Beyond the Giant Models: Alternative Paths for AI

🤖 AI Industry Update: What You Need to Know The pace of AI innovation continues to accelerate, with several key trends shaping the landscape: 🔹 Generative AI is expanding beyond text and images into video, code, and personalized content creation. 🔹 Edge AI is gaining traction, enabling real-time processing on devices from smartphones to IoT sensors. 🔹 Ethical AI and governance frameworks are becoming critical as regulations evolve globally. Growth areas include: - Healthcare: AI-driven diagnostics and drug discovery - Sustainability: Optimizing energy use and climate modeling - Finance: Fraud detection and hyper-personalized services Opportunities: - Upskilling in prompt engineering and AI ethics - Cross-industry collaborations leveraging AI for innovation - Investment in scalable, responsible AI solutions Stay ahead by embracing continuous learning and exploring how AI can transform your field. #ArtificialIntelligence #AI #TechTrends #Innovation #FutureOfWork

🚀 AI Industry Update: What’s Shaping the Future? 🤖 The pace of AI innovation continues to accelerate, with several key trends dominating the landscape: 🔹 Generative AI is evolving beyond text and images into video, code, and even 3D modeling—reshaping creative and technical workflows. 🔹 Edge AI is gaining traction, enabling real-time processing on devices from smartphones to IoT sensors, reducing latency and enhancing privacy. 🔹 AI in healthcare is booming, with breakthroughs in drug discovery, diagnostics, and personalized treatment plans. 🔹 Ethical AI and governance frameworks are becoming critical as regulations tighten globally. Growth areas include AI-driven cybersecurity, climate tech solutions, and hyper-automation across industries. For professionals, upskilling in prompt engineering, MLOps, and AI ethics presents huge opportunities. The future is intelligent—stay curious, adaptable, and ready to leverage these tools! 💡 #ArtificialIntelligence #AI #MachineLearning #TechTrends #Innovation #FutureOfWork

𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 (𝐀𝐈) 𝐌𝐚𝐫𝐤𝐞𝐭: 𝐏𝐨𝐰𝐞𝐫𝐢𝐧𝐠 𝐭𝐡𝐞 𝐍𝐞𝐱𝐭 𝐄𝐫𝐚 𝐨𝐟 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐃𝐨𝐰𝐧𝐥𝐨𝐚𝐝 𝐅𝐫𝐞𝐞 𝐒𝐚𝐦𝐩𝐥𝐞 𝐑𝐞𝐩𝐨𝐫𝐭: https://lnkd.in/g67q2fUd Global Artificial Intelligence Market was valued at USD 275.59 billion in 2024 and is expected to reach USD 1478.99 billion by 2030 with a CAGR of 32.32%. The Artificial Intelligence Market is experiencing exponential growth, transforming industries from healthcare and retail to finance, manufacturing, and mobility. With applications spanning predictive analytics, natural language processing, computer vision, and autonomous systems, AI is reshaping how businesses operate and how people interact with technology. 𝐊𝐞𝐲 𝐝𝐫𝐢𝐯𝐞𝐫𝐬 𝐟𝐮𝐞𝐥𝐢𝐧𝐠 𝐭𝐡𝐞 𝐀𝐈 𝐦𝐚𝐫𝐤𝐞𝐭 𝐢𝐧𝐜𝐥𝐮𝐝𝐞: ✅ Rising adoption of cloud-based AI solutions ✅ Growing investments in automation & digital transformation ✅ Expansion of generative AI applications across industries ✅ Strong demand for AI-driven cybersecurity, IoT, and smart assistants 𝐊𝐞𝐲 𝐌𝐚𝐫𝐤𝐞𝐭 𝐏𝐥𝐚𝐲𝐞𝐫𝐬 Alphabet Inc. Microsoft Amazon.com, Inc. IBM Corporation NVIDIA Corporation Apple Inc. Meta Platforms Ltd SAP SE #ArtificialIntelligence #AI #MachineLearning #Automation #DigitalTransformation #Innovation #MarketTrends

🤖 AI Industry Update: What's Shaping the Future? 🚀 The pace of innovation in artificial intelligence continues to accelerate, with several key trends reshaping the landscape: 🔹 **Generative AI** remains a dominant force, evolving from text and image generation to complex multimodal applications—think video synthesis and interactive agents. 🔹 **AI in Healthcare** is booming, from drug discovery to personalized treatment plans, driven by predictive analytics and improved data interoperability. 🔹 **Edge AI** is gaining traction, enabling real-time processing on devices and reducing latency—critical for IoT, autonomous systems, and smart infrastructure. 🔹 **Ethical & Responsible AI** is now a boardroom priority, with increased focus on transparency, fairness, and regulatory compliance (hello, EU AI Act!). 🔹 **AI-Augmented Development** tools are empowering coders to build faster and smarter, boosting productivity across software engineering. 💡 Opportunities? They’re everywhere: - Upskilling in AI/ML roles remains in high demand. - Startups focusing on niche vertical AI solutions are attracting investment. - Cross-industry collaborations (AI + sustainability, finance, logistics) are unlocking new value. The future is intelligent—stay curious, keep learning, and leverage these shifts to drive impact. #ArtificialIntelligence #MachineLearning #GenerativeAI #TechTrends #Innovation #FutureOfWork

. Infrastructure for AI Deployment in IoT: Gaps and Opportunities 1. Unified view of concepts 1.1 How AI, ML, and AIoT models converge in IoT systems. 1.2 Role of models in AI and ML. 2. Toolchains for deployment 2.1 End-to-end workflow for bringing AI into IoT devices. 2.2 Popular SDKs (do they already exist, or do developers need to create their own?), frameworks, and Model based Systems Engineering. 3. Arm processors in IoT Device 3.1 Capabilities of Arm processors for embedded AI workloads. 3.2 How Arm-based devices support real-time inference in constrained environments. 4. Ease of deployment 4.1 How easy is it for developers to deploy AI in IoT today? 4.2 Do developers need to rely on “roundabout” methods (e.g., ONNX model conversion, custom libraries, or specific methods from silicon vendors)? S Jayakumar PhD Arm Ambassador thanks to co-author Dr. Sanjeev Sarpal https://lnkd.in/gnJeurzR

The AI landscape continues to evolve at a breathtaking pace, with several key trends shaping the industry. Generative AI remains a dominant force, expanding beyond text and images into video, audio, and complex multimodal applications. Meanwhile, AI ethics and governance are gaining prominence as organizations prioritize responsible deployment. Growth areas are particularly strong in healthcare—think drug discovery and personalized medicine—as well as in climate tech, where AI optimizes energy consumption and supports sustainability initiatives. Edge AI is also on the rise, enabling real-time processing for IoT devices and reducing reliance on cloud infrastructure. Opportunities abound for professionals skilled in AI model optimization, MLOps, and ethical AI frameworks. Businesses investing in upskilling their workforce and integrating AI strategically will lead the next wave of innovation. What trends are you most excited about? Share your thoughts below! 👇 #ArtificialIntelligence #AI #MachineLearning #TechTrends #Innovation

🤖 Artificial intelligence is reshaping every industry and unlocking new opportunities. White Paper: The Future of AI 2030 Released by: Intel This report explores how AI is advancing through specialized hardware, edge AI, and responsible development. It highlights opportunities in healthcare, manufacturing, finance, and climate solutions powered by high-performance computing. Key Insights You Need to Know: ⚡ AI hardware accelerators improve training speed and reduce energy costs. 📊 Edge AI enables real-time decision-making in autonomous systems and IoT. 🌍 AI-driven analytics are critical for addressing climate and sustainability challenges. 🔒 Responsible AI frameworks are essential for fairness, transparency, and safety. 💡 Takeaway: The future of AI depends on the synergy of hardware, software, and ethics—driving innovation while ensuring trust. #WhitePaperSeries #ThoughtLeadership #Innovation #AI #EdgeAI #ResponsibleAI #FutureOfTech #ArtificialIntelligence #Intel #IntelInsights

🤖 AI Industry Update: Shaping Tomorrow's Tech Landscape 🚀 The pace of AI innovation continues to accelerate, with several key trends dominating the conversation: 🔹 Generative AI is evolving beyond text and images to multimodal systems, integrating audio, video, and code generation seamlessly. 🔹 AI in healthcare is booming—from drug discovery to personalized treatment plans, the sector is witnessing unprecedented investment and breakthroughs. 🔹 Edge AI is gaining traction, enabling real-time decision-making in IoT devices, autonomous systems, and smart infrastructure. 🔹 Ethical AI and governance frameworks are becoming central, as businesses prioritize transparency and responsible deployment. Growth areas to watch: - AI-driven cybersecurity solutions - Sustainable AI for climate and energy optimization - Hyperautomation in enterprise workflows Opportunities abound for professionals skilled in MLOps, AI ethics, and cross-domain applications. Now is the time to upskill and align with these transformative waves. #ArtificialIntelligence #MachineLearning #TechTrends #Innovation #FutureOfWork

🤖 AI Industry Update: What’s Shaping the Future? The pace of AI innovation continues to accelerate, with several key trends dominating the landscape: 🔹 Generative AI is evolving beyond text and images into video, code, and even 3D modeling—reshaping creative and technical workflows. 🔹 AI in healthcare is gaining momentum, from drug discovery to personalized treatment plans, offering unprecedented precision and efficiency. 🔹 Edge AI is on the rise, enabling real-time decision-making in IoT devices, autonomous systems, and smart infrastructure without relying on the cloud. 🔹 Ethical AI and governance remain critical as regulations tighten globally, emphasizing transparency, fairness, and accountability. Growth areas include: - AI-driven cybersecurity to combat sophisticated threats - Sustainable AI for optimizing energy and resource usage - Hyperautomation across industries to boost productivity Opportunities abound for professionals skilled in AI/ML, data engineering, and ethical AI design. Upskilling in these areas can unlock high-impact roles in tech, finance, healthcare, and beyond. What trends are you most excited about? Share your thoughts below! 👇 #ArtificialIntelligence #AI #MachineLearning #TechTrends #Innovation #FutureOfWork

We're excited to be featured in Unite.AI's Thought Leaders series through the article “The New Digital Divide in AI: Why Edge-Ready, CPU-First Models Will Win the Cost War,” published today! 🔍 This timely piece explores the evolving AI landscape and the advantages of CPU-first approaches in promoting efficiency and equity. Check out these compelling highlights: Why CPU-First AI is Poised to Lead🚀 👉Inference as the True Cost Culprit: Beyond training expenses, it's repeated inference that drives up costs, CPUs provide a smarter, more sustainable alternative to GPU reliance. 👉Empowering Decentralized Deployments: CPUs integrate seamlessly into common devices like laptops and IoT systems, enabling quick, privacy-centric AI without centralized cloud demands. 👉Closing the Access Gap: Heavy GPU needs exclude many, creating divides; CPU-first models open doors for global, inclusive adoption in diverse settings. 👉Focusing on Practical Impact: Shift the measure of AI success to real metrics like energy use, deployability, privacy, and affordability in edge applications. How Shunya Labs is Driving Change🚀 Our work embodies this vision, creating AI that's accessible and effective for real-world needs from healthcare to customer service. We deliver: 👉Efficient, edge-optimized models that minimize costs and cloud dependencies, making AI viable anywhere. 👉Lightning-fast responses under 100 ms, on-device security, coverage for 200+ languages with superior accuracy, and reliability in connectivity-challenged areas. 👉A commitment to equity, empowering startups, clinics, and enterprises with tools that prioritize impact over infrastructure. 🔗 Read here: https://lnkd.in/gQxkNxk7 What's your take on bridging AI's digital divide? Join the discussion in the comments! Ritu Mehrotra Sourav Banerjee #ShunyaLabs #VoiceAI #EdgeAI #CPUFirst #AIDemocratization #InclusiveTech #AIForAll #ThoughtLeadership