VERSES Demonstrates Smart Building Energy Optimization
VERSES AI (OTCQB:VRSSF) has showcased its smart building energy optimization technology at the invite-only Turing Grand Challenge at AI UK 2025. The exhibition, titled 'EcoNet: a Multi-Agent Active Inference System for Urban Energy Optimisation,' demonstrates how multiple AI agents can collaborate to optimize building energy management.
The system goes beyond traditional rule-based energy control by considering variables such as hyper-local weather, multiple energy sources (grid, solar, battery), carbon emissions, and room occupancy. According to the US Department of Energy, buildings account for 40% of global energy consumption, with approximately one-third wasted, resulting in $150 billion in annual losses.
The project, developed in collaboration with University College London (UCL), aims to address environmental and sustainability objectives by managing energy use effectively through autonomous multi-agent coordination. The technology is applicable across various scales, from studio apartments to skyscrapers and industrial buildings.
VERSES AI (OTCQB:VRSSF) ha presentato la sua tecnologia di ottimizzazione energetica per edifici intelligenti all'invito esclusivo Turing Grand Challenge presso AI UK 2025. L'esposizione, intitolata 'EcoNet: un sistema di inferenza attiva multi-agente per l'ottimizzazione energetica urbana,' dimostra come più agenti AI possano collaborare per ottimizzare la gestione energetica degli edifici.
Il sistema va oltre il controllo energetico tradizionale basato su regole, considerando variabili come il meteo iper-locale, diverse fonti energetiche (rete, solare, batteria), emissioni di carbonio e occupazione delle stanze. Secondo il Dipartimento dell'Energia degli Stati Uniti, gli edifici rappresentano il 40% del consumo energetico globale, con circa un terzo sprecato, risultando in 150 miliardi di dollari di perdite annuali.
Il progetto, sviluppato in collaborazione con l'University College London (UCL), mira a affrontare obiettivi ambientali e di sostenibilità gestendo efficacemente l'uso dell'energia attraverso il coordinamento autonomo di più agenti. La tecnologia è applicabile su diverse scale, da appartamenti studio a grattacieli e edifici industriali.
VERSES AI (OTCQB:VRSSF) ha mostrado su tecnología de optimización energética para edificios inteligentes en el exclusivo Turing Grand Challenge en AI UK 2025. La exposición, titulada 'EcoNet: un sistema de inferencia activa multi-agente para la optimización energética urbana,' demuestra cómo múltiples agentes de IA pueden colaborar para optimizar la gestión energética de los edificios.
El sistema va más allá del control energético tradicional basado en reglas, considerando variables como el clima hiperlocal, múltiples fuentes de energía (red, solar, batería), emisiones de carbono y ocupación de las habitaciones. Según el Departamento de Energía de EE. UU., los edificios representan el 40% del consumo energético global, con aproximadamente un tercio desperdiciado, resultando en 150 mil millones de dólares en pérdidas anuales.
El proyecto, desarrollado en colaboración con el University College London (UCL), tiene como objetivo abordar los objetivos ambientales y de sostenibilidad gestionando el uso de energía de manera efectiva a través de la coordinación autónoma de múltiples agentes. La tecnología es aplicable en diversas escalas, desde apartamentos estudio hasta rascacielos y edificios industriales.
VERSES AI (OTCQB:VRSSF)는 AI UK 2025에서 초청 전용 Turing Grand Challenge에서 스마트 빌딩 에너지 최적화 기술을 선보였습니다. 'EcoNet: 도시 에너지 최적화를 위한 다중 에이전트 능동 추론 시스템'이라는 제목의 전시회는 여러 AI 에이전트가 협력하여 빌딩 에너지 관리를 최적화할 수 있는 방법을 보여줍니다.
이 시스템은 하이퍼 로컬 날씨, 다양한 에너지원(전력망, 태양광, 배터리), 탄소 배출 및 방 점유와 같은 변수를 고려하여 전통적인 규칙 기반 에너지 제어를 넘어섭니다. 미국 에너지부에 따르면, 건물은 전 세계 에너지 소비의 40%를 차지하며, 약 3분의 1이 낭비되어 연간 1500억 달러의 손실을 초래합니다.
이 프로젝트는 런던 대학교(UCL)와 협력하여 개발되었으며, 자율 다중 에이전트 조정을 통해 에너지 사용을 효과적으로 관리하여 환경 및 지속 가능성 목표를 달성하는 것을 목표로 합니다. 이 기술은 스튜디오 아파트에서 마천루 및 산업 건물에 이르기까지 다양한 규모에 적용 가능합니다.
VERSES AI (OTCQB:VRSSF) a présenté sa technologie d'optimisation énergétique pour bâtiments intelligents lors du Turing Grand Challenge, sur invitation uniquement, à AI UK 2025. L'exposition, intitulée 'EcoNet : un système d'inférence active multi-agents pour l'optimisation énergétique urbaine,' démontre comment plusieurs agents d'IA peuvent collaborer pour optimiser la gestion énergétique des bâtiments.
Le système va au-delà du contrôle énergétique traditionnel basé sur des règles, en prenant en compte des variables telles que la météo hyper-locale, plusieurs sources d'énergie (réseau, solaire, batterie), les émissions de carbone et l'occupation des pièces. Selon le Département de l'Énergie des États-Unis, les bâtiments représentent 40 % de la consommation énergétique mondiale, avec environ un tiers gaspillé, entraînant 150 milliards de dollars de pertes annuelles.
Le projet, développé en collaboration avec l'University College London (UCL), vise à atteindre des objectifs environnementaux et de durabilité en gérant efficacement l'utilisation de l'énergie grâce à la coordination autonome de plusieurs agents. La technologie est applicable à différentes échelles, des studios aux gratte-ciels et bâtiments industriels.
VERSES AI (OTCQB:VRSSF) hat seine Technologie zur Optimierung des Energieverbrauchs in intelligenten Gebäuden auf der exklusiven Turing Grand Challenge bei AI UK 2025 präsentiert. Die Ausstellung mit dem Titel 'EcoNet: ein Multi-Agenten aktives Inferenzsystem zur städtischen Energieoptimierung' zeigt, wie mehrere KI-Agenten zusammenarbeiten können, um das Energiemanagement von Gebäuden zu optimieren.
Das System geht über die traditionelle regelbasierte Energiesteuerung hinaus, indem es Variablen wie hyperlokales Wetter, verschiedene Energiequellen (Netz, Solar, Batterie), Kohlenstoffemissionen und Raumbelegung berücksichtigt. Laut dem US-Energieministerium entfallen 40% des globalen Energieverbrauchs auf Gebäude, wobei etwa ein Drittel verschwendet wird, was zu 150 Milliarden Dollar jährlichen Verlusten führt.
Das Projekt, das in Zusammenarbeit mit dem University College London (UCL) entwickelt wurde, zielt darauf ab, Umwelt- und Nachhaltigkeitsziele zu erreichen, indem der Energieverbrauch effektiv durch autonome Multi-Agenten-Koordination verwaltet wird. Die Technologie ist in verschiedenen Maßstäben anwendbar, von Studio-Apartments bis hin zu Wolkenkratzern und Industriegebäuden.
- Technology addresses $150 billion annual energy waste market opportunity
- Partnership with prestigious University College London (UCL)
- Scalable solution applicable from residential to industrial buildings
- Advanced AI capability demonstrated at exclusive Turing Grand Challenge
- No immediate revenue or commercial implementation timeline provided
- Results of the technology demonstration not yet disclosed
Exhibition Showcases Multi-Agent Smart Grid Automation and Efficiency Management
VANCOUVER, British Columbia, March 18, 2025 (GLOBE NEWSWIRE) -- VERSES AI Inc. (CBOE:VERS) (OTCQB:VRSSF) ("VERSES'' or the "Company”) a cognitive computing company specializing in next-generation intelligent software systems, announces the completion and exhibition of its work on sustainable building management, or smart homes, for the invite-only Turing Grand Challenge at AI UK 20251 on March 17th and 18th.
“We believe the challenge with today’s rule-based energy control systems, such as smart homes, is that they are reactive and don’t take into account other variables like hyper-local weather, multiple energy sources (grid, solar, battery), carbon emissions or room occupancy, and therefore they really aren't ‘smart’,” said VERSES CEO, Gabriel René. “In this exhibition, we show how multiple agents working together can better predict which actions to take, given various trade-offs to achieve a desired goal. This might include deciding to switch a source of power from solar to electrical or preemptively adjust heating and cooling temperature based on weather conditions, occupancy, cost or efficiency goals.”
According to the US Department of Energy, buildings are responsible for
The VERSES exhibit, entitled EcoNet: a Multi-Agent Active Inference System for Urban Energy Optimisation, is a joint effort between VERSES researchers and University College London (UCL), that addresses a key aspect of the environment and sustainability objectives of Turing Grand Challenge, which seeks to develop AI systems that can reduce the impacts of climate change by managing energy use effectively.
“We believe this demonstration of autonomous multi-agent coordination in a complex dynamic system like energy management is an ideal showcase for Genius,” said CTO Hari Thiruvengada. “While this specific use case is applicable from studio apartments all the way up to skyscrapers and to large industrial buildings, the more general problem that Genius is designed to solve is generating reliable predictions in the face of complex, uncertain and changing conditions that can be applied across enterprises universally.”
The Company expects to share further details regarding the results of this test in an upcoming blog at Verses.ai.
About VERSES
VERSES is a cognitive computing company building next-generation intelligent software systems modeled after the wisdom and genius of Nature. Designed around first principles found in science, physics and biology, our flagship product, Genius™, is a suite of tools for machine learning practitioners to model complex dynamic systems and generate autonomous intelligent agents that continuously reason, plan, and learn. Imagine a Smarter World that elevates human potential through technology inspired by Nature. Learn more at verses.ai, LinkedIn, and X.
On behalf of the Company
Gabriel René, Founder & CEO, VERSES AI Inc.
Press Inquiries: press@verses.ai
Investor Relations Inquiries
U.S., Matthew Selinger, Partner, Integrous Communications, mselinger@integcom.us 415-572-8152
Canada, Leo Karabelas, President, Focus Communications, info@fcir.ca 416-543-3120
About UCL
Founded in 1826 in the heart of London, UCL is London's leading multidisciplinary university, with more than 16,000 staff and 50,000 students from over 150 different countries.
Media contact
Matt Midgley
Tel: +44 (0)20 3108 6995
Email: m.midgley [at] ucl.ac.uk
______________________
1 https://verses.atlassian.net/wiki/spaces/RDLAB/pages/1068400658/UK+Turing+Institute+-+Grand+Challenge+-+Demo+UK+2025
2 https://www.energy.gov/articles/doe-announces-46-million-boost-energy-efficiency-and-slash-emissions-residential-and
FAQ
What is the main purpose of VERSES AI's (VRSSF) EcoNet system demonstrated at AI UK 2025?
How much energy waste could VRSSF's smart building technology potentially address?
What distinguishes VERSES AI's (VRSSF) system from traditional smart home technology?
What types of buildings can implement VERSES AI's (VRSSF) energy management system?
