Conversational recommender systems (CRSs) often utilize external knowledge graphs (KGs) to introduce rich semantic information and recommend relevant items through natural language dialogues. However, original KGs employed in existing CRSs are often incomplete and sparse, which limits the reasoning capability in recommendation. Moreover, only few of existing studies exploit the dialogue context to dynamically refine knowledge from KGs for better recommendation. To address the above issues, we propose the Variational Reasoning over Incomplete KGs Conversational Recommender (VRICR). Our key idea is to incorporate the large dialogue corpus naturally accompanied with CRSs to enhance the incomplete KGs; and perform dynamic knowledge reasoning conditioned on the dialogue context. Specifically, we denote the dialogue-specific subgraphs of KGs as latent variables with categorical priors for adaptive knowledge graphs refactor. We propose a variational Bayesian method to approximate posterior distributions over dialogue-specific subgraphs, which not only leverages the dialogue corpus for restructuring missing entity relations but also dynamically selects knowledge based on the dialogue context. Finally, we infuse the dialogue-specific subgraphs to decode the recommendation and responses. We conduct experiments on two benchmark CRSs datasets. Experimental results confirm the effectiveness of our proposed method.

When you think of artificial intelligence, you might imagine a world where robots and computers run the show. But looking at how AI is used in today's world, from voice-activated assistants to virtual assistants answering phones, you will recognize how this technology is improving our lives. Here is a deeper dive into artificial intelligence and the companies leading the way right now. Artificial intelligence is the concept of teaching a computer to think and act independently. That includes rational speech, complex problem-solving, speech recognition, decision making, and initiating actions.

This holiday season, feast on the bounty of food-themed stories NVIDIA Blog readers gobbled up in 2022. Startups in the retail industry -- and particularly in quick-service restaurants -- are using NVIDIA AI and robotics technology to make it easier to order food in drive-thrus, find beverages on store shelves and have meals delivered. They're accelerated by NVIDIA Inception, a program that offers go-to-market support, expertise and technology for cutting-edge startups. For those who prefer eye candy, artists also recreated a ramen restaurant using the NVIDIA Omniverse platform for creating and operating metaverse applications. Toronto startup HuEx is developing a conversational AI assistant to handle order requests at the drive-thru speaker box.

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Etsy is the global marketplace for unique and creative goods. We build, power, and evolve the tools and technologies that connect millions of entrepreneurs with millions of buyers around the world. As an Etsy Inc. employee – whether a team member of Etsy, Reverb, Depop, or Elo7 – you'll tackle unique, meaningful, and large-scale problems alongside passionate coworkers, all the while making a rewarding impact and Keeping Commerce Human. We are looking for a Sr. Software Engineer to join the Recommendations team in order to better understand Etsy's unique inventory and enable personalized recommendations and ranked content for product teams across Etsy. Our aim is to present recommendations of the best of Etsy's inventory.

For greater efficiency and innovation, IT leaders are exploring AI applications that streamline operations, generate text and images, and even write code. With more streamlined operations and greater agility you can embrace emerging trends in AI more readily. Corporate operations switch to a backup datacenter after a local power outage darkens the primary systems. As such scenarios unfold, virtual assistants text alerts and summaries about these events and resolutions to their human counterparts. Until recently, IT leaders have dreamt of such autonomous computing remediation for decades.

Artificial Intelligence (AI) technology is gradually taking the world in its arms. The capabilities and applications of this intelligent technology are incredible and can completely revolutionize the world. Nowadays, enterprises of all sizes are adopting AI technology. AI can optimize work efficiency, automate repetitive tasks, and also assist companies in providing virtual customer support services. AI-powered mobile applications are also one of the best innovations of technology that help businesses reach targeted audiences globally and generate sustainable revenues.

This article was published as a part of the Data Science Blogathon. In addition to socializing with pals, humans are addicted to their smartphones. We primarily communicate via social media, such as WhatsApp, Facebook, Telegram, Instagram, and many others. It's always interesting to see how people start using technology on social media platforms. Especially because it is a very simple pattern to understand.

In simple terms the AI or the Artificial Intelligence means the replicating the Human Intelligence. In deeply the artificial intelligence is a large concept that spread through a huge domain. Actually I assume there is no domain when we come to the AI, because it spread in each and every domain that exists. So, the artificial intelligence is the theory and development of computer systems with the ability to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision making and translation between languages. Also there are another two concepts that goes with AI very closely.

Datasets for training recommender systems are often subject to distribution shift induced by users' and recommenders' selection biases. In this paper, we study the impact of selection bias on datasets with different quantization. We then leverage two differently quantized datasets from different source distributions to mitigate distribution shift by applying the inverse probability scoring method from causal inference.