Readiness And Transformation Roadmap
Transform Roadmap AI Yield
In the Silicon Wafer Engineering sector, "Transform Roadmap AI Yield" signifies the strategic integration of artificial intelligence to enhance production efficacy and yield optimization. This concept encompasses advanced methodologies and frameworks designed to leverage AI technologies for improving operational workflows and decision-making processes. As the industry evolves, this approach aligns seamlessly with the broader shift towards AI-led transformations, addressing the pressing need for innovation and efficiency that stakeholders prioritize today. The Silicon Wafer Engineering ecosystem is increasingly influenced by AI-driven practices that redefine competitive landscapes and innovation cycles. By harnessing AI, organizations can enhance efficiency and streamline decision-making, thereby altering long-term strategic directions. This transformation presents significant growth opportunities, yet it also introduces challenges such as adoption barriers and integration complexities, which stakeholders must navigate while responding to evolving expectations in a dynamic environment.
{"page_num":5,"introduction":{"title":"Transform Roadmap AI Yield","content":"In the Silicon Wafer <\/a> Engineering sector, \"Transform Roadmap AI Yield <\/a>\" signifies the strategic integration of artificial intelligence to enhance production efficacy and yield optimization <\/a>. This concept encompasses advanced methodologies and frameworks designed to leverage AI technologies for improving operational workflows and decision-making processes. As the industry evolves, this approach aligns seamlessly with the broader shift towards AI-led transformations, addressing the pressing need for innovation and efficiency that stakeholders prioritize today.\n\nThe Silicon Wafer Engineering <\/a> ecosystem is increasingly influenced by AI-driven practices that redefine competitive landscapes and innovation cycles. By harnessing AI, organizations can enhance efficiency and streamline decision-making, thereby altering long-term strategic directions. This transformation presents significant growth opportunities, yet it also introduces challenges such as adoption barriers <\/a> and integration complexities, which stakeholders must navigate while responding to evolving expectations in a dynamic environment.","search_term":"AI yield transformation Silicon Wafer"},"description":{"title":"How AI is Revolutionizing Silicon Wafer Engineering?","content":"The Silicon Wafer Engineering <\/a> market is undergoing a transformative phase as AI <\/a> technologies streamline manufacturing processes and enhance quality control. Key growth drivers include the optimization of production efficiency and the reduction of defects through predictive analytics, reshaping competitive dynamics in the industry."},"action_to_take":{"title":"Drive AI-Enhanced Transformations in Silicon Wafer Engineering","content":"Silicon Wafer Engineering <\/a> companies should strategically invest in AI-driven initiatives and forge partnerships with leading technology firms to maximize the potential of Transform Roadmap AI Yield <\/a>. By leveraging AI, organizations can achieve significant operational efficiencies, enhance product quality, and gain a competitive edge <\/a> in the marketplace.","primary_action":"Download the Transformation Roadmap Template","secondary_action":"Take the AI Readiness Assessment"},"implementation_framework":[{"title":"Assess Current Systems","subtitle":"Evaluate existing processes and technologies","descriptive_text":"Conduct a thorough assessment of current silicon wafer engineering <\/a> systems, identifying inefficiencies and areas for AI integration. This ensures alignment with AI readiness <\/a> objectives and enhances operational efficiency and competitiveness.","source":"Industry Standards","type":"dynamic","url":"https:\/\/www.semi.org\/en\/standards","reason":"This step is crucial for understanding gaps and opportunities for AI-driven improvements, laying the groundwork for a strategic roadmap to enhance yield."},{"title":"Implement AI Solutions","subtitle":"Integrate AI technologies into processes","descriptive_text":"Adopt advanced AI solutions tailored for silicon wafer engineering <\/a>, such as predictive analytics and machine learning algorithms. This elevates production precision, reduces waste, and fosters continuous improvement in yield performance.","source":"Technology Partners","type":"dynamic","url":"https:\/\/www.intel.com\/content\/www\/us\/en\/ai\/overview.html","reason":"Integrating AI solutions directly addresses efficiency and yield challenges, positioning the company to leverage data insights for strategic decision-making and competitive advantage."},{"title":"Train Workforce","subtitle":"Enhance skills in AI technologies","descriptive_text":"Provide targeted training programs for employees on AI tools and methodologies. This empowers the workforce to effectively utilize AI technologies, fostering innovation and improving operational performance in silicon wafer engineering <\/a>.","source":"Internal R&D","type":"dynamic","url":"https:\/\/www.forbes.com\/sites\/bernardmarr\/2021\/01\/18\/the-top-5-ai-skills-every-business-needs-in-2021\/?sh=5c1f0b8a7f3f","reason":"Workforce training is vital for successful AI implementation, ensuring that employees are equipped to maximize the benefits of AI-driven processes and maintain competitive edge."},{"title":"Monitor and Optimize","subtitle":"Continuously evaluate AI performance","descriptive_text":"Establish metrics to monitor AI-driven outcomes in silicon wafer production <\/a>. Regularly analyze performance data to optimize processes, ensuring continuous improvement and alignment with yield enhancement goals and operational resilience.","source":"Cloud Platform","type":"dynamic","url":"https:\/\/azure.microsoft.com\/en-us\/solutions\/ai\/","reason":"Ongoing monitoring and optimization are essential to sustain improvements and adaptability in AI implementations, reinforcing supply chain resilience and operational efficiency."},{"title":"Scale Successful Practices","subtitle":"Expand AI initiatives to broader operations","descriptive_text":"Identify successful AI implementations and scale these practices across other areas of silicon wafer engineering <\/a>. This promotes innovation and drives overall yield improvements, enhancing the companys competitive positioning in the market.","source":"Industry Standards","type":"dynamic","url":"https:\/\/www.semi.org\/en\/standards","reason":"Scaling successful practices ensures that the benefits of AI are maximized across the organization, fostering a culture of innovation and continuous improvement."}],"primary_functions":{"question":"What's my primary function in the company?","functions":[{"title":"Engineering","content":"I design and implement AI-driven solutions for the Transform Roadmap AI Yield in Silicon Wafer Engineering. My focus is on developing algorithms that enhance production efficiency. I ensure seamless integration of AI systems, driving innovation and improving yield metrics through data-driven decision-making."},{"title":"Quality Assurance","content":"I manage the quality control of AI implementations in the Transform Roadmap AI Yield process. I conduct rigorous testing and validation of AI outputs, ensuring they meet industry standards. My efforts directly enhance product reliability and customer satisfaction by identifying potential quality issues early."},{"title":"Operations","content":"I oversee the operational deployment of Transform Roadmap AI Yield solutions. I analyze real-time data from AI systems to optimize workflows, ensuring maximum efficiency. My role involves collaborating across teams to implement strategies that boost production without compromising safety or quality."},{"title":"Research","content":"I conduct research to explore new AI technologies that can enhance the Transform Roadmap AI Yield initiatives. I analyze market trends and emerging technologies, providing insights that drive innovation. My findings help the company stay ahead in the competitive Silicon Wafer Engineering landscape."},{"title":"Marketing","content":"I shape the marketing strategies for our Transform Roadmap AI Yield solutions. I communicate the benefits of our AI innovations to stakeholders and potential clients. My role involves creating compelling narratives around our technology, driving engagement, and enhancing our brand's visibility in the industry."}]},"best_practices":null,"case_studies":[{"company":"Intel","subtitle":"Implemented AI workflow for repetitive defect detection in manufacturing yield analysis, pushing results to engineers for root cause investigation.","benefits":"Supports more products, scales to new technologies.","url":"https:\/\/www.intel.com\/content\/dam\/www\/central-libraries\/us\/en\/documents\/intel-it-manufacturing-yield-analysis-with-ai-paper.pdf","reason":"Demonstrates AI integration with human expertise to accelerate yield analysis, enabling scalability across products and processes in semiconductor fabs.","search_term":"Intel AI yield analysis","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/transform_roadmap_ai_yield\/case_studies\/intel_case_study.png"},{"company":"TSMC","subtitle":"Deployed AI algorithms to classify wafer defects and generate predictive maintenance charts during semiconductor production.","benefits":"Significantly improves manufacturing yield rates.","url":"https:\/\/innovationatwork.ieee.org\/revolutionizing-semiconductors-through-ai-driven-innovation\/","reason":"Highlights AI's role in defect classification and maintenance prediction, key for high-volume wafer production and yield optimization.","search_term":"TSMC AI wafer defects","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/transform_roadmap_ai_yield\/case_studies\/tsmc_case_study.png"},{"company":"Qorvo","subtitle":"Adopted C3 AI Process Optimization to predict low-yield wafers early and identify manufacturing process improvements.","benefits":"Estimated economic impact over $30 million yearly.","url":"https:\/\/c3.ai\/customers\/optimizing-overall-semiconductor-yield\/","reason":"Shows rapid AI deployment for wafer prediction and process tuning, transforming yield management in high-performance semiconductor manufacturing.","search_term":"Qorvo C3 AI yield","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/transform_roadmap_ai_yield\/case_studies\/qorvo_case_study.png"},{"company":"GlobalFoundries","subtitle":"Utilizes AI and ML for anomaly detection, predictive maintenance, and yield forecasting in semiconductor wafer production.","benefits":"Enhances pattern recognition, improves yield prediction accuracy.","url":"https:\/\/yieldwerx.com\/blog\/overcoming-semiconductor-yield-management-challenges-using-ai-and-ml\/","reason":"Illustrates AI\/ML overcoming yield challenges through real-time analytics, vital for efficient silicon wafer engineering and cost reduction.","search_term":"GlobalFoundries AI yield management","case_study_image":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/transform_roadmap_ai_yield\/case_studies\/globalfoundries_case_study.png"}],"call_to_action":{"title":"Elevate Your AI-Driven Yield Now","call_to_action_text":"Transform your Silicon Wafer Engineering <\/a> processes with AI solutions. Seize this opportunity to enhance efficiency and outperform competitors today!","call_to_action_button":"Take Test"},"challenges":null,"ai_initiatives":{"values":[{"question":"How does your AI yield strategy enhance silicon wafer quality assurance?","choices":["Not started","Basic implementation","Optimizing processes","Fully integrated system"]},{"question":"What metrics guide your AI initiatives in wafer production efficiency?","choices":["No metrics defined","Basic KPIs","Advanced data analytics","Comprehensive performance metrics"]},{"question":"How are you addressing AI talent gaps in your wafer engineering team?","choices":["No strategy yet","Training programs","Collaborations with universities","Dedicated AI talent acquisition"]},{"question":"What role does AI play in reducing wafer fabrication costs for your business?","choices":["No impact identified","Minimal cost reduction","Significant savings projected","Cost-effective AI integration"]},{"question":"How prepared is your organization for AI-driven innovation in wafer design?","choices":["Not prepared","Exploring opportunities","Pilot projects underway","Full-fledged innovation strategy"]}],"action_to_take_ai_initiatives":"Next"},"left_side_quote":[{"text":"Deployed Guided Analytics to automatically detect yield deviations.","company":"Renesas","url":"https:\/\/www.pdf.com\/resources\/ai-driven-collaboration-transforming-the-semiconductor-industrys-operating-model\/","reason":"Automates 90% of yield analysis, boosting engineer productivity and enabling continuous monitoring across wafer operations, key to AI-driven yield transformation in silicon engineering."},{"text":"Chip-on-Wafer-on-Substrate central to chip construction roadmaps.","company":"TSMC","url":"https:\/\/montaka.com\/ai-backbone-semiconductors\/","reason":"Advances beyond Moore's Law with AI-era packaging, scaling performance 40x for high-yield wafer integration, transforming silicon engineering roadmaps."},{"text":"AI optimizes yield through process control and manufacturing gains.","company":"HTEC Research (Semiconductor Leaders)","url":"https:\/\/htec.com\/insights\/media-coverage\/htec-research-unlocking-ais-full-value-in-semiconductors-why-only-27-4-are-ready-to-scale\/","reason":"39.6% of leaders prioritize AI for yield optimization, addressing scaling gaps in wafer production to unlock AI value in semiconductor engineering."},{"text":"Gen AI demands additional wafers from advanced nodes by 2030.","company":"McKinsey","url":"https:\/\/www.mckinsey.com\/industries\/semiconductors\/our-insights\/generative-ai-the-next-s-curve-for-the-semiconductor-industry","reason":"Projects 1.2-3.6M extra wafers needed, driving AI roadmap investments in silicon wafer capacity and innovation for industry transformation."}],"quote_1":null,"quote_2":{"text":"We are now manufacturing the most advanced AI chips in the world, in the most advanced fab in the United States for the first time, marking the beginning of a new AI industrial revolution in semiconductor production.","author":"Jensen Huang, CEO of Nvidia","url":"https:\/\/www.foxbusiness.com\/media\/nvidia-ceo-touts-new-ai-industrial-revolution-praises-trump-tariffs-role-chip-production","base_url":"https:\/\/www.nvidia.com","reason":"Highlights US wafer manufacturing milestone for AI chips, directly advancing the transform roadmap by enabling domestic AI yield through policy-driven semiconductor engineering."},"quote_3":null,"quote_4":null,"quote_5":{"text":"Semiconductors are propelling an unprecedented era of technological progress through AI, requiring sound government policies to promote continued growth in wafer engineering.","author":"Semiconductor Industry Association (SIA) Leadership","url":"https:\/\/www.semiconductors.org\/sia-news-roundup\/","base_url":"https:\/\/www.semiconductors.org","reason":"Stresses policy needs for AI-driven semiconductor advancement, significant for AI yield roadmaps by addressing challenges in high-tech wafer production scaling."},"quote_insight":{"description":">90% accuracy in detecting baseline patterns through AI yield analysis on silicon wafers","source":"Intel IT","percentage":90,"url":"https:\/\/www.intel.com\/content\/dam\/www\/central-libraries\/us\/en\/documents\/intel-it-manufacturing-yield-analysis-with-ai-paper.pdf","reason":"This high accuracy enables Transform Roadmap AI Yield by automating GFA detection across 100% of wafers, accelerating root cause analysis, improving silicon wafer quality, and driving efficiency in semiconductor engineering."},"faq":[{"question":"What is Transform Roadmap AI Yield and its significance in Silicon Wafer Engineering?","answer":["Transform Roadmap AI Yield optimizes manufacturing processes using advanced AI technologies.","It enhances precision in wafer fabrication, leading to higher product quality and yield.","The roadmap guides companies in integrating AI effectively into their operations.","Organizations can achieve significant cost reductions through improved efficiency and automation.","This approach fosters innovation, helping companies stay competitive in a rapidly evolving market."]},{"question":"How do we start implementing Transform Roadmap AI Yield in our organization?","answer":["Begin by assessing your current processes and identifying areas for AI integration.","Engage cross-functional teams to ensure a comprehensive understanding of needs.","Develop a phased implementation strategy to minimize disruption during the transition.","Invest in training programs for staff to foster AI competency and acceptance.","Regularly review progress and adjust strategies to meet evolving organizational goals."]},{"question":"What measurable outcomes can we expect from AI implementation in our processes?","answer":["Companies typically see improved yield rates through enhanced process control and monitoring.","AI-driven analytics provide insights that lead to better decision-making capabilities.","Operational costs often decrease, resulting in improved profitability and efficiency.","Customer satisfaction metrics can improve due to higher quality and faster delivery.","Organizations may also experience reduced time-to-market for new products and innovations."]},{"question":"What challenges might we face when integrating AI into our existing systems?","answer":["Resistance to change from employees can hinder the adoption of new technologies.","Data quality issues might complicate AI training and implementation processes.","Integration with legacy systems can present significant technical challenges.","Organizations may encounter a skills gap, necessitating external training or hiring.","Ongoing support and maintenance requirements can strain resources if not planned."]},{"question":"When is the best time to implement Transform Roadmap AI Yield in our operations?","answer":["Identify opportunities during periods of low production demand to minimize disruptions.","Consider implementing during strategic planning cycles to align with business objectives.","Monitor technological advancements and market trends that may necessitate timely action.","Assess internal readiness and capability to adopt AI solutions effectively.","Launching pilot projects can provide valuable insights before full-scale implementation."]},{"question":"Why should we invest in Transform Roadmap AI Yield for long-term growth?","answer":["Investing in AI technologies enhances operational efficiency and minimizes waste significantly.","Companies can gain a competitive edge through faster innovation and improved product quality.","AI implementation fosters a culture of continuous improvement and agility.","Long-term savings and profitability can be achieved by optimizing resource allocation.","The strategic use of AI positions companies favorably in a highly competitive landscape."]},{"question":"What are the regulatory considerations for AI in Silicon Wafer Engineering?","answer":["Compliance with industry standards is crucial to avoid legal repercussions and fines.","Data privacy regulations must be adhered to when collecting and processing information.","Organizations should regularly audit AI systems to ensure adherence to regulatory requirements.","Transparency in AI operations fosters trust among stakeholders and clients.","Engaging with regulatory bodies can provide guidance on best practices and compliance."]}],"ai_use_cases":null,"roi_use_cases_list":null,"leadership_objective_list":null,"keywords":{"tag":"Transform Roadmap AI Yield Silicon Wafer Engineering","values":[{"term":"Yield Optimization","description":"A process that enhances the manufacturing yield of silicon wafers through data-driven insights and AI algorithms.","subkeywords":null},{"term":"Machine Learning Models","description":"Algorithms that analyze data patterns to predict outcomes, crucial for improving silicon wafer production efficiency.","subkeywords":[{"term":"Regression Analysis"},{"term":"Classification Techniques"},{"term":"Neural Networks"}]},{"term":"Predictive Analytics","description":"The use of AI to forecast production issues and maintenance needs, minimizing downtime in wafer fabrication.","subkeywords":null},{"term":"Data Integration","description":"Combining data from various sources to create a comprehensive view of production processes, essential for AI applications.","subkeywords":[{"term":"ETL Processes"},{"term":"Data Warehousing"},{"term":"Real-time Analytics"}]},{"term":"Process Automation","description":"Utilization of AI to automate routine tasks in silicon wafer engineering, enhancing productivity and reducing errors.","subkeywords":null},{"term":"Digital Twins","description":"Virtual replicas of physical processes that help simulate and optimize wafer production through AI-driven insights.","subkeywords":[{"term":"Simulation Tools"},{"term":"Real-time Monitoring"},{"term":"Predictive Maintenance"}]},{"term":"Quality Assurance","description":"AI-driven techniques to ensure that silicon wafers meet stringent quality standards throughout the manufacturing process.","subkeywords":null},{"term":"Supply Chain Optimization","description":"Using AI to enhance the efficiency of the supply chain for silicon wafers, from raw materials to delivery.","subkeywords":[{"term":"Inventory Management"},{"term":"Logistics Automation"},{"term":"Demand Forecasting"}]},{"term":"AI-Driven Analytics","description":"Advanced analytics that leverage AI to derive actionable insights from production data, improving decision-making.","subkeywords":null},{"term":"Performance Metrics","description":"Key indicators used to measure the success and efficiency of AI implementations in silicon wafer production.","subkeywords":[{"term":"KPIs"},{"term":"Benchmarking"},{"term":"ROI Analysis"}]},{"term":"Smart Manufacturing","description":"The integration of AI and IoT technologies to create intelligent manufacturing environments for silicon wafers.","subkeywords":null},{"term":"Innovation Strategies","description":"Methods for fostering innovation through AI in silicon wafer engineering, leading to competitive advantages.","subkeywords":[{"term":"R&D Investments"},{"term":"Collaboration Models"},{"term":"Agile Methodologies"}]},{"term":"Operational Efficiency","description":"The capability to optimize processes and resource usage in silicon wafer manufacturing through AI applications.","subkeywords":null},{"term":"Market Trends","description":"Current shifts and forecasts in the silicon wafer engineering sector influenced by AI advancements and technologies.","subkeywords":[{"term":"Emerging Technologies"},{"term":"Industry Standards"},{"term":"Consumer Demands"}]}]},"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 AI Compliance Regulations","subtitle":"Legal penalties arise; conduct regular compliance audits."},{"title":"Data Breach from AI Vulnerabilities","subtitle":"Sensitive info exposed; enhance cybersecurity measures immediately."},{"title":"Bias in AI Decision-Making","subtitle":"Unfair outcomes result; implement diverse training datasets."},{"title":"Operational Disruption from AI Failures","subtitle":"Production halts occur; establish robust contingency plans."}]},"checklist":null,"readiness_framework":{"title":"AI Readiness Framework","pillars":[{"pillar_name":"Data Infrastructure","description":"Data lakes, sensor data integration, real-time analytics"},{"pillar_name":"Technology Stack","description":"AI algorithms, automation tools, cloud computing services"},{"pillar_name":"Workforce Capability","description":"Reskilling, AI training programs, cross-functional teams"},{"pillar_name":"Leadership Alignment","description":"Vision articulation, strategy development, stakeholder engagement"},{"pillar_name":"Change Management","description":"Agile methodologies, user adoption strategies, feedback loops"},{"pillar_name":"Governance & Security","description":"Data privacy, compliance standards, risk management protocols"}]},"domain_data":null,"table_values":null,"graph_data_values":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/graphs\/transform_roadmap_ai_yield\/oem_tier_graph_transform_roadmap_ai_yield_silicon_wafer_engineering.png","key_innovations":null,"ai_roi_calculator":null,"roi_graph":null,"downtime_graph":null,"qa_yield_graph":null,"ai_adoption_graph":null,"maturity_graph":null,"global_graph":"https:\/\/d1kmzxl7118mv8.cloudfront.net\/graphs\/global_map_transform_roadmap_ai_yield_silicon_wafer_engineering\/transform_roadmap_ai_yield_silicon_wafer_engineering.png","yt_video":null,"webpage_images":null,"ai_assessment":null,"metadata":{"market_title":"Transform Roadmap AI Yield","industry":"Silicon Wafer Engineering","tag_name":"Readiness & Transformation Roadmap","meta_description":"Unlock the potential of AI in Silicon Wafer Engineering with our Transform Roadmap AI Yield guide. Learn strategies for efficiency and growth.","meta_keywords":"Transform Roadmap AI Yield, Silicon Wafer Engineering, AI in manufacturing, predictive maintenance, operational efficiency, technology transformation, roadmap for AI"},"case_study_images":["https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/transform_roadmap_ai_yield\/case_studies\/intel_case_study.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/transform_roadmap_ai_yield\/case_studies\/tsmc_case_study.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/transform_roadmap_ai_yield\/case_studies\/qorvo_case_study.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/transform_roadmap_ai_yield\/case_studies\/globalfoundries_case_study.png"],"introduction_images":["https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/transform_roadmap_ai_yield\/transform_roadmap_ai_yield_generated_image.png","https:\/\/d1kmzxl7118mv8.cloudfront.net\/images\/transform_roadmap_ai_yield\/transform_roadmap_ai_yield_generated_image_1.png"],"s3_urls":["https:\/\/atomicloops-website.s3.amazonaws.com\/graphs\/global_map_transform_roadmap_ai_yield_silicon_wafer_engineering\/transform_roadmap_ai_yield_silicon_wafer_engineering.png","https:\/\/atomicloops-website.s3.amazonaws.com\/graphs\/transform_roadmap_ai_yield\/oem_tier_graph_transform_roadmap_ai_yield_silicon_wafer_engineering.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/transform_roadmap_ai_yield\/case_studies\/globalfoundries_case_study.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/transform_roadmap_ai_yield\/case_studies\/intel_case_study.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/transform_roadmap_ai_yield\/case_studies\/qorvo_case_study.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/transform_roadmap_ai_yield\/case_studies\/tsmc_case_study.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/transform_roadmap_ai_yield\/transform_roadmap_ai_yield_generated_image.png","https:\/\/atomicloops-website.s3.amazonaws.com\/images\/transform_roadmap_ai_yield\/transform_roadmap_ai_yield_generated_image_1.png"]}