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Robotics News
Pymnts
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Walgreens Ups Use of Robotics With New Micro-Fulfillment Center
- Walgreens is increasing its use of robotics with a new micro-fulfillment center in Minnesota.
- The center in Brooklyn Park will support nearly 200 Walgreens locations, processing 13 million prescriptions annually.
- The micro-fulfillment centers use robotic technology to dispense and ship prescriptions efficiently throughout the country.
- Walgreens aims to enhance patient care and experiences by freeing up pharmacists to focus on tasks like medication adherence support and vaccine administration.
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The Robot Report
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Orbit 5.0 adds features to Boston Dynamics’ Spot quadruped robot
- Orbit 5.0 for the Spot quadruped robot by Boston Dynamics uses AI to provide insights into site health, detect problems earlier, and offer visual context over time.
- Orbit 5.0 applies AI to automatically detect visual anomalies like debris, spills, or corrosion without manual image review, enabling alerts of changes and historical context.
- Site View feature in Orbit 5.0 allows users to review site conditions, compare changes, and conduct remote plant walk-throughs using 360° images captured by Spot.
- Orbit 5.0 enables centralized management of Spot robots across facilities, including dashboards for aggregating data, automated face blurring, flexible user permissions, and over-the-air updates.
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Dronelife
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Michael Robbins at XPONENTIAL 2025: U.S. Drone Industry Must Lead “Uncrewed Arsenal of Democracy” to Secure National Security
- XPONENTIAL 2025 by AUVSI focuses on advancing innovation in uncrewed systems and robotics for national security.
- Michael Robbins emphasizes the importance of a strong U.S. drone industry for national security and warns against reliance on Chinese-manufactured drones.
- AUVSI is working on policies to strengthen domestic drone production, foster partnerships, and enhance cybersecurity initiatives.
- Debate exists regarding security concerns with Chinese drones versus functionality and cost, with Robbins advocating for a resilient U.S. drone industry for national defense.
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Analyticsindiamag
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NVIDIA Unveils DreamGen for Robot Learning Through Digital Video ‘Dreams’
- NVIDIA has introduced DreamGen, an engine designed to scale robot learning using synthetic video data instead of human operators.
- DreamGen generates neural trajectories and photorealistic robot videos paired with motor action labels to train robots on new tasks and environments.
- The technology enables robots to dream inside a video generative model, teaching them new behaviors without direct training and achieving high success rates on novel tasks.
- DreamGen bypasses the need for physical deployment in numerous homes by creating synthetic training data through a 4-step pipeline, training robots to perform tasks zero-shot.
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Dev
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The Physical Turing Test: How NVIDIA is Revolutionizing Embodied AI and Robotics
- The traditional Turing Test has been surpassed by the concept of embodied AI, where AI systems interact with the physical world intelligently.
- NVIDIA's Director of AI introduced the Physical Turing Test, emphasizing the importance of AI in physical actions and real-world problem-solving.
- Embodied AI poses challenges like perceiving the environment, planning complex tasks, and exhibiting motor control, beyond text-based conversation capabilities.
- Data scarcity in training physical AI systems is a significant challenge due to the need for real-world interaction data.
- NVIDIA is pioneering simulation-based training for robots with digital twins, digital cousins, and digital nomads to overcome data limitations.
- Key innovations like the Groot N1 model and the embodied scaling law by NVIDIA are advancing the development of physical AI systems.
- The ultimate goal of physical AI is to create systems that seamlessly integrate into daily life, performing tasks and enhancing experiences.
- A future vision includes a 'physical API' for controlling physical actuators through code, transforming physical work and creating new economies.
- Practical applications of physical AI range from industrial automation to domestic assistance, skill economy development, and integration with existing systems.
- As AI progresses in embodied intelligence, industries will be transformed, economic opportunities will emerge, and the quality of life globally will be enhanced.
- The future of AI is not just about thinking but also about doing, with tangible impacts expected on various aspects of human life.
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Unite
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CivitAI in New Payment Provider Crisis, as Trump Signs Anti-Deepfake Act
- President Trump signs the Take It Down Act, criminalizing sexual deepfakes at a federal level in the US.
- The deepfake porn site Mr. Deepfakes went offline, with over five million monthly visits, after a critical service provider withdrawal.
- CivitAI's attempt to regulate NSFW AI content failed to satisfy payment processors, leading to a payment crisis.
- CivitAI users face payment hurdles as VISA and Mastercard halt card payments due to NSFW content issues.
- CivitAI struggles to find alternative payment providers comfortable with AI innovation amidst the payment processor cutoff.
- President Trump's Federal TAKE IT DOWN Act aims to tackle non-consensual intimate imagery distribution, including AI-generated deepfakes.
- The new law requires platforms to remove flagged content within 48 hours, raising concerns about privacy and legitimate content suppression.
- The TAKE IT DOWN Act may not cover all AI-generated celebrity content, depending on the reasonable expectation of privacy.
- State-level deepfake legislation varies, with California and Tennessee having laws targeting celebrities' identity use and safeguarding musicians from unauthorized AI reproductions.
- The evolving legal landscape around deepfakes and the impact of federal and state laws on AI-generated content remains a complex and evolving issue.
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Dev
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AGV Handling Robot Commonly Uses Sensor Principles and Their Advantages and Disadvantages, Application Introduction
- LiDAR is a sensor system that emits laser beams to detect target information, widely used in autonomous driving and mapping.
- Point cloud data from LiDAR contains reflectivity characteristics and spatial coordinates for object detection.
- Laser navigation in AGV systems allows for flexible movement and precise positioning based on map construction and real-time positioning.
- Laser navigation features high-precision positioning, environmental adaptability, no fixed-path limitations, and high intelligence for multi-AGV cooperation.
- AI-driven laser obstacle avoidance in AGVs uses laser radar and intelligent algorithms to detect and navigate around obstacles.
- ToF technology in cameras uses light waves for spatial measurement, offering accurate depth information and 3D environment modeling.
- ToF cameras in AGVs are used for obstacle avoidance, safety protection, pallet identification, fork picking, and volume measurement.
- Ultrasonic sensors are used for AGV obstacle avoidance, transparent object detection, and offer advantages like resistance to interference and low cost.
- IMUs in AGVs provide dynamic attitude control, infrastructure-free positioning, and high-frequency updates but face challenges related to accumulated error and calibration.
- Photoelectric distance sensors are cost-effective, non-contact, and offer high-speed response for simple obstacle detection.
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Unite
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The Faster AI Developers Code, the Quicker the Cloud Needs to Be
- Cloud computing is evolving to support the next generation's software development needs, driven by AI advancements.
- AI-driven tools like GPT-4.1 are accelerating code development, putting pressure on traditional cloud infrastructure.
- The fixed capacity of traditional cloud setups hinders AI models with bursty resource demands and real-time processing requirements.
- Transitioning to decentralized cloud computing is crucial to avoid delays and capacity constraints for AI development.
- Cloud computing is now an active enabler of the development process, offering real-time collaboration and automation.
- Adopting advanced cloud systems with virtual resources reduces costs, improves scalability, and optimizes performance.
- Supercloud systems provide unified resources across multiple cloud environments, enabling efficient AI training and deployment.
- Supercloud infrastructure offers greater flexibility and scalability compared to traditional cloud setups, enhancing innovation speed.
- Aligning cloud infrastructure with the pace of AI development streamlines ideation to deployment processes.
- Modernizing infrastructure to support AI advancements is crucial for businesses to stay competitive and agile in the digital landscape.
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Unite
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Securing the Software Supply Chain with AI
- Cyber attacks have become increasingly impactful in recent years, affecting utilities, major companies, and leaking sensitive information.
- AI, while offering benefits in commerce and efficiency, also poses challenges for cybersecurity with the increasing scale and sophistication of attacks.
- AI serves as a force multiplier for cybersecurity defenders, augmenting the capability of security teams to prioritize and remediate network vulnerabilities.
- AI-powered security enhances user experience by simplifying tools and offering a centralized interface for strategizing security.
- Securing AI itself is crucial, as adversaries target AI models to influence training, exploit weaknesses, and utilize deepfake technology for malicious purposes.
- Zero trust network access (ZTNA) and other AI-specific safeguards are essential for governing access to AI services and data, limiting unauthorized access and behavior.
- Organizations must focus on securing the AI pipeline, educating users, and establishing protocols to protect sensitive data from being shared with public AI engines.
- AI is considered a foundational technology for future innovation, but implementing centralized, AI-powered security systems is crucial to drive efficiency, growth, and development.
- Prioritizing security as a strategic objective can help organizations effectively leverage AI tools and improve operations.
- By securing the software supply chain with AI, organizations can mitigate risks and enhance their overall security posture for future advancements.
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The Robot Report
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Saildrone brings in $60M to expand European maritime presence
- Saildrone Inc. secured a $60 million investment to expand its maritime technology to Europe for maritime security and defense applications.
- The investment was led by EIFO of Denmark along with existing investors and new participants like Pinegrove.
- Saildrone plans to establish its European headquarters in Copenhagen, Denmark, and work with the Danish Armed Forces to provide maritime intelligence services to multiple NATO countries.
- Their uncrewed surface vehicles (USVs) equipped with advanced sensors and AI algorithms aim to enhance maritime surveillance in the Baltic, North Sea, and European Arctic waters.
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Unite
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See, Think, Explain: The Rise of Vision Language Models in AI
- Vision Language Models (VLMs) merge visual and language skills, enabling them to explain images with a human-like touch.
- VLMs excel in tasks like image description, video comprehension, question answering, and image generation from text.
- Their functioning involves a vision system analyzing images and a language system processing text, trained on vast image-text datasets.
- Chain-of-Thought reasoning in VLMs ensures step-by-step explanations, enhancing transparency and trustworthiness of AI decisions.
- CoT facilitates tackling complex problems, as seen in healthcare diagnostics and self-driving car decision-making.
- In industries like healthcare, self-driving cars, geospatial analysis, robotics, and education, VLMs with CoT are revolutionizing processes.
- In medicine, VLMs like Med-PaLM 2 diagnose based on symptoms, providing detailed reasoning for doctors to follow.
- Self-driving cars leverage CoT-enhanced VLMs for safer navigation and natural language explanations of actions taken.
- Google's Gemini model integrates CoT to expedite geospatial analysis for disaster response and decision-making.
- In robotics, CoT and VLM integration enhances planning and execution of multi-step tasks, boosting adaptability and response clarity.
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Unite
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Kuljesh Puri, SVP & GM of Communications, Media & Technology, Persistent Systems – Interview Series
- Kuljesh Puri is the Senior Vice President and General Manager of Communications, Media & Technology at Persistent Systems with 26 years of industry experience.
- AI is transforming call centers by enabling predictive analytics, automation, and NLP to enhance customer interactions and drive loyalty.
- AI contributes to seamless omnichannel experiences by integrating interactions across various channels and personalizing client support.
- Challenges in deploying AI in call centers include integrating with legacy systems, data quality, transition complexities, and privacy concerns.
- Telecom companies focus on optimizing operations and predictive analytics, while media companies use AI for content curation and engagement.
- Full AI adoption requires cultural shifts towards data-driven organizations, cross-department collaboration, and investment in AI talent.
- The acquisition of Starfish Associates strengthens Persistent's AI-powered contact center capabilities and reinforces focus on operational excellence.
- Persistent addresses data security and privacy in AI-enabled customer service solutions by implementing safeguards and ensuring regulatory compliance.
- Success in AI-powered client experience for telecom players involves proactive engagement, personalized support, and seamless omnichannel integration.
- Persistent Systems aims to help telecom and media companies implement AI solutions for improved customer interactions and business success.
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Unite
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Why GenAI Stalls Without Strong Governance
- Many organizations struggle to move Generative AI projects from pilot to production due to fundamental data issues.
- GenAI models heavily rely on quality data to avoid producing inaccurate or biased results.
- Companies often deploy low-effort AI use cases without addressing deep data infrastructure changes.
- Data reliability, completeness, privacy issues, and governance gaps are key barriers to AI deployment.
- Data governance is crucial for scaling GenAI strategically and ensuring data readiness for AI models.
- Building AI literacy and embedding data governance in organizational culture are essential for successful AI adoption.
- Accountability and transparency are increasingly important in AI due to regulatory requirements and consumer demands.
- Compliance with regulations and establishment of trusted data foundations are vital for building trustworthy AI.
- Strong data foundations lead to reduced model drift, faster speed to value, and increased innovation potential.
- Investing in data quality, governance, and culture can help companies turn GenAI from a promising pilot to a successful implementation.
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Unite
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From Tariffs to Triumph: How CEOs Can Leverage AI for a Competitive Edge
- Trade shifts and tariffs have become significant challenges for businesses, affecting cost structures and profitability across industries.
- Generative AI offers a strategic advantage for executive leadership to navigate complex trade-offs and decision-making in the face of economic uncertainties.
- AI provides precision pricing intelligence, helps reconfigure the supply chain, identifies operational inefficiencies, and aids in customer retention through behavioral intelligence.
- AI-powered pricing engines recommend hyper-targeted pricing adjustments, enabling businesses to maintain price stability and raise margins selectively.
- Generative AI systems assist in optimal sourcing moves and supply chain strategies, balancing tax implications and quality consistency.
- AI-driven forecasting models facilitate shifts in procurement to lower-tariff regions, aiding businesses in maintaining food costs and operational efficiency.
- Predictive analytics and machine learning models help companies reduce operational waste and improve demand forecasting accuracy, offsetting tariff-driven cost increases.
- AI enables businesses to anticipate consumer behavior shifts during economic stress and adapt promotional campaigns and loyalty incentives accordingly.
- As tariffs become a structural shift, leadership teams must embrace real-time intelligence and systems-level adaptation powered by AI for enterprise-wide visibility.
- AI offers the capability to simulate scenarios, recommend integrated strategies, and scale across sourcing decisions, pricing, and customer engagement initiatives.
- The integration of AI tools is essential for organizations to adapt and lead in the face of evolving tariff challenges and economic uncertainties.
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Unite
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AI Can Make Our Food Safer and Healthier
- Artificial intelligence is revolutionizing the food industry by addressing challenges such as foodborne illnesses, nutrition, and personalized diets.
- AI is used to predict contamination risks in foods by analyzing factors like pH, water activity, and salt content, leading to targeted antimicrobial interventions.
- New technologies like Evja’s OPI system leverage AI to forecast irrigation schedules and pest risks, promoting smarter resource management and enhancing food safety.
- Companies like FreshSens use AI and IoT sensors to monitor environmental conditions during storage and transportation, reducing spoilage-related contamination risks.
- AI plays a crucial role in developing functional foods fortified with bioactive compounds to provide health benefits beyond basic nutrition, addressing the demand for convenient and healthy food options.
- AI accelerates the discovery of bioactive ingredients, as seen in Brightseed’s Forager AI mapping plant compounds and MAOLAC optimizing bio-functional proteins from natural sources.
- AI models simulate ingredient interactions during food processing to predict nutrient stability, flavor profiles, and shelf life, aiding in faster innovation cycles for foods targeting specific health needs.
- Personalized nutrition powered by algorithms analyzes biomarkers, genetic data, and lifestyle factors to provide dietary advice tailored to individual biology, shifting towards precision-driven nourishment solutions.
- For individuals with chronic diseases like diabetes, AI-enabled solutions such as GenAI app by January AI democratize access to blood sugar monitoring and personalized dietary recommendations.
- Though AI won't replace essential roles in the food industry, its integration throughout the food value chain can lead to a proactive approach in preventing health problems and improving human longevity and healthspan.
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