Introduction: The advantages and far-reaching effects of AI can only be seen from the new AI competition between China and the United States. In the future, artificial intelligence will reshape everything from the nature of work to daily communication to transportation. Everything, the “creative destruction” it releases, will revolutionize a large number of existing skills and work conditions, opening up a new era of intelligence.
Artificial intelligence (AI) can be said to be the most revolutionary technology in recent decades, whether it is Google, Facebook, Intel, Alibaba and other Internet companies that enter the field of artificial intelligence through industrial layout, or For example, the original technology companies that started directly with artificial intelligence, such as Vision Technology++, Extreme Chain Technology Video++, and Excellence Technology, have led the new round of AI contours.
The advantages and far-reaching effects of AI can only be seen from the new AI competition between China and the United States. In the future, artificial intelligence will reshape from the nature of work to daily communication to transportation. Everything, the “creative destruction” it releases, will revolutionize a large number of existing skills and work conditions, opening up a new era of intelligence.
Next, let's take a look at a few AI trends in 2019.
The development of AI is a dedicated processor that relies on CPU/GPU to work together. However, the next major drawback is that even if AI is developing at a faster speed, there are cases where the CPU/GPU cannot be trained, such as the need for additional hardware to perform mathematical calculations of complex tasks. At this time, the importance of the AI chip is Prominent.
This year, Intel, NVidia, AMD, ARM, Huawei, Qualcomm and other leading chip manufacturers have put the production of AI chips on the agenda. In 2019, they will be able to quickly improve the speed of AI-based execution. The chips, which will be used in a variety of customized applications not limited to computer vision, language processing, etc., will be based on market needs, and will be launched in specialized applications such as healthcare and automotive.
In 2019, the combination of AI and IoT will achieve a 1+1 2 effect.
For AI, because AI can improve accuracy and improve its analysis and pre-The function of measurable maintenance, so IoT equipment through the optimization of the advanced machine learning model of the AI neural network, and even embedded in the specially designed AI chip, will achieve a more diverse adaptation of the Internet of Everything.
In addition, in 2019, with the popularity of 5G, all equipment and infrastructure will be linked together, technology and products will make our society more efficient, plus AI+IoT More and more will be integrated into edge computing, most of the cloud-trained models will be placed at the edge layer, and finally from the cloud to the edge to the terminal, and finally this network will become more and more complex.
Automated Machine Learning
With the advent of the AutoML (Automatic Machine Learning) algorithm, machine learning will undergo fundamental changes. AutoML will allow developers and programmers to solve complex problems without creating a specific model. The advantage of AutoML is that it allows analysts and developers to focus only on the issues, not the entire process and workflow.
Therefore, AutoML uniquely combines flexibility and portability. AutoML seamlessly aligns with cognitive APIs and custom ML platforms, saving a lot of time and effort by solving problems directly rather than completing the entire workflow.
Due to the huge gap between the needs and supply of cybersecurity experts, and the shortcomings of cybersecurity and the increasing risk of security vulnerabilities requiring innovative approaches, 2019, artificial intelligence and The use of machine learning in network security will be greatly enhanced.
Among them, especially organizations with large amounts of big data, as the scale of the system expands and vigilantly monitors threats, without the artificial intelligence, the network security process becomes vulnerable and leads to reduced efficiency. Incorporating AI into cybersecurity does not mean that no experts are needed. Instead, AI will give experts more power and make the security system more complete.
It is reported that in 2018, artificial intelligence has become one of the highest paid jobs, and many organizations and universities have already added skills training and discipline training in the field of artificial intelligence. Big investment, the same trend will continue in 2019.
However, some of these challenges are also emergingFor example, it is difficult for enterprises to cultivate a high-level talent with strong artificial intelligence skills in the short term. Therefore, they may prefer to set up an artificial intelligence tool that does not need supervision to replace it.
Automation of DevOps through AI
Today, the massive data generated by the Internet cannot be estimated, and it is often necessary to filter and then analyze it. Among them, use AI to sort out the data set. Finding the relevance and new models that can satisfy hardware and other applications will gradually become mainstream.
In 2019, the optimal solution was to apply machine learning models on these datasets to make them predictive, and as AI deepens, the way IT infrastructure is managed will be repositioned. Deploying AI in IT operations will help them complete tasks in a shorter period of time and solve problems quickly. Therefore, AI-based DevOps will be put into operation in 2019, and cloud providers will benefit from it.
Neural Network Interoperability
In some current neural network operations, the most important problem lies in choosing the most appropriate framework, so developers often face a choice from a range of tools. Difficult issues are not limited to Apache MXNet, Microsoft Cognitive Toolkit, TensorFlow, and more.
This is because once the neural network selects and trains a specific model, it is difficult to work on another framework. In response to this challenge, AWS, Facebook and Microsoft collaborated to build an open neural network exchange ( ONNX) makes it possible to reuse trained neural network models in multiple frameworks. In 2019, breakthroughs in interoperability in neural networks will become one of the key trends of AI.
Open Source AI
In 2019, most of AI's projects will be open source because more and more companies are focusing on collaboration and knowledge sharing, and artificial intelligence will follow the same development track. . Open source AI as the next phase of artificial intelligence development, multiple companies will begin to open their AI stack to build a broader AI community support network.
Gartner predicts "to 2020In the year, AI technology will generally appear in almost every new software product and service. Before the day, open source AI will always play an important role. Currently, including Acumos AI, Facebook framework, Yahoo's CaffeOnSpark, Google's TensorFlow, H2O.ai and Microsoft Cognitive Toolkit, etc., both occupy a large share of the market as open source AI tools. In addition, more AI companies are vying to open up their own projects.
Actually With the arrival of 2019, no one can foresee the incredible changes that will happen in the AI field. We can only feel the exciting future from these trends.Written by the author of Cutting-edge technology, the opinion only represents the author and does not represent the position of OFweek. If there is any infringement or other problem, please contact the report.