Modular soft robot arms (MSRAs) are composed of multiple independent modules connected in a sequence. Due to their modular structure and high degrees of freedom (DOFs), these modules can simultaneously bend at different angles in various directions, enabling complex deformation. This capability allows MSRAs to perform more intricate tasks than single module robots. However, the modular structure also induces challenges in accurate planning, modeling, and control. Nonlinearity, hysteresis, and gravity complicate the physical model, while the modular structure and increased DOFs further lead to accumulative errors along the sequence. To address these challenges, we propose a flexible task space planning and control strategy for MSRAs, named S2C2A (State to Configuration to Action). Our approach formulates an optimization problem, S2C (State to Configuration planning), which integrates various loss functions and a forward MSRA model to generate configuration trajectories based on target MSRA states. Given the model complexity, we leverage a biLSTM network as the forward model. Subsequently, a configuration controller C2A (Configuration to Action control) is implemented to follow the planned configuration trajectories, leveraging only inaccurate internal sensing feedback. Both a biLSTM network and a physical model are utilized for configuration control. We validated our strategy using a cable-driven MSRA, demonstrating its ability to perform diverse offline tasks such as position control, orientation control, and obstacle avoidance. Furthermore, our strategy endows MSRA with online interaction capability with targets and obstacles. Future work will focus on addressing MSRA challenges, such as developing more accurate physical models and reducing configuration estimation errors along the module sequence.

Microsoft has been quietly debating the future of its advanced AI lab in China, sources say. The lab was opened in 1998 and has become one of the most important artificial intelligence hubs in the world, leading to advancements in the company's speech, image and facial recognition software. Microsoft Research Lab Asia (MSRA) opened at a time of optimism about China as an emerging democracy but as tensions between the US and the communist state have intensified, internal pressure has mounted to shut or scale it down. That pressure has only intensified in recent months, after the Biden administration banned US investments in Chinese tech ventures that might aid the rival superpower's'military, intelligence, surveillance, or cyber-enabled capabilities.' But, the tech giant's founder Bill Gates continues to defend the lab and has pushed to keep it open, alongside Microsoft's research leaders and its current president.

Through decades of support, Microsoft was an instrumental force helping China become the AI powerhouse it is today. Now, as the very thought of a U.S. company partnering in tech projects in China draws scrutiny from lawmakers, national security hawks, and human rights advocates, Microsoft could be forced to grapple with tough decisions surrounding the thriving AI ecosystem it fostered there. Microsoft established its research lab in Beijing in 1998, when it was a pioneer paving the way for AI research and business collaborations between the U.S. and China. It was three years before China joined the World Trade Organization, a time when President Bill Clinton actively pushed for closer trade ties with the country, and when AI was mostly the stuff of sci-fi pipe dreams. Since then, Microsoft Research Asia, or MSRA, has been known as one of the most influential hubs of AI research in the world, advancing speech recognition, natural language and image processing, and other deep-learning work, spreading its discoveries far and wide. Elements of research conducted at MSR China have been used to build Microsoft's advertising, chatbots, Bing search, Windows, Xbox, Azure Cloud, and other products used everywhere.

Who benefits from the research breakthroughs made in the China-based research labs of American artificial intelligence (AI) companies? Just five years ago, that question hardly ever came up, and if it was asked, the answer often centered on the shared benefits of global research. The field of machine learning has made major strides, China's technology markets and its surveillance apparatus have boomed, and technological competition has moved to the center of the US-China relationship. What do all these changes mean for the overseas research labs of leading American technology companies? To answer that question, it's useful to zoom in on a specific research breakthrough to examine the ideas, institutions, and people involved in it. By tracing those factors over time, a better assessment can be made on where the benefits from this research flow to, and how government policies and corporate practices can best shape those flows.

Microsoft Research Asia (MSRA) has achieved eight top places in the recent machine translation challenge organized by the 2019 fourth Conference on Machine Translation (WMT19), out of the eleven tasks it undertook. Overall, there are nineteen machine translation categories in WMT this year. MSRA achieved first place in machine translation tasks for Chinese-English, English-Finnish, English-German, English-Lithuanian, French-German, German-English, German-French and Russian-English. Three other tasks were placed second in their respective categories, which included English-Kazakh, Finnish-English and Lithuanian-English. As one of the leading machine translation competition globally, WMT is a platform for leading researchers to demonstrate their solutions, as well as to understand the continuous evolvement of machine translation technology. Now in its 14th year, more than 50 teams globally from technology companies, leading academic institutions and universities participated in a bid to demonstrate their machine translation capabilities.

Jeff Ding, a researcher at the University of Oxford who studies China's AI development, shared some recent reflections on the most important things he's learned in the past year. They offer a great snapshot into the current state of the industry, so I've summarized them briefly below. The Chinese- and English-speaking AI communities have an asymmetrical understanding of each other. Most Chinese researchers can read English, and nearly all major research developments in the Western world are immediately translated into Chinese, but the reverse is not true. Therefore, the Chinese research community has a much deeper understanding than the English-speaking one of what's happening on both sides of the aisle.

Jeff Ding, a researcher at the University of Oxford who studies China's AI development, shared some recent reflections on the most important things he's learned in the past year. They offer a great snapshot into the current state of the industry, so I've summarized them briefly below. The Chinese- and English-speaking AI communities have an asymmetrical understanding of each other. Most Chinese researchers can read English, and nearly all major research developments in the Western world are immediately translated into Chinese, but the reverse is not true. Therefore, the Chinese research community has a much deeper understanding than the English-speaking one of what's happening on both sides of the aisle.

Hong Kong-based shipping company Orient Overseas Container Line Limited (OOCL) has partnered with Microsoft's research arm to improve network operations and achieve efficiencies within the shipping industry through applied Artificial Intelligence (AI) research. The partnership, between OOCL and Microsoft Research Asia (MSRA), will apply deep learning research to shipping network operations with a projected $10 million annual operational cost saving. The collaboration is also expected to nurture over 200 AI developers over the next 12 months. "With MSRA's efforts and expertise, we expect to save around 10 million in operation costs annually by applying the AI research and techniques for optimizing shipping network operations from our most recent 15-week engagement," said Steve Siu, Chief Information Officer of OOCL. "Moving forward, we will embark on an 18-month joint-partnership in research and development to apply deep learning and reinforcement learning in shipping network operations. Moreover, MSRA will assist us in training over 200 AI engineers by conducting machine learning and deep learning sessions at the Hong Kong Science Park over the next 12 months. We look forward to strengthening our partnership with MSRA to leverage AI research and innovations to drive digital transformation in the shipping industry and to exchange knowledge among our top developers so that we can better address customer needs with advanced technologies and predictive analytics."