Complex dialogue mappings (CDM), including one-to-many and many-to-one mappings, tend to make dialogue models generate incoherent or dull responses, and modeling these mappings remains a huge challenge for neural dialogue systems. To alleviate these problems, methods like introducing external information, reconstructing the optimization function, and manipulating data samples are proposed, while they primarily focus on avoiding training with CDM, inevitably weakening the model's ability of understanding CDM in human conversations and limiting further improvements in model performance. This paper proposes a Sentence Semantic \textbf{Seg}mentation guided \textbf{C}onditional \textbf{V}ariational \textbf{A}uto-\textbf{E}ncoder (SegCVAE) method which can model and take advantages of the CDM data. Specifically, to tackle the incoherent problem caused by one-to-many, SegCVAE uses response-related prominent semantics to constrained the latent variable. To mitigate the non-diverse problem brought by many-to-one, SegCVAE segments multiple prominent semantics to enrich the latent variables. Three novel components, Internal Separation, External Guidance, and Semantic Norms, are proposed to achieve SegCVAE. On dialogue generation tasks, both the automatic and human evaluation results show that SegCVAE achieves new state-of-the-art performance.

The following is a conversation with an AI assistant. The assistant is helpful, creative, clever, and very friendly. Human: Hello, who are you? AI: I am an AI created by OpenAI. How can I help you today?

Welcome to our November 2022 monthly digest, where you can catch up with any AIhub stories you may have missed, get the low-down on recent events, and much more. This month, we hear from researchers who've developed an AI system for live music accompaniment and improvisation. Amongst other things, we also find out more about counterfactual explanations for reinforcement learning, planning robust frictional multi-object grasps, and social bias in knowledge graphs. Olga Vechtomova and Gaurav Sahu envisioned and developed a system, LyricJam Sonic, that uses AI to create a real-time generative stream of music based on an artist's own catalogue of studio recordings. The purpose is to inspire the artist with potentially unexpected combinations of sounds.

To address the widespread problem of uncivil behavior, many online discussion platforms employ human moderators to take action against objectionable content, such as removing it or placing sanctions on its authors. This reactive paradigm of taking action against already-posted antisocial content is currently the most common form of moderation, and has accordingly underpinned many recent efforts at introducing automation into the moderation process. Comparatively less work has been done to understand other moderation paradigms -- such as proactively discouraging the emergence of antisocial behavior rather than reacting to it -- and the role algorithmic support can play in these paradigms. In this work, we investigate such a proactive framework for moderation in a case study of a collaborative setting: Wikipedia Talk Pages. We employ a mixed methods approach, combining qualitative and design components for a holistic analysis. Through interviews with moderators, we find that despite a lack of technical and social support, moderators already engage in a number of proactive moderation behaviors, such as preemptively intervening in conversations to keep them on track. Further, we explore how automation could assist with this existing proactive moderation workflow by building a prototype tool, presenting it to moderators, and examining how the assistance it provides might fit into their workflow. The resulting feedback uncovers both strengths and drawbacks of the prototype tool and suggests concrete steps towards further developing such assisting technology so it can most effectively support moderators in their existing proactive moderation workflow.

In the first episode of the Talking Language AI series, I spoke with Maarten Grootendorst, author and maintainer of the BERTopic open source package (over 3,000 stars on Github). BERTopic is used to explore collections of text to spot trends and identify the topics in these texts. This is an NLP task called Topic Modeling. It's also embedded in the bottom of this overview. Feel free to post questions or comments in this thread in the Cohere Discord.

"…the very enterprise of communication among human beings is transforming in some way. We've been at this for a while. The first telegraph lines were strung around 1819. The telephone became a common object of the upper class around 1900.

If you are reading this article then chances are that some part of your life is affected by technology. In 2019, there were a number of technological advancements that changed our lives and brought us closer than ever. From smartphones to computers, these innovations have had a big impact on us all but they also had a major effect on humans as well. Artificial Intelligence is one such innovation, which has made people think about how we can make machines able to learn as we do with animals. So, if AI gets smarter, it means that humans are getting more intelligent too; making them a bit less human and more machinery.

I recently caught up with Ian Hogarth and Nathan Benaich, who each year produce The State of AI Report, a must-read snapshot of how commercial applications of A.I. are evolving. Benaich is the founder of Air Street Capital, a solo venture capital fund that is one of the savviest early-stage investors in A.I.-based startups I know. Hogarth is the former co-founder of concert discovery app Songkick and has since go on to become a prominent angel investor as well one of the founders behind the founder-lead European venture capital platform Plural. There's always a lot to digest in their report. But one of the key takeaways from this year's State of AI is that concerns established tech giants and their affiliated A.I. research labs would monopolize the development of A.I. have been proven, if not exactly wrong, then at least premature. While it is true that Alphabet (which has both Google Brain and Deepmind in its stable), Meta, Microsoft, and OpenAI (which is closely partnered now with Microsoft) are building large "foundational models" for natural language processing and image and video generation, they are hardly the only players in the game.

Jaron Lanier, the eminent American computer scientist, composer and artist, is no stranger to skepticism around social media, but his current interpretations of its effects are becoming darker and his warnings more trenchant. Lanier, a dreadlocked free-thinker credited with coining the term "virtual reality", has long sounded dire sirens about the dangers of a world over-reliant on the internet and at the increasing mercy of tech lords, their social media platforms and those who work for them. Nothing about the last few weeks – of chaos on Twitter and the ever-increasing spread of conspiracy theory and disinformation – has changed that. The current state of the tech industry is ripe with danger and poses an existential threat, he believes. "People survive by passing information between themselves," Lanier, 61, told the Guardian in an interview.

This is an opinion editorial by Sydney Bright, a professional science writer on the topic of health benefits from mindfulness-based practices. Where is technology taking us? Will robots surpass our intelligence and replace us altogether? Will we combine with machines in some symbiotic merge that creates a new super being? Or are machines merely tools that will allow our more fundamental nature to thrive? In this article, I will argue that technology is how human beings will be able to return to a more natural life that is devoid of the harsh realities that existed 10,000 years ago. Those who are aware of my work on the science of meditation ask me why there is also a discussion of economics and Bitcoin on my blog. First, I feel that any curious mind should be well-rounded: Multiple fields of study are worth pursuing, as they all compile a more complete understanding of reality. At first, I felt that they were simply separate interests of mine. However, now I have come to realize that they are partly connected and suggest an exciting forecast for humanity's future.