Rajesh Shetty

Diagram of Thought (DoT): An AI Framework that Models Iterative Reasoning in Large Language Models (LLMs) as the Construction of a Directed Acyclic Graph (DAG) within a Single Model https://flip.it/Mh_Mhu

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Interesting insight from Santosh Rao on Marketplace by APM My research talks about metrics Tech/SaaS Leaders should measure depending on your scale https://lnkd.in/gGfBWgn5

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At a Generative AI thought leadership dinner with other CTOs in NYC today and some interesting trends are emerging: * a consensus that LLMs are converging on a general set of features and basically comparable performance * a consensus that an org's data pipelines will matter more than the LLM chosen * and a group of people who read the TOS that are really scares about what these LLMs will do with access to all your data. Lastly, my prediction: the work of tech is moving from the keyboard to the whiteboard. Ai as microservice means structuring your data, thinking with ai, and chaining ai agents will supercharge your career and your cause -- but only if social change orgs platform their data. In my study of polymaths, Charles Babbage designed the basic idea for a unit of computing being something that takes an input, does something to it and gives an output -- the so called Babbage difference engine. In a real way, GenAI is approaching a world where chaining inputs ala a babbage difference engine is accessible to all. This can be an awesome opportunity if we get Non profits to work together!

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Incorporating Generative AI into business workflows presents immense opportunities, but managing its hallucinations—when the AI generates inaccurate or misleading information—is crucial for long-term success. Unchecked hallucinations can erode trust, misinform decision-making, and expose businesses to reputational and financial risks, particularly in industries like healthcare where precision is non-negotiable. By implementing robust safeguards such as fine-tuning models on domain-specific data, integrating human-in-the-loop systems, and reinforcing AI outputs with fact-checking mechanisms, businesses can mitigate these risks. Our latest report highlights our point of view on how the hallucinations can be effectively managed.

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AI-powered knowledge management is revolutionizing productivity, as highlighted in Sirjad Parakkat's insightful article. It's essential reading for understanding AI's potential in transforming traditional systems. Our "Tailored Intelligence" consultancy and tech services go further by ensuring that private data is not used to train public AI tools and keeping human experts in the loop. We combine AI's power with human insight to protect your proprietary knowledge and enhance decision-making. Discover how we take AI-driven knowledge management to the next level. #tailoredintelligence #ai #artificialintelligence #digitaltransformation #aiinsociety #impactai #innovation #visionaires #business #wikiexpert #solutions

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What happens when two industry veterans and former analysts meet and have a private chat about the marketing hyperboles and product overpromise of tech vendors? What do they say to each other? Welcome to Reality Distortion Fields (RDFs)! A new long form conversation podcast hosted by Elias Khnaser and Alessandro Perilli 🇺🇦. In this first episode, Elias and Alessandro talk about: - Humane AI Pin and MKBHD - Rabbit R1 - what's the job of a reviewer/critic/analyst - how companies grow reality distortion fields and if there's a way to avoid them - tech vendors' responsibility towards customers and corporate incentives - how they typically deal with failures, and the contrarian perspective of Peter Thiel - if we really need yet another device - what's the vision for an AI assistant compared to what vendors are selling today Watch it here or wherever you get your podcasts: https://lnkd.in/g9Pdr7P5

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Ready for an #Agentic future where AI agents collaborate, adapt, and act autonomously? OpenAI announced the next frontier in Enterprise AI: "Swarm." It introduces the concept of agent chaining: If an agent cannot complete a task independently, it can delegate the task to another agent through a handoff. Want to learn more about Agentic AI? Attend the IIT Bay Area Leadership Conference 2024 this Saturday (October 19, 2024). Jeremiah Owyang will give a talk on "Agentic AI: Shaping Autonomous Future." The article mentions: "Swarm’s release has also rekindled debates about the ethical implications of advanced AI systems." You can attend Brian Green's "Ethical Decision Making In the Age of Data and AI" talk to learn more. It mentions: "Security experts stress the need for robust safeguards to prevent misuse or malfunction in networks of autonomous agents." You can attend two sessions: (1) "Driving Business Innovation: AI, Zero-Trust, and Investment Insights" by Mario Espinoza (CPO of Illumio), Dr. Vipin Chaudhary (Prof and Chair at Case Western University), Hitesh Sheth (CEO of Vectra AI), and Pramod Gosavi (Venture Partner at Blumberg Capital) and (2) "Gen AI: Data Security and Privacy" by Dr. Anand Kashyap (CEO at Fortanix), Nilesh Thakker (President at Zinnov), and Dr. Anirban Ghosh (AI/ML Consultant at Infosys). The article mentions: "The specter of job displacement adds another layer of complexity," and you can attend the session "Future of Work in the Age of Data and AI: VCs' Perspectives" by Ashmeet Sidana (Engineering Capital), Raviraj Jain (Lightspeed Ventures), Apoorva Pandhi (Zetta Ventures) and Lochan Alagh (VC Nest). And, of course, there are many more sessions. Register here: ttps://lnkd.in/gRUVzbfA #Leadership #IITBayArea #TechIcon Speaker Affiliations: Databricks, Glean, Sapphire Ventures, Accenture, Illumio, SAP, Okta, Birlasoft, Infosys, Vectra AI, Fortanix, Postman, Workato, and many more Nidhi Kannoujia, Arnab Debnath, Ashis Khan, Anshu Agarwal, Swapnil Sinvhal, Lochan Alagh, Rao Charagondla (CNR), Dipty Desai, Ph.D., Praveen Vayalamkuzhi, PhD, FRSA, Surbhi Kaul, Ishita Sharan, Hrishikesh Sathawane, Bidyut Parruck https://lnkd.in/gJwa_ZXJ.

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Fantastic panel on GTM for Enterprise AI. Thanks to fellow panelists for a sharp discussion and to Emergent Ventures for hosting. Anupam Rastogi Ankur Jain Preethy Padmanabhan Chandini M Ammineni Jason Griggs Deb Bardhan #GTM #EnterpriseAI

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On this episode of The Drill Down Insider, host Cory Johnson is joined by Elastic's Ashutosh Kulkarni, CEO, for a conversation on the transformative potential of Generative AI and the Vectorization of Search that Elastic is pioneering. Their discussion covers: - The impact of Generative AI on search technologies and user experiences - Elastic's approach to integrating vector search with conventional search methodologies - Future trends in AI and search technologies that businesses should watch out for - Practical applications and case studies of Elastic's search technologies in various industries - The challenges and opportunities in developing AI-driven search solutions Watch the video below, and be sure to subscribe to our YouTube channel, so you never miss an episode: https://lnkd.in/eRuTSnkg #Elastic #AI #GenerativeAI #SearchTechnology #TheDrillDownInsider #CoryJohnson #AshutoshKulkarni #SixFiveOnTheRoad

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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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"The new Columnar capabilities enable rapid real-time intelligence for data analysis and quick insights, along with further opportunities for traditional ML and AI" ⚡ Check out this write up on Capella columnar from private preview user Will Thayer, MBA Technologist 📝 https://bit.ly/3JGo8UR

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The Economist's article “Large language models are getting bigger and better” on April 17, 2024 on the challenges of scaling large language models (LLMs) rightly identifies the limitations of current AI architectures. While the relentless pursuit of larger LLMs suggests a future of limitless progress, a deeper dive reveals significant flaws. The "scaling hypothesis"—that more data and power equals human-like intelligence—misses crucial aspects. LLMs face serious hurdles: the dwindling supply of high-quality data, the inefficiency of scaling, and the simple fact that size doesn't equate to cognitive complexity. Here, neurosymbolic AI presents a promising alternative, blending the data-handling prowess of neural networks with the logical precision of symbolic AI. This combination not only promises enhanced efficiency and structured reasoning but also aligns closer with human cognitive processes. Neurosymbolic AI excels in areas where traditional models falter, offering a path to more sustainable, intelligent systems capable of real-world applications like airplane design and financial risk assessment. It’s time for the AI community to pivot towards technologies that not only scale but think smarter. https://loom.ly/96rDCD0

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𝗧𝗵𝗮𝗻𝗸 𝘆𝗼𝘂 ETCIO 𝗳𝗼𝗿 𝗮𝗻 𝗮𝗺𝗮𝘇𝗶𝗻𝗴 𝘄𝗲𝗯𝗶𝗻𝗮𝗿 𝗼𝗻 "𝗙𝘂𝗲𝗹𝗶𝗻𝗴 𝘁𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗛𝗼𝘄 𝗚𝗲𝗻𝗔𝗜 𝗶𝘀 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗶𝘇𝗶𝗻𝗴 𝗦𝘁𝗮𝗿𝘁𝘂𝗽𝘀!" I am in sync with Tara Lodh, Customer Engineer, Google Cloud when he says he is excited about the voice perspective when it comes to GenAI Voice, as per his vision, will be used in: • code generation • workflow generation • even in the way we use search • day-to-day activities His data strategies are also very well-thought-out: • 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 & 𝗖𝗼𝗻𝘀𝗼𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻: Data is all around flowing all around systems, departments and processes. Therefore, high chance of duplication is there. So, number one strategy should be to break this replication as it can lead to errors and inefficiencies.   And consolidate data as it leads to unification to a centralized platform as it'll ensure that all teams can have access to consistent info. • 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗮𝗿𝗼𝘂𝗻𝗱 𝗗𝗮𝘁𝗮: There should be policies and standards to manage data securely and ethically. Compliance ensures protecting sensitive information and maintaining accountability for data usage. • 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Scalability depends on having solid foundation of quality, consolidation, and governance around data. Growth isn’t just about handling more, rather it’s about handling more effectively and responsibly.    • 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲: It's about maintaining speed and reliability while managing increasing demands. This is directly related to clean, accurate data that is unified across systems and managed with compliance. Manish Kumar's, Customer Engineer, Google Cloud, tip for startup is worth noting, "Build app that is powered by Gen AI than building GenAI itself" Also, big thanks to Soumik Ghosh, for leading such an engaging and impactful session. I really appreciate for the insights and energy you brought to the table! Conversive #GenAI #DataStrategy #AIInnovation https://lnkd.in/gNi_dAK3

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Kumo helps data scientists build highly accurate predictive AI models that predict user and customer behavior by combining graph learning over enterprise data and generative AI models trained on public data—all entirely within Snowflake. If you want to create better machine learning models faster with Kumo, try our Snowflake Native App now. 🔗 You can request a free trial at the following link: https://hubs.ly/Q02HgQ1P0. If you need additional support and more details, contact us. We'd love to get in touch with you and help you query the future: https://hubs.ly/Q02HgGvG0. #AI #MachineLearning #PredictiveModels #DataScience #GraphLearning #GenerativeAI #Snowflake #TechInnovation #KumoAI #FutureOfData

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"LLMs don’t reason like humans—understanding that is key to unlocking their true potential in the real world." — Drew Banin. In this insightful conversation, Drew explores how dbt Labs transformed cloud data workflows, the evolving role of semantic layers in AI, and how vector embeddings are changing the game. He also dives into the limitations of LLMs' reasoning and why prompt engineering might become less crucial as AI continues to evolve. This is a must-listen for anyone interested in how data and AI are shaping the future. To listen to Drew, click here :

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In today's rapidly evolving business landscape, Generative AI stands out as a transformative technology capable of driving significant impact across various domains. This one-day workshop is designed for executive and departmental leaders, aimed at fostering a deep understanding of GAI, aligning strategic vision, and catalyzing actionable insights. Participants explore practical applications, engage in hands-on activities, and develop strategies to leverage GAI for enhanced business outcomes. While the primary focus of the sample workshop is on marketing, the workshop framework is adaptable for other functional areas such as engineering, operations, finance, administration, HR, and recruiting. #generativeartificialintelligence #generativeAI #GAI #AI #digitaltransformation #CIOs #CTOs #CDOs #CDAOs #CMOs #CFOs #CEOs #EQengineered

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My quick thoughts about the pent-up innovation inside the enterprise that is set to explode with those who make GenAI a priority. This video was in support of a great article from Brett A. Hurt around the same topic. You can read that here: https://lnkd.in/gwBBbX4M https://lnkd.in/gvDyRKZN

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With the non-stop buzz around generative AI, the excitement is undeniable — but so is the confusion. As new large language models (LLMs) flood the market, each claiming to be more powerful or specialized than the last, choosing the right one can feel like an impossible task. Every model seems to come with its own set of strengths, trade-offs, and tech jargon that’s tough to decode. Trying to keep up with this rapid evolution is overwhelming. This article is an attempt to provide a simple guide about choosing the right AI Model amidst the Generative AI Hype. https://lnkd.in/gCFz3UC6

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