Scientists at the University of Sharjah have developed an advanced digital twin technology designed to replicate renewable energy stored in tanks, substantially improving their efficiency and reliability. The team presents the details of their invention, called a "data-driven digital twin," in a paper published in the journal Energy.

كشف باحثون في جامعة الشارقة عن تقنية توأم رقمي تهدف إلى تحسين كفاءة وموثوقية أنظمة تخزين الطاقة المتجددة. تم تفصيل هذه الابتكار في مجلة Energy، حيث يسعى إلى تقليل خسائر الطاقة بشكل كبير في التخزين، وهو أمر حاسم لتحسين استخدام الطاقة المتجددة وتعزيز الحلول المستدامة.

Investigadores de la Universidad de Sharjah han presentado una tecnología de gemelo digital que mejora la eficiencia y fiabilidad de los sistemas de almacenamiento de energía renovable. Esta innovación, detallada en la revista Energy, busca reducir significativamente las pérdidas de energía en el almacenamiento, lo cual es crucial para optimizar el uso de energías renovables y avanzar en soluciones energéticas sostenibles.

Des chercheurs de l'Université de Sharjah ont présenté une technologie de jumeau numérique qui améliore l'efficacité et la fiabilité des systèmes de stockage d'énergie renouvelable. Cette innovation, détaillée dans le journal Energy, vise à réduire considérablement les pertes d'énergie dans le stockage, ce qui est crucial pour optimiser l'utilisation des énergies renouvelables et faire progresser les solutions énergétiques durables.

Researchers at the University of Sharjah have introduced a digital twin technology that enhances the efficiency and reliability of renewable energy storage systems. This innovation, detailed in the journal Energy, aims to significantly reduce power losses in energy storage, which is crucial for optimizing renewable energy use and advancing sustainable energy solutions.

Scientists unveil digital twin tech to slash power losses in energy storage systems

<A HREF="https://fortune.com/2025/11/19/exclusive-doppel-raises-70-million-series-c-at-more-than-600-million-valuation-to-fight-ai-powered-social-engineering-attacks/"><IMG VSPACE="4" HSPACE="4" BORDER="0" ALIGN="RIGHT" SRC="http://www.techmeme.com/251119/i39.jpg"></A>
<A HREF="http://www.techmeme.com/251119/p39#a251119p39" TITLE="Techmeme permalink"><IMG WIDTH=11 HEIGHT=12 SRC="http://www.techmeme.com/img/pml.png" STYLE="border:none;padding:0;margin:0;"></A> Allie Garfinkle / <A HREF="http://www.fortune.com/">Fortune</A>: 
<A HREF="https://fortune.com/2025/11/19/exclusive-doppel-raises-70-million-series-c-at-more-than-600-million-valuation-to-fight-ai-powered-social-engineering-attacks/">Doppel, which makes an AI social engineering detection service, raised a $70M Series C led by Bessemer at a $600M+ valuation, up from $205M in May</A>&nbsp; &mdash;&nbsp; Senior Finance Reporter And Author Of Term Sheet&nbsp; &mdash;&nbsp; I tried to fool my brother, sort of.&nbsp; &mdash;&nbsp; Next to him and his Pekingese on the couch &hellip;

دوبل، وهي شركة متخصصة في خدمات الكشف عن الهندسة الاجتماعية باستخدام الذكاء الاصطناعي، نجحت في جمع 70 مليون دولار في جولة تمويل من السلسلة C بقيادة بيسمر. وقد زادت هذه الجولة من تقييم الشركة إلى أكثر من 600 مليون دولار، ارتفاعًا من 205 مليون دولار في مايو.

Doppel, una empresa que se especializa en servicios de detección de ingeniería social mediante IA, ha recaudado con éxito 70 millones de dólares en una ronda de financiación Serie C liderada por Bessemer. Esta ronda ha elevado la valoración de la empresa a más de 600 millones de dólares, un aumento significativo desde los 205 millones en mayo.

Doppel, une entreprise spécialisée dans les services de détection d'ingénierie sociale par IA, a levé avec succès 70 millions de dollars lors d'un tour de financement de série C dirigé par Bessemer. Ce tour de financement a porté la valorisation de l'entreprise à plus de 600 millions de dollars, contre 205 millions en mai.

Doppel, a company specializing in AI social engineering detection services, has successfully raised $70 million in a Series C funding round led by Bessemer. This funding round has increased the company's valuation to over $600 million, a significant rise from $205 million in May.

Doppel, which makes an AI social engineering detection service, raised a $70M Series C led by Bessemer at a $600M+ valuation, up from $205M in May (Allie Garfinkle/Fortune)

The service is customized for teachers' needs and includes added security and privacy, a collaborative workspace, and more.

OpenAI expands free educational offerings - here's what ChatGPT for Teachers can do

GPT-5.1-Codex-Max is ready to take on your next massive coding job. Here's what's new.

OpenAI's Codex Max solves one of my biggest AI coding annoyances - and adds dramatically faster performance

The agent offers one-click buying for all your holiday needs and will be free for all US-based users.

Perplexity's AI shopping tool is free for all now, just in time for Black Friday - how to use it

<a href="https://fetch.ai/">Fetch AI</a>, a startup founded and led by former DeepMind founding investor, Humayun Sheikh, <a href="https://www.businesswire.com/news/home/20251119088395/en/Fetch-Combines-Personalized-AI-with-Multi-Agent-Collaboration-to-Handle-Complex-Consumer-Tasks-Launches-Claim-Your-Agent-to-Fight-Brand-Knock-Offs">today announced the release</a> of three interconnected products designed to provide the trust, coordination, and interoperability needed for large-scale AI agent ecosystems. The launch includes <a href="https://asi1.ai/">ASI:One</a>, a personal-AI orchestration platform; <a href="https://business.fetch.ai/">Fetch Business</a>, a verification and discovery portal for brand agents; and <a href="https://agentverse.ai/?sort=relevancy&amp;page=1&amp;recommended=true">Agentverse</a>, an open directory hosting more than two million agents. Together, the system positions Fetch as an infrastructure provider for what it calls the “Agentic Web”—a layer where consumer AIs and brand AIs collaborate to complete tasks instead of merely suggesting them.The company says the tools address a central limitation in current consumer AI: models can provide recommendations but cannot reliably execute multi-step actions that require coordination across businesses. Fetch’s approach centers on enabling agents from different organizations to interoperate securely, using verified identities and shared context to complete end-to-end workflows.“We’re creating the same foundation for agents that Google created for websites,” said Humayun Sheikh, Founder and CEO of Fetch AI, and an early investor in DeepMind, in a press release provided to VentureBeat. “Instead of just finding information, your personal AI coordinates with verified brand agents to get things done.”<h2>Background: Fetch’s Founding and DeepMind Connection </h2>Fetch AI was founded in 2017 by Humayun Sheikh, an entrepreneur whose early investment in DeepMind helped support the company’s commercial development before its acquisition by Google. “I was one of the first five people at DeepMind and its first investor. My check was the first one in,” Sheikh said, reflecting on the period when advanced machine learning research was still largely inaccessible outside major technology companies.His early experience helped shape Fetch’s direction. “Even in 2013, it was clear to me that agentic systems were going to be the ones that worked. That’s where I focused—on the agentic web,” Sheikh noted. Fetch built on this thesis by developing infrastructure for autonomous software agents, focusing on verifiable identity, secure data exchange, and multi-agent coordination. Over the past several years, the company has expanded to a 70-person team across Cambridge and Menlo Park, raised approximately $60 million, and accumulated more than one million users interacting with its model—data that informed the design of the newly launched products.Sheikh added that his decision to bootstrap the company initially came directly from the proceeds of the DeepMind exit, noting in the interview that while the sale to Google was “a good exit,” he believed the team could have held out for a higher valuation. The early self-funding period allowed Fetch to begin work in 2015—well before transformer architectures went mainstream—on the hypothesis that agentic infrastructure would become foundational to applied AI.<h2>ASI:One — A Platform for Multi-Agent Orchestration</h2>At the core of the launch is ASI:One, a language model interface designed specifically for coordinating multiple agents rather than addressing isolated queries. Fetch describes it as an “intelligence layer” that handles context sharing, task routing, and preference modeling.The system stores user-level signals such as favored airlines, dietary constraints, budget ranges, loyalty program identifiers, and calendar availability. When a user requests a complex task—such as planning a trip with flights, hotels, and restaurant reservations—ASI:One retrieves those preferences and delegates work to the appropriate verified agents. The agents then return actionable outputs, including inventory and booking options, rather than generic recommendations.In practice, ASI:One functions as a workflow generator across organizational boundaries. By contrast with conventional LLM applications, which often rely on APIs or RAG techniques to surface information, ASI:One is built to coordinate autonomous agents that can complete transactions. Fetch notes that personalization improves over time as the model accumulates structured preference data.Sheikh emphasized the distinction between orchestrated execution and traditional AI output. “This isn’t searching for options separately and hoping they work together,” he said. “It’s orchestration.” He added that Fetch’s architecture is intentionally modular: “Our architecture is a mix of agentic and expert models. One large model isn’t enough—you need specialists. That’s why we built ASI1, tuned specifically for agentic systems.”The interview also revealed new details about ASI:One’s personalization systems: the platform uses multiple user-owned knowledge graphs to store preferences, travel history, social connections, and contextual constraints. These knowledge graphs are siloed per user and not co-mingled with any Fetch-operated data. Sheikh described this as a “deterministic backbone” that gives the personal AI a stable memory layer beyond the probabilistic output of a single large model.ASI:One launches in Beta today, with a broader release planned for early 2026. Fetch also offers ASI:One Mobile, released earlier this year, giving users access to the same agent-orchestration capabilities on iOS and Android. The mobile app connects directly to Agentverse and the user’s knowledge graphs, enabling on-the-go task execution and real-time interaction with registered agents.<h2>Fetch Business — Verified Identity and Brand Control</h2>To enable reliable coordination between consumers and companies, Fetch is introducing a verification and discovery portal called Fetch Business. The platform allows organizations to verify their identity and claim an official Brand Agent handle—for example, @Hilton or @Nike—regardless of which tools they use to build the underlying agent.Fetch positions the product as an analogue to ICANN domain registration and SSL certificate systems for websites. Verified status is intended to protect consumers from interacting with counterfeit or untrusted agents, a problem the company describes as a major barrier to widespread agent adoption.The system includes low-code tools for small businesses to create agents in a few steps and connect real-time APIs such as inventory, booking systems, or CRM platforms. “With Fetch, you can create an agent in one minute. It gets a handle, like a Twitter username, and you can personalize it completely—even give it your social media permissions to post on your behalf,” Sheikh said. Once a brand claims its namespace, its agent becomes discoverable to consumer AIs and other agents inside Agentverse.The company has pre-reserved thousands of brand namespaces in anticipation of demand. Verification status persists across any platform that integrates with Agentverse, creating a portable identity layer for business agents.The interview highlighted that Fetch Business inherits web-trust primitives directly: domain owners verify their identity by inserting a short code snippet into their existing website backend, allowing the system to pass a cryptographic challenge and grant the agent an authenticity badge similar to a “blue check” for agent identities. Sheikh framed this as “reusing the trust layer the web already spent decades building.”Companies can begin claiming agents now at <a href="https://business.fetch.ai/">business.fetch.ai</a>.<h2>Agentverse — An Open Directory of More Than Two Million Agents</h2>The final component of the release is <a href="https://agentverse.ai/">Agentverse</a>, an open directory and cloud platform that hosts agents and enables cross-ecosystem discoverability. Fetch states that millions of agents have already registered, spanning travel, retail, entertainment, food service, and enterprise categories.Agentverse provides metadata, capability descriptions, and routing logic that ASI:One uses to identify appropriate agents for specific tasks. It also supports secure communication and data exchange between agents. The company notes that the directory is platform-agnostic: agents built with any framework can join and interoperate.According to Sheikh, the lack of a discovery layer is one reason most AI agents see little or no usage. “Ninety percent of AI agents never get used because there’s no discovery layer,” he said. He framed the role of Agentverse in more technical terms: “Right now, if you build an agent, there’s no universal way for others to discover it. That’s what AgentVerse solves—it’s like DNS for agents.” He also described the system as an essential component of the emerging agent economy: “Fetch is building the Google of agents. Just like websites needed search, agents need discovery, trust, and interaction—Fetch provides all of that.”The interview further underscored that Agentverse is cloud-agnostic by design. Sheikh contrasted this with competing agent ecosystems tied to specific cloud providers, arguing that a universal registry is only viable if independent of proprietary cloud environments. He said the open architecture enables an LLM to query any agent “within one minute of deployment,” turning agent publication into a near-instantaneous process similar to registering a domain.Agentverse also integrates payment pathways, enabling agents to execute purchases using partners such as Visa, Skyfire, and supported stablecoins. Consumers can configure spending limits or require explicit approval for transactions.<h2>Industry Context and Implications</h2>Fetch’s launch comes at a time when consumer AI platforms are exploring the shift from static chat interfaces toward autonomous agents capable of completing actions. However, most agent systems remain limited by siloed architectures, limited interoperability, and weak verification standards.Fetch positions its infrastructure as a response to these limitations by providing a cross-platform coordination layer, identity system, and directory service. The company argues that an agent ecosystem requires consistent verification mechanisms to ensure that consumers interact with authentic brand representatives rather than imitations. By establishing namespace control and portable trust indicators, Fetch Business aims to fill a gap similar to early web domain verification.At the same time, ASI:One attempts to centralize user preference data in a way that enables more efficient personalization and multi-agent coordination. This approach differs from generalist LLM applications, which often lack persistent preference architectures or direct access to brand-controlled agents.The interview also made clear that micropayments and digital transaction infrastructure are central to Fetch’s long-term vision. Sheikh referenced integrations with protocols such as Coinbase’s 402 and AP2, positioning these capabilities as essential for autonomous agents to complete end-to-end tasks that include financial execution.<h2>Takeaway</h2>Fetch’s combined release of ASI:One, Fetch Business, and Agentverse introduces an interconnected stack designed to support large-scale deployment and usage of AI agents. The company frames the system as foundational infrastructure for an agentic ecosystem, where consumer AIs can coordinate with verified brand agents to complete tasks reliably and securely. The additions to its identity, discovery, and orchestration layers reflect Fetch’s long-standing thesis—rooted partly in lessons from DeepMind’s early development—that intelligence becomes meaningful only when paired with the capacity to act.

أطلقت شركة Fetch AI، وهي شركة ناشئة يقودها هميون شيخ، ثلاثة منتجات مترابطة تهدف إلى تعزيز نظام وكلاء الذكاء الاصطناعي. تشمل العروض الجديدة ASI:One، وهي منصة تنسيق ذكاء اصطناعي شخصي، وFetch Business، وهو بوابة للتحقق والاكتشاف لوكلاء العلامات التجارية، وAgentverse، وهو دليل مفتوح يضم أكثر من مليوني وكيل. تسعى هذه المبادرة إلى إنشاء بنية تحتية قوية لما تصفه Fetch بـ 'الويب الوكالي.'

Fetch AI, una startup dirigida por Humayun Sheikh, ha lanzado tres productos interconectados destinados a mejorar el ecosistema de agentes de IA. Las nuevas ofertas incluyen ASI:One, una plataforma de orquestación de IA personal, Fetch Business, un portal de verificación y descubrimiento para agentes de marca, y Agentverse, un directorio abierto con más de dos millones de agentes. Esta iniciativa busca establecer una infraestructura sólida para lo que Fetch describe como la 'Web Agente.'

Fetch AI, une startup dirigée par Humayun Sheikh, a lancé trois produits interconnectés visant à améliorer l'écosystème des agents IA. Les nouvelles offres comprennent ASI:One, une plateforme d'orchestration d'IA personnelle, Fetch Business, un portail de vérification et de découverte pour les agents de marque, et Agentverse, un annuaire ouvert avec plus de deux millions d'agents. Cette initiative vise à établir une infrastructure robuste pour ce que Fetch décrit comme le 'Web Agentique.'

Fetch AI, a startup led by Humayun Sheikh, has launched three interconnected products aimed at enhancing the ecosystem of AI agents. The new offerings include ASI:One, a personal-AI orchestration platform, Fetch Business, a verification and discovery portal for brand agents, and Agentverse, an open directory with over two million agents. This initiative seeks to establish a robust infrastructure for what Fetch describes as the 'Agentic Web.'

The Google Search of AI agents? Fetch launches ASI:One and Business tier for new era of non-human web

If aesthetics and efficiency top your list of needs, there are several Linux distributions that are right up your alley. Both Ubuntu Budgie and Pop!_OS should top that list.

Ubuntu Budgie vs. Pop!_OS: I've used both Linux distros - here's how to choose

arXiv:2511.10668v1 Announce Type: new 
Abstract: AI systems improve by drawing on more compute, data, energy, and better training methods. This paper asks a precise, testable version of the "runaway growth" question: under what measurable conditions could capability escalate without bound in finite time, and under what conditions can that be ruled out? We develop an analytic framework for recursive self-improvement that links capability growth to resource build-out and deployment policies. Physical and information-theoretic limits from power, bandwidth, and memory define a service envelope that caps instantaneous improvement. An endogenous growth model couples capital to compute, data, and energy and defines a critical boundary separating superlinear from subcritical regimes. We derive decision rules that map observable series (facility power, IO bandwidth, training throughput, benchmark losses, and spending) into yes/no certificates for runaway versus nonsingular behavior. The framework yields falsifiable tests based on how fast improvement accelerates relative to its current level, and it provides safety controls that are directly implementable in practice, such as power caps, throughput throttling, and evaluation gates. Analytical case studies cover capped-power, saturating-data, and investment-amplified settings, illustrating when the envelope binds and when it does not. The approach is simulation-free and grounded in measurements engineers already collect. Limitations include dependence on the chosen capability metric and on regularity diagnostics; future work will address stochastic dynamics, multi-agent competition, and abrupt architectural shifts. Overall, the results replace speculation with testable conditions and deployable controls for certifying or precluding an AI singularity.

تناقش الورقة المعنونة 'إطار رياضي للانفجار الذكي: الشروط والحدود والتحكم في التحسين المتكرر' الشروط التي يمكن أن تشهد فيها أنظمة الذكاء الاصطناعي نمواً غير منضبط. تقدم الورقة إطاراً يربط بين نمو القدرات وسياسات نشر الموارد، مع تحديد حدود تعتمد على الطاقة وعرض النطاق الترددي والذاكرة. تقترح الدراسة قواعد قرار لتحديد ما إذا كان يمكن أن تتصاعد تحسينات الذكاء الاصطناعي بشكل غير قابل للتحكم أو تبقى ضمن الحدود، مما يسهم في فهم سلامة الذكاء الاصطناعي والتحكم فيه.

El artículo titulado 'Un marco matemático para la singularidad de la IA: condiciones, límites y control de la mejora recursiva' explora las condiciones bajo las cuales los sistemas de IA pueden experimentar un crecimiento descontrolado. Presenta un marco que vincula el crecimiento de capacidades a las políticas de despliegue de recursos, definiendo límites basados en potencia, ancho de banda y memoria. El estudio propone reglas de decisión para determinar si la mejora de la IA puede escalar incontrolablemente o permanecer dentro de límites, contribuyendo a la comprensión de la seguridad y el c…

L'article intitulé 'Un cadre mathématique pour la singularité de l'IA : conditions, limites et contrôle de l'amélioration récursive' examine les conditions sous lesquelles les systèmes d'IA peuvent connaître une croissance incontrôlée. Il présente un cadre reliant la croissance des capacités aux politiques de déploiement des ressources, définissant des limites basées sur la puissance, la bande passante et la mémoire. L'étude propose des règles de décision pour déterminer si l'amélioration de l'IA peut s'intensifier de manière incontrôlable ou rester dans des limites, contribuant ainsi à la com…

The paper titled 'A Mathematical Framework for AI Singularity: Conditions, Bounds, and Control of Recursive Improvement' explores the conditions under which AI systems can experience runaway growth. It presents a framework linking capability growth to resource deployment policies, defining limits based on power, bandwidth, and memory. The study proposes decision rules to determine whether AI improvement can escalate uncontrollably or remains within bounds, contributing to the understanding of AI safety and control.

A Mathematical Framework for AI Singularity: Conditions, Bounds, and Control of Recursive Improvement

Computer-aided design (CAD) is the go-to method for designing most of today's physical products. Engineers use CAD to turn 2D sketches into 3D models that they can then test and refine before sending a final version to a production line. But the software is notoriously complicated to learn, with thousands of commands to choose from. To be truly proficient in the software takes a huge amount of time and practice.

تم تطوير وكيل ذكاء اصطناعي جديد يمكنه إنشاء كائنات ثلاثية الأبعاد من رسومات ثنائية الأبعاد باستخدام برنامج التصميم بمساعدة الكمبيوتر (CAD). يعد CAD أساسيًا للمهندسين في تصميم المنتجات المادية، ولكنه غالبًا ما يكون معقدًا ويتطلب وقتًا طويلاً لإتقانه. قد تبسط هذه التطورات عملية التصميم وتحسن الإنتاجية في مجالات الهندسة المختلفة.

Se ha desarrollado un nuevo agente de IA que puede crear objetos 3D a partir de bocetos 2D utilizando software de diseño asistido por computadora (CAD). El CAD es esencial para que los ingenieros diseñen productos físicos, pero a menudo es complejo y requiere mucho tiempo para dominarlo. Este avance podría simplificar el proceso de diseño y mejorar la productividad en varios campos de la ingeniería.

Un nouvel agent d'IA a été développé pour créer des objets 3D à partir de croquis 2D en utilisant un logiciel de conception assistée par ordinateur (CAO). La CAO est essentielle pour les ingénieurs dans la conception de produits physiques, mais elle est souvent complexe et nécessite beaucoup de temps pour être maîtrisée. Cette avancée pourrait simplifier le processus de conception et améliorer la productivité dans divers domaines de l'ingénierie.

A new AI agent has been developed that can create 3D objects from 2D sketches using computer-aided design (CAD) software. CAD is essential for engineers to design physical products, but it is often complex and time-consuming to master. This advancement could simplify the design process and enhance productivity in various engineering fields.

AI agent learns to create 3D objects from sketches using CAD software

The global investment frenzy around AI has seen companies valued at trillions of dollars and eye-watering projections of how it will boost economic productivity.

لقد أدت جنون الاستثمار العالمي حول الذكاء الاصطناعي (AI) إلى تقييم الشركات بمليارات الدولارات، مع توقعات متفائلة حول إمكانيته في تعزيز الإنتاجية الاقتصادية. ومع ذلك، تزداد المخاوف بشأن استدامة هذا الازدهار مع ارتفاع تقلبات السوق التي تثير تساؤلات حول مستقبل الاستثمارات في الذكاء الاصطناعي.

La locura de inversión global en inteligencia artificial (IA) ha llevado a que las empresas sean valoradas en billones de dólares, con proyecciones optimistas sobre su potencial para aumentar la productividad económica. Sin embargo, hay crecientes preocupaciones sobre la sostenibilidad de este auge, ya que las fluctuaciones del mercado plantean preguntas sobre el futuro de las inversiones en IA.

La frénésie d'investissement mondial autour de l'intelligence artificielle (IA) a conduit à des valorisations d'entreprises atteignant des milliers de milliards de dollars, avec des projections optimistes sur son potentiel à améliorer la productivité économique. Cependant, des inquiétudes croissantes se font sentir quant à la durabilité de cet essor alors que les fluctuations du marché soulèvent des questions sur l'avenir des investissements dans l'IA.

The global investment frenzy surrounding artificial intelligence (AI) has led to companies being valued at trillions of dollars, with optimistic projections about its potential to enhance economic productivity. However, there are growing concerns about the sustainability of this boom as market fluctuations raise questions about the future of AI investments.

Is the AI bubble about to burst? What to watch for as the markets wobble

Imagine a world in which a humanoid robot cares for you when you need help and support with daily activities.

يتناول المقال مفهوم 'روبوتات الرعاية'، وهي روبوتات شبيهة بالبشر مصممة لمساعدة الأفراد في الأنشطة اليومية. يثير المقال تساؤلات حول الآثار المترتبة على دمج هذه التكنولوجيا في الرعاية الشخصية والمخاوف المحتملة المتعلقة باستخدامها.

El artículo discute el concepto de 'carebots', robots humanoides diseñados para ayudar a las personas con actividades diarias. Plantea preguntas sobre las implicaciones de integrar esta tecnología en el cuidado personal y las preocupaciones potenciales en torno a su uso.

L'article aborde le concept des 'carebots', des robots humanoïdes conçus pour aider les individus dans leurs activités quotidiennes. Il soulève des questions sur les implications de l'intégration de cette technologie dans les soins personnels et les préoccupations potentielles liées à leur utilisation.

The article discusses the concept of 'carebots,' humanoid robots designed to assist individuals with daily activities. It raises questions about the implications of integrating such technology into personal care and the potential concerns surrounding their use.

Scientists unveil digital twin tech to slash power losses in energy storage systems

Was this article worth reading? Share it