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#AndroidDevChallenge

Radar Challenge

#AndroidDevChallenge

By 2022, 80 per cent of smartphones shipped will have on-device AI capabilities, up from 10 per cent in 2017 — Gartner.

Cloud based AI can have both advantages and disadvantages.

Advantages

• Access to a large amount of data on servers and we know it is the data that drives AI
• AI on cloud takes data analysis to the next level. This is because there is a plethora of historical and current data available within a cloud environment. AI learn patterns from data and makes recommendations which tend to be nearly accurate.
• Cost Saving is an essential aspect of using cloud-based services. Organizations need to spend money only on the storage they need — when they need it.

Disadvantages

• However, cloud-based AI also comes with certain drawbacks.
• Latency, i.e., the time lag between input sent and output/results obtained especially in cases of autonomous automobiles where results need to be achieved instantly.
• Privacy concerns which may arise by sending data on the cloud.
• Reliability issues

AI is becoming ubiquitous today. The AI-based services are slowing moving towards personalized experiences in smart home, smart office, smart building, etc. Having on device AI has some tremendous benefits.

Performance

Undoubtedly, on-device processing is much faster than the cloud since it saves the trip from phone to server and back. This is an important factor because some used AI cases cannot afford latency. This can be especially useful in case of autonomous vehicles where the vehicle needs to apply brakes and cannot afford lag of even a second.

Privacy

Today a smartphone stores a lot of our sensitive data in the form of fingerprints, iris scans, voice identifications, etc. having all this data on the device ensures security which can be compromised on the server.

Reliability

Network connectivity is an issue in many parts of the world. This means it would become difficult to fetch data from the servers at locations of bad and no signals. On- device AI can provide a solution to this reliability problem.

Network bandwidth

On device AI also conserves network bandwidth. Regularly sending data back and forth to the cloud will bring a sharp increase in network bandwidth.

Power Saving

Power saving is also an important concern for phones today. Having AI locally will save power — both on the phone and in the server room — since the phone is no longer using its mobile radios to send or receive data and a server isn’t being used to do the processing hardware

On Cloud AI is still very important . They offer the best solutions for Big data problems and running machine learning algorithms on the cloud. However, on-device AI can have a powerful role for real-time and sensitive applications which cannot afford latency or information leak to achieve performance, increase privacy and reduce power.