speakers and the other was audio from a variety of television shows played through a TV sound bar. Roy and his colleagues then captured the laser signal sensed by the vacuum’s navigation system as it bounced off a variety of objects placed near the sound source. Objects included a trash can, cardboard box, takeout container and polypropylene bag—items that might normally be found on a typical floor.

The researchers passed the signals they received through deep learning algorithms that were trained to either match human voices or to identify musical sequences from television shows. Their computer system, which they call LidarPhone, identified and matched spoken numbers with 90% accuracy. It also identified television shows from a minute’s worth of recording with more than 90% accuracy.

“This type of threat may be more important now than ever, when you consider that we are all ordering food over the phone and having meetings over the computer, and we are often speaking our credit card or bank information,” Roy said. “But what is even more concerning for me is that it can reveal much more personal information. This kind of information can tell you about my living style, how many hours I’m working, other things that I am doing. And what we watch on TV can reveal our political orientations. That is crucial for someone who might want to manipulate the political elections or target very specific messages to me.”

The researchers emphasize that vacuum cleaners are just one example of potential vulnerability to Lidar-based spying. Many other devices could be open to similar attacks such as smartphone infrared sensors used for face recognition or passive infrared sensors used for motion detection.

“I believe this is significant work that will make the manufacturers aware of these possibilities and trigger the security and privacy community to come up with solutions to prevent these kinds of attacks,” Roy said.

Source: https://techxplore.com/news/2020-11-hacked-robotic-vacuum-cleaner-speech.html

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iPhone 12 Pro Max receives ‘highest ever’ rating from DisplayMate, sets 11 records

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DisplayMate has put the iPhone 12 Pro Max Super Retina XDR display through its highly detailed testing and the outcome isn’t surprising: Apple has once again earned “DisplayMate’s highest ever Display Performance Grade of A+” and “Best Smartphone Display Award.” However, going beyond the iPhone 11 Pro’s accolades last year, the 12 Pro Max has matched or set 11 smartphone display performance records.

DisplayMate just published its deep dive review of the iPhone 12 Pro Max display. As has become a tradition, this year’s iPhone has garnered another highest ever A+ rating from the firm but more notably it has hit a milestone for how many new records it’s broken or matched: 11. For comparison, the iPhone 11 Pro matched or set 9 display performance records last year and did the same for 8 with the iPhone XS Max in 2018.

Here are the smartphone display records that DisplayMate says the iPhone 12 Pro Max has set/matched:

Note that Numerical Performance Differences that are Visually Indistinguishable are considered Matched and Tied Performance Records.

· Highest   Absolute Color Accuracy  (0.9 JNCD)  –  Visually Indistinguishable From Perfect.

· Highest   Image Contrast Accuracy and Intensity Scale Accuracy  (2.19 Gamma)  –  Visually Indistinguishable From Perfect.

· Smallest  Shift in Color Accuracy and Intensity Scale with the Image Content APL  (0.2 JNCD)  –  Visually Indistinguishable From Perfect.

· Smallest  Shift in Image Contrast and Intensity Scale with the Image Content APL  (0.00 Gamma)  –  Visually Indistinguishable From Perfect.

· Smallest  Change in Peak Luminance with the Image Content Average Picture Level APL  (1 percent)  –  Visually Indistinguishable From Perfect.

· Highest   Full Screen Brightness for OLED Smartphones  (825 nits for 100% APL).

· Highest   Full Screen Contrast Rating in Ambient Light  (172 at 100% APL).

· Highest   Contrast Ratio  (Infinite).

· Lowest    Screen Reflectance  (4.8 percent).

· Smallest  Brightness Variation with Viewing Angle  (27% at 30 degrees).

· Highest   Visible Screen Resolution 2.8K (2778×1284)  –  4K Does Not appear visually sharper on a Smartphone.

DisplayMate also touches on the iPhone 12 lineup featuring a 60Hz display instead of an upgraded 120Hz one like on the iPad Pro. It concludes that it “should be fine for most applications.”

The iPhone 12 Pro Max display has the standard 60 Hz Refresh Rate, rather than the higher 90 Hz and 120 Hz Refresh Rates now being introduced. With the very fast Response Time of the OLED display, and the very fast CPU and GPU processors on the iPhone 12 Pro Max, the lower 60 Hz Refresh Rate should be fine for most applications.

For a detailed look at all the ways DisplayMate tested Apple’s latest state-of-the-art iPhone display, check out the full report here.

Source: https://9to5mac.com/2020/11/17/iphone-12-pro-max-receives-highest-ever-rating-from-displaymate-sets-11-records/

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Research

SSD or HDD For Laptop, Which Is Better?

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samsung solid state drives

 

Seagate Barracuda Hard Disk Drive

 

 

  

 

fast ssds

  

  

 

slow hdds
 

   

  

  


 

  

   

   

magnet

 

 

 

 

 

  

   


  
 

 

 

  

 

 

 

   

  

  

 

Source: https://www.techconsumerguide.com/ssd-vs-hdd-for-a-laptop/

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