Faster Innovation and Development with a Full-Stack AI Strategy

Faster Innovation and Development with a Full-Stack AI Strategy

The future is here and companies that have incorporated the latest innovations led by AI in their business processes are reaping the rewards. 
A full-stack AI strategy is the way forward and is being adopted by numerous organizations with their eyes on the future. Organizations that have currently implemented the full-stack approach within their business processes are developing at a rate faster than the others in the market. 
AI currently presents numerous changes that host the potential to shape the future for the better. Training data models that were conducted in days or months will now be conducted within a matter of minutes or seconds. Compute processing power that is too scarce and costly currently will be available in abundance, and at affordable rates. AI, which is currently being hosted in the cloud, will soon become pervasive across all scenarios. The algorithms we see today were created back in the 1980s, while the algorithms of the future will be more energy-efficient and boast more secure features. Currently, data labeling is often done without intelligence, while in the future it will be automated. 
Models that currently perform only in tests will deliver exemplary results when managed by skilled teams. Models that aren’t updated in real-time will work in real-time within a closed-loop setup. While the current intelligent setup can be limited by inadequate integration within technologies, the future with AI will see a heightened synergy between all modern technologies. Only highly skilled talent can work with AI currently, but it will soon become a basic skill without the user complexity that distinguishes it today. We currently have a scarcity of data scientists, but the industry will soon be marked by an abundance of experts and data science engineers. AI has the full potential to shape the future, and if it does go as predicted, we are in for a ride. 
Ronald van Loon has been associated with the AI industry for years, and is a prominent Huawei partner. He recently had a chance to watch Huawei CEO Eric Xu deliver a live broadcast, wherein they discussed numerous challenges and the benefits of a full-stack AI strategy
The creation of a full-stack environment will improve integration and communication between different members of your team. A full-stack environment will go from chips to connected networks, to the people that are working on the network, and will eventually deliver a seamless experience to customers. By controlling the full-stack environment, you not only ensure a better user experience for your brand, but can also experience faster improvements across the setup. 
What Is the All Scenario AI Framework, and Why Is It Important? 
The presence of AI across all computing frameworks is essential for AI growth and implementation. The All Scenario AI Framework is crucial to the implementation and development of AI across the board, and is essential to Huawei’s integrated AI solution. This framework has the potential to make simple AI applications more pervasive and accessible for everyone involved, while protecting all of your private information and data.. 
Huawei’s AI framework is an indication of all that can be achieved through the implementation of AI across all deployment scenarios. “We have been making steady progress since we announced our AI strategy in October last year,” mentioned Eric Xu, Huawei’s Rotating Chairman. “Everything is moving forward according to plan, from R&D to product launch. We promised a full-stack, all-scenario AI portfolio. And today we delivered, with the release of Ascend 910 and MindSpore. This also marks a new stage in Huawei’s AI strategy.”
The framework by Huawei can help with the easy development of AI while streamlining execution across all kind of scenarios. The adaptability of this framework across various scenarios is what makes it one of the best around. 
Huawei’s Mindspore is a computing framework that is believed to be 50% more efficient for developers. The comparison of the framework was done with other data libraries and frameworks, such as Tensorflow. 
“In a typical neural network for natural language processing (NLP), MindSpore has 20% fewer lines of core code than leading frameworks on the market, and it helps developers raise their efficiency by at least 50%,” Huawei asserts. 
Importance of a Developer Community 
Huawei’s current developer community Huawei is extremely important to the processes they are handling. At present, Huawei has more than 30k developers working on Model Arts to handle around more than 4k plus training tasks for a total of 32k hours per day. 85% of all these developers are related to visual processing, 10% with the processing of audio data, and 5% with Machine Learning. 
With more developers, we get to see more applications in use, which will eventually lead to a better user experience. 
Challenges in Model Development 
Numerous challenges can hinder the path of model development and delay the process. 
Firstly, you require cross-disciplinary expertise, which isn’t always available. Your labor should have expertise in AI, computer systems, and mathematics. 
Secondly, these models are difficult to tune regularly. And, thirdly they rely heavily on experience in distributed system architectures. This third complication can lead to difficulties in parallelism planning. 
The intricacies of AI computing include complex computing processes and diverse computing processors, or units that extend the process. 
Impact of Faster Chip Performance 
The existing chips you have within your system will only be able to meet some of your expectations. These chips do not have the capabilities or the characteristics to handle a diverse range of complications and challenges. This leads to certain limitations that can restrain the scope of your work and your ability to innovate quickly. 
The Ascend 910 by Huawei is the perfect example of how a faster chip can drastically change processes. The combination of Mindspore’s framework with Ascend 910 is currently considered to be around 2 times faster than usual chips at handling AI-related problems. 
The computing powers of AI are currently considered scarce and expensive, but the Ascend 910 challenges all of these limitations. The Ascend 910 promises to bring the greatest AI power packed in a single chip. The chip will speed up the model training process and lower all of the barriers that currently come in the way of model training and algorithmic innovation. The chip is also highly adaptable and can be used across multiple scenarios. 
Role of Expertise and Talent
MindSpore does a great job at reducing all of your reliance on human effort and resources. The framework can go a long way in making AI a skill set that everyone with basic training can handle. 
While only a select few can currently work with AI, this number will grow and Mindspore will soon become integrated across networks. Huawei’s approach can speed up the journey to the next generation by leaps and bounds. 
Speeding up the User Experience
It is pertinent to note that Huawei’s full-stack approach is making waves within the industry, and has two components that can surely dictate the change shortly. The open AI framework, Mindspore, and the fastest AI chip, Ascend 910, are both built to impress. The AI future envisioned by Huawei is one of faster AI model development, faster processes, and faster innovation.
You can learn more about these innovations by clicking here.


Link: Faster Innovation and Development with a Full-Stack AI Strategy