Emly Labs

Elective healthcare decisions are deeply personal and often come with a range of concerns — from uncertainty about treatment options to financial worries and trust issues. 💬 Here's how AI chatbots can bridge the gap: 1. Personalized treatment recommendations 2. Instant cost estimates and financing guidance 3. Transparent information on risks and recovery 4. Verified patient reviews for added trust 5. Effortless appointment booking with reminders Don’t let hesitation hold your patients back! AI chatbots keep potential patients informed, engaged, and confident in their decisions. 🔍 Swipe through to see how AI chatbots address common concerns and improve patient experience! #ElectiveHealthcare #PatientEngagement #AIChatbots #HealthcareInnovation

When it comes to GPU servers, AMD and NVIDIA dominate the market, offering high-performance solutions for AI, machine learning, high-performance computing (HPC), and cloud-based workloads. But which one is the better choice for your specific needs? Both brands have their strengths: 1. NVIDIA leads in AI and deep learning, thanks to its CUDA-powered ecosystem and Tensor Cores. 2. AMD offers cost-effective solutions with strong performance in HPC and scientific computing while emphasizing open-source flexibility. When to Use NVIDIA a. AI/ML workloads requiring top-tier performance b. Deep learning and neural network training c. Cloud-based AI deployments d. Optimized software ecosystem (CUDA, cuDNN) When to Use AMD a. Cost-effective GPU solutions for large-scale deployments b. Scientific computing and HPC workloads c. Open-source projects requiring flexibility d. Energy-efficient data centers with high computational needs This breakdown was put together by Oltjano Terpollari to help you make an informed decision. 🔽 Swipe through the carousel for a detailed breakdown of AMD vs. NVIDIA in architecture, performance, cost, and best use cases! #GPU #AI #MachineLearning #HighPerformanceComputing #CloudComputing #NVIDIA #AMD Stay updated! Follow Emly Labs

The Complex Patient Journey in Elective Healthcare Elective healthcare decisions are rarely made on impulse. Patients research, compare and evaluate every aspect before committing. From treatment options to provider credibility and cost transparency, the journey is filled with questions. In a landscape where trust is everything, timely information, and personalized guidance make all the difference. How are healthcare providers ensuring patients get the clarity they need—at the right moment? #ElectiveHealthcare #PatientExperience #HealthcareInnovation

Discover how AI chatbots are transforming client engagement in elective healthcare—join our webinar on March 29th! To secure your spot, please take a moment to complete the registration below: Register here: https://lnkd.in/d7awpdax Looking forward to having you join us! #generativeai #WebinarAlert #JoinUsNow #AIChatbots

Nvidia Unveils AI Personal Supercomputers – A New Era of Computing! Nvidia just dropped a game-changer at GTC 2025: two AI-powered personal supercomputers, DGX Spark and DGX Station, built on the Grace Blackwell chip platform. Key Highlights: 1. DGX Spark – 1,000 trillion AI operations per second with the GB10 Superchip. 2. DGX Station – Powered by GB300 Ultra Desktop Superchip with 784GB of memory for high-performance AI workloads. 3. Edge AI Ready – Designed to prototype, fine-tune, and run AI models at scale. 4. Enterprise Focused – Coming via Asus, Dell, HP, Lenovo, and more later this year. Our Take With AI agents becoming ubiquitous, Nvidia’s new lineup redefines AI computing for enterprises—bringing powerful AI closer to businesses of all sizes. The future of AI isn’t just in the cloud; it’s now at the edge! Read more on TechCrunch – Link in the comments! #Nvidia #AIComputing #Supercomputers #GTC2025 #GraceBlackwell #AIAgents #EdgeAI #AIInnovation Stay updated! Follow Emly Labs

AI makes patient support faster, but without the human touch, something crucial is missing. The best clinics don’t choose between AI and human care—they combine both. Enjoy reading! #AIinHealthcare #PatientCare #HealthcareInnovation #HumanVsAI #HealthTech Stay updated! Follow Emly Labs

WEBINAR ALERT: Transform Your Elective Healthcare Practice with AI! 🔹 Patient expectations are evolving—is your clinic keeping up? 🔹 Discover how Gen AI is reshaping patient acquisition & engagement. 🔹 Learn practical strategies for seamless AI adoption from industry experts. 📅 Join us on March 29 for an exclusive webinar! Key Takeaways: ✅ How AI is revolutionizing patient acquisition & engagement ✅ Best practices for integrating AI seamlessly into your clinic Early bird registration is now open! Secure your spot today! 👉 Register now! The Event link (in the comment section) #HealthcareAI #ElectiveHealthcare #AIinMedicine #MedicalInnovation

Stop Losing Patients—Boost Your Revenue with AI! Elective Healthcare providers, are you struggling with patient engagement and appointment no-shows? AI-powered automation is the solution you need! ✅ Engage Visitors Instantly, 24/7 – Never miss a potential patient inquiry again. ✅ Personalized Follow-ups – Keep patients engaged and build long-term trust. ✅ Automated Scheduling & Reminders – Reduce missed appointments and optimize your revenue. Embrace AI-driven efficiency and keep your practice thriving! #HealthcareAI #PatientEngagement #MedicalAutomation #AIForHealthcare Stay updated! Follow Emly Labs

🔹 97% of website visitors don’t convert 🔹 Patients spend 2-3 weeks researching before booking 🔹 Lead costs range from $30 to $320 Can Generative AI be the key to boosting patient trust, engagement, and conversions? Join us as we uncover the game-changing role of Gen AI in elective healthcare! 📅 [29th March, noon] #HealthcareAI #PatientExperience #GenerativeAI #AIinHealthcare #ElectiveHealthcare #DigitalHealth Stay updated! Follow Emly Labs

Google Pushes for Weaker Copyright & Export Rules in AI Policy Proposal In a bold move, Google has unveiled its AI policy proposal, calling for relaxed copyright restrictions and balanced export controls to foster innovation while addressing national security concerns. Key Takeaways: 1. Copyright and AI Training:  Google advocates for "fair use" and text-and-data mining exceptions, allowing AI developers to train on copyrighted but publicly available data without significant restrictions. This stance aligns with OpenAI's position but faces criticism from copyright holders. 2. Export Controls: Google challenges existing U.S. export rules on advanced AI chips, arguing they hinder economic competitiveness. The company seeks "balanced" controls that protect security while enabling global business operations. 3. Federal AI Legislation:  Highlighting the fragmented regulatory landscape of state-level AI laws, Google urges the U.S. government to adopt cohesive federal legislation, including a comprehensive privacy and security framework. 4. Liability and Transparency:  Google opposes strict liability obligations for AI misuse, suggesting that deployers, not developers, should manage downstream risks. It also criticizes transparency rules that could compromise trade secrets or national security. 5. R&D Investments:  The tech giant calls for increased federal funding for foundational AI research and the release of government datasets to support innovation. Read more via TechCrunch (link in the comment section) #AI #Google #ArtificialIntelligence #TechPolicy #Copyright #AIRegulation #FairUse #ExportControls