Phone Hardware of 2025

Machine Learning Hardware

Machine learning is a subset of AI which has been around in theory since the 1960's. Only lately modern hardware has made it possible to utilize machine learning for practical purposes like image recognition and natural language processing (Forbes, 2018). At present, machine learning is hard to access for anyone who does not dabble in state of the art technology. Take a look at the below video - it showcases Microsoft's president speaking about the future of AI on smartphones and the transformative technology of smart assistants for everybody on Earth:

Until very recently, all state of the art AI research was conducted on traditional Graphical Processing Units (Fogarty, 2017). Companies like Google and ARM are developing specialized hardware which will likely be embedded into our phone hardware by 2025. New advances in technology like Tensor Processing Units developed by Google will allow us all to harness the power of machine learning in an energy efficient manner, and in the small form factor suitable for a phone (Galeon, 2018).

Quantum Computing

Quantum Computing is a fascinating leap forward in how we look at computers. Everything is changed, down to how we interpret the smallest logical unit of a computer: the bit. It is estimated that by 2025 we will be capable of harnessing the power of 100+ QuBits (Quantum Bits).

Source: Engaget.com: This is what a 50-qubit quantum computer looks like (https://www.engadget.com/2018/01/09/this-is-what-a-50-qubit-quantum-computer-looks-like/)

A quantum bit is a unit of information that can achieve quantum entanglement. A normal computer bit can have the value of 1 or 0. A quantum bit can have a value of 1 and 0 at the same time!

Unfortunately, QuBits must always be kept at sub-zero temperatures. At present only industrial-sized freezers can reliably house the massive but fragile power of quantum computers. However, by 2025 it is estimated that cloud computing platforms and specialized hardware will be capable of delivering this immense power into the palm of your hand, right on your phone (Dolev, 2018; Peng, 2018).

“Quantum computing will definitely be applied anywhere where we’re using machine learning, cloud computing, data analysis...” - Kevin Curran, a cybersecurity researcher at Ulster University and IEEE senior member

References

Dolev, S. The quantum computing apocalypse is imminent. (2018, January 05). Retrieved from https://techcrunch.com/2018/01/05/the-quantum-computing-apocalypse-is-imminent/

Fogarty, K. The Next Phase Of Machine Learning. (2017, November 9). Retrieved from https://semiengineering.com/the-next-phase-of-machine-learning/

Galeon, D. AI smartphones will soon be standard, thanks to machine learning chip. (2018, February 14). Retrieved from https://futurism.com/ai-smartphones-machine-learning-chip/

Microsoft - The Impact of Artificial Intelligence - President of Microsoft, Brad Smith. (2018, March 31). Retrieved from https://youtu.be/pYW12_TZyWA

Peng, T. (2018, February 23). Alibaba Launches 11-Qubit Quantum Computing Cloud Service. Retrieved from https://medium.com/syncedreview/alibaba-launches-11-qubit-quantum-computing-cloud-service-ad7f8e02cc8

Team, I. From Imitation Games To The Real Thing: A Brief History Of Machine Learning. (2018, July 18). Retrieved from https://www.forbes.com/sites/insights-intelai/2018/07/17/from-imitation-games-to-the-real-thing-a-brief-history-of-machine-learning/