esg
22 articles about esg in AI news
ESGLens: A New RAG Framework for Automated ESG Report Analysis and Score
ESGLens combines RAG with prompt engineering to extract structured ESG data, answer questions, and predict scores. Evaluated on ~300 reports, it achieved a Pearson correlation of 0.48 against LSEG scores. The paper highlights promise but also significant limitations.
Avoko Launches 'Behavioral Lab' for AI Agent Testing & Development
Avoko AI announced 'Avoko,' a platform described as a behavioral lab for AI agents. It aims to provide structured environments for testing, evaluating, and improving agent performance and reliability.
FRAGATA: A Hybrid RAG System for Semantic Search Over 20 Years of HPC
A new paper details FRAGATA, a system enabling semantic search over two decades of technical support tickets at a supercomputing center. It uses hybrid retrieval-augmented generation (RAG) to find relevant past incidents despite typos, language, or wording differences, showing a qualitative improvement over the legacy search.
Bentley's 'Phygital' Future
Bentley Motors is pioneering a 'phygital' design approach, merging physical and digital processes. The automaker is deploying real-time 3D visualization and AI-assisted tools to enable faster, more collaborative, and data-informed design decisions for its luxury vehicles.
Ensembles at Any Cost? New Research Quantifies Accuracy-Energy Trade-offs
A comprehensive study of 93 experiments across four datasets reveals the severe energy inefficiency of ensemble methods in recommender systems. While accuracy improves slightly, energy consumption and CO2 emissions can increase by orders of magnitude, forcing a critical cost-benefit analysis for production systems.
Coresight Research Report: Technology and Resilience as Path to Stronger Retail Margins
Coresight Research has published a report titled 'Supply Chain Insights for Food, Drug and Mass Retail: Technology, Resilience and the Path to Stronger Margins.' The research focuses on how strategic tech adoption can fortify operations and profitability in key retail segments.
New Research: Fine-Tuned LLMs Outperform GPT-5 for Probabilistic Supply Chain Forecasting
Researchers introduced an end-to-end framework that fine-tunes large language models (LLMs) to produce calibrated probabilistic forecasts of supply chain disruptions. The model, trained on realized outcomes, significantly outperforms strong baselines like GPT-5 on accuracy, calibration, and precision. This suggests a pathway for creating domain-specific forecasting models that generate actionable, decision-ready signals.
From BM25 to Corrective RAG: A Benchmark Study Challenges the Dominance of Semantic Search for Tabular Data
A systematic benchmark of 10 RAG retrieval strategies on a financial QA dataset reveals that a two-stage hybrid + reranking pipeline performs best. Crucially, the classic BM25 algorithm outperformed modern dense retrieval models, challenging a core assumption in semantic search. The findings provide actionable, cost-aware guidance for building retrieval systems over heterogeneous documents.
When AI Becomes the Buyer: How Agentic Commerce is Reshaping Retail
The Wall Street Journal examines the emerging trend of 'Agentic Commerce,' where AI agents autonomously research, compare, and purchase products. This represents a fundamental shift in the retail landscape, moving beyond simple chatbots to systems that act as independent buyers, requiring brands to fundamentally rethink digital strategy, pricing, and customer engagement.
AWS Launches 'The Luggage Lab': A Generative AI Framework for Physical Product Innovation
Amazon Web Services has introduced 'The Luggage Lab,' a new reference architecture and framework using its generative AI services to accelerate the design and development of physical products. This is a direct, vendor-specific playbook for applying GenAI to tangible goods.
Google Unveils Universal Commerce Protocol (UCP) for Securing Agentic Commerce
Google has released the Universal Commerce Protocol (UCP), an open-source standard designed to secure transactions conducted by AI agents. This framework aims to establish trust and provenance in automated commerce, with direct implications for luxury goods authentication and supply chain transparency.
Smarter Shopping: Forecasting the Future of AI Agents in Retail
The Wall Street Journal reports on the emerging role of autonomous AI agents in retail, forecasting their potential to transform shopping by handling complex, multi-step tasks. This signals a shift from passive chatbots to active, goal-oriented assistants.
How Large Language Models 'Counter Poisoning': A Self-Purification Battle Involving RAG
New research explores how LLMs can defend against data poisoning attacks through self-purification mechanisms integrated with Retrieval-Augmented Generation (RAG). This addresses critical security vulnerabilities in enterprise AI systems.
CATCHES Launches Generative AI with Physics-Based Sizing Technology for Fashion E-Commerce
CATCHES has launched a generative AI platform for fashion e-commerce featuring physics-based sizing technology. The launch is in partnership with luxury brand AMIRI and is powered by NVIDIA's AI infrastructure. This directly targets a core pain point in online apparel retail: fit uncertainty and high return rates.
Algorithmic Trust and Compliance: A New Framework for Visibility in Generative AI Search
A new arXiv study introduces Generative Engine Optimization (GEO), a framework for optimizing content for AI search engines. It finds AI exhibits a strong bias towards authoritative, third-party sources, making compliance and trust signals critical for visibility in regulated sectors.
LLMGreenRec: A Multi-Agent LLM Framework for Sustainable Product Recommendations
Researchers propose LLMGreenRec, a multi-agent system using LLMs to infer user intent for sustainable products and reduce digital carbon footprint. It addresses the gap between green intentions and actions in e-commerce.
LLM-as-a-Judge: A Practical Framework for Evaluating AI-Extracted Invoice Data
A technical guide demonstrating how to use LLMs as evaluators to assess the accuracy of AI-extracted invoice data, replacing manual checks and brittle validation rules with scalable, structured assessment.
From Megafactories to Micro-Ateliers: How Embodied AI Will Redefine Luxury Manufacturing
Embodied AI reaching critical capability thresholds will trigger a phase transition in manufacturing geography. For luxury, this enables demand-proximal micro-manufacturing, hyper-personalization, and resilient, sustainable supply chains, fundamentally restructuring production logic.
From Tactical to Strategic: How AI Agents Will Transform Luxury Supply Chain Leadership
AI agents are shifting supply chain roles from tactical execution to strategic integration. By 2028, 15% of daily decisions will be autonomous, requiring leaders who focus on relationship-building and critical thinking over manual oversight.
The Green AI Revolution: How Smart Model Switching Could Slash LLM Energy Use by 67%
Researchers propose a context-aware model switching system that dynamically routes queries to appropriately-sized language models based on complexity, reducing energy consumption by up to 67.5% while maintaining 93.6% response quality. This breakthrough addresses growing sustainability concerns in AI deployment.
Trump's AI Energy Summit: Tech Giants Pledge to Self-Generate Power Amid Grid Concerns
Former President Donald Trump is convening Amazon, Google, Meta, Microsoft, xAI, Oracle, and OpenAI at the White House to sign a 'Rate Payer Protection Pledge,' committing them to generate or purchase their own electricity for new AI data centers, signaling a major shift in how tech's energy demands are addressed.
NVIDIA's Blackwell Ultra Shatters Efficiency Records: 50x Performance Per Watt Leap Redefines AI Economics
NVIDIA's new Blackwell Ultra GB300 NVL72 systems promise a staggering 50x improvement in performance per megawatt and 35x lower cost per token compared to previous Hopper architecture, addressing the critical energy bottleneck in AI scaling.