Rajdeep Biswas

Yesterday we demonstrated how quickly you can move contextualize and normalized data from Flow to Snowflake during a webinar with our partners at Streamline Control. This strategy makes all of the historical data in your legacy or enterprise data historians and SQL databases immediately available to Snowflake, and it's EASY!

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SAS, in collaboration with Coleman Parkes Research, surveyed business organizations about generative AI early adoption. Data analytics tell a story, and this one is no different. Take a peek at the report to see where your region lands on the leaderboard 🌏. http://2.sas.com/6047i2dlB #ArtificialIntelligence #GenAI

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My CTO, Philip Rathle explores the powerful impact of GraphRAG—the combination of knowledge graphs + Retrieval Augmented Generation (RAG)— for GenAI in his latest blog post, "The GraphRAG Manifesto.” Over the last year I have been working with some of our largest global SI's and I agree 100% - 𝐓𝐡𝐞 𝐛𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐭𝐡𝐞𝐲 𝐚𝐫𝐞 𝐬𝐞𝐞𝐢𝐧𝐠 𝐟𝐫𝐨𝐦 𝐆𝐫𝐚𝐩𝐡𝐑𝐀𝐆 relative to vector-only RAG fall into three main buckets: 1. 𝐇𝐢𝐠𝐡𝐞𝐫 𝐚𝐜𝐜𝐮𝐫𝐚𝐜𝐲 and more complete answers (runtime / production benefit) 2. 𝐈𝐦𝐩𝐫𝐨𝐯𝐞𝐝 𝐦𝐚𝐢𝐧𝐭𝐚𝐢𝐧𝐚𝐛𝐢𝐥𝐢𝐭𝐲 with knowledge graph, it’s easier to both build5 and subsequently maintain your RAG application (development time benefit) 3. 𝐁𝐞𝐭𝐭𝐞𝐫 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 with explainability, traceability6, and access controls These are the topics that are resonating and solving the critical issues in deploying GenAI based solutions. Take a look and get ready to take the next step with GraphRAG.🚀

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I just published a new blog on how we are seeing many architectures for intelligent organizations use the same pattern of combining LLMs and Knowledge Graphs. I use the metaphor of Convergent Evolution to illustrate these points. Looking for feedback! #LLM #GenAI #KnowledgeGraphs #EnterpriseKnoweldgeGraphs #Evolution #Metaphor #AI #IntelligentOrganizations #BiologyInspired

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2025 is the year for AI Agents. Does your organization have a plan for them? Do you know the difference between AI Agents and Automation? Do you know how AI Agents could possibly help automation? One thing to do to help you in your data AI journey is follow the right people. One to follow is Allie K. Miller. She is hosting a webinar from Maven next week on December 17th. Join in to learn more on AI Agents. Register here: https://lnkd.in/gff8cqK5 Don’t miss these opportunities to further knowledge. Stay nerdy, my friends!! #data #AI #AIAgents #dataliteracy #AILiteracy

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Tech Talk - The power of Compound #AI systems and advanced #RAG implementations: https://lnkd.in/gRjCypYj On December 5th, join Anant Bhardwaj (CEO, Instabase) and Clemens Mewald (Head of Product) for a no-fluff, tech-first webinar designed for #AI/#ML professionals. What’s on the agenda? 🔹 Pushing past context limits with advanced #RAG techniques 🔹 Leveraging #CompoundAI systems to tackle intricate workflows 🔹 Decoding the trade-offs between large generative models and fine-tuned AI models This isn’t just another AI webinar—it’s a candid deep dive into what works, what doesn’t, and what’s next in deploying #AI effectively. Ready to sharpen your AI game? -  Register Now 👉: https://lnkd.in/gRjCypYj #ArtificialIntelligence #MachineLearning #DataScience #Python #DataScientist

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With all of the hype around AI, it's hard to separate fact from fiction. Booz Allen Hamilton is here to help with the release of the Modern Artificial Intelligence Primer. As the number one provider of AI to the federal government, we are to help with you gain the right foundational knowledge to accelerate your #AI adoption and transformation! The Modern Artificial Intelligence Primer is an essential technical guidebook for leaders and practitioners who want to learn more about all facets of #AI. This newly published report provides a deep dive into #GenerativeAI, multimodal AI, and other innovations transforming our world. Download The Modern Artificial Intelligence Primer today! Find it here: https://lnkd.in/gKrYmArT Congrats to my brilliant colleagues on publishing this report: Catherine Ordun Alexa Hoffman, MBA Edward Raff Alison Smith Patrick Biltgen Bryan Castle Drew Farris Kate Helfet Matthew Keating Chu Lahlou Justin Neroda Ryan Swope John Conley

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Teams of AI #agents working together could enhance AI capabilities, mirroring the success of human collaboration. This approach, known as "multi-agent systems," is gaining traction as a way to overcome the limitations of individual large language models (#LLMs). Microsoft's AutoGen software library has facilitated the creation of LLM teams, allowing multiple AI agents to communicate and collaborate on tasks. The advantages of AI teamwork include parallel processing of subtasks and the potential for leadership emergence among agents. However, challenges remain, such as the high computational costs and the risk of cascading errors. To make this technology more accessible, Microsoft recently released AutoGen Studio, a low-code interface for building AI teams. While promising, the approach still faces hurdles in determining optimal team structures, distributing responsibilities, and integrating with human teams. Despite these challenges, the concept of AI collaboration is rapidly gaining momentum in the field. AI agent startups are attracting substantial investments from venture capitalists, with companies like Adept achieving billion-dollar valuations. While these investments are not as large as those going into AI model companies, they still significantly outpace the startups' current business fundamentals. Notable examples include H, a French AI agent startup that raised $220 million in seed funding, and Artisan AI, which secured $7.3 million and has already onboarded over 100 companies. That is an exciting transformation journey on how to become an Agent Augmented Organization ! Alex Marandon Philippe Cordier Pierre Demeulemeester Adrien Vignes Hao LI Ziad Nader Sylia Bouzid https://lnkd.in/ePjrGFq5

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The results of our AI in the Enterprise survey make for very interesting reading. I can’t say I found them surprising, as the challenges Enterprises face in adopting and achieving value with AI is something I’ve been helping them with for years. As the AI hype-cycle we’re living through drops away from its peak, we’re already hearing lots of stories that AI is failing. On the other side of the coin, we’re increasingly hearing the success stories: how more Enterprises are embedding AI and GenAI into their ways of working, building new services and changing existing processes with AI to bring value. The survey results show that achieving this value is hard, but that there is still a significant desire to do so and it’s recognised that succeeding with AI can be transformational. The reality is that achieving value with AI is far from just putting some new technology live: success with AI is at least as much a hearts and minds piece for an Enterprise as it is a technology and process change. Enterprises want to be Responsible with AI – in industries currently unregulated for AI this requires new ways of working. And the survey results affirm the shortage of key personnel across industry globally. If you are yet to commence your AI journey and want to, my advice is to start, and to start small. Use Proof of Concepts (PoCs) across your business to discover and learn how you can embed and utilise AI responsibly. While you’re doing this, take the learnings from these PoCs and conversations across your business to strategically plan, and tie these plans to your vision for what you want your business to achieve. Make sure you baseline and measure how you are achieving value and embedding change. And data – did some mention data? AI is one of the fundamental reasons why so much investment has been made into Enterprise data over the past decade… is yours ready for AI? It's a journey – make sure you celebrate success along the way! UST #AI #GenAI #ResponsibleAI #AIStrategy

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PRINCIPAL COMPONENTS ANALYSIS (PCA) Curious about how to make sense of complex datasets? Principal Components Analysis (PCA) is your key to uncovering hidden patterns and reducing data complexity! 📊✨ Discover how PCA can enhance your data analysis and drive smarter decisions. 👉 CLICK LINK IN BIO to dive deeper into PCA and transform your data strategy! #DataScience #PCA #PrincipalComponentsAnalysis #DataReduction #MPRW #KEYS #DataVisualization #BigData #Analytics #DataAnalytics #DataDriven #TechInnovation #Efficiency #DecisionMaking #DataSimplification #DataManagement #DataInsights #MachineLearning #AI #TechSolutions #BusinessGrowth #DataStrategy #WRIRK #DataOptimization #DataPatterns #DataTech #InformedDecisions #RESEARCH

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Really good article by David Linthicum outlining current challenges and suggesting practical advice to accelerate AI adoption for enterprise use cases. I couldn't agree more with author's statement that "[AI)] necessitates a comprehensive strategy that includes ADEQUATE TRAINING, CULTURE SHIFTS, AND ONGOING SUPPORT". Way too many people grossly oversimplify AI Revolution as new way of offshoring (eg cheap machines will replace expensive humans). This is way more complex than that, as AI (as any technology wave) is about MACHINES + HUMANS with specialized skillsets (skillsets that yet to be developed)! #GenerativeAI #largelanguagemodels #artificialintelligence #airevolution

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Meta has released pre-trained models that utilize a novel multi-token prediction approach for #LLM, potentially revolutionizing AI development. This technique, which predicts multiple future words simultaneously instead of just the next word, promises enhanced performance and significantly reduced training times. The new approach could lead to more efficient and sustainable AI, addressing concerns about computational power demands and environmental impact. Meta's multi-token prediction models may offer a more nuanced understanding of language structure and context, potentially improving tasks like code generation and creative writing. The company has released these models under a non-commercial research license on Hugging Face. The initial release focuses on code completion tasks, reflecting the growing market for AI-assisted programming tools. https://lnkd.in/eMBCXu8p

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The future of AI education should include hands-on experience with private AI agents. With tools like Ollama and phidata setting up your own AI agent requires minimal coding - think under 10 lines. Perfect for beginners and enthusiasts. Integrating such practical knowledge into standard education could transform how we understand and interact with AI technology. Github: https://lnkd.in/g2fpAQDP #AI #Education #Technology #Innovation

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Sam Altman's (OpenAI CEO) latest perspectives on AI. A few things that stand out for me: 👉 AI will bring in a new age of prosperity, but that doesn't necessarily make people happy 👉 how is this possible? "deep learning worked" 👉 the more compute and data available, the better it gets at helping people solve hard problems As Sam says in the article, " The dawn of the Intelligence Age is a momentous development with very complex and extremely high-stakes challenges. It will not be an entirely positive story, but the upside is so tremendous that we owe it to ourselves, and the future, to figure out how to navigate the risks in front of us." https://ia.samaltman.com/

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For this week's #AI review, I share advice from @BillGates who says everyone should get up to speed on AI. I also recap the @NaNoWriMo fallout over their tacit endorsement of AI tools for their speed-writing novel challenge. https://lnkd.in/gp2wSu6P

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Key to building trustworthy AI systems is to design decision algorithms that are auditable, accountable & thus, less biased. #AI #GenAI ##DeepLearning #MachineLearning

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