Google Cloud has launched the Vertex AI Evaluation Suite. This toolkit measures how well digital agents perform and how reliable they are. As more businesses use autonomous digital agents for complex customer and internal tasks, solid benchmarking is needed. The suite offers a standard way to test how well these digital agents follow instructions and use external data. By uniting these evaluation tools in the cloud, Google Cloud aims to replace subjective impressions with objective, repeatable technical audits.  

Quantifying Digital Performance and Precision 

The main feature of the new evaluation suite is “instruction following”. It measures how accurately a system completes multi-step requests. Previously, engineers had to check these systems manually, which took a lot of time. Now, the suite automates this process. It compares the system’s results to a set of predefined “ground truth” datasets. It gives a score based on relevance, accuracy, and safety. This helps developers pinpoint where a process fails during a complex task.  

The suite also adds “contextual recall” testing. This ensures systems use the right information from their knowledge base. This is critical in areas such as finance or legal services, where rules change frequently. The tools check if your digital assistant is using the latest policy documents. They also flag it if it pulls from outdated sources by mistake. Finding defects early helps companies avoid spreading wrong information. This detailed oversight acts as a safety net for large enterprise projects.  

Rapid Prototyping And Iterative Benchmarking 

The Vertex Evaluation Suite speeds up the move from development to production. In test days, by enabling repeated benchmarking, developers can run thousands of simulated interactions much faster than they can conduct manual reviews. These tests check how well the system handles unusual situations and tricky problems. The platform gives a detailed side-by-side comparison of different software versions. This makes it easier for teams to choose the best setup for speed and accuracy.  

Connection with existing “continuous integration and deployment” (CI/CD) workflows is a key feature of the April 2026 update. This means that a major feature in the April 2026 update is integration with existing continuous integration and deployment (CI/CD) workflows. Now, whenever a developer updates the code, the evaluation suite automatically runs a new set of tests. If the performance score falls below a set level, the system block can block the update from going live. This automated gatekeeping ensures only stable, verified versions are deployed, reducing the risk of errors that could upset customers or compromise end data variability.  

Governance And Observability In The Cloud 

The release focuses on visibility, introducing the new agentic health dashboard. This tool provides a real-time view of how virtual assistants are working across the company’s network. It tracks reasoning latency, the time a system takes to process a request and generate a plan. If an agent starts acting strangely or slows down, administrators get instant alerts. This kind of observability helps teams fix faults early before small problems become bigger ones.  

This suite also comes with bias and safety guardrails built into its evaluation process. These tools can automatically scan for outputs that could break company policies or ethical rules. They mark anything unusual or possibly harmful for people to review. This keeps the digital agents aligned with the organization’s values. By delivering a clear audit trail for every automated decision, Google Cloud helps businesses meet new international transparency rules.  

Scaling Infrastructure For Universal Intelligence 

To handle the heavy computing needs of these evaluations, the suite uses the latest TPU and GPU hardware clusters. This lets it run even the most elaborate digital agent simulations almost instantly. The evaluation suite can adjust its testing power to fit each project. A small business might run a few hundred tests daily, while a global retailer could simulate millions of digital agent interactions every hour.  

The rollout features a Library of Templates with ready-made testing scenarios for different industries. There are special modules for retail, healthcare, and telecommunications, each having its own key performance indicators. This speeds up project start-ups, so teams can begin auditing their systems right away. By standardizing these metrics, Google Cloud is helping the industry speak the same language about software reliability. This supports partners and customers in building a better-connected and more reliable digital infrastructure.  

The Crystalline Watchman of Integrity 

As we watch these digital synapses fire faster across our screens, we are witnessing the rise of a new kind of quiet protector, the clouds, whose architecture is now more attentive, acting as a tireless protector that keeps up with our need for certainty. We are moving toward a future where errors are simply technical challenges handled by clear logic. Over time, worries about mistakes or hallucinations may fade, replaced by trust in systems that deal with complex tasks with integrity. One day, we may realize that much of our world is managed by reliable and unseen technology. The machine is learning to monitor itself, serving as a steady and dependable partner.

SourceVertex AI offers new ways to build and manage multi-agent systems 

Meta has launched a new initiative to make it easier for small- and medium-sized companies to leverage AI. This is part of a larger effort to democratize access to the latest advances in digital technology and to provide businesses with practical tools, training, and AI-based solutions to improve their operations, customer relations, and marketing results.  

As businesses across virtually every sector recognize the importance of incorporating AI into their operations, Meta is offering this program to help reduce some of the hurdles that smaller companies often encounter when adopting advanced technology. Meta plans to provide a roadmap for adopting AI-powered work processes through structured guidance and integrated tools.  

Expanding Access to AI for Small Businesses  

Small companies typically lack the technology, knowledge, or funding needed to fully implement AI systems. Meta’s initiative aims to provide an accessible solution, supplying the tools needed for easy integration into current operations without requiring great technical skills.  

The initiative includes AI-based assistants and automated features to help manage customer interactions, generate content, and optimize advertising campaigns. The intention is to make it easier for small-business owners to perform tasks that are often difficult and lengthy, enabling owners to focus on strategy and growth rather than manual procedures.  

The initiative is positioned as part of Meta’s broader effort to make AI more accessible and usable across its digital ecosystem.  

AI-Powered Business Workflows  

The program integrates artificial intelligence into daily work processes as a core feature. Examples of these types of tasks include answering customer inquiries, writing marketing content, and analyzing customer engagement metrics through data analysis, all of which are automated through this program (the integration of AI); this means that when AI is included within their workflow management tools (office suites such as Google Workspace), Meta provides businesses with the ability to run their business’s operations and utilize these tools, allowing them to make data-based decisions almost instantaneously. These capabilities are incredibly useful to small businesses with little or no marketing or data analysis, and they can significantly improve performance and decision-making.  

Automating the workflows of digital businesses represents a shift in our society from a world of manual business processes to one in which the most efficient methods of completing tasks are becoming the standard across the entire digital infrastructure.  

Enhancing Digital Advertising Capabilities  

Part of Meta’s ecosystem is advertising, which remains important, while the new program is being introduced to enhance small business use of Meta’s advertising platform, or Meta Ad Manager. The use of AI tools enables small businesses to develop more effective advertising campaigns by targeting audiences, generating creative content, and analyzing advertising performance metrics.  

With AI systems readily available to small businesses, they can connect with their customers more quickly, with less time and knowledge required from a campaign manager. For small businesses without large marketing budgets, using AI can significantly improve ROI.  

Meta will use its advertising infrastructure and incorporate AI capabilities into the Meta Ad Manager tools used by small businesses.  

Reducing Barriers to Digital Transformation  

The purpose of this initiative is to help small businesses successfully transition to using digital technologies. For many small organizations, barriers such as high costs, complexity, and insufficient support and training can hinder their ability to adapt to new technologies effectively.  

Meta has developed simplified tools and instructional materials that make it easier for small businesses to access and use AI solutions, enabling them to participate more fully in the digital economy. Some examples include providing step-by-step instructions for implementing AI; offering assistance throughout the implementation process (onboarding); and creating automated systems that help ease the transition to using AI.  

The program aligns with an increasingly recognized understanding that AI must be available to all organizations for AI to have a significant effect on improving overall GDP growth.  

Competitive Landscape in AI Business Tools  

Meta has decided to implement this strategy because technology companies are currently competing to develop AI business solutions. The main platforms are making substantial financial commitments to develop AI systems that will enhance their marketing, customer support, and business operations systems.   

Meta targets small business owners because they represent a significant market segment that most companies fail to reach. This strategy allows the company to grow its customer base while building a stronger ecosystem that depends on its various platforms.  

As AI becomes an essential feature of business software, the competition within this industry will become more intense.  

AI in Customer Engagement and Communication  

The program develops better customer engagement through its AI-based communication tools. Businesses can use AI assistants to respond to inquiries, provide product recommendations, and manage customer interactions across platforms.  

The systems enable quicker customer response times while delivering standardized communication, resulting in better customer satisfaction and retention. This automation provides essential benefits for small businesses that operate with minimal staffing.  

Meta is implementing these functions throughout its messaging services and social media platforms to establish a complete communication system.  

Data-Driven Decision Making for SMEs  

Using AI tools from this program, small business owners can make better decisions by utilizing data analysis. By collecting data on customer behavior, how their campaigns perform, and overall engagement trends, small businesses can adjust their strategy in real time.  

This use of data-driven decision-making gives small companies a competitive advantage over large competitors who have historically been able to hire sophisticated analytical teams. The use of AI has given all small businesses access to sophisticated insights that help them compete.  

Challenges in AI Adoption  

The implementation of AI systems in small enterprises offers advantages but also presents challenges, including data protection issues, the need for employees to learn new skills, and the requirement to use specific technology platforms. Organizations need to verify that their artificial intelligence systems produce results that align with both their brand identity and customers’ expectations.  

Meta requires a system that enables automated processes to operate while giving users complete control over their operations, enabling businesses to leverage artificial intelligence while maintaining operational independence.  

Future of AI for Small Business Growth  

Smaller businesses will increasingly be able to use AI to improve their operational capabilities as AI tool sophistication increases. Future advances will include fully automated, fully articulated marketing systems, predictive consumer insights, and AI-driven assistance for product development.  

Meta’s program is an early step toward moving AI into the backbone of a business’s daily operations alongside traditional business functions and processes, rather than treating it as just a tool.  

Conclusion: Democratizing AI for Business  

Meta’s AI support program demonstrates the growing trend of businesses providing artificial intelligence resources to companies of all sizes. Meta enables small businesses to use enterprise-level technology through its AI integration across marketing communication and operational systems.  

Standard business operations at companies will soon adopt AI-powered workflows, as their adoption has reached a significant level. Companies’ operational procedures will transform through AI, enabling new approaches to business growth, competitive strategies, and customer relationship management.

Source: Meta Newsroom 

The U.S. Food and Drug Administration has approved a new AI-based diagnostic tool for use in clinical settings, demonstrating the increasing integration of AI technologies into front-line healthcare clinical decision-making. The authorization indicates an increase in regulatory acceptance of machine learning technologies for medical workflows, especially when they can enable rapid analysis of complex clinical information, improving the speed and accuracy of diagnosis.  

The approved system will help healthcare providers identify and assess medical problems by analyzing patient information (clinical data) and other inputs, such as imaging and clinical indicators. Although not designed to replace physicians, it will be used as an aid to help providers make better decisions by improving diagnostic consistency and reducing the risk of human error in an emergency environment.  

AI Moves Into Clinical Decision Support  

The FDA’s approval represents an important change in the use of AI in healthcare. Rather than being applied solely to administrative and/or research tasks, AI is now being used directly in a clinical setting to support real-time clinical decision-making.  

AI systems can quickly process large amounts of data (e.g., patient records) and identify opportunities for improvement that a human clinician may not be able to identify within the time it would take them to analyze the same amount of data. Some examples of what AI will be able to provide to the healthcare system include detecting extremely subtle variations in medical images, predicting disease progression rates, and correlating one type of health-related data with other types across multiple patients.  

Incorporating AI into the diagnostic process will allow the FDA to provide faster, potentially more accurate clinical evaluations, especially in situations where healthcare practitioners are under significant stress (e.g., working in an emergency room).  

Enhancing Diagnostic Accuracy and Speed  

AI will revolutionize diagnostics in healthcare. A major advantage of this technology is its capability to rapidly analyze large amounts of complex information, contributing to better patient outcomes when rapid decision-making is essential, for instance, in an emergency room or an intensive care unit.  

With the help of AI tools, physicians can receive immediate analyses of whether a patient has an abnormality from imaging tests, lab results, and patient histories, thereby decreasing the time it takes them to make decisions before they receive a lengthy manual review performed by someone other than the physician.  

Finally, FDA-approved AI systems do not replace the physician’s judgment but rather serve as a supportive layer, increasing the physician’s confidence in diagnostic decisions.  

Integration into Hospital Workflows  

Healthcare providers and hospitals are increasingly using artificial intelligence systems to enhance the digital systems already in place in their medical environments, including digital imaging platforms, electronic health records, and diagnostic equipment.  

It is anticipated that the new authorized system will integrate with current processes/techniques. Therefore, clinicians can access AI-generated recommendations during patient evaluations. Integrating these systems seamlessly will be vital to getting AI tools accepted, as they will not disrupt the way healthcare is delivered today.  

FDA regulatory approval provides confidence that the systems will meet safety and effectiveness expectations for use in real clinical practice.  

Applications Across Medical Fields  

AI diagnostic systems can assist with many different types of medical diagnoses (i.e., radiology, cardiology, oncology/pathology). For instance, in radiology, AI can detect abnormalities (X-ray, MRI, and CT scan) with a high degree of accuracy.    

Cardiology AI models can interpret electrocardiograms (ECGs) and predict the likelihood that a patient will develop a heart problem (before symptoms appear). Oncology machine learning systems enable users to identify and characterize tumors and generate potential treatments using data from past patients.  

The versatility of these systems means they provide valuable assistance across almost all diagnostic specialties, especially in high-volume healthcare environments.  

Reducing Pressure on Healthcare Systems  

Due to increasing population, growth, and aging, there are significant demands on the healthcare systems in the U.S. because of the increased number of people suffering from chronic diseases. One way to relieve this pressure is to use AI tools for routine diagnostics and clinical decision support.  

With less time needed for the initial diagnostic process, hospitals can increase throughput and allocate staff resources more effectively. This is especially valuable in rural or underserved areas where access to specialist caregivers is limited.  

The FDA has approved AI technology in response to systemic pressures and AI’s potential to address them.  

Ensuring Safety and Regulatory Oversight  

AI is advantageous for healthcare, but it still needs thorough regulation to be safe and reliable for patients. Before granting approval, regulatory agencies such as the FDA evaluate new medical diagnostic devices using three methods: assessing clinical validation, comparing them to accepted standards for similar devices, and evaluating the risks associated with their proposed use.  

Another aspect of ensuring AI system safety is monitoring it after approval. An AI diagnostic system can change over time due to AI system evolution or new training data. Regular monitoring will ensure consistent performance and enable early detection of any problems caused by bias or data errors.  

The FDA has stressed the importance of transparency with new AI-based devices used in healthcare and of being held accountable for their use.  

Addressing Concerns About AI in Medicine  

Health care professionals should take an active role in decision-making and interpreting the AI system’s output to achieve accurate, effective outcomes.  

There are various concerns associated with AI, including the privacy of personal data, the potential for algorithms to be biased, and the lack of an understanding of how AI arrived at its decisions. All health care professionals and service providers must ensure they provide fair and equitable treatment to all patients, regardless of ethnicity, gender, or other criteria.  

Innovating in AI systems while maintaining ethical standards will be a major challenge for health care service providers.  

The Role of AI in Preventive Healthcare  

Along with diagnostic purposes, preventive health solutions are leveraging artificial intelligence as part of their systems that use patient data over extended periods to identify risk indicators and accurately predict medical problems before they reach crisis levels. This growing trend toward precautionary healthcare will enable medical services to implement preventive measures earlier, reducing the likelihood of extended hospitalizations and enhancing overall health after discharge through improved patient outcomes. The new software approval will support a broader set of predictive healthcare trends by improving early detection.  

Future of AI in Clinical Environments  

AI is evolving rapidly, and its application in healthcare will continue to grow. Future solutions may also leverage multimodal data (combining images, genomics, and real-time assessments) to support more informed clinical decision-making.  

Through the development of wearable technologies and remote patient monitoring systems, we may also be able to continuously assess patients beyond the walls of a clinical setting.  

The FDA will likely remain a primary player in facilitating the introduction of these technologies into the healthcare system.  

Conclusion: A New Era of AI-Assisted Medicine  

The FDA’s approval of A.I.-based diagnostic tools is a major step forward in the development of medical technology. The introduction of A.I. into clinical decision-making environments has given health care providers new and powerful tools to increase the accuracy and speed of their care delivery processes. Although there are still challenges to providing appropriate oversight and following ethical guidelines in the use of A.I., the integration of A.I. into front-line health care significantly changes how health care is delivered and practiced by physicians.  

As A.I. use becomes more prevalent in different areas of health care, it will likely be an important component of contemporary clinical care. This will improve the quality of medical care by providing physicians with better capabilities and ultimately improving patient health outcomes on a global basis.

Source: FDA Gov 

With its recent announcement about drone delivery, Amazon is looking to offer a faster way to fulfill prescriptions for customers who use its Amazon Pharmacy service through the healthcare logistics network it currently operates. This move is part of a larger initiative to integrate autonomous delivery systems into essential services such as healthcare, where speed, reliability, and accessibility all play an important role in determining how well patients receive care.  

Using drone-based logistics, Amazon anticipates providing quicker delivery options for patients who need medications but are unable to use traditional courier networks because the networks either do not operate in their area or are very slow. The new program represents a major convergence of healthcare infrastructure and advanced automation technologies, in which last-mile delivery is being transformed by autonomous aerial delivery systems and AI-powered coordination.  

Transforming Prescription Fulfillment  

Traditionally, prescriptions are delivered via ground-based logistics, but factors such as traffic, distance, and gaps in regional infrastructure can lead to delays. Amazon is working to simplify the prescription delivery process by using drones to deliver medication directly to patients without using conventional roads. This is particularly helpful for patients who require time-sensitive medications; delays in delivery can disrupt treatment continuity and/or negatively affect patient health. 

Furthermore, leveraging drone technology in pharmacy logistics can help improve access to healthcare by enabling patients in underserved areas to obtain essential medications more easily, with fewer delays, and by reducing the travel burden on these patients.  

The Role of Amazon Pharmacy in Automation  

The Amazon Pharmacy forms the backbone of Amazon’s healthcare delivery vision. When you bring together digital prescription fulfillment (such as online prescription ordering) and automated logistics processes (‘warehouse to pharmacy’), you create a truly seamless end-to-end system for ordering and fulfilling medications.  

The introduction of drone delivery provides that layer of rapid medication fulfillment, eliminating the need for traditional shipping timelines. With drone delivery, once a medication has been dispensed from a prescription and packaged, an autonomous drone can deliver it to its final destination within your delivery window. This introduces a significant decrease in the overall timeline for how fast you will receive your medication as a patient. These integrations create a larger strategy to define a vertically integrated healthcare logistics supply chain (software, pharmacy operations, and delivery) that all use autonomy in their delivery processes.  

Why Speed Matters in Healthcare Logistics  

Delivery speed is an important metric for measuring customer satisfaction in the healthcare industry. As a key factor in patient care, medicine can be disrupted when medication is delayed. It is especially true for patients who have chronic conditions like diabetes, hypertension, or chronic lung diseases.  

The potential benefits of implementing a drone delivery system, as well as how Amazon will position its healthcare service to meet real-world medical needs, will greatly help alleviate these issues by enabling faster delivery. In addition to making the delivery system more predictable and faster, improving delivery speed can reduce strain on local pharmacies and courier services and their respective supply chains, preventing bottlenecks during peak demand and emergencies.  

Expanding Drone Infrastructure for Medical Use  

Amazon is building infrastructure specifically for healthcare-based drone delivery, including not only fulfillment centers but also launch sites and secure landing or delivery locations. The entire set of systems is intended to ensure the safe handling of packages and to maintain strict operational standards for package delivery in the medical industry. The routes the drones will take have been optimized using AI-based logistics systems that factor in weather, airspace regulations, and delivery priorities, ensuring that all prescriptions are delivered efficiently without compromising safety.  

These infrastructure expansions signify Amazon’s substantial investment in developing a new automated logistics process to deliver healthcare goods to consumers with high accuracy and reliability. 

Regulatory and Safety Considerations  

There is a strict regulatory framework governing the use of drones for the delivery of medical products. This is due to the need to ensure the secure and consistent handling of the medical products being delivered. As a result, aviation regulators require detailed safety procedures for drone pilots and for drones to operate safely.   

In addition to the requirements above, the healthcare drone logistics process also requires Amazon to ensure that the integrity of the pharmaceuticals being delivered is maintained during delivery (temperature control, secure packaging), which makes this type of logistics more complicated than standard e-commerce delivery; however, they also provide an opportunity to innovate in a regulated environment.  

Expanding Access to Underserved Areas  

Drone delivery has a unique ability to deliver packages to otherwise inaccessible locations, such as rural communities, suburban areas, and areas with few pharmacies. Faster, more direct delivery systems can significantly benefit these communities and help reduce the geographic inequities of access to healthcare services.  

Healthcare systems are modernizing by improving delivery and expanding access across many areas. The use of drones to access remote locations by going over land will help to improve access to healthcare services.  

Amazon is one of many technology companies providing solutions to the systemic challenges of delivering healthcare services to rural and remote areas.  

Integration with AI-Driven Logistics Systems  

The delivery of products by drones will occur as part of an overall logistics network that uses many types of AI. All logistics systems use machine learning models to optimize delivery route planning and predict future medicine order volume and demand. Furthermore, Amazon will use this technology to facilitate real-time coordination of its drone fleets for delivery.  

The use of AI and autonomous capabilities in logistics helps facilitate dynamic changes to order delivery timelines based on current conditions such as prescription volume, weather, and urgency. This same technology enables better coordination among drone fleets, resulting in reducing downtime and enhancing overall operations.  

The use of AI, combined with autonomous capabilities, enables an overall transition to a fully digitized logistics ecosystem in healthcare.  

Competitive Landscape in Healthcare Delivery  

Amazon is venturing into a market that is expanding, where technology firms, pharmacy operations, and logistics companies are researching quicker, more automated ways to deliver healthcare. As demand for same-day or nearly instant prescription fulfillment increases, competition will grow. If Amazon can successfully combine its pharmacy services with drone delivery systems, it will have the opportunity to scale operations across multiple areas. The ability to scale will depend on obtaining regulatory approvals, ensuring infrastructure readiness, and securing patient acceptance.  

Future of Medical Drone Delivery  

The expanding capabilities of drones in healthcare logistics may extend their role beyond delivering prescriptions to include transporting medical supplies, diagnostic samples, and materials needed for emergency response. This will likely improve response times for healthcare providers, especially when the need is urgent.  

Future systems may also enable predictive healthcare logistics, where artificial intelligence can anticipate patient needs and proactively position medications for faster fulfillment. The recent expansion of Amazon is an early implementation of this future model of more responsive, timely healthcare delivery.  

Conclusion: Redefining Healthcare Logistics  

Amazon Pharmacy’s drone delivery is a landmark change in how pharmaceuticals are delivered through the supply chain and logistics. Combining A.I.-based optimization with autonomous systems and pharmaceutical distribution to your home has changed the perception of how fast prescriptions should be delivered.  

As these systems grow in scale, we could see a completely different way for patients to access prescriptions that meets the standard of nearly instant filling, rather than just a rare case at a few locations.

Source: CEO Andy Jassy shares 3 ways Amazon is innovating to make customers’ lives easier and better 

Tesla has released an expanded update to its autonomous vehicle platform, now available to all U.S. markets, representing the latest advancement toward its objective of achieving complete AI-based mobility. This new software update adds new function/capacity enhancements to the Full Self-Driving (FSD) software function for further making changes to how cars will use AI techniques to interpret what is happening on the road, as well as how the cars will use those AI techniques throughout very complex traffic situations, while reducing the reliance on human drivers in making real-time decisions about driving/traffic.  

With this latest software update, Tesla continues to work diligently to scale its AI-derived traffic management system whenever it gets the opportunity. Real-world driving data from its fleet of vehicles across the country will be used to continuously adjust performance and improve system reliability as autonomous vehicle systems/technologies become more advanced over time, thus demonstrating an increasing transition to vehicles operated through machine intelligence.  

Advancing Real-World Autonomy  

Tesla’s self-driving system uses a neural network architecture and is trained on real-world performance data from Tesla’s global fleet. The software update has improved how cars respond to dynamic road environments, including lane additions and removals, intersection layouts, pedestrian movement, and other unpredictable driver behaviors.  

The system learns by adapting to the dynamic changes in real-world environments, enabling it to achieve capabilities that standard rule-based systems fail to deliver in controlled testing scenarios. The system enables Tesla to expand its automation capabilities beyond current technological boundaries. 

While the goal of the software update is to reduce the need for drivers to take control of their vehicles, drivers are still required to maintain vehicle supervision under current laws and regulations.  

Improvements in Decision-Making AI  

The main purpose of the recent update was to enable more accurate, reliable decision-making for real-time driving. The system now more accurately assesses multiple alternative options for each action regarding safety, efficiency, and traffic conditions before actually executing the action.  

One area where the AI model improves is predicting other drivers in the surrounding area, recognizing road signs and signals, and increasingly handling rare occurrences such as construction zones or double-lane roads. Other benefits of these improvements include making driving with autonomous vehicles much less stressful and providing a smoother/unpredictable driving experience when completing day-to-day tasks.  

Tesla is still working with its data feedback loop system to continuously improve its AI models using fleet-based data that is fed back into the model to retrain and optimize the performance of the automation system.  

Expanding Coverage Across US Roads  

The recent rollout of the enhanced Full Self-Driving (FSD) system within America has added additional coverage and usability compared to the previous release. Both the FSD system’s expanded capabilities compared with earlier versions and the number of drivers now able to access more advanced autonomous features will allow Tesla to gather data across many different types of real-world roads and conditions.  

The United States now provides drivers with access to multiple driving environments, including urban areas with complex traffic patterns, suburban areas, rural areas, and highway systems with different types of roads and structures. The company will enhance its advanced driver-assist systems through testing Tesla’s latest FSD version across diverse geographic locations and multiple users. 

Broader deployment enables Tesla to iterate its development process more quickly, allowing it to update the underlying AI models that process data collected across various environments.  

Safety Systems and Human Oversight  

While Tesla’s autonomous driving technology is more advanced than before, it requires the driver to actively supervise the vehicle’s operation. There are safety features integrated into the vehicle’s software that ensure the driver is paying attention and ready to take over the vehicle’s operation at any time.  

These features include warning systems, monitoring systems, and other fail-safe devices designed to reduce the risk of operating a vehicle in unexpected or unpredictable circumstances. These features are vital as regulatory agencies evaluate the overall safety of autonomous vehicles. Tesla has stated that the development of its autonomous driving system will progress gradually rather than instantaneously toward full autonomy, with safety design as the top priority.  

Data-Driven Development Model  

The data-driven development approach Tesla has implemented is a significant component of its autonomous driving advancement. All vehicles in Tesla’s fleet provide anonymous driving data to train and enhance AI systems.  

This giant feedback loop is one way that the company can identify edge cases, which are often rare, and enhance overall system performance through data collected over millions of miles of driving. The total number of vehicles on the road means the complete dataset used to train AI systems is extensive, which, in turn, helps speed up the development of the autonomous driving stack.  

This methodology has now become one of the core elements of the company’s AI strategy and sets it apart from other companies that rely principally on simulations or limited datasets to produce their AI technologies.  

Competitive Landscape in Autonomous Driving  

Tesla’s full self-driving (FSD) software is expanding as competition for autonomous vehicles intensifies. Many companies, including traditional automakers and tech companies, are investing in AI-driven mobility solutions, such as ride-hailing platforms. While this trend toward autonomous vehicle technologies is accelerating, Tesla has a clear advantage over most other manufacturers because of its combined hardware/software strategy and access to large amounts of driving data; therefore, it can iterate quickly and implement new features at an accelerated pace.  

Additionally, because Tesla can remotely update its cars via over-the-air (OTA) updates (instead of requiring rework/modification), it has an enormous opportunity to enhance its fleet of vehicles over time (all while making no physical changes to those vehicles).  

Tesla will continue to be an innovator and leader in the transition to AI-native transportation systems.  

Regulatory and Ethical Considerations  

Regulatory authorities have maintained their investigations into self-driving vehicle technology because safety standards and liability frameworks are still being established through ongoing work. The increasing use of AI-powered self-driving technology creates new challenges in determining how to assign accountability for its partially automated functions. 

In addition to the regulatory issues mentioned above, ethical issues include transparency about system capabilities and limitations, awareness of the potential risks of over-dependence on automated vehicle systems, and the limitations of the system’s information. Regulatory authorities will be required to continue examining how these types of systems are used on public roads once they are fully deployed.  

Future of AI-Powered Mobility  

It shows that the trend for integrating artificial intelligence with transportation systems is growing. This means that the use of self-driving vehicles as intelligent software agents will only continue to increase.  

The future of autonomous systems at Tesla will hopefully continue to reduce human intervention, enabling fully autonomous driving in specific environments.  

As AI models grow, mobility will become increasingly safer, more efficient, and better able to adapt to real-world situations.  

Conclusion: A Step Toward Full Autonomy  

Tesla’s recent release of an expanded update for its FSD capability is a major step in the evolution of AI-enabled mobility. By enhancing real-time decision-making and increasing the use of FSD vehicles in America, the company is accelerating the transition towards intelligent transportation systems.  

Although full autonomy has not been realized, ongoing improvements to AI systems are moving the automotive industry towards achieving a state where vehicles can function with little or no human intervention, therefore changing how people use transportation.

Source: Standardizing Automotive Connectivity 

Imagine cutting research compliance time from over a year to just weeks. Traditional local systems are slow, leading to missed funding deadlines, while compliant institutions secure grants more quickly.  

Amazon Web Services (AWS) created the Secure Research Environment (SRE) to help institutions stay flexible and competitive as security and compliance standards change. This ready-to-use cloud setup provides a solid security foundation and standard designs that accelerate your compliance process. When funding is tight, the SRE enables organizations to build compliance-ready systems, allowing researchers to focus on their work and institutions to better compete for grants.  

With years of experience in cloud security, compliance audits, and risk management, this post explains how secure research spaces (SREs) use security controls and design patterns to help meet various compliance standards. It shows how automation and standard designs make it easier to access regulated research settings, but also notes that final compliance depends on how your organization sets up and manages the system.  

When Compliance Becomes A Barrier To Discovery. 

At the moment, your researchers are dealing with a tough situation. Compliance standards are changing quickly, and grant funding is harder to find.  

The NIH now requires NIST SP 800-171 for controlled access. Biomedical data repositories handling controlled unclassified information (CUI) require CMMC 2.0, or your institution will lose access to federal research grants. Other US agencies are moving to similar requirements. Internationally, organizations must comply with the GDPR and ISO 27001 standards to protect sensitive data. Canada and the UK enforce their own data privacy regulations.  

As compliance requirements grow, so do the costs of keeping up. These problems can affect your whole institution. If you can’t secure funding from limited resources, you can’t grow your research programs. For universities, this might affect their R1 status and future growth. For national labs, research hospitals, and defense contractors, it could mean losing out on important grants and making it harder to attract top talent. Not meeting compliance standards can also bring regulatory and financial risks. False claims can lead to large fines, and if controlled unclassified information (CUI) is leaked, there may be extra penalties.  

Address Multiple Compliance Frameworks With A Single Pre-Configured Solution 

The SRE on AWS helps your institution address these problems by providing a strong, secure foundation for working with sensitive and protected data. In the US, this covers standards like NIST SP 800-172, CMMC, HIPAA, FISMA, and others. Internationally, the SRE supports GDPR, PIPEDA, ISO 27001, and more. The SRE establishes a central environment that empowers your research, IT, and support teams to help researchers across several fields while maintaining compliance with funding rules. AWS delivers this through a ready-made multi-account setup that addresses key compliance needs.ds.  

Your research organization can set up this solution in less than 3 months, and sometimes in just 1 week. For single frameworks, it costs much less than traditional local systems, which often require significant investments and can leave researchers waiting or resorting to workarounds that may not meet compliance standards.  

Under the AWS shared responsibility model, AWS is responsible for the technical foundation, infrastructure, security, automated controls, and preventive safeguards. Your institution manages its own data, policies, and documentation with help from AWS guides and training materials for IT teams. For example, researchers using sensitive health data can rely on the SRE’s automated HIPAA configuration to meet compliance without manual policy setup. Another example: when applying for a new grant, a researcher’s workspace is automatically created in the correct compliance group, eliminating the need for lengthy paperwork. This central approach makes compliance management easier and reduces last-minute requests from researchers.  

How the SRE Architecture Automates Compliance 

The SRA uses the Landing Zone Accelerator on AWS (LZA) to automate the setup of a secure, resilient, and scalable cloud foundation. Depending on what your organization needs, you can deploy the SRA on AWS GovCloud (US), on commercial AWS, or both.  

Figure 1 shows the setup, which includes AWS Organizations with a multi-account structure, centralized identity and access management (IAM), logging and monitoring, a segmented network with traffic checks, and centralized DNS management. The SRI creates separate compliance groups called organizational units for different roles. When a researcher gets a grant, they work with IT to see which standards apply. IT then assigns them to the appropriate group, such as HIPAA for health research or CMMC for defense projects. Researchers with multiple grants can access multiple groups at once, and each project automatically receives the appropriate controls.  

When your researchers start services in their assigned group, they automatically get the right security and compliance controls. For instance, a biomedical researcher logging in will immediately work within an environment configured to meet the necessary CUI or HIPAA protocols, requiring no additional setup on the researcher’s part. This lets them meet standards and do their research securely without extra setup.  

Scale and Adapt as Your Compliance Needs Evolve. 

As your institution’s needs change, your IT team can quickly add new compliance groups or expand existing ones without rebuilding everything. When rules change, you simply update your SRE settings instead of starting over. This protects your investment and keeps you eligible for grants as your research grows. To address protection requirements that go beyond standard compliance frameworks, your team can extend the SRE with a trusted research environment (TRE) on AWS. This adds an additional security layer at the data level for fine-grained control over data ingress and egress.  

Give Your Researchers A Perfect Compliance Experience 

While the SRE manages compliance at the infrastructure level, your researchers experience a much simpler process. For them, compliance runs in the background. They do not need to know HIPAA rules or configure security. Researchers just log in to a secure research portal that displays only what they need for their grant. This lets them focus on their work while the system handles compliance automatically. The portal also serves as the main entry point for researchers and their partners, enabling easier collaboration while maintaining strict compliance. 

This straightforward approach provides your researchers with what they need and helps your institution avoid common issues such as shadow IT, unauthorized server purchases, and last-minute compliance resource setups.  

Extending Secure Research Globally 

Research institutions worldwide face the same challenge: meeting strict compliance rules without slowing down discovery. The AWS SRE uses a flexible multi-account setup that enables you to comply with any country’s rules, whether you follow a single national standard or several international ones. The SRE delivers a steady, scalable foundation that supports your research wherever you operate.  

Get Started With Alignment And Deployment 

To implement the SRE successfully, your organization needs to be aligned from the start. Your CIO, vice president of research, and CISO should work together early to support your researchers’ compliance needs. Bringing these leaders alongside a shared goal before you begin will help ensure success. Once you lay the foundation, each SRE setup proceeds along two main work streams that run in parallel. By building the infrastructure and preparing compliance documents together, you avoid the long wait between technical completion and audit readiness. The two work streams are:re:  

  1. Technical build-deploy infrastructure, including AWS organizations, organizational work, network architecture, security controls, and automation using the LZA  
  1. Compliance and audit readiness-AWS Security Assurance Services prepares you for certification by providing documentation, control mapping, and evidence collection.  

AWS offers three flexible pathways for deployment:  

  1. AWS Partners and Security Assurance Services: Partners handle deployment, while assurance services prep you for certifications. Ideal for expert-supported implementation. Partners can maintain your environment or teach your team. Start by exploring the AWS Partner Network.  
  1. Guided build and security assurance services – your team builds the SRE with guidance from AWS solutions architects, while security assurance services handle compliance. Best for bodies seeking to develop internal expertise and gain deep knowledge for independent management and scaling. To get started, review the LZA implementation guide and connect with your AWS account team.  
  1. AWS Professional Services and Security Assurance Services – AWS Professional Services builds your environment, and Security Assurance Services handles compliance. Best for bodies seeking AWS engagement with full service implementation. To get started, contact AWS Professional Services to scope your engagement.  

Is Your Institution Ready to Gain an Edge in Competing for Grants? 

Choose the SRA option that best fits your needs to streamline compliance and stay grant-competitive.  

You can also contact AWS directly to learn more about setting up your SRE.  

SourceAccelerate your organization’s compliance journey with a Secure Research Environment on AWS 

As NASA takes the next necessary steps towards the launch of the Artemis II mission, it is laying the groundwork for recovery operations after its return, a critical element in the US’s preparation for its return to human-led lunar missions.  

In the final preparations for recovery plans for the Artemis II mission, which will carry a crew of astronauts around the Moon for the first time in over 50 years, NASA is now completing preparations for its recovery teams, defining naval operations coordination, and developing final safety systems for recovery procedures after splashdown.  

NASA has made significant strides towards establishing a permanent human presence on and near the Moon as part of its larger Artemis program by creating Artemis II; however, this emphasizes that we must be prepared for the overall recovery of the astronauts from the current mission, which illustrates how precise and complicated conducting human spaceflight missions to date has been. The three events, the launch of the satellite, the return of the astronauts, and the recovery of the spacecraft, must be executed successfully to facilitate a safe return for the astronauts to Earth. 

Preparing for Crew Recovery at Sea  

Splashdown operations in the Pacific Ocean provide an opportunity for recovery teams to recover the Orion spacecraft and astronauts after the Artemis II mission. This phase of the mission is one of the most critical, as it requires planning and executing operations that coordinate naval assets, medical teams, and engineering specialists to safely extract astronauts from the capsule and transport them for post-mission evaluation.  

Recovery operations are set up to provide a timely response to retrieve the capsule after it reenters and lands in ocean waters. Specialized ships, helicopters, and recovery personnel will be pre-positioned and ready to recover, stabilize, and assist astronauts as they leave the spacecraft.  

NASA has stated that the recovery procedures are based on extensive experience gained through a series of simulations and lessons learned from prior missions, especially those of the Apollo program and prior Artemis missions, to refine modern procedures for spacecraft recovery post-splashdown.  

Lessons from Artemis I and Apollo Missions  

NASA has been developing the recovery plan for Artemis II for a long time, drawing on lessons from previous human spaceflight missions. Apollo laid the foundation for ocean recovery operations, and Artemis I was a modern example of retrieving the Orion without an astronaut on board.  

In Artemis I, NASA tested how the heat shield would perform, how it would work during re-entry, and how it would land in water to develop improved recovery planning processes for crewed missions. NASA has incorporated this knowledge into the recovery plan for Artemis II to ensure that astronauts transitioning from space to Earth have a smooth, safe journey.  

By leveraging historical knowledge from Apollo missions and the latest technologies, NASA will be able to reduce risk while ensuring the most efficient recovery of astronauts during the mission’s most critical phase.  

The Role of the Orion Spacecraft  

The Artemis II spacecraft and the missions designed to take humans to explore the universe are being developed using the Orion spacecraft, which was purpose-built to enable people to venture into the depths of space beyond our planet. The Orion spacecraft has life support systems, navigation aids, and measures to protect against heat and stress when it returns to Earth after being launched from a launch pad for many years, thereby providing astronauts with an opportunity to travel beyond Earth into space.  

The Orion spacecraft encounters intense thermal conditions and structural strain during re-entry, traveling at high speed through different atmospheric layers before parachute deployment, which leads to a safe descent to Earth for an Atlantic Ocean landing. After the capsule lands, recovery personnel will have specific instructions on how to be ready to respond to the splashdown and to keep the capsule from rolling onto its side or rocking to prevent injury to the astronauts during extraction.  

The Orion spacecraft is essential to enabling NASA’s long-term mission to establish a permanent presence on the Moon and pave the way for future manned space expeditions to Mars.  

Coordination with Naval and Recovery Teams  

NASA Recovery Operations for Artemis II require extensive coordination between NASA and the U.S. Navy. The U.S. Navy provides the primary recovery vessels and the personnel to perform splashdown recovery operations. The recovery team is responsible for locating the capsule, securing the landing site, and performing astronaut recovery procedures.  

Training has been conducted under various ocean conditions to simulate actual operations, including rough seas, delayed communication, and emergency and contingency operations. The training is critical to ensuring that recovery personnel are prepared to operate effectively in all potential conditions.  

The integration of both military and civilian resources reflects the complexity of current space operations and the need for highly coordinated operations support.  

Ensuring Astronaut Safety Post-Splashdown  

Once the Orion capsule has been recovered, astronauts will undergo an initial health evaluation immediately after returning from microgravity. The purpose of the initial health evaluations is to determine the astronaut’s health status after exposure to multiple accelerations from microgravity, high-speed reentry, and ocean landing. Medical personnel on recovery vessels will be prepared and capable of providing immediate medical assistance as required.  

The transition from the spacecraft to the recovery ship will occur in a controlled, expeditious manner to reduce the risk of the crew encountering environmental hazards. This phase of the recovery process is critical for providing both physical safety and psychological comfort to the astronaut after prolonged exposure to microgravity.  

NASA has placed a high priority on these recovery procedures as a demonstration of its firm commitment to the health, safety, and success of the astronauts and their mission.  

Advancing Human Space Exploration  

Artemis II is a crucial component of NASA’s plan to send people back to the Moon and eventually to Mars on a long-term basis. In contrast to Artemis I, which used robotic crew members to conduct system tests, Artemis II will use trained astronauts who will fly around the Moon. As a result, recovery operations for Artemis II will be much more complicated and time-sensitive than those of Artemis I.  

The successful completion of this mission will help to demonstrate the function of critical systems for future exploratory trips into deep space, such as navigation, life support systems, and re-entry procedures. The successful completion of this mission will also mark the first time that humans have returned to deep space to explore beyond Earth’s gravity.  

Challenges of Deep Space Mission Recovery  

Recovery operations are major challenges for space missions, even when space agencies prepare extensively. This is due to a variety of ever-changing factors, including weather, ocean currents, and communications delays.  

NASA is continually refining its contingency planning process to account for these variables and equip recovery teams with the tools they need to adapt to rapidly changing circumstances. In addition, all stages of the recovery operation contain built-in redundancy systems and backup procedures.  

Broader Implications for Space Infrastructure  

In addition to exploring the moon, the Artemis Program will help build infrastructure that enables long-term human habitation in deep space. Recovery operations will be a necessary component of this ecosystem and will enhance the safety, repeatability, and scalability of all rocket and spacecraft missions.  

As NASA’s ambitions for lunar flight grow, the need for efficient recovery systems will increase to support more frequent crewed missions and continued commercial partnerships.  

Conclusion: A Step Closer to Lunar Return  

By showing how complex and exacting Artemis II recovery operations will be, it has demonstrated the advanced quality of astronauts’ human space flight activities today. Now that NASA is preparing to launch its first manned lunar fly-by in almost 50 years, it is focusing on planning every detail of the mission from launch to splashdown.  

The success of these activities will mark an important milestone in mankind’s effort to probe the universe. This sets the foundation for further missions by providing humanity with the tools needed to reach deeper into outer space.

Source: NASA News Release 

This advisory is a joint effort by the FBI, CISA, EPA, and NSA. It emphasizes ongoing cyber risks from known and unknown sources targeting the IT and OT networks, systems, and devices of US water and wastewater systems (WWS) facilities. These threats, which include attempts to gain unauthorized access, put at risk the ability of WWS facilities to provide clean water and manage wastewater for their communities. Note: cyberattacks are rising across all critical infrastructure sectors. However, this advisory does not suggest that the WWS sector is being targeted more than others.  

To help protect WWS facilities, including Department of Defense water treatment sites in the US and overseas, CISA, FBI, EPA, and NSA strongly encourage organizations to follow the steps in the recommended mitigations section below.  

Technical Details 

Threat Overview 

Tactics, Techniques, And Procedures 

WWS facilities may be exposed to common attacker tactics, techniques, and procedures (TTPs). These are the methods attackers use to break into and control information technology (IT) and operational technology (OT) networks, systems, and devices. IT refers to computers and communications used for data processing, while OT refers to industrial equipment and systems that control physical processes, such as those that treat water or manage wastewater.  

  • Spear phishing, the practice of sending targeted emails to trick recipients into installing malicious software such as ransomware by clicking links or attachments, is a common tactic used by attackers [T1566].  

Spear phishing is one of the most common ways attackers first gain access to IT networks. Employees who are not fully aware of cyber risks can be a weak point. They might open harmful attachments or links in emails that have slipped past security filters. This action can allow attackers to run malicious software.  

When organizations connect to IT and OT systems, attackers can sometimes reach OT assets after breaking into the IT system through spear-phishing or other methods, whether intentionally or by accident.  

Attackers can exploit internet-connected services and applications that allow remote access to WWS (water and wastewater systems) networks [T1210].  

For example, attackers can exploit a remote desktop protocol (RDP) connection that is not securely connected to the internet to spread ransomware across a network. If RDP is used for process control equipment, this could likewise disrupt WWS operations.  

Note: the rise in remote work during the COVID-19 pandemic has likely made weaknesses in remote access more common.  

  • Exploitation of unsupported or outdated operating systems and software  

Attackers frequently target organizations that lack the resources or do not prioritize updating their IT and OT systems. WWS facilities usually spend more on replacing or repairing physical infrastructure, such as pipes, rather than modernizing IT or OT systems.  

Many WWS facilities are municipal systems with varying resources. Not all can maintain high cybersecurity standards. This can lead to the use of unsupported or outdated operating systems and software.  

  • Exploitation of control system devices with vulnerable firmware versions  

WWS commonly uses outdated control system devices or firmware, exposing WWS networks to publicly accessible, remotely exploitable vulnerabilities. Successful compromise of these devices may lead to loss of system control, denial-of-service attacks (preventing system access), or loss of sensitive data [T0827].  

WWS Sector Cyber Intrusions 

Cyber intrusions targeting US WWS facilities underscore vulnerabilities associated with the following threats:  

  • Insider threats from current or former employees who maintain improperly active credentials  
  • Ransomware attacks  

WWS cyber intrusions from 2019 to 2021 include:  

  • In August 2021, malicious cyber actors used the Ghost variant ransomware against a California-based WWS facility. The ransomware variant had been in the system for about a month and was discovered when three Supervisory Control and Data Acquisition (SCADA) servers displayed a ransomware message.  
  • In July 2021, cyber actors used remote access to install the ZuCaNo ransomware on an underwater SCADA computer at a Maine-based WWS facility. The treatment system was run manually until the SCADA computer was restored using local control and more frequent operator rounds.  
  • In March 2020, cyber attackers used a known ransomware variant against a Nevada-based water and wastewater systems (WWS) facility. The ransomware affected the victim’s supervisory control and data acquisition (SCADA) system and backup systems. SCADA refers to computer systems that gather and analyze real-time data within industrial control systems. The SCADA system provides visibility and monitoring, but is not a full industrial control system (ICS). An ICS is a broader system that automatically manages industrial processes.  
  • In September 2020, personnel at a New Jersey-based WWS facility discovered that potential Makop ransomware had compromised files within their system.  
  • In March 2019, a former employee at the Kansas-based WWS facility unsuccessfully attempted to threaten drinking water safety by using his user credentials, which had not been revoked at the time of his resignation, to remotely access a facility computer.  

Mitigations 

The FBI, CISA, EPA, and NSA recommend that WWS facilities, including DoD treatment sites in the US and abroad, use a risk-based approach to determine technical and non-technical steps to prevent, detect, and respond to cyber incidents.  

WWS Monitoring 

Staff who monitor WWS systems should watch for these signs of suspicious activity, which could point to a cyber threat:  

  • Inability of water and wastewater systems facility personnel to access SCADA system controls at any time, either entirely or in part;  
  • Unfamiliar data windows or system alerts appearing on SCADA system controls and facility data screens that could indicate a ransomware attack;  
  • Detection by SCADA system controls or water treatment staff of unusual operating parameters like chemical addition rates that are much higher than normal, used in treating drinking water;  
  • Access to SCADA systems by unauthorized individuals or groups. For example, former employees and current employees who are not authorized or assigned to operate SCADA systems and controls.  
  • Access to SCADA systems at unusual times, which may indicate that a legitimate user’s credentials have been compromised  
  • Unexplained SCADA system restarts  
  • Unchanging parameter values that normally fluctuate  

Remote Access Mitigations 

Note: because remote operations have increased during the COVID-19 pandemic, it’s even more important for asset owners and operators to review the risks of remote access and make sure they are acceptable  

  • Require multi-factor authentication for all remote access to the OT network, including from the IT network and external networks.  
  • Use blocklisting and allowlisting to limit remote access to users with verified business and/or operational needs.  
  • Ensure that all remote access technologies have logging enabled, and regularly audit these logs to identify instances of illicit access.  
  • Use manual start and stop features instead of always-activated unattended access to reduce the time remote access services run.  
  • Audit networks for systems using remote access services  
  • Close unneeded network ports associated with remote access services.  
  • When configuring access control for a host, utilize custom settings to limit the access a remote party can attempt to acquire.  

Network Mitigations 

Implement and ensure secure network segmentation between IT and OT networks to limit malicious cyber actors’ ability to move to the OT network after compromising the IT network. Network segmentation means separating networks into different zones, so a breach in one area does not easily allow access to other areas.  

  • Implement demilitarized zones, firewalls, jump servers, and one-way communication diodes to prevent unregulated communication between DIT and OT networks.  
  • Develop/update network maps to ensure full accounting of all network-connected equipment.  

Remove any equipment from networks that is not required for operations to reduce the attack surface that threat actors can exploit.  

Planning And Operational Mitigations 

Make sure your organization’s emergency response plan covers all cyberattack impacts like losing or changing system views, losing or changing control, and safety risks.  

  • Include third parties who access the OT network, such as plant engineers and vendors.  
  • Review, test, and update the emergency plan annually to keep it current.  

Practice switching to backups, including manual operation if electronic communications fail.  

Give employees a chance to practice decision-making through tabletop exercises that include scenarios where visibility is lost. Use resources like the EPA’s Cybersecurity Incident Action Checklist and the Ransomware Response Checklist on page eleven of the CISA/MS-ISAC Joint Ransomware Guide.  

Safety System Mitigations 

Set up independent cyber-physical safety systems. These prevent physical escalation in dangerous situations if a threat actor compromises control.  

Examples of cyber-physical safety system controls include:  

  • Size of the chemical feed pump  
  • Gearing on valves.  
  • Pressure switches also serve as controls.  

These controls help WWS sector facilities, especially smaller ones with less cybersecurity. Staff can review systems from a worst-case view and find new protections. With these safety systems, operators can act physically to limit damage. For example, they can stop cyber attackers who control a sodium hydroxide pump from raising the pH to dangerous levels.  

Additional Mitigations 

Build a workplace culture ready to address online threats. Check out the CISA Cyber Essentials and Resources section below for more guidance.  

Keep software up to date, including operating systems, applications, and firmware on IT network devices. Use a risk-based approach when choosing OT network devices and areas for the patch management program. You may also use a centralized patch management system.  

Set antivirus and anti-malware programs to scan IT devices regularly with the latest signatures. Use a risk-based inventory to decide how OT devices are checked for malware.  

Backup data regularly on both IT and OT networks. PS: Disconnected from the network to stop ransomware from spreading to them.  

When possible, turn on OT device authentication. Use encrypted OT protocols and encrypt all wireless communications. This keeps process control data private and authentic while it is sent.  

Use user account management to enable or rename any default system accounts wherever possible.  

  • Set up account lockout policies to reduce the risk of brute-force attacks. Create administrator-level accounts. Use strong account management policies and procedures.  
  • Have a user account policy that sets time limits for removing accounts after employees leave. Apply time limits for deactivating accounts after long periods of inactivity.  

Use data execution prevention controls. Apply tools like application allowlisting and software restriction policies to stop programs from running in common ransomware locations, such as temporary folders used by internet browsers.  

Train users with awareness programs and simulations to spot and report phishing and social engineering. Watch for unusual activity and suspend access if needed.

SourceOngoing Cyber Threats to U.S. Water and Wastewater Systems 

Highlights 

  • Qualcomm and Snap have signed a multi-year strategic agreement deepening their 10-year partnership to accelerate innovation in wearable tech.  
  • The agreement will bring Snapdragon XR solutions to future versions of Specs.  
  • The collaboration will give developers and customers a strong foundation to create smarter experiences on eyewear.  

Qualcomm Technologies Inc and Specs Inc, a Snap subsidiary, announced a strategic agreement to use Qualcomm’s Snapdragon system-on-chip in future Specs generations.  

Powering The Next Generation Of Eyewear 

This is Specs Inc’s first major project as it prepares to launch its advanced eyewear, Specs (Snap’s new see-through AR glasses, building on but not the same as Spectacles), blending digital experiences with the real world later this year. Specs are standalone, see-through glasses that enable users to see, hear, and interact with digital content as if it were part of their surroundings.  

Specs use Snapdragon XR platforms. These platforms combine edge AI with high performance and low power consumption, enabling intelligent, context-aware experiences to run directly on the device. This means faster and more private interactions. The initiative embodies both companies’ goals to make computing more human and more smoothly embedded in daily life, changing how people work, learn, and play together.  

Building on a Decade-Long Relationship 

Snap and Qualcomm Technologies have a history of innovation, with Snapdragon platforms powering earlier versions of Snap’s Spectacles (Snap’s previous AR glasses). This new agreement focuses on Specs, their new eyewear product, to further work in immersive technology.  

With coordinated planning and close collaboration, both companies aim to quickly add features to Specs such as on-device AI, advanced graphics, and multi-user digital experiences. We believe the future of computing will be more human and grounded in the real world, said Evan Spiegel, co-founder and CEO, Snap Inc. Our work with Qualcomm Technologies provides a foundation for the specs we deliver, delivering advanced technology and performance for developers and consumers.  

The next era of computing will be defined by devices that understand what you see, hear, and say, as well as context, and respond instantly to the world around you, said Cristiano Amon, president and chief executive officer, Qualcomm Incorporated. Our work on future generations of specs will enable power-efficient interactive AR devices that deliver agentic experiences that feel natural and intuitive, and integrate seamlessly with daily life.  

Qualcomm is committed to enabling intelligent computing everywhere and addressing global challenges. With over 40 years of technology leadership, we deliver solutions powered by AI and strong connectivity. Snapdragon platforms offer great consumer experiences, and our Dragon Wing products help industries grow. Working with partners, we drive digital transformation to improve lives, businesses, and society.  

Qualcomm Incorporated includes our licensing business, QTL, and the vast majority of our patent portfolio. Qualcomm Technologies Inc., a subsidiary of Qualcomm Incorporated, operates, along with its subsidiaries, substantially all of our engineering and research and development functions and substantially all of our product and service businesses, including our QCT semiconductor business. Snapdragon and Qualcomm-branded products are products of Qualcomm Technologies, Inc. and/or its subsidiaries. Qualcomm patents are licensed by Qualcomm Incorporated.  

About Specs Inc 

Specs Inc., a Snap subsidiary, is dedicated to more human computing by creating specs eyewear that blends digital experiences with the real world.  

Specs have see-through lenses for placing digital objects in 3D space and use Snap OS for natural interaction.  

Specs Inc. also offers Lens Studio, a suite for developers to build immersive AR experiences for Specs, Snapchat, and other platforms. 

SourceQualcomm and Snap Expand Strategic Collaboration to Advance Intelligent Computing Experiences on Specs 

What’s Changing? 

Earlier this year, we launched Google Vids, a new AI-powered video creation tool in Google Workspace, which helps teams create more compelling work stories through video.  

Now Google Vids is generally available for select workspace editions. Here’s how you can use it:  

  • Customer service teams are using Vids to provide better customer support, supplementing help center articles and videos.  
  • Leaders are creating videos to share company-wide updates and announcements.  
  • Learning and development teams are using builds to deliver employee training and education at scale.  
  • Marketers are using videos within their organizations to share campaign and event recaps.  
  • Project management teams are building videos to share meeting recaps, business updates, and report share-outs.  

With Vids, you can quickly create videos by using Gemini’s generative AI features to help you get to a first draft faster. The Help Me Create tool can build an editable storyboard from a prompt and a document in your Google Drive. Once you pick a style, Gemini puts together your video draft with suggested scenes, recommended stock media, text scripts for each scene, and even background music.  

You can also start your own video with a range of templates designed for different needs. Then add motion with animations, transitions, and photo effects. You can customize your video using Vids, royalty-free stock content, or your own media from Google Drive or Google Photos.  

With ‘Help me create,’ Gemini suggests scripts to help you get started, or you can write your own. Adding a voiceover is simple: choose from Gemini’s preset AI voices or record your own using a teleprompter with Gemini’s read-along and rolling features. You can also use the Vids recording studio to:  

  • Add a video recording of yourself.  
  • Add a screen recording with narration.  
  • Add a screen recording with a video recording.  
  • Add an audio-only recording.  

Like Docs, Sheets, and Slides, Vids have a simple, easy-to-use interface. You can collaborate in real time and share projects securely, right from your browser.  

In short, Vids helps you create engaging videos that spread your message, build connections, and stand out across your organization.  

Who’s Impacted? 

End users  

Why You’d Use It 

We understand that making and editing videos used to be hard because they often needed special skills or licenses. With Google Wiz, anyone can tell their story. Now, teams can create and share compelling stories at work, helping their message reach and engage coworkers more effectively.  

Additional Details 

Before this launch, only Gemini for G Suite customers could use Vids. Now Google Vids is available with select Workspace subscription plans.  

Users will have full access to AI-powered features in Google Vids, such as “Help me create” and AI voiceovers, until at least December 31, 2025. Starting in 2026, usage limits for these features may apply. We’ll let you know before any changes happen.  

Vids’ generative AI features include Help Me Create, Generate a Voiceover, Remove Image Backgrounds, Generate an Image, Recording Studio, and Read Along a Teleprompter.  

To learn more about Waves features and capabilities for the Google Workspace environment for education customers, refer to this Workspace Updates blog.  

Getting Started 

  • Admins: Vids will be on by default and can be disabled at the organizational level. Visit the Help Center to learn more about turning Waves on or off for users and new core services coming to the Google Workspace platform.  
  • End users: to get started, open Google Vids and choose how you want to create a new video. You can start from scratch or copy an existing video to edit. Visit the Help Center to learn more about using Google Vids.  
  • You can use Vids on your computer with the two most recent versions of Chrome, Firefox, or, on Windows devices only, Microsoft Edge. Other browsers may work, but some features might not function fully or be available.  

You can find helpful resources in the Google Workspace platform Learning Center to learn more about what you can do with Google Wiz. However, the AI features are only available in English at this time.  

Note: View and collaborate access is available to anyone with a Google Workspace platform account, while create and copy access is available for select editions of Google Workspace and Gemini for Google Workspace edition customers.  

Rollout Pace 

Rapid release and scheduled release domains: extended rollout (potentially longer than 15 days for feature visibility) starting on November 7, 2024  

Availability 

Available for Google Workspace:  

  • Business Standard and Plus  
  • Enterprise, Standard, and Plus  
  • Essentials, Enterprise Essentials, and Enterprise Essentials Plus  
  • Education Plus  
  • Customers with a Gemini Business, Enterprise, Education, or Education Premium add-on  

SourceAnnouncing general availability of Google Vids: Our new AI-powered video creation app for work to help tell stories across your organization