Information technology

  • Article
    | Open Access

    Social media platforms moderating misinformation have been accused of political bias. Here, the authors use neutral social bots to show that, while there is no strong evidence for such a bias, the content to which Twitter users are exposed depends strongly on the political leaning of early Twitter connections.

    • Wen Chen
    • , Diogo Pacheco
    •  & Filippo Menczer
  • Article
    | Open Access

    Storage technology based on DNA is emerging as an information dense and durable medium. Here the authors use machine learning-based encoding and hybridization probes to execute similarity searches in a DNA database.

    • Callista Bee
    • , Yuan-Jyue Chen
    •  & Luis Ceze
  • Article
    | Open Access

    Deep neural networks usually rapidly forget the previously learned tasks while training new ones. Laborieux et al. propose a method for training binarized neural networks inspired by neuronal metaplasticity that allows to avoid catastrophic forgetting and is relevant for neuromorphic applications.

    • Axel Laborieux
    • , Maxence Ernoult
    •  & Damien Querlioz
  • Article
    | Open Access

    Optical analog computing has so far been mostly limited to solving a single instance of a mathematical problem at a time. Here, the authors show that the linearity of the wave equation allows to solve several problems simultaneously, and demonstrate it using an MW transmissive cavity.

    • Miguel Camacho
    • , Brian Edwards
    •  & Nader Engheta
  • Article
    | Open Access

    Theoretical aspects of automated learning from data involving deep neural networks have open questions. Here Giambagli et al. show that training the neural networks in the spectral domain of the network coupling matrices can reduce the amount of learning parameters and improve the pre-training process.

    • Lorenzo Giambagli
    • , Lorenzo Buffoni
    •  & Duccio Fanelli
  • Article
    | Open Access

    Simple lower bounds on the rates of device-independent quantum information protocols can often overestimate the power of the eavesdropping party. Here, the authors use new entropic quantities defined as semidefinite programs to improve bounds in several regimes without expensive computational resources

    • Peter Brown
    • , Hamza Fawzi
    •  & Omar Fawzi
  • Article
    | Open Access

    Large volumes of true random numbers are needed for increasing requirements of secure data encryption. Here the authors use the stochastic nature of DNA synthesis to obtain millions of gigabytes of unbiased randomness.

    • Linda C. Meiser
    • , Julian Koch
    •  & Robert N. Grass
  • Article
    | Open Access

    Multiplayer games can be used as testbeds for the development of learning algorithms for artificial intelligence. Omidshafiei et al. show how to characterize and compare such games using a graph-based approach, generating new games that could potentially be interesting for training in a curriculum.

    • Shayegan Omidshafiei
    • , Karl Tuyls
    •  & Rémi Munos
  • Article
    | Open Access

    Designing efficient system for digital connectivity preserving information security remains a challenge. Here, the authors present hardware-intrinsic security solutions based on physical unclonable functions incorporating an inkjet-printed core circuit as an intrinsic source of entropy, integrated into a silicon-based CMOS system environment.

    • Alexander Scholz
    • , Lukas Zimmermann
    •  & Jasmin Aghassi-Hagmann
  • Article
    | Open Access

    Designing efficient analog dynamical systems for solving hard optimization problems remains a challenge. Here, the authors demonstrate a dynamical system of thirty oscillators with reconfigurable coupling to compute optimal/near-optimal solutions to the hard Maximum Independent Set problem with over 90% accuracy.

    • Antik Mallick
    • , Mohammad Khairul Bashar
    •  & Nikhil Shukla
  • Article
    | Open Access

    Extracting central information from ever-growing data generated in our lives calls for new data mining methods. Ferreira et al. show a simple model, called chronnets, that can capture frequent patterns, spatial changes, outliers, and spatiotemporal clusters.

    • Leonardo N. Ferreira
    • , Didier A. Vega-Oliveros
    •  & Elbert E. N. Macau
  • Article
    | Open Access

    Multiple access channels model communication from multiple independent senders to a common receiver. By drawing a connection to the study of classical and quantum correlations using nonlocal games, Leditzky et al. reveal remarkably complex behaviour of the entanglement-assisted and unassisted information transmission capabilities of a multiple access channel.

    • Felix Leditzky
    • , Mohammad A. Alhejji
    •  & Graeme Smith
  • Article
    | Open Access

    Understanding the underlying mechanisms behind the successes of deep networks remains a challenge. Here, the author demonstrates an implicit regularization in training deep networks, showing that the control of complexity in the training is hidden within the optimization technique of gradient descent.

    • Tomaso Poggio
    • , Qianli Liao
    •  & Andrzej Banburski
  • Article
    | Open Access

    Small non-polymeric molecules have tremendous structural diversity that can be used to represent information. Here the authors encode data in synthesized libraries of Ugi products.

    • Christopher E. Arcadia
    • , Eamonn Kennedy
    •  & Jacob K. Rosenstein
  • Article
    | Open Access

    DNA strand displacement reactions can be difficult to scale up for computational tasks. Here the authors develop DNA switching circuits that achieve high-speed computing with fewer molecules.

    • Fei Wang
    • , Hui Lv
    •  & Chunhai Fan
  • Article
    | Open Access

    People are able to mentally time travel to distant memories and reflect on the consequences of those past events. Here, the authors show how a mechanism that connects learning from delayed rewards with memory retrieval can enable AI agents to discover links between past events to help decide better courses of action in the future.

    • Chia-Chun Hung
    • , Timothy Lillicrap
    •  & Greg Wayne
  • Article
    | Open Access

    The extent to which brain structure and function are coupled remains a complex question. Here, the authors show that coupling strength between structural connectivity and functional activity can be quantified and reveals a cortical gradient spanning from lower-level sensory areas to high-level cognitive ones.

    • Maria Giulia Preti
    •  & Dimitri Van De Ville
  • Article
    | Open Access

    There is a lack of systematic approaches to identify and analyze the hierarchical structure of geo-industrial clusters at the global scale. Here the authors use LinkedIn's employment history data to construct a global labor flow network from which they find that the resulting geo-industrial clusters exhibit a stronger association between the influx of educated-workers and financial performance compared to existing aggregation units.

    • Jaehyuk Park
    • , Ian B. Wood
    •  & Yong-Yeol Ahn
  • Article
    | Open Access

    Recovering the properties of a network which has suffered adversarial intervention can find applications in uncovering targeted attacks on social networks. Here the authors propose a causal statistical inference framework for reconstructing a network which has suffered non-random, targeted attacks.

    • Yuankun Xue
    •  & Paul Bogdan
  • Article
    | Open Access

    DNA as a high density storage medium is receiving increasing attention, but long term physical storage is an unsolved problem. Here the authors show that up to 1 TB of data stored as dehydrated DNA spots on a glass cartridge can be retrieved in a spot of water using digital microfluidics with minimal data loss and contamination.

    • Sharon Newman
    • , Ashley P. Stephenson
    •  & Luis Ceze
  • Article
    | Open Access

    AI is used increasingly in medical diagnostics. Here, the authors present a deep learning model that masters medical knowledge, demonstrated by it having passed the written test of the 2017 National Medical Licensing Examination in China, and can provide help with clinical diagnosis based on electronic health care records.

    • Ji Wu
    • , Xien Liu
    •  & Ping Lv
  • Article
    | Open Access

    Designing molecular keys and combining advanced encryption standard cryptography with molecular steganography is a secure way for encoding messages. Here, the authors use the Ugi four-component reaction of perfluorinated acids to create a library of 500,000 molecular keys for encryption and decryption.

    • Andreas C. Boukis
    • , Kevin Reiter
    •  & Michael A. R. Meier
  • Article
    | Open Access

    Construction of a scalable quantum computer requires error-correcting codes to overcome the errors introduced by noise. Here, the authors develop a decoding algorithm for the gauge color code, and obtain its threshold values when physical errors and measurement faults are included.

    • Benjamin J. Brown
    • , Naomi H. Nickerson
    •  & Dan E. Browne
  • Article
    | Open Access

    Irreversible computation cannot be performed without a work cost, and energy dissipation imposes limitations on devices' performances. Here the authors show that the minimal work requirement of logical operations is given by the amount of discarded information, measured by entropy.

    • Philippe Faist
    • , Frédéric Dupuis
    •  & Renato Renner
  • Article |

    Routing packets on the growing and changing underlying structure of the Internet is challenging and currently based only on local connectivity. Here, a global Internet map is devised: with a greedy forwarding algorithm, it is robust with respect to network growth, and allows speeds close to the theoretical best.

    • Marián Boguñá
    • , Fragkiskos Papadopoulos
    •  & Dmitri Krioukov