A desert robot depicts the vast potential of AI

When Hongji Gao was young, he lived with his family in Gansu, a province in central northern China near the Tenger Desert. Remembering his childhood, he remembers the constant, constant wind of earth outside their house, and that for most months of the year it was less than a minute after going outside before the sand filled every empty space and slipped into his pockets. boots and his mouth. The monotony of the desert had been on his mind for years, and at university he turned that memory into the idea of ​​building a machine that could bring plant life to the desert landscape.

Efforts to stop desertification – the process by which fertile land is turned into a desert – are focused on expensive manual solutions. Hongzhi designs a robot with deep learning technology to automate the process of planting trees: from identifying optimal locations to planting tree seedlings to watering. Although he has no experience with AI, as a student Hongzhi used Baidu’s PaddlePaddle deep learning platform to combine different modules to build a robot with a better ability to detect objects from similar machines already available on the market. It took less than a year for Hongji and his friends to spin the final product and put it into operation.

Hongji’s desert robot serves as a prime example of the growing availability of artificial intelligence.

Today, more than four million developers use Baidu’s open source artificial intelligence technology to create solutions that can improve the lives of people in their communities, and many have little or no technical expertise in the field. “Over the next decade, artificial intelligence will be a source of change in every fabric of our society, transforming the way industries and businesses operate. Technology will enhance the human experience by taking us deeper into the digital world, ”said Baidu CEO Robin Lee at Baidu Create 2021, an AI developer conference.

As we enter a new chapter in the evolution of AI, Haifeng Wang, Baidu’s Chief Technical Officer, identifies two key trends that are at the heart of the industry’s way forward: AI will continue to evolve and increase its technical sophistication. At the same time, deployment costs and barriers to entry will be reduced, benefiting both AI-scale enterprise builders and software developers exploring the AI ​​world.

Combining knowledge and data with deep learning

Integrating knowledge and data with deep learning has significantly improved the efficiency and accuracy of AI models. Since 2011, Baidu’s AI infrastructure has acquired and integrated new information into large-scale knowledge graphics. Today, this knowledge graph has more than 550 billion facts, covering all aspects of everyday life, as well as industry-specific topics, including manufacturing, pharmaceuticals, law, financial services, technology and media, and entertainment.

This graph of knowledge and massive data points together make up the building blocks of the newly released pre-trained Baidu PCL-BAIDU Wenxin language model (ERINIE version 3.0 Titan). The model outperforms other language models without graphs of knowledge in 60 natural language processing (NLP) tasks, including reading comprehension, text classification, and semantic similarity.

Learning in different modalities

Cross-modal learning is a new field of AI research that seeks to improve cognitive understanding of machines and better mimic adaptive human behavior. Examples of research efforts in this area include automatic text-to-image synthesis, in which the model is trained to generate images only from textual descriptions, as well as algorithms designed to understand visual content and express that understanding in words. The challenge in these tasks is for machines to build semantic connections between different types of data sets (eg images, text) and to understand the interdependencies between them.

The next step for AI is to merge AI technologies such as computer vision, speech recognition and natural language processing to create a multimodal system.

On this front, Baidu has released a version of its NLP models that link language and visual semantic comprehension. Examples of real-world applications for this type of model include digital avatars that can perceive their surroundings as human beings and deal with customer support for business, and algorithms that can “paint” works of art and compose poems based on their understanding of the generated works of art.

There are even more creative, impactful potential outcomes for this technology. The PaddlePaddle platform can build semantic links between vision and language, prompting a group of master’s students in China to create a dictionary to preserve endangered languages ​​in regions such as Yunnan and Guangxi, making it easier to translate them into Simplified Chinese.

Integration of AI into software and hardware and industry-specific applications

As artificial intelligence systems are used to solve increasingly complex and industry-specific problems, more emphasis is placed on optimizing software (deep learning framework) and hardware (AI chip) in general, rather than optimizing each individually, taking into account factors such as computing power, energy consumption and latency.

In addition, huge innovations are taking place in Baidu’s AI infrastructure platform, where third-party developers are using deep learning opportunities to create new applications tailored to specific applications. The PaddlePaddle platform has a series of APIs to support AI applications in newer technologies such as quantum computing, life sciences, fluid computational mechanics and molecular dynamics.

AI also has practical applications. For example, in Shouguang, a small town in Shandong Province, AI is used to streamline the fruit and vegetable industry. It only takes two people and one app to manage dozens of vegetable sheds.

And this is remarkable, says Wang: “Despite the increasing complexity of AI technology, the open source deep learning platform integrates CPU and applications as an operating system, reducing barriers to entry for companies and individuals who want to incorporate AI into their business.

Reduced entry barrier for developers and end users

In the field of technology, pre-training of large models such as PCL-BAIDU Wenxin (ERNIE version 3.0 Titan) has solved many common difficulties faced by traditional models. For example, these general-purpose models helped lay the groundwork for different types of downstream NLP tasks, such as text classification and answering questions, in one consolidated place, whereas in the past each type of task had to be solved separately. model.

PaddlePaddle also has a series of developer-friendly tools, such as model compression technologies to customize general-purpose models to suit more specific applications. The platform provides an officially maintained library of industrial-grade models with more than 400 models, ranging from large to small, which retain only part of the size of general-purpose models, but can achieve comparable performance while reducing model development and implementation costs.

Today, Baidu’s open source technology supports a community of more than four million AI developers, who together have created 476,000 models, contributing to the AI-driven transformation of 157,000 enterprises and institutions. The examples listed above are the result of innovations occurring in all layers of the Baidu AI infrastructure, which integrates technologies such as voice recognition, computer vision, AR / VR, graphics graphics and pre-training of large models that are one step closer to perceiving the world as human.

In its current state, AI has reached a level of maturity that allows it to perform amazing tasks. For example, the recent launch of Metaverse XiRang would not have been possible without PaddlePaddle’s platform for creating digital avatars for participants from around the world to connect from their devices. In addition, future breakthroughs in areas such as quantum computing could significantly improve the productivity of metauniverses. This shows how Baidu’s various proposals are interconnected and interdependent.

In a few years, AI will be close to the core of our human experience. This will be for our society what steam, electricity and the internet have been for previous generations. As AI becomes more sophisticated, developers like Hongzhi will work harder as artists and designers, given the creative freedom to study uses that were previously considered only theoretically possible. The sky is the limit.

This content was created by Baidu. Not written by the MIT Technology Review.

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