Relevance modeling in e-commerce search remains challenged by semantic gaps in term-matching methods (e.g., BM25) and neural models' reliance on the scarcity of domain-specific hard samples. We propose ADORE, a self-sustaining framework that synergizes three innovations: (1) A Rule-aware Relevance Discrimination module, where a Chain-of-Thought LLM generates intent-aligned training data, refined via Kahneman-Tversky Optimization (KTO) to align with user behavior; (2) An Error-type-aware Data Synthesis module that auto-generates adversarial examples to harden robustness; and (3) A Key-attribute-enhanced Knowledge Distillation module that injects domain-specific attribute hierarchies into a deployable student model. ADORE automates annotation, adversarial generation, and distillation, overcoming data scarcity while enhancing reasoning. Large-scale experiments and online A/B testing verify the effectiveness of ADORE. The framework establishes a new paradigm for resource-efficient, cognitively aligned relevance modeling in industrial applications.

Ensuring safety in autonomous driving requires a seamless integration of perception and decision making under uncertain conditions. Although computer vision (CV) models such as YOLO achieve high accuracy in detecting traffic signs and obstacles, their performance degrades in drift scenarios caused by weather variations or unseen objects. This work presents a simulated autonomous driving system that combines a context aware CV model with adaptive control using the ADORE framework. The CARLA simulator was integrated with ADORE via the ROS bridge, allowing real-time communication between perception, decision, and control modules. A simulated test case was designed in both clear and drift weather conditions to demonstrate the robust detection performance of the perception model while ADORE successfully adapted vehicle behavior to speed limits and obstacles with low response latency. The findings highlight the potential of coupling deep learning-based perception with rule-based adaptive decision making to improve automotive safety critical system.

What I have always admired about Japanese role-playing games is their unashamed grandiosity. The likes of Final Fantasy, Persona and Shin Megami Tensei don't restrict themselves to the familiar trappings of good v evil, wizards-and-goblins, swords-and-magic; they absorb all of those things, and plenty else besides, from science fiction and mythology and comic books and psychology and classical art and whatever else interests their creators, and construct these absurdly ambitious worlds and narratives out of them. The themes are never small, the playtimes never short. Think of them as the operas of the video game world: a theatrical synthesis of different virtual arts, from storytelling and stagecraft to music and movement. And as something of an acquired taste.

Working together, they move the bins around nonstop, accessing specific items and delivering them to the people on the outside. On a busy day, these robots churn through 20,000 online orders, 80% of which are placed via smartphones. A growing number of retailers are turning to this kind of automation to out-compete their rivals. Robots keep costs down and make order fulfillment quicker and more accurate. Now, given a series of lockdowns that could go on for months or even years, this kind of small-scale automation could be key if retailers are to survive.

Increase the ROI of your Customer Care Service by implementing our AI powered customer care agent. With ADORE your team is up and running in no time, providing an enhanced customer experience with Natural Language Processing. Do you hate manual work too? Get in touch to find out more about ADORE! Your support cost is going through the roof because a significant amount of time is repeatedly spent on searching the right information and answering your valuable customers.

In this digital age, the smartest brands are the ones that make use of social media monitoring. The process of social media monitoring allows brands to keep track of their online reputation and image. However, with the size and complexity of data increasing day by day, brands need to understand not only how to make use of this data but also about how to cope with this growing data. We have previously seen the influence of artificial intelligence on social media monitoring. In this article, we look at how a sub-branch of artificial intelligence, i.e. machine learning is affecting social media monitoring.

Acquiring customers is a very high cost activity for businesses and for most of the companies it requires extensive cold-calling, trial and error, and exploration of multiple channels. Improved lead generation is the primary reason why businesses are investing in Artificial Intelligence (AI), according to a survey by the Aberdeen Group. Businesses that implement AI see 59% better close rates for sales, 58% increased revenue, 54% more traffic and engagement, and 52% higher conversion. Having a long list of potential clients is great, but going through the data can be a huge task. AI-powered analytics can help the enterprise identify those leads that are likely to have a high chance of being converted. It can be used to discover and recommend new potential customers by mining the connections between people, companies, products and the Internet, while integrating with your marketing automation software to find new leads.

Adore Me is tapping artificial intelligence to win over lingerie shoppers online. The four-year-old brand is part of a recent e-commerce boom in the bras and underwear space, which has seen the rise of modern, digital players set on eating into Victoria's Secret's market share. As Adore Me took on the likes of other online-born lingerie companies like True & Co., Negative Underwear and ThirdLove, it was using the "spray and pray" method of messaging customers through email marketing. "We had a one-size-fits-all strategy for reaching out to customers," said Josselin Petit-Hoang, Adore Me's marketing manager who has been with the company since 2014. "But as the company grew, and the volume of our customers grew, we wanted to narrow down, as well as reach people outside of email." Adore Me -- which has raised close to $12 million in venture capital -- did $80 million in sales in 2016 and is projected to hit $100 million in 2017, according to internal figures.