The New Scientist Book Club read Silvia Park's near-future sci-fi novel Luminous in May, and had lots of good things to say (along with a few complaints) The New Scientist Book Club read Silvia Park's Luminous in May The New Scientist Book Club had quite a change of science-fictional pace in May, moving from the wilds of space in our April read, Kim Stanley Robinson's, to a much closer-to-home future in Silvia Park's . Like another of our reads this year, Sierra Greer's, this imagines a world where robots are integrated into society - and explores how we might deal with this on many different levels: emotionally, spiritually, practically, sexually. Set in a reunified Korea, it's a compelling blend of three storylines: a police procedural, in which detective Jun is out to discover what might have become of a robot girl who has gone missing; a ragtag bunch of kids on an adventure, in which Ruijie and her schoolmates find an abandoned robot boy in a scrapyard; and a tale of a dysfunctional family. Jun and his younger sister Morgan grew up with a third sibling, a robot who disappeared when they were young, fracturing their family. Author Silvia Park: 'No one is your enemy, not even death' Silvia Park, author of the May read for the New Scientist Book Club, 'Luminous' on emotional artificial intelligence, our inevitable love for robots and coping with grief.

Luminous by Silvia Park and Ode to the Half-Broken by Suzanne Palmer are both thoughtful and well-written science fiction novels, featuring robots in richly realised worlds. But there the similarities end, says Emily H. Wilson Do we relate better to stories about robots with faces and bodies? Robots and whether they will one day deserve to be treated like people - or destroy humanity, or both - have interested writers for well over a century now. In the real world, the robot threat appears to involve the uses of artificial intelligence in misinformation and more direct forms of warfare such as drone attacks. In the world of literature, however, many writers focus on individual robots.

Memorization in large language models (LLMs) is a growing concern. LLMs have been shown to easily reproduce parts of their training data, including copyrighted work. This is an important problem to solve, as it may violate existing copyright laws as well as the European AI Act. In this work, we propose a systematic analysis to quantify the extent of potential copyright infringements in LLMs using European law as an example. Unlike previous work, we evaluate instruction-finetuned models in a realistic end-user scenario. Our analysis builds on a proposed threshold of 160 characters, which we borrow from the German Copyright Service Provider Act and a fuzzy text matching algorithm to identify potentially copyright-infringing textual reproductions. The specificity of countermeasures against copyright infringement is analyzed by comparing model behavior on copyrighted and public domain data. We investigate what behaviors models show instead of producing protected text (such as refusal or hallucination) and provide a first legal assessment of these behaviors. We find that there are huge differences in copyright compliance, specificity, and appropriate refusal among popular LLMs. Alpaca, GPT 4, GPT 3.5, and Luminous perform best in our comparison, with OpenGPT-X, Alpaca, and Luminous producing a particularly low absolute number of potential copyright violations. Code will be published soon.

Foundation models are subject to an ongoing heated debate, leaving open the question of progress towards AGI and dividing the community into two camps: the ones who see the arguably impressive results as evidence to the scaling hypothesis, and the others who are worried about the lack of interpretability and reasoning capabilities. By investigating to which extent causal representations might be captured by these large scale language models, we make a humble efforts towards resolving the ongoing philosophical conflicts.

Microsoft co-founder Bill Gates, Uber co-founder Travis Kalanick's 10100 fund and current Uber CEO Dara Khosrowshahi have invested in Luminous, a small start-up building an artificial intelligence chip. The investment shows key figures in the technology industry believe there is still an opportunity for a new standard to emerge when it comes to hardware for AI, which can be incorporated into a variety of software applications. In all, the company raised $9 million in this seed round. Several start-ups have been working on next-generation hardware in recent years as AI has become trendy. Intel bought one, called Nervana, in 2016.