AI Driven Disruptions And Innovations
Power AI Innovation Physics Informed
Power AI Innovation Physics Informed refers to the integration of artificial intelligence with principles of physics to enhance decision-making and operational efficiency within the Energy and Utilities sector. This innovative approach leverages data-driven insights to optimize energy management, predictive maintenance, and resource allocation. As stakeholders face increasing pressure to adapt to sustainability goals and evolving regulatory frameworks, the relevance of this concept becomes paramount in aligning technological advancements with strategic priorities. In the context of the Energy and Utilities ecosystem, the significance of Power AI Innovation Physics Informed lies in its ability to redefine competitive dynamics and foster innovation. AI-driven practices are transforming how organizations interact with stakeholders, optimize processes, and make informed decisions. While the adoption of such technologies leads to enhanced efficiency and strategic foresight, challenges such as integration complexity and changing expectations must be navigated carefully. Ultimately, the landscape presents substantial growth opportunities for organizations willing to embrace this paradigm shift, despite the inherent obstacles they may encounter.
{"page_num":6,"introduction":{"title":"Power AI Innovation Physics Informed","content":"Power AI Innovation Physics Informed refers to the integration of artificial intelligence with principles of physics to enhance decision-making and operational efficiency within the Energy and Utilities sector. This innovative approach leverages data-driven insights to optimize energy management, predictive maintenance, and resource allocation. As stakeholders face increasing pressure to adapt to sustainability goals and evolving regulatory frameworks, the relevance of this concept becomes paramount in aligning technological advancements with strategic priorities.\n\nIn the context of the Energy and Utilities ecosystem <\/a>, the significance of Power AI <\/a> Innovation Physics Informed lies in its ability to redefine competitive dynamics and foster innovation. AI-driven practices are transforming how organizations interact with stakeholders, optimize processes, and make informed decisions. While the adoption of such technologies leads to enhanced efficiency and strategic foresight, challenges such as integration complexity and changing expectations must be navigated carefully. Ultimately, the landscape presents substantial growth opportunities for organizations willing to embrace this paradigm shift, despite the inherent obstacles they may encounter.","search_term":"Power AI Innovation Energy Utilities"},"description":{"title":"How Power AI is Revolutionizing Energy and Utilities?","content":"The Energy and Utilities sector is experiencing a transformative shift due to the integration of Power AI <\/a> Innovation, focusing on physics-informed models to enhance operational efficiency and predictive maintenance. Key growth drivers include the rising need for renewable energy optimization, real-time data analytics, and AI-driven decision-making processes that are reshaping market dynamics."},"action_to_take":{"title":"Accelerate AI-Driven Transformation in Energy and Utilities","content":"Energy and Utilities companies should strategically invest in partnerships focused on AI capabilities, particularly in Power AI <\/a> Innovation Physics Informed technologies, to enhance operational efficiencies and predictive analytics. The expected outcomes include significant cost savings, improved reliability, and a stronger competitive edge in an evolving market landscape driven by data and innovation.","primary_action":"Download AI Disruption Report 2025","secondary_action":"Explore Innovation Playbooks"},"implementation_framework":null,"primary_functions":{"question":"What's my primary function in the company?","functions":[{"title":"Engineering","content":"I design and implement Power AI Innovation Physics Informed solutions tailored for the Energy and Utilities sector. I ensure technical feasibility and select appropriate AI models, driving innovation from concept to execution while addressing integration challenges to enhance operational efficiency."},{"title":"Data Science","content":"I analyze vast datasets to extract actionable insights for Power AI Innovation Physics Informed applications. I develop predictive models and leverage AI algorithms to optimize energy consumption, enhancing operational decision-making. My work directly contributes to reducing costs and improving service reliability in the energy sector."},{"title":"Operations","content":"I oversee the implementation and management of Power AI Innovation Physics Informed systems in daily operations. I optimize processes based on AI-driven insights, ensuring smooth integration into existing workflows. My efforts are focused on enhancing efficiency and maximizing productivity across our energy operations."},{"title":"Research","content":"I conduct research on emerging AI technologies and their applications within Power AI Innovation Physics Informed frameworks. I evaluate trends, assess new methodologies, and collaborate with cross-functional teams to innovate solutions that propel our energy initiatives forward, aligning with strategic business objectives."},{"title":"Marketing","content":"I develop strategies to communicate the benefits of Power AI Innovation Physics Informed solutions to our stakeholders. I utilize market research and AI analytics to tailor messaging, ensuring we effectively reach our audience and highlight our commitment to innovation and efficiency in the energy sector."}]},"best_practices":null,"case_studies":[{"company":"Vistra","subtitle":"Implemented AI-driven heat rate optimization across power plants using existing data and equipment for efficiency improvements.","benefits":"Achieved one-percent average efficiency improvement and $23 million savings.","url":"https:\/\/www.mckinsey.com\/~\/media\/mckinsey\/business%20functions\/mckinsey%20digital\/how%20we%20help%20clients\/inside%20an%20ai%20power%20play\/an-ai-power-play-fueling-the-next-wave-of-innovation-in-the-energy-sector-may-2022.pdf","reason":"Demonstrates scalable AI application in power generation, leveraging physics-based models to optimize operations and reduce costs effectively.","search_term":"Vistra AI heat rate optimization","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/power_ai_innovation_physics_informed\/case_studies\/vistra_case_study.png"},{"company":"Pacific Gas and Electric","subtitle":"Deployed Palantir Foundry's AI for predictive maintenance and prognostics on transformers and 25,000 miles of grid wire.","benefits":"Reduces downtime, improves availability, optimizes maintenance scheduling.","url":"https:\/\/www.eba-net.org\/wp-content\/uploads\/2024\/05\/6-Slate-et-al1-23.pdf","reason":"Highlights AI's role in grid asset management, using data-driven physics insights for proactive infrastructure reliability.","search_term":"PG&E Palantir predictive maintenance","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/power_ai_innovation_physics_informed\/case_studies\/pacific_gas_and_electric_case_study.png"},{"company":"ThermoChem Recovery International","subtitle":"Utilized NVIDIA GPU-accelerated CPFD Barracuda software for physics simulations in biomass-to-jet fuel conversion processes.","benefits":"Gained 1,500x model speedups, reducing computation time from years to days.","url":"https:\/\/blogs.nvidia.com\/blog\/energy-efficient-ai-industries\/","reason":"Showcases physics-informed AI accelerating energy simulations, enabling faster innovation in renewable fuel production.","search_term":"TRI Barracuda biomass simulation","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/power_ai_innovation_physics_informed\/case_studies\/thermochem_recovery_international_case_study.png"},{"company":"US Department of Energy","subtitle":"Implemented AI techniques with physics-informed models to enhance power plant performance and preventative maintenance.","benefits":"Improves real-time on-line preventative maintenance system effectiveness.","url":"https:\/\/www.energy.gov\/sites\/default\/files\/2022-07\/DOE_AI_Use_Cases.pdf","reason":"Illustrates government-led physics-informed AI strategies for operational efficiency in energy infrastructure.","search_term":"DOE AI power plant physics","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/power_ai_innovation_physics_informed\/case_studies\/us_department_of_energy_case_study.png"}],"call_to_action":{"title":"Ignite AI-Driven Energy Solutions","call_to_action_text":"Seize the opportunity to revolutionize your Energy and Utilities operations with physics-informed AI. Transform your approach and lead the industry today!","call_to_action_button":"Take Test"},"challenges":null,"ai_initiatives":{"values":[{"question":"How can AI physics-informed models optimize our energy generation efficiency?","choices":["Not started","Pilot phase","Limited integration","Fully optimized"]},{"question":"What role does real-time data play in our AI-driven energy decision-making?","choices":["Data collection only","Basic analytics","Predictive insights","Autonomous adjustments"]},{"question":"How do we ensure regulatory compliance while leveraging AI innovations?","choices":["Ignoring compliance","Basic awareness","Proactive compliance measures","Integrated compliance systems"]},{"question":"In what ways can AI enhance predictive maintenance in our utility operations?","choices":["No predictive tools","Basic alerts","Advanced analytics","Self-healing systems"]},{"question":"How can we measure the ROI of AI initiatives in our energy projects?","choices":["No metrics established","Basic tracking","Comprehensive analysis","Real-time ROI dashboards"]}],"action_to_take_ai_initiatives":"Next"},"left_side_quote":[{"text":"Physics-informed AI optimizes complex oil and gas production systems in real time.","company":"SLB","url":"https:\/\/www.slb.com\/products-and-services\/delivering-digital-at-scale\/software\/physics-informed-ai","reason":"SLB's physics-informed AI enhances real-time optimization in energy production, reducing emissions and energy use while integrating physical laws with data-driven insights for utilities and oil\/gas operations."},{"text":"Extends physics-informed AI to drive industrial autonomy and cut energy use.","company":"Geminus","url":"https:\/\/www.geminus.ai\/news\/geminus-extends-physics-informed-ai-to-drive-industrial-autonomy\/","reason":"Geminus achieves 40% energy reduction in networks and eliminates flaring, showcasing scalable physics-informed AI for autonomous control in energy suppliers' piping systems."},{"text":"Physics-driven AI with NVIDIA Modulus optimizes oil well flows in real-time.","company":"SoftServe","url":"https:\/\/info.softserveinc.com\/leverage-physics-driven-ai-for-energy-innovation","reason":"SoftServe's PINNs combine physics laws with ML to monitor flows, extend equipment life, and boost profitability, advancing AI innovation in energy sector operations."},{"text":"AI\/ML grid optimization limits peak load growth using existing infrastructure.","company":"PG&E","url":"https:\/\/www.utilitydive.com\/news\/avista-pge-ameren-ai-utilities-modeling\/740705\/","reason":"PG&E leverages AI for DER optimization to double consumption while capping peaks at 10%, demonstrating physics-aligned AI for reliable power system management amid renewables."}],"quote_1":null,"quote_2":{"text":"Utilities have gotten the message and are putting their budgets to work to rapidly embrace innovation, deploy AI and build a more dynamic grid amid soaring demand for datacenters, EVs, and renewables.","author":"Steve Smith, President of National Grid Partners and Chief Strategy and Regulation Officer at National Grid","url":"https:\/\/www.prnewswire.com\/news-releases\/utility-innovation-report-64-of-utility-leaders-have-expanded-their-innovation-budgets--and-nearly-all-see-ai-as-a-strategic-focus-302579127.html","base_url":"https:\/\/www.nationalgrid.com","reason":"Highlights budget-driven AI deployment trends in utilities, directly relating to physics-informed innovations for dynamic grid management and energy demand balancing."},"quote_3":null,"quote_4":{"text":"Artificial intelligence itself can help solve the challenges of powering AI by deploying the technology across power forecasting, planning, and operations to match supply to demand more efficiently.","author":"Anonymous Fortune Contributor, Energy\/Utilities Innovation Leader (surveyed utility executive perspective)","url":"https:\/\/fortune.com\/2025\/02\/20\/ai-energy-demand-electric-utilities-innovation\/","base_url":"https:\/\/fortune.com","reason":"Showcases AI's role in predictive grid optimization, a physics-informed approach reducing energy waste and enabling scalable AI-powered utilities."},"quote_5":{"text":"National Grid Partners is driving innovation by investing in AI startups like those advancing virtual power plants and grid optimization to scale from pilots to operational control rooms.","author":"Amit Narayan, Founder of Aina Climate AI Ventures (former CEO and founder of AutoGrid)","url":"https:\/\/www.prnewswire.com\/news-releases\/utility-innovation-report-64-of-utility-leaders-have-expanded-their-innovation-budgets--and-nearly-all-see-ai-as-a-strategic-focus-302579127.html","base_url":"https:\/\/www.nationalgrid.com\/ngpartners","reason":"Illustrates investment outcomes in AI for smarter grids, relating to physics-informed models for dynamic energy management and datacenter integration."},"quote_insight":{"description":"Physics-informed neural networks achieve up to 31.9% energy savings in building efficiency compared to traditional methods.","source":"National Technical University of Athens Research","percentage":32,"url":"https:\/\/arxiv.org\/html\/2311.08035v2","reason":"This highlights how physics-informed AI accelerates computations, outperforms data-intensive models, and drives efficiency gains in energy systems, providing competitive edge in utilities."},"faq":[{"question":"What is Power AI Innovation Physics Informed and its role in Energy and Utilities?","answer":["Power AI Innovation Physics Informed integrates AI with physics-based models for enhanced decision-making.","It optimizes energy production and distribution through predictive analytics and real-time data.","This approach reduces operational risks and improves efficiency across utility operations.","Organizations can expect better resource management and lower environmental impact.","The technology fosters innovation by providing insights that drive strategic initiatives."]},{"question":"How do I start implementing Power AI Innovation Physics Informed solutions?","answer":["Begin with a clear strategy outlining objectives and desired outcomes for implementation.","Assess existing infrastructure to identify integration points for AI technologies.","Engage stakeholders early to ensure alignment and support throughout the process.","Consider piloting on a smaller scale to gauge effectiveness before wider rollout.","Utilize training programs to upskill staff on new technologies and methodologies."]},{"question":"What benefits can Energy and Utilities expect from AI-driven solutions?","answer":["AI enhances operational efficiency by automating routine tasks and processes effectively.","Organizations can achieve significant cost savings through optimized resource allocation.","Improved predictive maintenance reduces downtime and extends equipment longevity.","Data-driven insights enable better decision-making and strategic planning capabilities.","AI fosters innovation, allowing companies to remain competitive in a rapidly evolving market."]},{"question":"What are common challenges when adopting Power AI Innovation Physics Informed?","answer":["Resistance to change within organizations can hinder successful AI adoption efforts.","Data quality and availability issues often challenge effective AI implementation.","Integrating AI solutions with legacy systems can be complex and resource-intensive.","Lack of skilled personnel may create barriers to fully utilizing AI technologies.","Addressing regulatory compliance is crucial to mitigate risks associated with AI deployment."]},{"question":"When is the right time to implement AI in Energy and Utilities?","answer":["Organizations should assess their digital maturity before pursuing AI initiatives.","Timing can align with strategic planning cycles or following major technology upgrades.","Early adopters can gain competitive advantages in rapidly evolving markets.","Monitoring industry trends can indicate optimal windows for AI implementation.","When ready, organizations should ensure stakeholder buy-in for successful integration."]},{"question":"What are the key use cases for Power AI Innovation Physics Informed in the sector?","answer":["AI can optimize grid management by predicting demand and adjusting supply accordingly.","Predictive maintenance models help utilities reduce downtime and improve service reliability.","Energy efficiency programs benefit from AI insights that identify areas for improvement.","AI-driven simulations can enhance renewable energy integration into existing grids.","Regulatory compliance can be streamlined through automated reporting and monitoring systems."]},{"question":"What compliance considerations exist for AI in the Energy and Utilities sector?","answer":["Organizations must comply with data privacy regulations when handling customer information.","AI models should be transparent and auditable to meet regulatory standards.","Collaborating with regulatory bodies can ensure alignment with industry guidelines.","Continuous monitoring of AI systems helps maintain compliance and mitigate risks.","Training staff on compliance issues is essential for responsible AI use in operations."]},{"question":"How can Energy and Utilities measure the success of AI implementations?","answer":["Establish clear KPIs to evaluate the impact of AI on operational efficiency.","Regularly track cost savings associated with AI-driven process improvements.","Customer satisfaction metrics should reflect the benefits of enhanced service delivery.","Analyze the reduction in downtime as a key indicator of predictive maintenance success.","Conduct periodic reviews to assess strategic alignment and ongoing value generation."]}],"ai_use_cases":null,"roi_use_cases_list":null,"leadership_objective_list":null,"keywords":{"tag":"Power AI Innovation Physics Informed Energy Utilities","values":[{"term":"Predictive Maintenance","description":"A proactive approach to maintenance that uses AI to predict equipment failures and optimize performance in the energy sector.","subkeywords":null},{"term":"Digital Twins","description":"Virtual replicas of physical systems allowing real-time monitoring and optimization through data analysis in energy operations.","subkeywords":[{"term":"Simulation Models"},{"term":"Real-time Data"},{"term":"Performance Monitoring"}]},{"term":"Machine Learning Algorithms","description":"AI techniques used to analyze data and improve decision-making in energy management and resource allocation.","subkeywords":null},{"term":"Smart Grids","description":"Advanced electrical grids that utilize AI for efficient energy distribution and demand management.","subkeywords":[{"term":"Demand Response"},{"term":"Grid Optimization"},{"term":"Energy Storage"}]},{"term":"Data Analytics","description":"The process of examining data sets to uncover insights and trends relevant to energy production and consumption.","subkeywords":null},{"term":"Automation Technologies","description":"Use of AI-driven tools to automate processes in energy production and distribution for increased efficiency.","subkeywords":[{"term":"Robotic Process Automation"},{"term":"Control Systems"},{"term":"Workflow Automation"}]},{"term":"Anomaly Detection","description":"AI techniques used to identify unusual patterns in operational data, helping to preempt issues in energy systems.","subkeywords":null},{"term":"Energy Forecasting","description":"Using AI to predict future energy needs and production levels, enhancing planning and resource allocation.","subkeywords":[{"term":"Load Forecasting"},{"term":"Renewable Integration"},{"term":"Market Analysis"}]},{"term":"Natural Language Processing","description":"AI technology enabling machines to understand and interpret human language, useful for customer interactions in utilities.","subkeywords":null},{"term":"Grid Resilience","description":"The ability of the energy grid to withstand and recover from disruptions, enhanced through AI analytics.","subkeywords":[{"term":"Disaster Recovery"},{"term":"Risk Assessment"},{"term":"Infrastructure Strengthening"}]},{"term":"Operational Efficiency","description":"Maximizing productivity and minimizing waste in energy operations using AI-driven insights and optimizations.","subkeywords":null},{"term":"Renewable Energy Integration","description":"The process of incorporating renewable energy sources into the grid, supported by AI for stability and efficiency.","subkeywords":[{"term":"Energy Management Systems"},{"term":"Storage Solutions"},{"term":"Regulatory Compliance"}]},{"term":"Performance Metrics","description":"Quantitative measures used to assess the effectiveness of AI implementations in energy systems and utilities.","subkeywords":null},{"term":"Change Management","description":"Strategies for managing organizational change when implementing AI solutions in energy and utilities sectors.","subkeywords":[{"term":"Stakeholder Engagement"},{"term":"Training Programs"},{"term":"Process Reengineering"}]}]},"call_to_action_3":{"description":"Work with Atomic Loops to architect your AI implementation roadmap from PoC to enterprise scale.","action_button":"Contact Now"},"description_memo":null,"description_frameworks":null,"description_essay":null,"pyramid_values":null,"risk_analysis":{"title":"Risk Senarios & Mitigation","values":[{"title":"Neglecting Regulatory Compliance","subtitle":"Fines and penalties arise; ensure compliance audits."},{"title":"Data Breach and Security Risks","subtitle":"Loss of trust occurs; enhance cybersecurity measures."},{"title":"AI Algorithm Bias Issues","subtitle":"Inaccurate predictions result; implement bias detection tools."},{"title":"Operational Failures in Deployment","subtitle":"Downtime impacts production; establish robust testing protocols."}]},"checklist":null,"readiness_framework":null,"domain_data":{"title":"The Disruption Spectrum","subtitle":"Five Domains of AI Disruption in Energy and Utilities","data_points":[{"title":"Automate Production Processes","tag":"Revolutionizing energy generation methods","description":"AI-driven automation in production processes enhances efficiency in energy generation. By leveraging predictive analytics, utilities can optimize operations, reduce downtime, and increase output, leading to substantial cost savings and improved service reliability."},{"title":"Enhance Design Innovations","tag":"Transforming energy solutions with AI","description":"AI fosters innovative design approaches for energy systems, enabling smarter infrastructure development. Integration of physics-informed models allows for rapid prototyping and tailored solutions, ensuring more resilient and adaptable energy systems for future demands."},{"title":"Optimize Simulation Testing","tag":"Revolutionizing testing through AI insights","description":"AI enhances simulation and testing phases in energy projects, allowing for more accurate forecasting of system performance. This leads to reduced risks, efficient resource allocation, and accelerated project timelines, ultimately improving project success rates."},{"title":"Streamline Supply Chains","tag":"Improving logistics in energy distribution","description":"By utilizing AI for predictive analytics, energy companies can enhance supply chain logistics. This results in better inventory management, reduced operational costs, and ensures timely delivery of resources, ultimately driving efficiency across the sector."},{"title":"Enhance Sustainability Practices","tag":"Driving efficiency for a greener future","description":"AI technologies empower utilities to enhance sustainability efforts by optimizing energy consumption and reducing waste. Implementing AI solutions leads to lower carbon footprints and promotes renewable energy integration, significantly benefiting environmental goals."}]},"table_values":{"opportunities":["Enhance market differentiation through tailored AI-driven energy solutions.","Improve supply chain resilience via predictive AI analytics for resource management.","Achieve automation breakthroughs by integrating AI with existing energy systems."],"threats":["Risk of workforce displacement due to increasing AI automation.","Increased technology dependency can lead to critical system vulnerabilities.","Navigating compliance and regulatory bottlenecks may hinder AI adoption."]},"graph_data_values":null,"key_innovations":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/graphs\/power_ai_innovation_physics_informed\/key_innovations_graph_power_ai_innovation_physics_informed_energy_and_utilities.png","ai_roi_calculator":{"content":"Find out your output estimated AI savings\/year","formula":"input_downtime+enter_through=output_estimated(AI saving\/year)","action_to_take":"calculate"},"roi_graph":null,"downtime_graph":null,"qa_yield_graph":null,"ai_adoption_graph":null,"maturity_graph":null,"global_graph":null,"yt_video":null,"webpage_images":null,"ai_assessment":null,"metadata":{"market_title":"Power AI Innovation Physics Informed","industry":"Energy and Utilities","tag_name":"AI-Driven Disruptions & Innovations","meta_description":"Explore how Physics Informed AI is revolutionizing Energy and Utilities, enhancing efficiency and driving innovation. Discover actionable insights today!","meta_keywords":"Power AI Innovation, Physics Informed AI, Energy and Utilities AI, AI-driven efficiency, predictive analytics, intelligent energy solutions, AI innovations"},"case_study_images":["https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/power_ai_innovation_physics_informed\/case_studies\/vistra_case_study.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/power_ai_innovation_physics_informed\/case_studies\/pacific_gas_and_electric_case_study.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/power_ai_innovation_physics_informed\/case_studies\/thermochem_recovery_international_case_study.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/power_ai_innovation_physics_informed\/case_studies\/us_department_of_energy_case_study.png"],"introduction_images":["https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/power_ai_innovation_physics_informed\/power_ai_innovation_physics_informed_generated_image.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/power_ai_innovation_physics_informed\/power_ai_innovation_physics_informed_generated_image_1.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/power_ai_innovation_physics_informed\/power_ai_innovation_physics_informed_generated_image_2.png"],"s3_urls":["https:\/\/atomicloops-website.s3.amazonaws.com\/graphs\/power_ai_innovation_physics_informed\/key_innovations_graph_power_ai_innovation_physics_informed_energy_and_utilities.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/power_ai_innovation_physics_informed\/case_studies\/pacific_gas_and_electric_case_study.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/power_ai_innovation_physics_informed\/case_studies\/thermochem_recovery_international_case_study.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/power_ai_innovation_physics_informed\/case_studies\/us_department_of_energy_case_study.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/power_ai_innovation_physics_informed\/case_studies\/vistra_case_study.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/power_ai_innovation_physics_informed\/power_ai_innovation_physics_informed_generated_image.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/power_ai_innovation_physics_informed\/power_ai_innovation_physics_informed_generated_image_1.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/power_ai_innovation_physics_informed\/power_ai_innovation_physics_informed_generated_image_2.png"]}