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Medium
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Is Artificial Intelligence Performing Surgeries Instead of Doctors?
- Artificial Intelligence (AI) is making its mark in the world of surgery by assisting in pre-surgery planning, analyzing medical scans, guiding robotic instruments, predicting complications, and suggesting alternative surgical paths.
- Surgical robots like the Da Vinci Surgical System improve cutting and stitching accuracy, minimize bleeding, shorten operating and recovery times, and automatically correct movements based on AI integration, while still being controlled by human surgeons.
- AI learns from millions of medical images, surgical records, and patient data to enhance surgical procedures by offering unmatched precision, real-time 3D visual analysis, and alerting surgeons about critical situations during operations.
- While AI has performed soft tissue surgery successfully on a pig without human intervention, current regulations prevent AI from independently operating on humans due to ethical, legal, and emotional considerations. Surgeons view AI as an ally that enhances surgical skills, reduces errors, and allows them to focus on saving lives.
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The State of AI Security in 2025: Key Insights from the Cisco Report
- AI adoption is increasing rapidly, but organizations face significant security risks that need to be addressed for trust, privacy, and business continuity.
- Cisco's 'State of AI Security in 2025' report emphasizes the gap between AI adoption rates and organizational readiness to secure AI systems effectively.
- New threats in AI security include infrastructure attacks targeting AI frameworks like NVIDIA's Container Toolkit and Ray, as well as supply chain vulnerabilities.
- Emerging AI-specific attacks like prompt injection, jailbreaking, and training data extraction pose challenges to traditional cybersecurity methods.
- Attack vectors targeting AI systems include jailbreaking, indirect prompt injection, and training data poisoning, making AI systems vulnerable at various stages of their lifecycle.
- Cisco's research reveals vulnerabilities in top AI models, risks in fine-tuning models, training data extraction methods, and the ease and impact of data poisoning.
- AI is not only a target for cyber threats but also a tool for cybercriminals, enabling more effective attacks and personalized scams.
- Best practices for securing AI systems include risk management across the AI lifecycle, using established cybersecurity practices, focusing on vulnerable areas like supply chains, and educating employees on AI security risks.
- As AI adoption continues to rise, organizations need to prioritize security alongside innovation to navigate evolving security risks and opportunities in the AI landscape.
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Roman Axelrod, Founder and Managing Partner of XPANCEO – Interview Series
- Roman Axelrod is the Founder and Managing Partner of XPANCEO, a company developing smart contact lenses for extended reality experiences, integrating real and digital worlds.
- His inspiration came from the need for a revolutionary computer that seamlessly blends AI into daily life, leading to the conception of XPANCEO.
- XPANCEO envisions enhancing human-computer interaction through transhumanism, integrating biology and technology to surpass current limitations.
- The smart contact lens prototypes utilize advanced 2D materials for transparency and lightweight design, allowing for integration of electronics without compromising functionality.
- The lenses aim to offer features like night vision, zoom, health tracking, and biometric transactions, providing enhancements beyond health monitoring and content consumption across industries.
- XPANCEO foresees a future where smart lenses could become mainstream, catering to various needs and potentially reaching 10 million users by 2032.
- The company emphasizes elegance and embracing challenges in day-to-day decision-making, focusing on innovation and problem-solving in product design.
- XPANCEO seeks to strike a balance between technology augmentation and intrusion, aiming to enhance lives while ensuring safety, privacy, and ethical usage.
- Roman Axelrod envisions a future where technology seamlessly integrates into daily life, transforming the relationship between humans and tech tools.
- Through XPANCEO's work, technology could become an invisible yet essential part of individuals, enhancing capabilities and reshaping interactions with the world.
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The Future of AI in Real Estate and Rentals
- Real estate is facing tech debt with manual processes and outdated systems, hindering AI adoption.
- The industry is resistant to change due to fragmented legacy systems and a lack of risk tolerance for automation.
- AI in real estate is currently used narrowly for tasks like chatbots, pricing tools, and document scanners.
- To accelerate AI adoption, real estate should focus on automation for reliability and risk reduction, not just speed.
- There's untapped potential for AI in areas like compliance automation, document verification, and tenant screening.
- AI can streamline tasks like property compliance checks, document verification, and internal operations in real estate.
- Innovation in real estate involves fully integrating existing tools like OCR, LLMs, and workflow engines for maximum efficiency.
- AI can transform real estate operations by reducing errors, improving quality, and automating processes.
- The key to successful AI implementation in real estate is a mindset shift towards risk reduction and complete process automation.
- By embracing AI, real estate companies can free up agents to focus on high-value tasks like client advisory and deal closure.
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The Robot Report
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MIT engineers create elder assist robot E-BAR to prevent falls at home
- MIT engineers have developed a robot, E-BAR, to assist the elderly in preventing falls at home.
- The U.S. population is aging, with a projected increase in adults older than 65 to 82 million by 2050.
- E-BAR acts as robotic handlebars that provide physical support and can prevent falls by lifting and catching a person.
- The robot aims to address the challenges of eldercare, including shortages in caregivers and rising healthcare costs.
- The design concept of E-BAR focuses on providing older adults with balance impairment robotic handlebars for stabilization.
- Researchers at MIT aim to design robots that prioritize patient needs and help the elderly age in place.
- E-BAR is designed to be unobtrusive, provide body weight support, and actively assist with gait and fall prevention.
- The robot can move in any direction without pivoting, with arms equipped with airbags to catch a falling person.
- Future iterations of E-BAR aim to automate its functions and make it more maneuverable in small spaces.
- The robot was tested successfully in various household scenarios, demonstrating its ability to support daily activities of older adults.
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The Evolving Role of AI in Shaping the Future of Physical Security
- Organizations are managing vast amounts of data and assets, making them prime targets for threats, leading to the adoption of AI in physical security.
- AI enhances human-powered security by analyzing real-time data, improving decision-making, and reducing security incidents.
- AI-driven behavioral analytics help detect suspicious behavior, allowing proactive responses and enhancing building safety.
- AI is transforming security beyond surveillance by improving operational efficiency and safety in workplaces through compliance automation.
- AI optimizes building occupancy, monitors safety hazards, and enables predictive maintenance for improved security systems.
- AI-powered compliance tools streamline processes, detect breaches, and ensure adherence to security policies and privacy regulations.
- While AI is invaluable in security, human creativity remains essential to tackle evolving threats collaboratively with AI solutions.
- AI will continue to revolutionize physical security, offering accurate protection and new use-cases while emphasizing the importance of ethical considerations.
- The future of security lies in AI collaboration, and organizations leveraging AI today will be better equipped for future security challenges.
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Evaluating Where to Implement Agentic AI in Your Business
- Agentic AI has the potential to reshape industries by enabling autonomous decision-making, real-time adaptability, and proactive problem-solving.
- Businesses need to carefully evaluate where to implement agentic AI for maximum impact, from supply chain optimization to customer experience enhancement.
- Agentic AI introduces autonomy by having multiple AI agents operating in parallel, making real-time decisions based on learning mechanisms and real-world conditions.
- To successfully adopt agentic AI, businesses should identify high-impact use cases, define risk tolerance levels, align investments with objectives, start small and scale gradually, and evaluate programs regularly for continuous improvement.
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Medium
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Meta AI Standalone App is Here | VBM
- Meta has launched a standalone Meta AI app to compete with OpenAI’s ChatGPT and Google’s Gemini.
- Rumors suggest that Meta may gradually remove AI from its social media platforms to cater to all sections of its fanbase.
- The Meta AI app introduces social elements and aims to enhance personalization, voice capabilities, and integration with Meta’s ecosystem.
- Meta aims to shape the future of AI-driven engagement leveraging its user base, with the app currently available for download with limited voice features in select countries.
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Cognichip Emerges from Stealth with $33M to Launch “Artificial Chip Intelligence” and Reinvent Semiconductor Design
- Cognichip has launched with $33 million funding to introduce Artificial Chip Intelligence (ACI®) for revolutionizing semiconductor design.
- Led by Lux Capital and Mayfield, the startup addresses cost and time barriers in chip design with ACI®, founded by Faraj Aalaei.
- ACI® combines physics-informed AI for chip design, focusing on cognitive abilities, parallelized cycles, cost reduction, and efficiency.
- Cognichip aims for 50% faster development, 75% cost reduction, smaller chips, adaptability, and democratizing chip design.
- The team includes AI and semiconductor experts, working towards creating a cognitive engine for chip creation.
- Cognichip seeks to democratize chip design for AI infrastructure, healthcare, energy, and autonomous systems with its innovative approach.
- Investors view ACI® as a paradigm shift in chip design by replacing brute-force methods with intelligent, AI-powered creation.
- The company's vision is to bridge the gap between AI model development and chip design, enabling faster, tailored chip creation.
- Cognichip positions itself as a key player in transforming the semiconductor industry, making chip creation intelligent and scalable.
- In the new era, the distinction between software and hardware blurs, as innovation comes from intelligent chip creation.
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The Robot Report
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New enabling technologies from Automate 2025
- Automate 2025 showcased various industrial automation technologies with over 40,000 attendees and 800 exhibitors announcing new products, partnerships, and applications.
- Cattron introduced the XBMCU Multi-Interface Machine Control Unit that integrates into PLCs through multiple serial protocols for robust machine-to-machine functionality.
- Schneider Electric unveiled its industrial copilot powered by Microsoft Azure AI Foundry to enhance productivity and workforce efficiency.
- Novarc Technologies launched the NovAI vision system for welding, combining machine vision and real-time adaptation for improved welding quality and efficiency.
- Rollon expanded its TH actuator range with the new size 200, catering to designers and engineers needing high precision and flexibility in demanding applications.
- Kistler introduced maXYmos BL 5867C for process monitoring and AkvisIO 7.0 for comprehensive data collection and quality control in plastics injection.
- Geisel Software unveiled the Symage synthetic data platform focusing on 3D photorealistic synthetic image data for training AI models in machine vision.
- MachineMetrics launched an AI-driven tool monitoring system for quick diagnosis, prediction, and prevention of failures in machine tools, leveraging high-frequency machine control data.
- These technologies aim to drive efficiency, quality, and innovation in industrial automation, showcasing advancements at Automate 2025.
- The event emphasized the importance of AI, machine vision, and predictive maintenance in meeting the evolving needs of manufacturing and logistics industries.
- Moving forward, these developments are expected to revolutionize industrial processes and elevate automation capabilities in various sectors.
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AI: Flattening Engineering Bureaucracy and Accelerating Innovation
- Engineering organizations often accumulate layers of processes that slow down development as they scale, leading to frustration and innovation stagnation.
- AI is offering a solution by enhancing individual capabilities and reducing the need for organizational complexity, thereby streamlining operations.
- AI helps engineers work across different parts of the codebase, reducing coordination overhead within teams and eliminating the need for parallel org structures.
- Through AI, engineers can engage in architecture discussions and refine ideas more efficiently without the delays of formal meetings.
- AI integration in testing processes minimizes back-and-forth between development and QA, ensuring high-quality standards with fewer roundtrips.
- The organizational simplification enabled by AI allows for more autonomous team operations and decreased reliance on complex scaling frameworks.
- Adapting agile processes by leveraging AI enhancements can significantly boost efficiency and productivity, promoting continuous improvements.
- Engineering leaders are urged to invest in AI capabilities, challenge team sizes and specialization, experiment with simplified process models, and measure reduced 'process time'.
- AI paves the way for simpler organizational structures, flattening hierarchies, reducing handoffs, and simplifying coordination for enhanced innovation speed.
- AI's role in engineering signifies a shift towards valuing individuals and interactions over processes and tools, ushering in a future of dramatically simpler engineering practices.
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Is Perplexity AI Really Worth $14 Billion?
- Perplexity AI is in talks to raise $500 million at a $14 billion valuation, reflecting a drastic increase in value over just a few years.
- While Perplexity's revenue and user base are impressive, its $14B valuation raises questions about its ability to compete against tech giants like Google.
- Perplexity positions itself as an "answer engine" that provides direct answers with sources, challenging traditional search methods.
- Despite its traction and backing from prominent investors, Perplexity's valuation prompts skepticism given the competitive landscape.
- Google's dominant position in the search market presents a significant obstacle for newcomers like Perplexity, which faces an uphill battle to make a lasting impact.
- The emergence of AI-driven tools such as Google's AI Overviews and OpenAI's ChatGPT poses additional challenges for Perplexity's market penetration.
- While Perplexity has carved a niche among early adopters, the question remains whether it can challenge Google's supremacy in the long run.
- ChatGPT's widespread adoption and versatility, coupled with Google's strategic advancements in AI search, present formidable competition for Perplexity.
- Perplexity's $14B valuation reflects high expectations for its growth and monetization potential, with challenges in revenue generation and user retention.
- Investor enthusiasm in the AI space may be contributing to Perplexity's inflated valuation, signaling a potential disconnect from its actual market impact.
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How Walled Gardens in Public Safety Are Exposing America’s Data Privacy Crisis
- Artificial intelligence is revolutionizing public health and public services, but the rapid collection of data has outpaced responsible governance.
- The proliferation of walled gardens in public safety, where one company controls data access and flow, poses serious privacy and transparency concerns.
- These closed systems in public safety hinder interoperability, leading to fragmented insights and ineffective community responses in emergencies.
- The public is often unaware of the extent of personal data flowing into these systems, raising issues of data privacy and potential misuse.
- Data locked in walled gardens limits cross-referencing and validation, risking inaccurate decision-making and civil liberties violations.
- Open ecosystems supporting secure, standardized data sharing are needed to ensure privacy protections and foster innovation in public safety tools.
- A privacy-first approach involves limiting data access, enabling audits, and involving community stakeholders in policy shaping for enhanced security and legitimacy.
- The absence of comprehensive federal data privacy legislation in the U.S. leads to a fragmented landscape, unlike Europe's GDPR that emphasizes consent-based data usage.
- Responsible AI implementation in public safety requires clear standards, transparency, and accountability, with community involvement at all stages of data handling.
- Prioritizing interoperability over vendor lock-in is crucial for equitable, efficient, and ethical data-driven decision-making in public safety systems.
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The Robot Report
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Intuitive Surgical is making a CEO change
- Intuitive Surgical announced the promotion of President Dave Rosa to the position of CEO, effective July 1, 2025, with current CEO Gary Guthart transitioning to the executive chair role.
- Gary Guthart, the outgoing CEO, spent the last 15 years overseeing the launches of new products at Intuitive, contributing to the company's dominance in the surgical robotics space.
- Dave Rosa, the incoming CEO, has been with Intuitive for nearly 30 years, holding various leadership positions and contributing to the development and commercialization of robotic systems.
- The succession plan reflects Rosa's instrumental role in guiding Intuitive's strategy, expanding the company's global presence, and leading the next phase of growth, according to the board.
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Unite
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Tom Dunlop, CEO and Founder of Summize – Interview Series
- Tom Dunlop, CEO & Founder at Summize, a Contract Lifecycle Management (CLM) platform, utilizes AI to simplify and accelerate contract processes for entire businesses.
- Inspired by the need to automate tasks and innovate in a high-growth tech environment, Summize was created to meet the demands of reviewing contracts efficiently.
- Summize evolved to focus on in-house counsel, leveraging AI and NLP to drive cost efficiency and streamline legal processes, setting it apart in the CLM market.
- AI adoption in legal work is prominent in technology and software industries, but general in-house teams may pose barriers to adoption despite productivity gains.
- AI can transform legal work beyond contract analysis by enabling data-driven decision-making, workflow orchestration, and potentially altering the legal service model.
- To move beyond initial AI adoption, legal teams need training, clear AI policies, and understanding of AI's impact on their roles over the next five years.
- AI-powered tools like Summize will free General Counsels from mundane tasks, allowing them to focus on higher-value work and scale their knowledge across legal teams.
- Regulatory frameworks must evolve to govern AI use in legal tech, specifying data use by language models and ensuring model accountability and data quality.
- Integrations with tools like Microsoft Word, Teams, and Slack make AI-driven legal tools more accessible and user-friendly by embedding AI into familiar workflows.
- Summize's future plans include the launch of an AI-Powered CLM with intelligent agents and expanded chatbot functionality to enhance contract reviews and interactions with data.
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