Anjum Javed

Large Language Models for Knowledge Graph Completion Class membership relations are critical components of knowledge graphs (KGs) that assign entities to given classes, and help KGs represent classification schemes which have significant effects on social policy and scientific consensus. Evaluation of these relations is necessary, but expensive as it is manually performed. This article evaluates the abilities of several large language models (LLMs) to evaluate class membership relations in a zero-shot manner.   Article link: https://lnkd.in/gxH4pttf 🔹To evaluate KG relations, knowledge engineers must translate natural language from domain experts into symbolic representations, then check if the knowledge is properly reflected in a KG. LLMs can use natural language directly when given descriptions of an entity and a KG class, to predict if the entity is an instance of the class. 🔹The authors determined LLMs’ abilities to do this effectively by studying if LLMs could detect missing or incorrect relations. They constructed evaluation datasets from the Wikidata and CaLiGraph KGs and evaluated seven LLMs, including OpenAI’s GPT-4 and Meta’s Llama-2. 🔹It was found that LLMs and KGs were well-aligned, meaning KGs could effectively address knowledge gaps in LLMs and LLMs could similarly do so for KGs. The LLMs that were evaluated also displayed abilities to detect missing or incorrect KG relations. Moreover, when analysing the LLMs’ classification errors, it was found that 40.9% of the errors were attributed to the KGs themselves, which had missing or incorrect relations. A further 29.1% of errors were due to insufficient data in entity descriptions. 🔹LLMs have demonstrated good performance across many tasks, and now display their capabilities to assist knowledge engineers in KG evaluation and refinement as well. However, they still face some challenges like slow speed of processing tasks and costly API calls, which future efforts could target by using locally deployed LLMs and sampling approaches. Add additional points if needed, for instance, about limitations or problems. 📑 Allen, B. P., & Groth, P. T. (2024). Evaluating Class Membership Relations in Knowledge Graphs using Large Language Models (Version 1). arXiv. DOI: 10.48550/ARXIV.2404.17000 📌 Ensuring the completeness and correctness of KGs has been a limiting factor in the widespread employment of KGs across applications. LLMs have previously been used to optimise KG construction, and now, they show their abilities to perform KG refinement as well, thus easing the burden of knowledge engineers.

2

📝𝐀𝐖𝐒 𝐫𝐞:𝐈𝐧𝐯𝐞𝐧𝐭 𝟐𝟎𝟐𝟒 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: 𝐒𝐰𝐚𝐦𝐢'𝐬 𝐍𝐨𝐭𝐞 Have you ever wondered what the future of AI and data looks like? 🤔 𝐃𝐫. 𝐒𝐰𝐚𝐦𝐢 𝐒𝐢𝐯𝐚𝐬𝐮𝐛𝐫𝐚𝐦𝐚𝐧𝐢𝐚𝐧’𝐬 𝐤𝐞𝐲𝐧𝐨𝐭𝐞 𝐚𝐭 𝐀𝐖𝐒 𝐫𝐞:𝐈𝐧𝐯𝐞𝐧𝐭 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐬 𝐚 𝐜𝐫𝐲𝐬𝐭𝐚𝐥-𝐜𝐥𝐞𝐚𝐫 𝐯𝐢𝐬𝐢𝐨𝐧! Packed with insights and actionable takeaways, it’s a must-watch for anyone in the tech and data space. But don’t worry if you missed it—here’s everything you need to know in just a few minutes! ⏱️ 𝟭. 𝐀𝐈 𝐚𝐧𝐝 𝐌𝐋: 𝐁𝐫𝐞𝐚𝐤𝐢𝐧𝐠 𝐁𝐚𝐫𝐫𝐢𝐞𝐫𝐬 AI adoption is now easier than ever! 🔹 AWS democratizes machine learning with tools that are user-friendly and scalable. 🔹 Businesses of all sizes can now leverage AI to streamline operations and make smarter decisions. 𝟮. 𝐓𝐡𝐞 𝐏𝐨𝐰𝐞𝐫 𝐨𝐟 𝐃𝐚𝐭𝐚 Data is the fuel for innovation, and AWS is unlocking its potential: ✔️ Real-time processing capabilities and seamless integration with advanced analytics. ✔️ Key innovations include enhanced data lakes, storage, and analytics tools. 𝟯. 𝐒𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐂𝐨𝐦𝐩𝐥𝐞𝐱𝐢𝐭𝐲 Scaling machine learning is no longer daunting. AWS’s latest MLOps tools simplify workflows, enabling faster deployments and results. 💡 𝐖𝐡𝐲 𝐢𝐭 𝐦𝐚𝐭𝐭𝐞𝐫𝐬: The future of AI and data is here. AWS is equipping businesses with the tools to innovate, scale, and thrive. 📖 𝐑𝐞𝐚𝐝 𝐦𝐨𝐫𝐞: Check out the full article https://lnkd.in/gqNyMzDn 💬 𝐋𝐞𝐭’𝐬 𝐝𝐢𝐬𝐜𝐮𝐬𝐬: How are you using AI, ML, and data in your organization? Share your thoughts! #𝐀𝐖𝐒 #𝐀𝐈 #𝐌𝐚𝐜𝐡𝐢𝐧𝐞𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 #𝐃𝐚𝐭𝐚𝐒𝐜𝐢𝐞𝐧𝐜𝐞 #𝐓𝐞𝐜𝐡𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 #𝐫𝐞𝐈𝐧𝐯𝐞𝐧𝐭

4

🚀 Tackling Interoperability Challenges in Enterprise AI Ecosystems Interoperability is crucial for seamless AI integration within enterprises. In this conversation Shivakumar Krishnamurthy, the co-founder of Prescience Decision Solutions highlights the layered approach needed to address these challenges. Watch the complete conversation https://lnkd.in/gtBtq_9u to know about #interoperability challenges as well as other important discussions like: 1. AI Governance Framework by DeepMind. 2. Practical Integration of Governance Processes. 3. Meta, Google, and Microsoft adopting comprehensive evaluation strategies 4. Importance of continuous evaluations and the involvement of external researchers for enhancing AI model safety and reliability. Link to the podcast 🔗 https://lnkd.in/gtBtq_9u #AI #EnterpriseAI #Interoperability #DataIntegration #Standardization #APIs #TechInnovation #PrescienceDecisionSolutions #AIConnect #AIPodcast #AItrends #Prescience

36

Thanks nasscom ai for creating this platform to share and learn new things. Thanks to fellow panelist Ankit Bose Subram Natarajan Padmashree Shagrithaya for enlightening me from your thoughts

42

Revised Evaluation of LLM Compression Using Distance Metrics Researchers from Microsoft Research, India, propose an advanced evaluation framework incorporating distance metrics like KL-Divergence and percentage flips alongside traditional accuracy metrics. https://is.gd/MDzsSN #ai #aitechnology #artificialintelligence #llm #llmcompression #machinelearning

1

1 Comment

"𝐔𝐥𝐭𝐢𝐦𝐚𝐭𝐞 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐒𝐜𝐢𝐤𝐢𝐭-𝐋𝐞𝐚𝐫𝐧"🎉 Authored by- Parag Saxena Technically reviewed by - Dr. Alok Tiwari (Ph.D, IIT-BHU) ✳ 𝐁𝐔𝐘 𝐍𝐎𝐖! ✳ 👉 AVA™: [https://lnkd.in/gECvrWh2] 👉 Amazon International: [https://rb.gy/wpyaja] 👉 Amazon India: [https://rb.gy/sfdj1e] #MachineLearning #ScikitLearn #DataScience #Python #AI #ML #DataAnalysis #PredictiveModeling #DataMining #ArtificialIntelligence #Programming #Technology #Coding #DataAnalytics #DataPreprocessing #FeatureEngineering #ModelTraining #ModelEvaluation #Deployment #Algorithm #DataInsights #PatternRecognition #DataVisualization #AVA #Orangeava #Publishers #itandsoftware #Sneakpeek

51

The most neglected domain of knowledge in formal academia and even by individuals . we ourselves hardly make efforts to learn shastras which are basic prerequisite of our svadharma purushartha and therefore we hardly pass it on to our next generation.. https://lnkd.in/gigaGFhx

1

Dive into the realm of Machine Learning (ML) through the insightful lens of Navaneet Mishra, Senior Vice President and Head of Hexagon R&D India, as he delves deep into the transformative power of ML. Gain valuable insights into the nuances distinguishing Artificial Intelligence, Generative AI, and ML, unravelling their roles in shaping our digital landscape. Click to know more: https://shorturl.at/jDFJK #MachineLearning #ArtificialIntelligence #GenerativeAI #TechInsights #TransformativeTechnology #

1

How do you get to a quantized model when you start out from a standard model? Arun Nanda looks into the nitty-gritty details of several quantization approaches for neural network models.

6

Moveworks - Pioneering #AI-driven Workplace #Automation  Authors: Manoj Joshi and Shraddha Gulati (Scholar Indian Institute of Information Technology Lucknow #TheBigQuestion: Moveworks integrates with existing communication tools. Can they expand their functionality to become a more comprehensive workplace platform, potentially disrupting existing enterprise software solutions in a #VUCAworld ? Moveworks is at the forefront of AI-driven workplace automation & #innovation, revolutionizing employee support and organizational efficiency. #TechnoEntrepreneurship by visionary founder leaders Jiang Chen, Bhavin Shah, Varun Singh, and Vaibhav N., the enterprise aims to transform the employee experience through seamless #AI-powered assistance solutions. This entrepreneurial and Innovative enterprise envisions a future where every worker has access to #AI-powered support solutions, enhancing #productivity and work satisfaction. Their mission is to leverage cutting-edge AI technology to automate repetitive tasks, provide self-service capabilities, and empower support staff to focus on strategic work. Since its inception in 2016, Moveworks has made significant strides, serving over 5 million workers at more than 300 top-tier corporations globally. Their AI-powered platform has delivered transformative value, including a 256% return on investment and $11 million in savings over three years. Looking ahead, this enterprise plans to expand its market presence, innovate its product offerings, and foster strategic partnerships to drive continued growth and innovation in the AI-driven employee assistance space. The inception story of Moveworks underscores creative leadership and a commitment to revolutionizing workplace dynamics. Founded in 2016, Moveworks was established after a close study of the challenges employees faced in accessing timely assistance and resolving work-related issues within businesses. This acknowledgement laid the foundation for using cutting-edge AI technology to enhance employee satisfaction and expedite support operations. Moveworks sets itself apart with a strategic business plan and innovative marketing strategies driving growth and innovation. Through targeted #content #marketing, thought #leadership initiatives, #strategic alliances, and #customer advocacy maintains a market presence and delivers cutting-edge solutions to enhance the employee experience with a #strategicforesight. #VUCA Challenges: #Volatility: Rapid shifts in market trends and technology advancements. #Uncertainty: Changing customer demands and economic fluctuations. #Complexity: Managing global operations and diverse customer needs. #Ambiguity: Interpreting market signals and navigating regulatory landscapes Katyayni Joshi Singapore Management University Benjamin Finzi Jagdish Shettigar Surendra Rosha Sun Sun Lim Sunil Shukla Huijin Kong harvard business review Archana Shukla Linda Hill Lindy Greer Reena Dayal Dr. Arun Mohan Sherry

25

1 Comment

🎯 Open Source Data Platforms: From Complexity to Clarity An excellent presentation by Priyanka Naik on building robust data platforms using open source tools. Key insights shared: 📊 Transitioning from batch to real-time streaming 🔄 Modular architecture for better maintainability 🎯 Data catalogs for non-technical user engagement ⚡ Apache Camel connectors for optimized Kafka workflows With 17 years of experience, Priyanka offered valuable perspectives on data democratization and quality management in modern architectures. Watch here: https://lnkd.in/gPcm8sZs #DataEngineering #OpenSource #Kafka #DataPlatform #Engineering

1

This interview of Mr. C. Sivasankaran, one of India's finest thinkers and ace businessmen, by Mr. Raj Shamani, one of my favourite YouTubers, is a great learning resource for all of us. I am thankful to both of them for great interview. I was one of the beneficiaries/ user of Mr. Sivasankaran's Aircel telecom service provider's service. Aircel's very small denomination recharge voucher of Rs.14 for 3 days unlimited internet was poor man's cow to me as we didn't have today's cost effective mobile combo plans at that time. I used to recharge with Rs.14 voucher for unlimited internet, most importantly for downloading big softwares from official websites of Microsoft, Oracle, etc. But unfortunately, Mr. Sankaran's one mistake put my old man's cow to an end. He has discussed that issue here. Apart from that, there are many lessons we can learn from this interview. I am sure that Mr. Sivasankaran's new venture of bio hacking or wellness will make a road to his comeback. All the best to him. Ace thinkers never stop their journeys and they continue to benefit large masses. And this is happening with Mr. C. Sivasankaran too.

4

Interested in quantization? Arun Nanda's article introduces this technique and sets the stage for exploring the journey from simpler models like BERT to advanced 1.58-bit LLMs. #LLM #ML

23

"If you think of AI, ML, and how it's entering the future, think about it in three ways," says Rahul Kulkarni, Chief Technologist at Samagra | Transforming Governance. That whole range of cognitive AI is yet to take off, but there are a lot of generative AI and interpretative AI use cases in the industry right now, he adds. Tune in as he breaks down the types and how they function, and share your take — what's the top AI use case you've observed in your industry? #LinkedInVideo

489

20 Comments

Watch Dinesh Chandrasekhar discuss the transformative power of AI in managing unstructured data through large language models (LLMs) with GAI Insights. He demonstrates how Unstract's AI-driven tools are revolutionizing business processes like mortgage processing and insurance claims by automating data extraction from complex documents. The session highlights the benefits of generative AI in:  - Reducing human error  - Improving customer experiences  - Lowering operational costs Watch the session here: https://lnkd.in/gCuAE6Py

11

Paanduv Applications Launching Quant Pracar: Democratizing Quantum AI Education in India Register for software access (Free): https://lnkd.in/gYf-_JqC (Note: For a live demo join our webinar: https://bit.ly/3NvJczp) GET READY! to enter the exciting world of Quantum Artificial Intelligence (AI)! Paanduv Applications, a leader in scientific software development, has announced the launch of Quant Pracar, the educational software designed specifically for quantum machine learning. Quant Pracar's mission is to make quantum computing accessible to everyone. This innovative software offers students and professionals a unique opportunity to: -Engage with cutting-edge quantum machine learning algorithms: Dive deep into the world of quantum AI and explore its potential to revolutionize various fields. -Learn by doing: Upload your own datasets and train them using quantum machine learning techniques, gaining practical experience with this revolutionary technology. -Embrace open-source and cross-platform support: Quant Pracar's commitment to open-source development ensures everyone has access to this powerful tool. Additionally, its cross-platform compatibility makes it usable on a variety of devices. This launch marks a significant step towards democratizing quantum computing in India. By fostering widespread interest and equipping users with the necessary skills, Paanduv Applications aims to position India as a leader in quantum computing software development. Are you ready to embark on your quantum AI journey? Stay tuned for more information on the official release of Quant Pracar by Paanduv Applications! #quantum #AI #machinelearning #technology #innovation #engineering #quantumcomputing

10

Join me and 30+ experts at the must attend event in India... Gartner's IT #GartnerSYM 2024 November 11th to November 13th. I will be conducting sessions on #CEO Priorities 2025: The Year of Dynamic Capacity; How to Present #AI to the Board; and What #CIOs can Learn from High-Growth Companies. I look forward to seeing you there. #GartnerSYM #India #Kochi #CIO #ITLeaders #AI #DigitalTransformation #Disruption #StrategicTechnology

25

1 Comment

QUANT PRACAR by Paanduv Applications - Democratizing Quantum AI Education. Register for software access (Free): https://lnkd.in/gYf-_JqC (Note: join our webinar on Quantum AI: https://bit.ly/3NvJczp) Quant Pracar's mission is to make quantum computing accessible to everyone. This innovative software offers students and professionals a unique opportunity to: -Engage with cutting-edge quantum machine learning algorithms: Dive deep into the world of quantum AI and explore its potential to revolutionize various fields. -Learn by doing: Upload your own datasets and train them using quantum machine learning techniques, gaining practical experience with this revolutionary technology. -Embrace open-source and cross-platform support: Quant Pracar's commitment to open-source development ensures everyone has access to this powerful tool. Additionally, its cross-platform compatibility makes it usable on a variety of devices. Are you ready to embark on your quantum AI journey? Stay tuned for more information on the official release of Quant Pracar by Paanduv Applications! #quantum #AI #machinelearning #innovation #quantumcomputing

7

𝐓𝐡𝐞 𝐏𝐨𝐰𝐞𝐫 𝐂𝐨𝐦𝐛𝐨 𝐨𝐟 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 𝐚𝐧𝐝 𝐭𝐡𝐞 𝐌𝐨𝐝𝐮𝐥𝐚𝐫 𝐃𝐚𝐭𝐚 𝐒𝐭𝐚𝐜𝐤: 𝐀𝐈 𝐭𝐡𝐚𝐭 𝐑𝐞𝐚𝐬𝐨𝐧𝐬 In this latest edition, Animesh Kumar, Brij Mohan Singh, and Ritwika C. explore the evolution of AI from LLMs (Large Language Models) to more sophisticated AI agents capable of reasoning, autonomy, and adaptive problem-solving. 𝐊𝐞𝐲 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬: 💠 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬: 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐭𝐡𝐞 𝐑𝐨𝐥𝐞 𝐨𝐟 𝐀𝐈 𝐢𝐧 𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞𝐬 AI Agents are the next frontier in enterprise AI, transforming from simple large language models (LLMs) to sophisticated, reason-driven systems. These agents don't just provide answers but deliver purpose-driven actions that align with business goals, making AI a more valuable strategic partner in enterprise innovation. 💠 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰 𝐨𝐟 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬: 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐓𝐡𝐫𝐨𝐮𝐠𝐡 𝐌𝐨𝐝𝐮𝐥𝐚𝐫 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 AI Agents are built on a modular architecture where each component, such as an LLM, handles a specific task within a larger workflow. This setup makes them exceptionally good at breaking down complex problems into manageable parts. 💠 𝐂𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐜𝐲 𝐢𝐧 𝐃𝐞𝐬𝐢𝐠𝐧: 𝐀𝐥𝐢𝐠𝐧𝐢𝐧𝐠 𝐀𝐈 𝐚𝐧𝐝 𝐃𝐚𝐭𝐚 𝐒𝐭𝐚𝐜𝐤𝐬 The power of design in AI agents comes from a consistent, modular approach that spans both AI and data stacks. Just as Apple's minimalist design philosophy permeates every layer of its ecosystem, aligning the data and AI layers creates a cohesive structure that supports transparency, efficiency, and a high degree of adaptability in AI systems. 💠 𝐋𝐋𝐌 𝐋𝐢𝐦𝐢𝐭𝐚𝐭𝐢𝐨𝐧𝐬: 𝐓𝐡𝐞 𝐍𝐞𝐞𝐝 𝐟𝐨𝐫 𝐀𝐠𝐞𝐧𝐜𝐲 𝐚𝐧𝐝 𝐑𝐞𝐚𝐥-𝐓𝐢𝐦𝐞 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐌𝐚𝐤𝐢𝐧𝐠 Traditional LLMs often fall short due to limited interactivity with real-world systems, resulting in generic or incomplete solutions. AI agents fill this gap by taking proactive, context-driven actions, allowing real-time decision-making that traditional LLMs cannot achieve, ensuring a more accurate and timely output for critical tasks. 💠 𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬: 𝐅𝐫𝐨𝐦 𝐑𝐞𝐟𝐥𝐞𝐱 𝐭𝐨 𝐔𝐭𝐢𝐥𝐢𝐭𝐲-𝐁𝐚𝐬𝐞𝐝 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐌𝐚𝐤𝐢𝐧𝐠 AI agents come in various forms, each suited to different types of tasks. Simple reflex agents provide basic reactions, while utility-based and goal-based agents excel in complex environments by prioritizing goals or optimizing outcomes. 𝐑𝐞𝐚𝐝 𝐭𝐡𝐞 𝐞𝐧𝐭𝐢𝐫𝐞 𝐛𝐥𝐨𝐠 𝐡𝐞𝐫𝐞: https://lnkd.in/dw3Htg8a 📢 Do share what you feel about this take! 🗣️ 𝐒𝐡𝐨𝐮𝐭 𝐨𝐮𝐭: At MD101, we actively collaborate with data experts to bring the best resources to a blooming community of data practitioners. If you are willing to share an insightful perspective on anything about data, we’re all ears!! Note: All submissions are vetted for quality & relevance. 🔔 Follow 𝐌𝐨𝐝𝐞𝐫𝐧 𝐃𝐚𝐭𝐚 101 and stay updated with our weekly highlights from the modern data space.

20

1 Comment