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Volume 1 Issue 12, December 2019

Portable haptics with foldable robotics

Robotic devices can be made more compact and lightweight by using origami techniques. In this issue, Stefano Mintchev et al. present an origami device that can be used as a portable haptic interface that can sense and initiate motion in three dimensions. Named Foldaway, the device folds flat and can be used as an intuitive haptic 3D joystick in different virtual-reality or augmented-reality applications.

See Mintchev et al.

Image: Renaud Defrancesco and Cyrille Verdon. Cover Design: Karen Moore.


  • The reach of artificial intelligence technologies across all parts of society is steadily growing, but so is the awareness of how they can negatively impact human rights. As 2019 draws to a close, the trajectory of technological progress defined by big technology companies is meeting resistance.



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Comment & Opinion

  • Artificial intelligence and machine learning are increasingly seen as key technologies for building more decentralized and resilient energy grids. However, researchers must consider the ethical and social implications of these developments.

    • Valentin Robu
    • David Flynn
    • Maizura Mokhtar
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News & Views

  • Photonic computing devices are a compelling alternative to conventional computing setups for machine learning applications, as they are nonlinear, fast and easy to parallelize. Recent work demonstrates the potential of these optical systems to process and classify human motion from video.

    • Kathy Lüdge
    • André Röhm
    News & Views
  • Loss-of-function mutations in metal-binding proteins are heavily implicated with numerous diseases, and identifying such ‘cracks’ will be valuable to biologists and medical doctors in the study and treatment of disease. A deep learning approach has been developed to tackle this challenging task.

    • Yuan Liu
    • Chu Wang
    News & Views
  • Origami engineering has long held the promise of complex and futuristic machines. A new foldable haptics system shows that this paradigm can be functional as well.

    • Samuel Felton
    News & Views
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  • Current national cybersecurity and defence strategies of several governments mention explicitly the use of AI. However, it will be important to develop standards and certification procedures, which involves continuous monitoring and assessment of threats. The focus should be on the reliability of AI-based systems, rather than on eliciting users’ trust in AI.

    • Mariarosaria Taddeo
    • Tom McCutcheon
    • Luciano Floridi
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  • Drug combinations are often an effective means of managing complex diseases, but understanding the synergies of drug combinations requires extensive resources. The authors developed an efficient machine learning model that requires only a limited set of pairwise dose–response measurements for the accurate prediction of synergistic and antagonistic drug combinations.

    • Aleksandr Ianevski
    • Anil K. Giri
    • Tero Aittokallio
  • Identifying abnormalities in medical images across different viewing angles and body parts is a time-consuming task. Deep learning techniques hold great promise for supporting radiologists and improving patient triage decisions. A new study tests the viability of such approaches in resource-limited settings, exploring the effect of pretraining, dataset size and choice of deep learning model in the task of abnormality detection in lower-limb radiographs.

    • Maya Varma
    • Mandy Lu
    • Bhavik N. Patel
  • Number processing is linked to bodily systems, especially finger movements. The authors apply convolutional neural network models in the context of cognitive developmental robotics. They show that proprioceptive information in the child-like robot iCub improves accuracy and recognition of spoken digits.

    • Alessandro Di Nuovo
    • James L. McClelland
  • To better extract meaning from natural language, some less informative words can be removed before a model is trained, which is usually done by using manually curated lists of stopwords. A new information theoretic approach can identify uninformative words automatically and more accurately.

    • Martin Gerlach
    • Hanyu Shi
    • Luís A. Nunes Amaral
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Challenge Accepted

  • A new open challenge tests whether algorithmic models can explain human brain activity in cognitive tasks and encourages interaction between researchers studying natural and artificial intelligence.

    • Radoslaw Martin Cichy
    • Gemma Roig
    • Aude Oliva
    Challenge Accepted
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