Nvidia In Its Fifth Gear Towards Success In AI
Nvidia born to win and it did it this time also with no one there to break Nvidia record. They will not feel tired of running the race and will stop after hitting the winning to the pole to start the next production.
Nvidia Growth Financially
Compared to 2016, Nvidia stock price is 69% more touching 178 USD. It is continually proving great in core technology and the GPU image processing units, and that takes Nvidia machine learning business to reach the sky up beating the algorithm of Google and Facebook.
To further increase the Nvidia revenue they have announced recent hardware dealings with 3 Chinese top most internet companies. Also, they are looking at tapping the potential market by partnering with the auto-driven cars. Due to these initiatives, Nvidia has doubled its revenue in 2017, and this trend will move at the rate of 61% increase annually till 2020.
Competition and Threat
However, Nvidia 2020 might get shaken a bit by the competitors who continuously focus on capturing the business in the AI chips second wave. This may be due to Nvidia GPU that was designed for gaming purpose later developed an interest in the AI applications.
Concerning the Tensor Processing Unit, Google claims to be up to 30 times faster when compared to others. Also, Google provides people with the option of using Google TPU on rent. Thus cloud TPU has caught the attention of people.
Next to look at Intel AI hardware bags top place due to their experience in making CPU. For the very purpose, Intel purchased Nervana Systems and Mobileye in 2016 and 17 respectively. With these associations, Intel’s release of Lake Crest chip will gain fame. Another edge for Intel is their investment in neuromorphic computing in which chips do not depend on the architecture of the microprocessor. On the other hand, intel neuron mimic will be attempted to mimic the brain neurons directly.
Previously Amazon used the GPU Nvidia. But, now started using the Amazon Alexa, the digital assistant to transmit via the cloud. Amazon strengthened the processor expertise by acquiring Annapurna Labs in 2015 with $350 million. Amazon with 450 employees is also trying to overtake Nvidia in AI processor development.
Apple’s A11 bionic chip also challenges Nvidia in handling the local AI function.
Nvidia Efforts to Stay Ahead of Competition
Still, if you look at the prediction by ARK, the investment firm, Nvidia will progress to the top of the AI programs by increasing the GPU architecture’s efficiency. It has already raised the GPU chip efficiency by ten times in the last four years.
Also, Nvidia deep learning process helps it to move and stays up the ladder. They are trying ways to optimize the machine learning frameworks that are used in building the AI programs.
Jen-Hsun Huang, Nvidia CEO, said that GPU was not built for machine learning and hence they aren’t efficient as the TPU. TPUs were designed keeping AI in mind, and that will retain Nvidia on the top continuously.
With confidence and constant improvement, Nvidia will continue to grow and stand up the competition.