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Volume 2 Issue 8, August 2020

Micromanipulator for telerobotic surgery

The cover image shows a miniature robotic manipulator that can be used in minimally invasive microsurgery. Its ‘remote centre of motion’ action, where a mechanism can rotate around a remote fixed point, is made possible by an origami-inspired design. The manipulator attains a positional precision of 26.4 μm and the authors demonstrate its potential utility as a precise tool for teleoperated microsurgery by performing a micro-cannulation procedure under a microscope on an imitation retinal vein. In addition, the device allows gravity compensation and back drivability for safety.

See Suzuki et al.

Image: Hiroyuki Suzuki (Sony Corporation) and Robert J. Wood (Harvard University) Cover design: Karen Moore


  • OpenAI released a beta version of its language model, GPT-3. As artificial writing permeates our lives, the challenge is how to think clearly about what it is and what impact it could have on society.



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Comment & Opinion

  • As robot swarms move from the laboratory to real-world applications, a routine checklist of questions could help ensure their safe operation.

    • Edmund R. Hunt
    • Sabine Hauert
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  • The part that artificial intelligence plays in climate change has come under scrutiny, including from tech workers themselves who joined the global climate strike last year. Much can be done by developing tools to quantify the carbon cost of machine learning models and by switching to a sustainable artificial intelligence infrastructure.

    • Payal Dhar
    News Feature
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News & Views

  • Bayesian networks can capture causal relations, but learning such a network from data is NP-hard. Recent work has made it possible to approximate this problem as a continuous optimization task that can be solved efficiently with well-established numerical techniques.

    • Yunan Luo
    • Jian Peng
    • Jianzhu Ma
    News & Views
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  • This review covers the history of procedural content generation (PCG) approaches for video games, and how these approaches are now used to generate training data and environments for machine learning models. The authors then discuss how PCG may be crucial for training agents which generalise well.

    • Sebastian Risi
    • Julian Togelius
    Review Article
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  • Robot-assisted microsurgery promises high stability and accuracy for instance in eye- or neurosurgery applications. A new miniature robotics device, based on an origami-inspired design, can make complex 3D motions and reaches a precision of around 26 micrometres.

    • Hiroyuki Suzuki
    • Robert J. Wood
  • Gene expression is regulated by a variety of mechanisms, which have been difficult to study in a unified way. The authors propose a flexible framework that can integrate different types of data for studying their joint effects on gene expression. The framework uses a general network representation for data integration, metapaths for inputting prior knowledge of gene regulatory mechanisms, and embedding techniques for capturing complex structures in the data.

    • Qin Cao
    • Zhenghao Zhang
    • Kevin Y. Yip
  • The role of DNA methylation on N6-adenine (6mA) in eukaryotes is a challenging research problem. Tan et al. develop a deep-learning-based algorithm to predict 6mA sites from sequences at single-nucleotide resolution, and apply the method to three representative model organisms. The method is further developed to visualize regulatory patterns around 6mA sites.

    • Fei Tan
    • Tian Tian
    • Hakon Hakonarson
  • Deep learning approaches can show excellent performance but still have limited practical use if they learn to predict based on confounding factors in a dataset, for instance text labels in the corner of images. By using an explanatory interactive learning approach, with a human expert in the loop during training, it becomes possible to avoid predictions based on confounding factors.

    • Patrick Schramowski
    • Wolfgang Stammer
    • Kristian Kersting
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