TECH OFFERS

The technology consists in a new type of neural networks, providing explainable, verifiable, compact and private AI solutions. Explainability: the technology provides precise global explanations and the exact rules learned by the AI model, even with large datasets. We transform clients' raw data and/or models into meaningful results through high-quality visual analytics, empowering them to enhance the model based on these explanations. Formal Verification: the technology allows the client to formally verify certain properties of the model, such as its robustness to adversarial attacks, its fairness according to certain features, etc. Our training and testing processes are fully automated and we are currently developing a client’s side software so that users can train/verify/modify/improve/protect the models themselves. In addition the interface will provide the client a complete explanation of the inference of their models, by providing a set of logical rules that describe exactly the model.   Compactness/AI for Embedded Systems: the models resulting from our technology are extremely small, requiring much fewer logical gates and/or latency than other existing solutions, even for large datasets. There are suited for both constrained software and hardware environments. Privacy-preserving AI: Privacy-preserving AI technologies are necessary if you want to protect the data of the client during inference, but they are extremely costly in terms of computation and memory. Using our technology, you can largely reduce this cost and eventually obtain practical privacy-preserving AI solutions for tabular datasets and more. - Banking (credit scoring, customer churn, anti-money laundering, etc.) - Insurance (claims management, fraud mitigation, etc.) - Healthcare (clinical workflow, predicting ICU transfers, etc.) - Data analytics (pricing optimization, etc.) and marketing companies (content personalization, lead scoring, etc.) - Research teams (DNA, health, environment, energy) and academia - Autonomous cars (embedded AI) - Energy (AI for edge computing) - Security / Military (private, safe, compact, verified AI) and Gov agencies / Customs (responsible, fair AI) - Manufacturing, logistic, supply chain (predictive maintenance, transportation optimization, etc.) - Individual users: data analysts, AI professionals  Our AI models are the first to be optimized to work on encrypted inputs, fully guaranteeing the privacy of the user’s data. In particular, we provide the first practical solution of a privacy-preserving AI model for tabular datasets.   Our AI models are very compact and can fit even in tiny microcontrollers (software) or in a very small area (hardware). It can be naturally transformed into a set of logical rules, providing global and exact interpretability of the inference. This would be impossible with current AI models that scale to large datasets. Our AI models can formally verify if certain properties are present, such as robustness to a certain noise level, fairness, etc.). Again, this is impossible with most AI models, and especially those who scale to large datasets.   Infocomm, Artificial Intelligence

Neurological diseases are the second leading cause of death. CT scans have been used as the primary modality to diagnose brain abnormalities such as Intracranial Haemorrhage (ICH) and neurodegeneration. Radiologists usually have to deal with an overwhelming scan backlog and writing radiology reports is a time consuming process. Manual segmentation of lesions is tedious and existing heuristics have been shown to overestimate lesion volumes. Clinicians are also wary of the ‘black box’ nature of deep learning models. Hence, an automated tool in the workflow could substantially improve clinical productivity and interpretability is crucial to build trust with clinical stakeholders. Our proposed technology is an AI solution that automates ICH detection and brain tissue segmentation on CT scans, producing accurate volumetric information to assist triaging. Our technology also comes with a set of tools to interact with the AI models and generate reports easily. Moreover, we strengthen our AI transparency with interpretable models. Our platform also focuses on model robustness tests to assure AI safety.   Our core technology is our trained deep learning detection and segmentation models. Our web user interface allows visualization of the medical images and the AI predictions. Users can upload their scan using our web interface (deployed locally or in a private cloud) and obtain the results and report instantly. In the report section, users can also customize the layout of the radiology report to suit their workflow. We look forward to deploying our solution in healthcare institutions that work with CT scanners. Our technology can be deployed locally or on a secured cloud platform and integrated with local PACS systems. Our current focus area is in neurology but our solutions can be generalisable across modalities and tasks. The size of the AI medical imaging market is projected to be 20.9 billion USD in 2030. The addressable market size in Neurology and CT is 2.85 billion USD (13.6%). Our AI solution is tailored to learn Asian population brain anatomical data, which is unique in the market, therefore we are targeting to serve the Asia Pacific market which is estimated to be around 769 million USD (27%). While some available products offer solution to predict whether ICH exists in the scan, our technology automates ICH segmentation that allows accurate calculation of the lesion volume from CT scans. Secondly, most available products in the market rely on MRI scans for brain tissue segmentation, but our technology allows fast inference on CT scans. Our technology is also able to perform Alzheimer’s Disease detection using CT scans. Crucially, our solution provides ways to identify drifts, quantify uncertainty and explain model decisions in discriminative tasks, which can help build trust with clinicians. Healthcare, Telehealth, Medical Software & Imaging

Digitalisation is a global trend with digital twin technology increasingly adopted in various industrial segments including smart factories and plants, digital facility management and operation & maintenance, building and construction, etc. Rapid generation of digital twin of physically existing is desired. Conventionally, digital twin is mainly generated using design software which requires professional modellers to spend substantial design time pending on the complexity of the physical twin (to be constructed) and the manpower available. Building information modelling (BIM) is increasingly used as a representation for the digital twin. For existing environments, scan to BIM technology and authoring software products are used for the process of reconstructing of BIM models from LiDAR scanned point clouds. This manual process is typically time consuming, tedious and error prone. Often, meshed models are used for visualization purpose of the digital twin. Our innovation is an integrated solution being able to autonomously scan physical environments using robotised LiDAR cameras, automatically stitch scanned point clouds using in-house developed software algorithms, automatically recognise BIM components as well as mechanical & electrical plumping using our innovated AI techniques, and automatically convert the reconstructed BIM (not mesh models) from point cloud in IFC4.0. The solution can significantly reduce manpower needs and improve productivity from days/weeks down to hours. Ideal collaboration partners include but are not limited to builders, government agencies, smart city or smart factory planners, construction project management service providers, architecture, engineering and construction companies.   Building & Construction, Safety, Oil & Gas，etc. are relevant Industries. Potential applications include Audit & Inspection, Altering & Addition, Construction Project Management, Smart City, Smart Factory, Smart Process Plant, Smart Power Grids, etc.  A cloud-based solution can be marketed as a product for this technological innovation. Automatic BIM conversion (not mesh models) from LiDAR scanned point clouds is a significant improvement over the current manual conversion; and Rapid BIM reconstruction (not mesh models) in IFC 4.0 format is another UVP with substantial productivity improvement. Infocomm, Green ICT

Coronary artery disease (CAD) is the leading cause of death worldwide. Computed Tomography Coronary Angiography (CTCA), as a non-invasive alternative to invasive catheterized coronary angiography, has emerged as a recommended first-line investigation for CAD. However, the current practice of generating reports involves a time-intensive process, with CT specialists spending 3-6 hours annotating scans. Furthermore, there is a lack of effective tools for analysing coronary calcium scores, stenosis severity, and plaque characterization. This AI driven platform is for CT data processing that provides a streamlined 'one-stop' solution spanning from diagnosis to clinical management and prognosis. Its key features include: AI-driven platform for CTCA, catering to clinical, research, and industrial applications. Large, shareable, de-identified, Personal Data Protection Act-compliant real-world CT data. Precision toolkits for anonymization, coronary calcium scoring, epicardial adipose tissue (EAT), stenosis severity assessment, plaque quantification, CT fractional flow reserve (FFR), and reporting. The platform’s highly automated features assist physicians in interpreting and synthesizing large volumes of CT data, while minimizing bias, increasing reproducibility, and providing numerical insights in a graphical manner. It offers a comprehensive ‘one-stop’ solution for diagnosis and clinical management of CAD. Seamless integration: The DICOM-compliant parser ensures compatibility with diverse CT scanners without interfering with hospitals’ original workflow processes. AI-driven workflow: It supports fully automated analysis, including deep learning-based segmentation of the coronary artery tree, extraction of artery centrelines, tracking and acquisition of cross-section lumen images, artery labelling, stenosis and plaque detection, and quantification with high accuracy within minutes.  Comprehensive modules for CAD assessment: The technology offers a comprehensive assessment of coronary calcium score, EAT, stenosis, and plaque phonotypes. Mixed Asian registry database: It houses a vast repository of multi-ethnic imaging and non-imaging data, serving as a valuable resource for research and analysis. Annotation by SCCT-certified experts: All annotations are performed and quality-checked by experts certified by the Society of Cardiovascular Computed Tomography (SCCT). Secure and reliable data platform: The data platform is certified by the Ministry of Health Singapore, ensuring the safety and reliability of data access. The technology can be applied across various industries: Software as a clinical service for healthcare institutions: It provides comprehensive CAD assessment and personalized treatment as a software-as-a-service (SaaS) solution for healthcare institutions. Pharmaceuticals: It enables objective and quantitative measurement of the effectiveness of treatments. MedTech and digital health industry: By harnessing state-of-the-art technology and big data capabilities, it provides the development of customized foreground intellectual property, addressing the specific needs of individual companies. Local MedTech industry development: It offers tailored solutions designed specifically for small and medium-sized enterprises (SMEs) and startups, empowering them to compete globally, foster innovation in product development and services that align with market demands, and enhance patient care. It provides a thorough evaluation of the coronary arteries using deep learning algorithms and patented post-processing technologies. It serves as a ‘one stop’ platform that spans from diagnosis to clinical management and prognosis, and aiding in predicting therapy response in the pharmaceutical industry. Superior diagnostic performance: The AI toolkits deliver exceptional accuracy, surpassing 90%, while processing the data within minutes. This remarkable speed is 20 times faster than the standard diagnostic and reporting process, enabling efficient and timely decision-making. Unparalleled big data repository: The platform houses the largest mixed Asian CAD registry, comprising 5,000 patients (n=3 million images). This vast collection contains a wealth of real-world imaging and non-imaging data, representing a unique and invaluable resource that is unmatched elsewhere. Trusted ground truth: Every CT scan has been meticulously annotated and quality-checked by SCCT-certified experts. This rigorous process ensures the accuracy and reliability of the data, establishing a safe and dependable foundation for clinical decision-making. Healthcare, Telehealth, Medical Software & Imaging

A Digital Twin is a digital representation of a physical object or system, often used in various industries for simulation, analysis, and monitoring. In the built environment, which encompasses everything from buildings and infrastructure to urban planning, Digital Twins have a wide range of potential applications that can significantly enhance efficiency, sustainability, and overall quality of life. Digital twins have emerged as a transformative concept in the built environment, revolutionizing how buildings, infrastructure, and cities are designed, constructed, and managed. This innovative technology leverages the power of digital simulations and real-time data to create virtual replicas of physical assets, offering numerous benefits across various sectors within the built environment. The technology owner is seeking co-development partnerships with building owners, facity management companies, smart city or urban planners to adopt their digital twin technology in achieving their sustainability objectives. Digital twin model development & data gap report This stage involves the creation of a baseline digital twin of the proposed facility. Measured performance data input This involves gathering measured data from various sources. This would be the building BMS system and/or any other source of live or streaming operation data. Model calibration This includes the testing of the model with logic checks and balances to verify the basic inputs. Actual building experience and monitored data will be used to make any final adjustments and calibration so that the virtual model outputs align closely to reality. Analysis & diagnosis Once the baseline model is complete and confidence exists as to its validity from the calibration accuracy (over 95% accuracy), the model can be used to run “what-if” scenarios for the future. Retro commissioning (RCx) i.e. change in operations without any additional investment options will be analysed. Corrective action The team will develop a set of bespoke/customized alarms, alerts and control rules to continuously optimize building energy performance using real-time data. Deployment A workshop will be conducted to make the participating stakeholders aware of the digital twin process. Required software access as well as the user guides will be shared during the deployment. Monitoring The final stage will be the monitoring of the digital twin post-implementation. Some key potential applications for Digital Twins in the built environment: Architectural and Urban Planning: Digital Twins can be used to create virtual models of cities, allowing urban planners and architects to simulate and visualize different design scenarios. Energy Efficiency and Sustainability: Digital Twins can be used to model and simulate a building's energy consumption and environmental impact. Facility Management: Once a building is operational, Digital Twins can be used for ongoing facility management. Smart Cities: Digital Twins can serve as the backbone of smart city initiatives. By creating digital replicas of urban infrastructure and systems, city authorities can monitor traffic flow, manage waste collection, and respond to emergencies more effectively. Real Estate Development: Developers can use Digital Twins to create virtual walkthroughs of properties, allowing potential buyers or tenants to explore spaces before they are built. The Digital Twin industry is growing phenomenally, the Digital Twin Market size is expected to reach 63.5 Bil USD by 2027. The number of cases using digital twins for implementation is likely to go up to 23% in 2024 from 10% in 2021. The opportunities to use a digital twin in a built environment are quite a few: Building Performance Optimization: Digital Twins allow for continuous monitoring of a building's performance, including energy consumption, HVAC systems, and structural integrity. Sustainable Building Practices: With increasing emphasis on sustainability, Digital Twins can facilitate the design and monitoring of green and sustainable buildings. Urban Planning and Smart Cities: Digital Twins extend beyond individual buildings to entire urban environments. Cities can create virtual replicas of their infrastructure to optimize traffic flow, manage resources efficiently, and improve the overall quality of life for residents. Real Estate and Property Management: Property owners and managers can use Digital Twins to enhance tenant experiences, monitor building health, and predict maintenance needs. Facility Maintenance and Operations: Digital Twins provide real-time insights into the condition of assets within a facility. Data-Driven Decision-Making: The wealth of data generated by Digital Twins allows for data-driven decision-making at all stages of a building's lifecycle. Integration with IoT and AI: The combination of Digital Twins with the Internet of Things (IoT) and Artificial Intelligence (AI) technologies further enhances their capabilities. Improved Design and Simulation: Architects and engineers can use Digital Twins to experiment with different design concepts and test how they perform in various conditions. This allows for better optimization of building systems, materials, and energy usage, resulting in structures that are more sustainable and resilient. Real-Time Monitoring and Maintenance: Once a building is operational, the Digital Twin continues to add value by collecting and analyzing real-time data from sensors and IoT devices. Energy Efficiency: Digital Twins can optimize energy usage by analyzing data from sensors that monitor temperature, humidity, occupancy, and more. Cost Savings: By preventing errors, reducing downtime, and improving energy efficiency, Digital Twins can generate substantial cost savings over the entire lifecycle of a building or infrastructure project. Sustainability: Digital Twins enable sustainable design and operation by allowing architects and engineers to assess the environmental impact of their decisions. Risk Management: By simulating different scenarios and continuously monitoring a building's performance, Digital Twins can help identify potential risks and vulnerabilities, allowing for proactive risk management and disaster preparedness. Remote Collaboration: In an increasingly globalized world, Digital Twins facilitate collaboration among teams located in different parts of the world. Data-Driven Insights: Digital Twins generate vast amounts of data, which can be leveraged for data-driven insights and machine learning applications. Green Building, Sensor, Network, Building Control & Optimisation

For many years, gas detection applications in industries have predominantly relied on single point detectors, which are applicable in many industries covering a wide market sector.   Starting from the year 2010 and onwards, open path line detectors have gained significant recognition and popularity due to their cost-effectiveness and ability to cover larger areas, thereby enhancing safety measures.  More device options are now on the market.   However, all of these devices have the inherent problems of false alarms due to environmental interference, such as rain and snow. A waveform matching technology – multi order laser emitting spectrum (MOLES) was invented. This cutting-edge technology ensures specific gas detection, it only detects when specific gas is detected, and eliminates all false alarms caused by environmental interference.   By gathering industrial inputs and feedbacks, improvements and user-desired features are incorporated into this invention, to enhance its overall performance, reliability and solving many user problems on site, such as no display, alignment problems, and calibration.  This breakthrough innovation will provide a more efficient and reliable gas detection solution for industries, safeguarding their operations and personnel. This Open Path Gas Detection technology is Laser Gas specific with: Customised micro-controller based CPU With built-in automatic calibration capability With built-in visible laser for ease of installation and alignment With built-in display for improved ease of use at site; single man operation instead of two With built-in audible siren for alarm warning Ideal collaboration: B2B – Gas detection manufacturers B2C – Gas detector users from the Chemical, Petro-Chemical, Oil & Gas industries This open path gas detection devices are applicable in a wide market sector, including Oil and Gas, Chemicals, Water and Wastewater, Marine, Transport, Semi-conductor, Food and beverage, and Energy.   According to a research report published by Spherical Insights & Consulting, the Global Gas Detection Equipment Market Size is to grow from USD 4.25 billion in 2022 to USD 13.87 billion by 2032, at a Compound Annual Growth Rate (CAGR) of 12.56% during the projected period. Additionally, increased exploration and production by several oil corporations, such as the National Offshore Oil Corporation of China and the Oil & Natural Gas Corporation of India, is increasing demand for the region's gas detection equipment market. The Asia Pacific gas detection equipment market is expected to be led by China. North America is predicted to expand the fastest during the forecast period. The abundance of a big oil and gas pipeline network, as well as oil and gas refinery operations, in nations such as the United States and Canada, predicts significant market growth. Though Open Path gas detection devices may constitute a small percentage in the gas detection market, estimated <5%, it has fast been recognised in recent years to be more cost-effective option, and many new installations and projects nowadays, specified in their constructions, to have more open path devices for improved and effective gas leaks safety preventions.  Therefore, it is projected that the market potential for this open path devices is encouraging.  This open Path Gas Detection Device is: More cost effective than existing point detection devices Extra long distance coverage ~200m Enhance reliability and performance as compared to existing open path gas detection devices Eliminates false alarms due to environment interferences Improved ease of use; installation and alignment Open Path, Gas Detection, Long Distance, Multi Order Detection, Laser, Oil & Gas Electronics, Sensors & Instrumentation, Green Building, Sensor, Network, Building Control & Optimisation, Environment, Clean Air & Water, Sensor, Network, Monitoring & Quality Control Systems

Lithium ion (Li-ion) battery is now the dominant energy storage system in portable electronics and electric vehicles (EV). The rapid expanding EV is driving the demand for next generation high-energy batteries. Compared to conventional Li-ion batteries with graphite anode, which has a theoretical capacity of 372 mAh/g, lithium-metal batteries can deliver ten times of specific capacity (3860 mAh/g). Theoretically, anode-free batteries can double the energy density in volume compared to Li-ion batteries at the cell level. However, current anode-free batteries suffer from faster capacity decay due to poor lithium plating on Cu foil. To overcome this challenge, the technology owner has developed a liquid electrolyte comprising lithium difluoro(oxalate)borate (LiDFOB) and a carbonate solvent, enabling reversible lithium plating of anode-free lithium metal batteries. This electrolyte ensures good thermal stability with smooth Li plating of counter electrode on the anodic side even at elevated temperatures. It facilitates a capacity retention of above 80% after 100 cycles for an anode-free battery or 80% after 400 cycles for a battery with a Li metal anode. The technology owner seeks collaboration with industrial partners such as battery developers and manufacturers for further co-development and test-bedding of electrolyte and subsequent licensing of this technology for commercialisation. The patented technology is an electrolyte comprising lithium difluoro(oxalate)borate (LiDFOB) dissolving in an organic carbonate solvent that has the following features: High concentration of the LiDFOB in the range of 1.5M to 3M Enable smooth and reversible lithium plating / stripping Good cycling performance and high charging rate Good thermal stability enabling high operating temperature (up to 80 °C) Good electrochemical stability compatible to high voltage cathodes The patented electrolyte can be applied to high-energy lithium ion batteries, which have the following potential applications: Aerospace and aviation (drones and satellites) Electric vehicles (EVs, HEVs) Grid-scale energy storage Backup power systems Enable smooth and reversible lithium plating Higher energy density (about 30% increase in gravimetric capacity) Good thermal stability and cycling performance Enable high-energy-density anode-free lithium metal batteries Lithium ion battery, Electrolyte, LiDFOB Energy, Battery & SuperCapacitor, Chemicals, Polymers, Organic

This technology is suitable for companies looking for a probiotics delivery system with increased probiotics viability. Spray-dried probiotic powder derived from this technology can be used as dietary supplements or functional food additives for human and animal consumption. Conventional probiotics often lose viability during shelf storage and upon ingestion, especially during their transit through the gastric region. Our industrially scalable encapsulation technology can improve probiotics’ shelf life and maintain viability during their passage through the human upper gastrointestinal tract. The encapsulated probiotic product achieves qualities of gastroprotection and targeted release in the intestinal region, overall boosting the beneficial effects of probiotics on gut health. Probiotics represent a US$ 58 billion market with immense growth potential, as global consumers are increasingly invested in digestive health and means to enhance the gut microbiome. Our patented technology of encapsulating probiotics involves a modified spray-drying process and is a high-throughput, food-grade, and inexpensive technique applicable to pharmaceutical, food and animal feed sectors. The modified spray drying technique used in this technology is a facile, high-throughput and industrially preferred method to produce environment resistant encapsulation systems. Key advantages of this optimized spray drying process include: High encapsulation efficiency High probiotics viability Achieving a dried product with high powder yield This technology provides four major advantages in probiotics supplementation: Scalability of production Uses food-grade materials and hence renders the advantage of non-toxicity Offers gastroprotection of probiotics in the upper GI tract High viability over shelf-life This technology may be versatilely used for a variety of candidate probiotic microorganisms and can henceforth be applied to many different applications and markets. The encapsulated dry probiotic powder product is: 1. Applicable to both human health product lines and animal feed formulations due to its use of generally regarded as safe (GRAS), non-toxic materials 2. Compatible with incorporation of other active pharmaceutical ingredients alongside probiotics (to promote or enhance desired therapeutic outcomes) 3. Dried probiotic powder is compatible with standard pharmaceutical or dietary supplement dosage formats (e.g. capsules, tablets, or sachets) 4. Dried probiotic powder can be incorporated into functional food or beverage matrices, such as confectionaries, dairy products and instant foods. The probiotics market was valued at US$ 58 billion in 2021 and is projected to grow at a compound annual growth rate (CAGR) of 7.5% through 2030. The market is driven by a rise in health expenditure, an increasing consumer inclination towards preventive healthcare and a growing consumer awareness about the importance of the gut microbiome in influencing human health. So far, probiotics are mainly consumed via dairy-based yogurts (74% of the global retail value of probiotics), while 11% is attributed towards probiotics supplements. The market for probiotic supplements is set to expand rapidly, at a CAGR of 7%, from its market size of US$ 6.5 billion in 2021 (Grand View Research, 2021). Probiotic supplements may be consumed in the form of capsules, chewables/gummies, powders, tablets and softgels. This technology is well-positioned to develop probiotic supplements suitable for these various formats, as the dried powder product can be versatilely incorporated. Besides supplements, there is a growing trend to incorporate probiotics in different foods and beverages. Several examples of innovation here include probiotic ice-creams, probiotic sodas, probiotic beers, probiotic candies, probiotic ice, etc. This technology can be useful to encapsulate and protect probiotics from the external food or beverage matrix and prolong its survivability and functionality. The use of probiotics in animal feed sectors represents another opportunity. The global probiotics in the animal feed market was valued at US$ 4.4 billion in 2020 and is projected to grow at a CAGR of 8.8% through 2026. This technology benefits from having a high-scale and inexpensive production process, which reduces the costs of the encapsulation of probiotics. Using an industry-approved spray drying technique and food-grade materials, our encapsulation system guarantees both safety and scalability. This advanced technology ensures the probiotics' viability as they pass through the upper gastrointestinal tract and reach the gut, providing a remarkable advantage over conventional probiotics. probiotics, encapsulation, viability, shelf-life, spray-drying, high throughput Personal Care, Nutrition & Health Supplements, Healthcare, Pharmaceuticals & Therapeutics, Manufacturing, Chemical Processes, Foods, Ingredients, Processes

Grasping technology, often associated with robotics and automation, addresses the challenge of manipulating and handling objects in various environments. The primary problem solved by grasping technology is the ability to securely and accurately pick up, hold, move, and release objects with different shapes, sizes, and materials. This technology is especially crucial in situations where human intervention may be difficult, dangerous, or inefficient. Before the deployment of new models and algorithms in the real world, it would be great to test the algorithm in a realistic simulation environment first.  The technology presented is a realistic simulation environment to test a robotic system for grasping and manipulation. Using the simulation environment, the movements of the physical and virtual robots are synchronized. This is done without the need for writing additional code to control the physical robot, which makes real-world deployment seamless and easy. The grasping system is tested in simulation and can easily be deployed in the real world with visualization of real-time feedback on robotics tasks via the same design and simulation platform.   The technology has potential applications in manufacturing, warehousing, and household robotics, where improving grasp success rates is critical for enhancing efficiency and reducing costs. These environments are often cluttered and contain dynamically moving objects.  A synchronized sim-to-real platform for robotic grasping and manipulation can be incredibly useful to the industry in several ways:   Reduced Cost: Traditional methods of developing robotic grasping and manipulation systems require expensive hardware, time-consuming trial-and-error testing, and large amounts of data. A synchronized sim-to-real platform allows for much of this testing and data collection to be done virtually, reducing costs and increasing efficiency.   Improved Efficiency: With a synchronized sim-to-real platform, researchers and developers can test and fine-tune robotic grasping and manipulation algorithms in simulation before deploying them on physical robots. This can reduce the time required for physical testing and enable more efficient algorithm development.   Increased Safety: The use of simulation environments can provide a safer testing environment for robotic grasping and manipulation systems, allowing developers to test and refine algorithms without risking damage to expensive hardware or injury to human operators.   Enhanced Performance: With the ability to test and optimize algorithms in simulation, developers can achieve higher levels of performance in robotic grasping and manipulation tasks, leading to more effective and reliable systems.   Better Scalability: A synchronized sim-to-real platform can also facilitate the development of more scalable robotic grasping and manipulation systems, as algorithms and methods can be tested and refined in simulation before being deployed on a larger scale.   Overall, a synchronized sim-to-real platform for robotic grasping and manipulation has the potential to significantly improve the efficiency, safety, and performance of industrial robotic systems, leading to greater productivity and cost savings for companies.   Robotics, Grasping, Manipulation, Simulation Manufacturing, Assembly, Automation & Robotics, Infocomm, Robotics & Automation