Samsung Galaxy S20 FE 5G (8GB RAM /128GB Storage) Cloud Navy

Today Offers :- save cost RS-27,000


Specification :-

ModelGalaxy S20 FE
Display6.5 inches (101.0 cm2 )
Body / Weight190 g (6.70 oz)
Operating System OS
Android 10, upgradable to Android 11, One UI 3.1

Chipset :- Qualcomm SM8250 Snapdragon 865 5G (7 nm+)
Front Camera12MP (wide)
8MP (telephoto)
12MP (ultra-wide)
Rear Camera32MP (wide)
CommsBluetooth :- 5.0, A2DP, LE


Radio :- FM Radio

USB :- Type-C 3.2
Battery25W (Fast Charging)
4.5W (Reverse wireless charging)
15W (Fast wireless charging)
USB Power Delivery 3.0
ColorsCloud Navy, Cloud Mint,Cloud White,Cloud Lavender
Memory8GB RAM / 128GB

HighLights :-

Samsung Galaxy S20 FE 5G smartphone was launched on 23rd September 2020. The phone comes with a 6.50-inch touchscreen display with a resolution of 1080×2400 pixels and an aspect ratio of 20:9. Samsung Galaxy S20 FE 5G is powered by an octa-core Qualcomm Snapdragon 865 processor. It comes with 8GB of RAM. The Samsung Galaxy S20 FE 5G runs Android 10 and is powered by a 4500mAh battery. The Samsung Galaxy S20 FE 5G supports proprietary fast charging.

The Samsung Galaxy S20 FE 5G runs One UI 2.0 is based on Android 10 and packs 128GB of inbuilt storage that can be expanded via microSD card (up to 1000GB) with a dedicated slot.

The Samsung Galaxy S20 FE 5G is a dual-SIM (GSM and GSM) smartphone that accepts Nano-SIM and Nano-SIM cards. The Samsung Galaxy S20 FE 5G measures 159.80 x 74.50 x 8.40mm (height x width x thickness) and weighs 190.00 grams. It was launched in Cloud Lavender, Cloud Mint, and Cloud Navy colours. It features an IP68 rating for dust and water protection.

As far as the cameras are concerned, the Samsung Galaxy S20 FE 5G on the rear packs a 12Mp primary camera; a 12MP camera, and an 8MP camera. The rear camera setup has autofocus. It sports a 32MP camera on the front for selfies.

Connectivity options on the Samsung Galaxy S20 FE 5G include Wi-Fi 802.11 a/b/g/n/ac, GPS, Bluetooth v5.00, USB Type-C, 3G, and 4G (with support for Band 40 used by some LTE networks in India). Sensors on the phone include accelerometer, ambient light sensor, compass/ magnetometer, gyroscope, proximity sensor, and in-display fingerprint sensor. The Samsung Galaxy S20 FE 5G supports face unlock.

Pros :-

  1. Excellent performance
  2. Long-lasting battery life
  3. Compact design
  4. IP68 water and dust resistance
  5. Decent hardware performance
  6. Android 11-based One UI
  7. Impressive cameras

Cons :

  1. Ships with a 15W charger
  2. No headphone jack
  3. Wide-angle sensor isn’t the best
  4. Hybrid SIM slot for storage


OPPO F19 Pro + 5G (Space Silver, 8GB RAM / 128GB Storage)

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Specification :-

ModelF19 Pro (5G)
Display6.43 inches (99.8 cm2 )
Body173 g (6.10 oz)
Operating SystemOS
Android 11, ColorOS 11.1

Chipset :- MediaTek MT6853 Dimensity 800U 5G (7 nm)
Memory8GB RAM / 128GB
Battery50W (Fast charging) 100% in 45 min
Rear Camera48MP (wide)
8MP (ultra-wide)
2MP (macro)
2MP (depth)
Front Camera16MP (wide)
CommsBluetooth :- 5.1, A2DP, LE, aptX HD

Radio :- Unspecified


USB :- Type-C 2.0

HighLights :-

Oppo F19 Pro Plus is the new entrant in the Oppo smartphone family that is available at a starting price of Rs 25,990. This dual SIM phone supports the 5G network and is available in Fluid Black and Space Silver colour options. Oppo F19 Pro Plus comes with mid-range specifications and impressive design. Also, being lightweight and sleek, you can carry it with ease. 


The smartphone receives an outstanding Quad-camera configuration on its backside, which includes a 48MP f/1.7 (Wide) Angle Primary Camera supported by an 8MP f/2.2 (Ultra-wide) Angle Camera, 2MP f/2.4 (Macro) Camera, and 2MP f/2.4 (Depth) Camera.

The device combines several camera-features such as LED Flash, Autofocus, Exposure compensation, Digital Zoom, HDR mode, Continuous Shooting, Auto Flash, Face detection, and Touch to focus. Furthermore, there is a 16MP f/2.4 (Wide) Angle Primary Camera placed on the front side of the device, which can capture amazing selfies.


OPPO F19 Pro Plus arrives with a 6.43-inch Super AMOLED type display offering an aspect ratio of 20:9 and a screen resolution of 1080 x 2400 pixels. The bezel-less display of the smartphone frames a punch-hole setup teamed with a pixel density of 409ppi.

Pros :-

  1. Decent cameras
  2. Looks attractive
  3. 50W fast charging support

Cons :-

  1. No stereo speakers
  2. Price-performance ratio isn’t great
  3. Lacks high refresh rate screen

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We are running after AI that has cognitive capabilities of the human brain

For a very long time, humans has been trying to design a machine that have complex capabilities like how human brain does. When artificial intelligence first came into existence, people thought that’s making a model that imitates human will be easy. But it is took more than five decades for scientists to turn the concept successful. we are running after machines that carry the cognitive capabilities of human brain in it.

Why is designing a mechanism that it is similar to human brain complex?

To be honest, researchers are still working on finding how human brain functions. Even though our daily work & action are just a part of simple routine, the brain has cognitive capabilities that power our body to cooperate with it. While researchers have explored some of the ends of brain, some others still remain an unsolved riddle. Maybe that’s why researchers took the complex human brain as an inspiration to formulate a machine brain. Unfortunately, recreating cognitive capabilities in a deep neural network is not easy & it is the elusive goal of artificial intelligence. But neural network emerge as a source to emulate human and machine connections. As neural network evolve, other human cognitive skills are also becoming increasingly relevant. However, despite the challenges, more AI researchers are engaged in implementing algorithms that are inspired by specific cognitive mechanisms in the human brain that have been producing incredibly promising results.

Human-machine interaction is already in place, thanks to Watson, Siri, Cortana, etc. But for artificial intelligence to have a truly transformational impact, artificial neural networks need to be further reinforced by human native intelligence. But why is it hard for scientists to replicate human brain with machine capabilities? It is because humans did not reach the place they are today easily. They have been through a lot. The human brain has advanced over time in responding to survival instincts, harnessing intellectual curiosity, and managing the demands of nature. Starting from the time when Neanderthals hunted animals for food to today, humans realizing that light-weighted wings could make a helicopter fly on Mars, everything was a slow evolution. While the human brain finds ways to exceed our physical capabilities, the combination of mathematics, algorithms, computational methods, and statistical methods is accelerating our scientific pursuit.

artificial intelligence

Attention :-

Have you ever thought that’s machines can’t focus on something or get distracted the other when it hear a sound or sees something out of the box? We humans do that all the time. Furthermore, we can do both. We can focus and give our attention to the certain thing for a long time by forgetting what is around us, & on the other hand, we can also divert our attention when necessary. Researchers are taking inspiration from the human brain’s attention mechanism. They are powering convolutional neural networks (CNN) or deep generative models by the deep learning methods.


Thinking is a routine activity of humans. We don’t put too much effort to come up with solutions. The reason behind this is we has memory, information process, speech or object recognition capabilities etc. that’s are simultaneously working along with us. This can be replicated in artificial intelligence models by a creating theoretical models of the human brain for inter-disciplinary studies on it is functions, including vision, motion, sensory control, and learning.

Reproducing sense:-

Recognizing certain things is comparatively tough for machines. In order to recognize in object or a voice, artificial intelligence models has to be fed with similar data. Only after showing thousands of images of a monkey, the model will be able to recognize it correctly. Henceforth, the mechanism behind a machine brain is reproducing brain data. It helps machines detect an object in various positions under different lighting conditions.