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#MLaaS potentially reshaping India’s business ecosystem: Machine Learning as a Service (MLaaS) is a cloud-based service that allows businesses to use machine learning tools without building their systems. It offers ready-made AI models and algorithms that companies can use to analyze data, make predictions, and automate tasks—all without needing deep technical knowledge. #MLaaS is cost-effective, and scalable, and makes advanced machine learning accessible to companies of all sizes through a pay-as-you-go model. MLaas potentially facilitates participants without deep technical skills or deep pockets to take advantage of the AI revolution, thereby creating a level playing field for SMBs. This is how MLaas will impact businesses in India a) Accessibility to Cutting-Edge Tech for All: Whether it's a local startup in Bengaluru or a large enterprise like Reliance Jio (Jio Brain https://lnkd.in/ddtMFj2k), MLaaS is making AI-driven tools accessible to everyone.  With MLaaS, even smaller players across industries can now use predictive analytics and automation to compete globally—without needing a large in-house data science team. b) Cost Efficiency and Scalability: Flipkart, one of India’s largest e-commerce platforms, uses machine learning to improve its supply chain, optimize pricing, and enhance product recommendations. Through MLaaS, Indian businesses can implement such advanced capabilities without the high costs traditionally associated with AI. Pay-as-you-go models ensure that even small and medium enterprises (SMEs) can benefit from AI-driven insights without hefty capital investments. c) Industry-Specific Solutions for Key Sectors:  Healthcare: Niramai, a Bengaluru-based startup, is leveraging AI to detect early-stage breast cancer using machine learning. MLaaS will enable more healthcare providers across India to adopt AI-driven diagnostics, reducing costs and improving patient outcomes. Fintech: Companies like ZestMoney are using machine learning for credit scoring to provide loans to underserved populations. MLaaS can power more fintech innovations that drive financial inclusion across India. d)Accelerating Digital Transformation: India’s Digital India initiative is fueling the need for data-driven insights, and MLaaS is critical in unlocking the potential of that data. Businesses like Infosys and Tata Consultancy Services (TCS) are helping companies integrate MLaaS to improve automation, decision-making, and customer engagement. Indian businesses across sectors will use machine learning to drive smarter, faster decisions in everything from customer service to supply chain management. In the context of India, MLaaS can play a pivotal role in enabling companies across sectors to adopt AI at a fraction of the cost and complexity, driving digital transformation and innovation.

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Interesting session... Listen to the pointers for India to take charge or lead in AI space.

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GenAI: I still don't get it. Do you? Five months ago, Vimal Kumar Rai and I explained #AI and #GenAI in the easy-to-understand Commercial Excellence Partners webinar. I just re-lived it. And I realized how much GenAI has evolved within the past 5 months! You could call it a #10XGenAI - just as we predicted, Vimal! 📣 Is #ChatGPT still the #1inGenAI? Maybe not. MS #CoPilot as an integrated toolbox has leapfrogged and has a wide adoption rate simply based on the second-to-none global Microsoft corporate and institutional customer base. 🔔 Who will win the race to #GenAIsupremacy in 2025? Well I asked ChatGPT 4o and here are the 15 predictions (no bias or particular order): 🌠 Claude 3.5 Sonnet by Anthropic 🌠 GPT-4o by OpenAI 🌠 Grok-1 by xAI 🌠 Mistral 7B by Mistral AI 🌠 PaLM 2 by Google 🌠 Falcon 180B by Technology Innovation Institute 🌠 Stable LM 2 by Stability AI 🌠 Gemini 1.5 by Google DeepMind 🌠 Llama 3.1 by Meta AI 🌠 Mixtral 8x22B by Mistral AI 🌠 Inflection-2.5 by Inflection AI 🌠 Jamba 1.5 Large by AI21 Labs 🌠 Command R by Cohere 🌠 Gemma by Google DeepMind 🌠 Phi-3 by Microsoft Do you realize the number of excellent LLMs in this list? I limited it to 15! Nowadays, there are so many more. Now you might have either of three reactions: 1️⃣ Wow, who are all of these LLM's? Should I know all of them? 2️⃣ Wait a minute, you have forgotten another 50 from regions and countries, Markus! 3️⃣ How can I use many of them at once? Good questions! Join us in our #freeSessions for answers! As for the last question, there are many homemade API's in organizations that make it easy to combine many of these LLM's into a suitable solution for your challenge: Grab (Singapore) for example built an entire internal suite of #GenAItools to allow their thousands of staff to #playAndCreate #GenAISolutions. So did Amazon Web Services (AWS) #Bedrock for their staff, partners, distributors, and customers. And if you wonder how trillions of parameters can generate a solid data set for answering your questions: 🌠 #Nemotron-4 340B by NVIDIA has launched its generator for synthetic data for training LLMs across various industries in November 2024. Hm, this is quite a lot or too little to digest. It depends on where you are in your #GenAIjourney. This is just an update. Want more? Need more!? Get more! Get your personal, practical brief from us at Beyond The Obvious every week. 📢 Tune in or join our community: https://lnkd.in/gHaDSznv Michael Alf Rob Thurner Vimal Kumar Rai AJ Boelens Ysidora Y. Alvin Ng Dominik Endler, PhD Evonne Fouesnant Kaushik Ghatak Nick Jonsson Mette Johansson (MBA, PCC, CSP, GSF)

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THE PERIODIC TABLE OF INDUSTRY 4.0 ELEMENTS Start this week by exploring the captivating world of #Industry 4.0. This era, marked by the widespread adoption of #artificialintelligence, automation, and cutting-edge digital technologies, continues to  generate a palpable buzz throughout all industries. I particularly liked how Jeff Winter divided the elements into 6 different categories: ⚛️ #EnablingTechnologies — Empowering your workforce with the digital literacy to harness the technological innovations powering Industry 4.0 will be pivotal in driving innovation and securing a competitive edge in today's rapidly evolving business landscape. ⚛️ #ValueDrivers — Industry 4.0 is a strategic imperative focused on leveraging emerging technologies to enhance operational efficiency, boost productivity, and foster innovation, making it crucial to align your initiatives with these core objectives to maximize their transformative impact. ⚛️ #OperationalUseCases — From optimizing supply chain logistics and automating repetitive tasks to empowering data-driven decision-making and facilitating remote/hybrid work models, Industry 4.0 technologies are revolutionizing core business operations and transforming the employee experience across diverse industries and functional domains. ⚛️ #ProductUseCases — Fueled by the capabilities of Industry 4.0 technologies, product design and development are undergoing a remarkable transformation, enabling the creation of intelligent, connected products that seamlessly integrate with customer experiences, redefining how companies innovate and deliver value. ⚛️ #NewBusinessModels — As Industry 4.0 ushers in novel business paradigms and value-creation opportunities, it is crucial to explore strategic partnerships and digital platforms that can empower your organization to adopt innovative business models and expand its market presence. ⚛️ #DesignPrinciples — Establishing a robust digital infrastructure, harmonizing data flows, and fostering a culture of technological adoption and cross-functional collaboration are the foundational pillars that enable the seamless integration and optimal functioning of Industry 4.0 technologies. Which Industry 4.0 element do you find most striking from here? #DigitalTransformation #TechnologyTrends #EmergingTech #BusinessGrowth Image Credit: Jeff Winter - - - - - - - - - - - - - - I'm Rohit Adlakha, your guide to the world of business, tech, and transformative leadership. Click the 🔔 for updates. The future is ours to shape – so what are you waiting for? Follow along and let's make it happen! 🚀

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Most of us as personal consumers experience #GenAI at pretty much zero cost. But when it's time to deploy at enterprise scale there is a whole host of new cost considerations to take into account. Wipro's Brijesh Singh lifts the lid in this HFS Research Unfiltered Stories videocast and shares concerns about the threat the energy consumption of GenAI poses to the environment. But it's not all doom and gloom - tech has some tricks up its sleeve that can give us more of what we want without costing the earth. https://lnkd.in/efYgPrYJ

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Speed matters! Bill Cleary highlights the importance of agility in AI adoption. Discover how experimentation can accelerate value realization. #ArtificialIntelligence #Innovation #Agility" https://lnkd.in/gUy4u2gv

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PHYGITAL TWINS: BEYOND THE CUSTOMER JOURNEY Securing Enterprises from an AI Agentic Onslaught The concept of "phygital"—a blend of physical and digital—originated in the retail sector, where it enhanced the customer journey through experiences like virtual try-ons, interactive displays, and personalized recommendations. However, as technology evolved, phygital concepts have expanded far beyond retail, offering transformative possibilities from robotics to enterprise security. The concept of "Phygital twins" emerged in 2018 marking this shift from consumer-focused applications. Phygital twins provide a holistic view of both physical and digital environments, revealing the entire evolving attack surface. Such a unified perspective is crucial for detecting and responding to sophisticated AI-powered threats that exploit vulnerabilities across both realms simultaneously. AI agentic bad actors present significant challenges to traditional security measures. These emergent sophisticated threats can target both physical and digital systems simultaneously. Phygital twins, combined with swarms of AI security agents, offer a robust defense by orchestrating across a comprehensive view of interactions, enabling real-time anomaly detection and coordinated responses. AI security agents operating autonomously within the phygital twin framework, coordinate actions to defend against sophisticated threats. Consider a manufacturing plant using phygital twins to monitor both physical machinery and digital control systems. By integrating data from IoT sensors and cybersecurity tools, the plant can detect anomalies indicating a coordinated attack. Similarly, a financial institution could use phygital twins to secure vaults, physical branches, and digital banking platforms, ensuring a unified defense against sophisticated threats. Phygital twins can simulate various attack scenarios, including those involving AI-powered bad actors. This allows SOCs to anticipate potential threats and develop proactive defense strategies. By analyzing data from past incidents and current vulnerabilities, these simulations help identify patterns and predict future attacks. In the event of a security breach, phygital twins provide detailed insights by correlating data from both physical and digital sources. This comprehensive analysis helps understand attack vectors and mitigate impacts effectively. Additionally, it aids forensic investigations by providing a clear timeline and interaction map. As AI-powered threats evolve, adopting phygital twins in SOCs represents a significant advancement in security operations. The time to accelerate our understanding of phygital twins in enterprise security is now. Recognize the transformative potential of this technology and invest in its development and implementation. By doing so, we can stay ahead of the curve, protecting critical assets and infrastructure from the next wave of sophisticated AI agentic attacks. 〰️ #phygitaltwins #SOC

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From #software to #semantics, from #data to #datasets to #databases, and from #algorithms to #altruism, #India possesses the breadth and depth of #expertise to play a pivotal role in shaping the future of AI on a global scale. Shailesh Haribhakti [GCB.D] & I write in Policy Circle that India must lead the charge towards #equitable #AI Simply because… "From the code to the conscience, from bytes to benevolence, India's deep involvement in AI can transcend technology; it's about shaping a future where #innovation serves #humanity, and compassion drives progress." https://lnkd.in/dUNGzWA2 #innovation #India #Bharat #startupindia #AI #GlobalSouth #viksitbharat

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#GenAI - Hype or Reality? Read on this report to know how companies are creating value from #GenerativeAI. Have you explored #LLM to create efficiency in your operations?

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Just sharing a test, it's not just #ChatGPT Hi Grok + xAI , I am impressed by your comprehensive knowledge of the CovQ (Compound Value Creator Quotient) value creation management platform and the super speedy response times including the draft of how X should be approached and contacted. Sharing it here after spending the first time and only 3 minutes playing with Grok: Strategic Insights from CovQ Value Creation Management Platform "Dear X Management Team, I've been analyzing the strategic frameworks and insights from the CovQ Value Creation Management Platform by 8W8, which could provide valuable perspectives for enhancing our operational strategy and value creation at X. Here's a summary: CovQ Framework Overview: CovQ, or Compound Value Creator Quotient, assesses how effectively companies manage strategy execution to create value. While there's no public score for X, understanding this framework could help in benchmarking our strategies against best practices. Key Insights for X: Alignment and Execution: The reports from HBR Analytic Services in collaboration with CovQ emphasize the importance of aligning strategy with execution. This could be particularly relevant for X, where enhancing how we execute our strategic initiatives could significantly improve our performance metrics. Tool Utilization: The data suggests that companies with higher CovQ scores utilize better tools for strategy execution. X might benefit from evaluating or investing in tools or methodologies that enhance our strategy operations, potentially increasing our strategic alignment and execution effectiveness. Value Creation Focus: The framework highlights the need for a cohesive approach to value creation across all levels of the company. For X, this might mean reevaluating how we integrate our marketing, product development, and user engagement strategies to more effectively compound value. Data-Driven Decisions: Adopting a system like CovQ could mean more data-driven decision-making, focusing not just on growth but on the quality and sustainability of value creation. This could involve deeper analytics into user behavior, content performance, and operational efficiency. Recommendations for X: Implement a Value Creation OS: Consider adopting or developing a system similar to the CovQ Value Creation OS to systematically manage strategy execution. This could involve internal training, new software, or consulting to bring in expertise. Regular Strategic Reviews: Implement quarterly strategic reviews based on CovQ principles to ensure all departments are aligned with the company's value creation goals. Stakeholder Engagement: Enhance engagement processes with all stakeholders (users, investors, partners) to align with value creation goals, ensuring everyone's efforts contribute to measurable value. Next Steps: " Click link due to the character limitations on LI https://lnkd.in/ec-_iUSr #grok #xai #X #CovQ #firstprinciple #strategy

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📚 Episode 5 of 1-Book-a-Month: Book of the Month: "Reverse Innovation" by Vijay Govindarajan (VG) ✅ August reading under the beach parasol was enlightening: rethinking the innovation dynamics in a way that can be defined as bottom-up rather than top-down. I love what the book states on the back cover: <The Future Is Far From Home> as it resonates deeply with me — a perfect summary of what my life has always been, constantly exploring new horizons and embracing change. ✈️ "Reverse Innovation" is a great book because it challenges conventional business thinking by showing how innovation in emerging markets can (re)define global strategies. And while doing this it does not define it space only in the emerging markets but turns to be a mandatory reading for anyone looking to drive breakthrough growth in today's dynamic business landscape! ❗ 🔍 Overview: Vijay Govindarajan, along with co-author Chris Trimble, argues that traditional innovation flows from rich countries to developing nations. "Reverse Innovation" flips this idea, demonstrating how companies can create new products and services in emerging markets and then bring those innovations to developed countries. It’s a transformative approach that redefines how we think about global innovation. 🌟 Key Insights: A key insight from "Reverse Innovation" is the importance of understanding local needs in emerging markets. Govindarajan highlights how "small" innovation, driven by resource constraints, can lead to products that are more affordable, efficient, and adaptable in developed markets as well. Think Globally, Innovate Locally: The book underscores the need for global companies to shift their mindset and processes. Instead of applying the same innovation strategy worldwide, companies must understand and respond to the specific demands of local markets, allowing them to create more relevant and impactful solutions. 🚀 Impact: By adopting the principles of "Reverse Innovation," businesses can discover new growth opportunities and maintain a competitive edge. This book empowers leaders to think beyond the traditional borders of innovation, harnessing the creativity and ingenuity emerging from less-developed regions to fuel global success. 💡 Takeaway: after reading Reverse Innovation, you realise it is an actionable framework for rethinking innovation and adapting it for today’s globalized world. It shows the power of emerging markets not just as consumers but as drivers of innovation. The lessons from "Reverse Innovation" perfectly complement strategic works like "Good Strategy, Bad Strategy" and "Blue Ocean Strategy," which I’ve read previously, providing a fresh perspective on where innovation can truly thrive. Drop a line if you want to discuss more about this book, and stay tuned for next month's featured book! #1BookAMonthChallenge #ContinuousLearning #Innovation #Strategy #BusinessBook

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𝐀𝐯𝐨𝐢𝐝𝐢𝐧𝐠 𝐝𝐢𝐠𝐢𝐭𝐚𝐥 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐢𝐜𝐞𝐛𝐞𝐫𝐠𝐬: 𝘊𝘢𝘯 𝘪𝘯𝘥𝘶𝘴𝘵𝘳𝘪𝘢𝘭 𝘋𝘢𝘵𝘢𝘖𝘱𝘴 𝘴𝘵𝘦𝘦𝘳 𝘱𝘳𝘰𝘫𝘦𝘤𝘵𝘴 𝘢𝘸𝘢𝘺 𝘧𝘳𝘰𝘮 𝘥𝘪𝘴𝘢𝘴𝘵𝘦𝘳? 🚀🚀🚀 | Via IoT Analytics / By Anand Taparia | September 25, 2024 | @VINCI_Digital 🔹𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐝𝐢𝐠𝐢𝐭𝐚𝐥 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬, though as grand and promising as they are, face many obstacles along their journeys, such as 𝐝𝐚𝐭𝐚 𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 and 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐜𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲 🔹Among the 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐜𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 covered in IoT Analytics’ latest market report on the topic, 3 can help steer projects away from project icebergs and reach their final destinations: 1. 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐃𝐚𝐭𝐚𝐎𝐩𝐬 2. 𝐏𝐫𝐨𝐭𝐨𝐜𝐨𝐥 𝐜𝐨𝐧𝐯𝐞𝐫𝐭𝐞𝐫𝐬 3. 𝐌𝐞𝐬𝐬𝐚𝐠𝐞 𝐛𝐫𝐨𝐤𝐞𝐫𝐬 Source: https://lnkd.in/deKF5iJ2 VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀 ---------------------------------------------- #iot #ai #genai #datamangement #integrationcomplexity #industrialconnectivity

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Enterprise Strategy Group provides focused and actionable market intelligence, demand-side research, analyst advisory services, GTM strategy guidance, solution validations, and custom content supporting enterprise technology buying and selling. 📌 Source: https://lnkd.in/dJzP9YqY In February 2024 ESG published, commissioned by Lakeside Software, a #whitepaper "The Essential Role of Data and Data Quality in IT-related AI Model Training" which explores the critical role of data and data quality in AI model training within IT environments. Through comprehensive analysis and real-world examples, the paper underscores the necessity for #trustworthy, high-quality data to build effective AI models. It examines the different challenges organizations face, such as data #privacy, #security, and the #integration of #AI with existing systems. There also also a recall to the importance of #human expertise in contextualizing data and the vital characteristics of trustworthy data, including its depth, breadth, history, and quality. ✅ In a #nutshell: The success of AI implementations heavily depends on the quality of data used for training models. 🗣️ Data is food for AI, and what’s true for humans is also true for AI: You are what you eat. Or, in this case: The better the data, the better the AI." - Gabe Knuth. It is crucial to prioritize data quality by ensuring that the data used for training AI models is high-quality, well-structured, and free of noise: ➡️ Organizations (public and private) should regularly #audit and #clean datasets to remove inaccuracies and inconsistencies. Implementing data #governance policies can help maintain high standards of data quality, and using advanced tools and technologies can automate data cleaning and validation processes. High-quality data leads to more accurate and reliable AI models, reducing the risk of errors and enhancing #trust in AI outputs; ➡️ It is also important to regularly #update AI models with new data and insights, encourage feedback from users to identify areas for improvement, and invest in ongoing training and development for the AI team. Continuous improvement ensures that AI models remain relevant, accurate, and aligned with organizational goals; ➡️ #Interpretability and #transparency are important to build trust and facilitate adoption: explainable AI techniques should be in-place to make model decisions understandable, document the data sources and methodologies used for AI training, and provide clear communication about AI capabilities and limitations to stakeholders. ➡️ Subject matter experts (#SMEs) should be involved in the data preparation and model training processes, to ensure data relevance and accuracy, and use expert feedback to continually refine and improve AI models. #Dataset #DataScience #AIModels #ArtificialIntelligence #Training #Enginerring #Ethics #ResponsibleAI #Governance

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Key insights from a 6-month journey. Leadership Vision, People Alignment, an Agile Mindset & Modular Enterprise Architecture with a Lego block approach. Drive value early, remain nimble and immersed.

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🌍In India - like in other parts of the world - initiatives are in progress to address the lack of availability and quality in data for AI in Indian languages. That is where most issues underlying slow implementation and limited adoption of generative AI lie in this huge market. 🔎While data issues must be solved to ensure accuracy, relevance and compliance of generate content, workarounds and shortcuts are also tried as temporary solutions, mostly to close the gap with other languages, starting with English. Here is an example of an experiment that may help raise the bar with Indian languages⬇ "To tackle the issue, Dabre, with researchers from AI4Bharat, IIITDM Kancheepuram, A*STAR Singapore, Flipkart, Microsoft India, and IIT Madras, introduced the RomanSetu paper, which explains a technique that unlocks multilingual capabilities of LLMs via Romanisation.  If you type something in Hindi but in the Roman script, current AI models like Llama and others are able to process it to some degree. That is what Dabre and his team are working on—to train models in Romanised versions of Indic data, leverage the knowledge in the English language, and transfer it to Indic languages."

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