If you love AI, you'll love Ken Liu's new cyberpunk thriller In Ken Liu's All That We See or Seem, a once-famous hacker must find a missing dream-weaver. The latest novel by Ken Liu, All That We See or Seem, is the near-future story of the mysterious disappearance of a professional dream-weaver called Elli. It is being marketed as a cyberpunk thriller . Full disclosure: I don't generally seek out thrillers or cyberpunk books, so I may not be the target audience for this. But I was keen to read it because Liu has not one but two claims to fame: as well as being the author of a celebrated fantasy series called The Dandelion Dynasty, he is also the translator of the sensationally good Remembrance of Earth's Past trilogy by Cixin Liu .

Natural language semantics has recently sought to combine the complementary strengths of formal and distributional approaches to meaning. More specifically, proposals have been put forward to augment formal semantic machinery with distributional meaning representations, thereby introducing the notion of semantic similarity into formal semantics, or to define distributional systems that aim to incorporate formal notions such as entailment and compositionality. However, given the fundamentally different 'representational currency' underlying formal and distributional approaches - models of the world versus linguistic co-occurrence - their unification has proven extremely difficult. Here, we define a Distributional Formal Semantics that integrates distributionality into a formal semantic system on the level of formal models. This approach offers probabilistic, distributed meaning representations that are also inherently compositional, and that naturally capture fundamental semantic notions such as quantification and entailment. Furthermore, we show how the probabilistic nature of these representations allows for probabilistic inference, and how the information-theoretic notion of "information" (measured in terms of Entropy and Surprisal) naturally follows from it. Finally, we illustrate how meaning representations can be derived incrementally from linguistic input using a recurrent neural network model, and how the resultant incremental semantic construction procedure intuitively captures key semantic phenomena, including negation, presupposition, and anaphoricity.

A robot companion could soon help prevent the elderly from feeling lonely. Elli.Q uses artificial intelligence to slowly learn what its owner likes, and will help those less confident with technology to use social media, video chats and play games online. The robot, which its inventors claim is one of most advanced social companion robots in the world, has now been launched during an exhibition at at The Design Museum in London. Elli.Q uses artificial intelligence to slowly learn what her owner likes, and will help those less confident with technology to use social media, video chats and play games online Using'body language' that conveys emotion, speech interface, sounds, lights and images to express herself, Elli.Q is designed to be easily understood. Using AI, it learns the preferences, behaviour and personality of her owner.