Deepthi Sigireddi

Stay ahead of the competition with an AI center of excellence. Learn how to gain the right #AI resources, skills, and strategies: https://lnkd.in/gagQUzft

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Cost optimization is a critical consideration for developers today. Knowing when to prioritize it and how to seamlessly incorporate it into our software development and operations lifecycle can greatly impact our bottom line. While there's no one-size-fits-all solution, Vaibhav Malhotra´s article offers practical insights and introduces powerful AWS tools for achieving cost efficiency while balancing performance for serverless applications. Don't miss out on this essential read! https://lnkd.in/dQ-scJcN #CostOptimization #AWS #SoftwareDevelopment 🌱💰

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Metrics for LLM. Nice article explaining the Grounding, hallucination, data correctness for fine-tuning, Prompt correctness, and RAG effectiveness by computing relevant Context awareness. https://lnkd.in/gFQMQ_ZR

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For those of you building RAG: next week (May 21) we're hosting a webinar with MongoDB that will help optimize those apps--

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Ai : Hunanity's greatest creation for Good and Bad. To secure ourself #zerotrustai In the journey, MS brings up VASA-1 will AI model which essentially spins a selfie image and turn it into a talking clip of you. All you have to do is upload a photo along with a voice note and let the AI model do the talking for you.

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Over the course of each month, I spend a few moments each day or so collecting interesting links, and then, at the end of the month, I bundle them (with the help of some nifty automation scripts) into an easily digestible reading list. Here's everything that I found interesting in May 2024 about the irresponsible use of machine intelligence: #qfm #quantumfaxmachine #blog #irresponsible #ai #genai https://lnkd.in/e2uE49up

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Gemini 1.5 Flash is now on Vertex AI!⚡ Get 1M context window, all modalities, and unparalleled quality/efficiency at a fraction of the cost. Gemini 1.5 Pro also got an upgrade with enhanced performance, quality, and instruction following. Explore parallel function calling, context caching, controlled generation, and 50% off batch API to revolutionize your claims processing and customer service. https://lnkd.in/eNBXDfuT

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Thanks to Suman Debnath good post on "Choose the best foundational model for your AI applications" at https://lnkd.in/gEug2Tbg Many good tips, tools and checklist of qualities to select the RIGHT FMs for your use case. I like the Amazon Bedrock's Model Evaluation tool which can help you compare FMs EASILY ! e.g. "in brief Amazon Bedrock offers a choice of #automatic evaluation and #human evaluation. You can use #automatic evaluation with #predefined #metrics such as accuracy, robustness, consistency and many more. You can create your own metric as well."

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In this podcast episode of "McKinsey on Building Products," GitHub CEO Thomas Dohmke discusses the transformative impact of generative AI on software development. As developers and engineering teams are being asked to accelerate the pace of change and improve quality simultaneously, tools like GitHub Copilot can enhance the software delivery experience. Initial areas of opportunity include providing intelligent code suggestions, taking over repetitive tasks, and democratizing coding by reducing language barriers and fostering innovation.

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Here is my column on the #TiEcon2024 conference in #indicanews:

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At Google Cloud India, we don't just build teams; we cultivate communities of collaboration, creativity, and inclusivity. Our teams are not simply engineers or product managers; we're problem solvers, dreamers, and innovators. From startups to large enterprises, our cloud solutions are more than just tools; they're catalysts for real, tangible change in the lives of our clients, empowering them to reach new heights and achieve their goals. In the ever-evolving landscape of cloud computing, Google Cloud isn't content with just keeping up. We're setting the pace, leading the charge with cutting-edge technologies like AI, machine learning, and data analytics. We're not just meeting industry standards; we're surpassing them, rewriting the rulebook and establishing new benchmarks for excellence. Join us as we continue to push boundaries, break barriers, and unlock new avenues for growth and innovation, shaping a future where the impossible becomes possible. Be a part of Google Cloud India, where together, we can change the world. Click here to know more:  https://lnkd.in/gCiYtDwj #GoogleCloud #Buildforeveryone

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There's undoubted excitement and hype around AI. Much like any large disruptive cycle, this one will net out a few winners. The question is which? I try to (naively) answer this question by looking at an ancient analogy: the emergence of the GUI https://lnkd.in/g4cgdBYD

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Looking to get started with in-database machine learning with MySQL HeatWave? This guide will help get you on the right path. https://lnkd.in/gPjuJU9g

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KV-cache quantization is super useful when you have a large batch-size and/or longer context-windows. This requires on-the-fly quantization. Happy to see HQQ used in this context: https://lnkd.in/eyxyPnhP

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Now we have two first class data catalogs integrated with MS Fabric now available in Azure. Of course DataBricks is the heavy heavy favorite in the enterprise lakehouses as well as AI (as of the conference that just finished 🤓)

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One of the key capabilities that sets Memgraph apart from the competition is our deep path traversal algorithms. Come read our latest blog explaining all about it: https://lnkd.in/gBtWPJuZ

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At Corgnit Research Lab, India, we are excited to share our latest findings on the convergence of Reinforcement Learning and Federated Learning and their implications for advancing AGI. Key Insights: - 𝐒𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲: The distributed nature of FL enables scalable and efficient training of RL models, significantly reducing computational overhead and accelerating convergence. - 𝐏𝐫𝐢𝐯𝐚𝐜𝐲-𝐏𝐫𝐞𝐬𝐞𝐫𝐯𝐢𝐧𝐠 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: By ensuring that sensitive data remains local, FL facilitates the development of AGI in privacy-sensitve domains, such as healthcare, without compromising data security. - 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐯𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Multiple RL agents can share knowledge through FL, enhancing overall learning efficiency and robustness without the need to share raw data. - 𝐏𝐞𝐫𝐬𝐨𝐧𝐚𝐥𝐢𝐳𝐞𝐝 𝐀𝐝𝐚𝐩𝐭𝐚𝐭𝐢𝐨𝐧: The integration of FL allows AGI models to be tailored to individual users or environments, combining global intelligence with local customization. - 𝐑𝐨𝐛𝐮𝐬𝐭𝐧𝐞𝐬𝐬 𝐚𝐧𝐝 𝐑𝐞𝐬𝐢𝐥𝐢𝐞𝐧𝐜𝐞: Aggregating diverse experiences through FL results in more generalized and resilient AGI models, mitigating the risk of overfitting. Benefits for Researchers: - 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Leveraging distributed computational resources lowers costs and enhances the feasibility of large-scale AGI experiments. - 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧: Model updates can be shared instead of raw data, promoting cross-institutional and interdisciplinary research. - 𝐀𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐞𝐝 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: Faster training times and rapid iteration lead to quicker advancements in AGI. - 𝐄𝐭𝐡𝐢𝐜𝐚𝐥 𝐀𝐈 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: Prioritizing user privacy and data security aligns with ethical standards and regulations, fostering responsible AI research. - 𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬: Immediate feedback and improvements from real-world data enable practical deployment in sectors like smart cities, healthcare, and IoT. Our research at Corgnit underscores the transformative potential of merging RL and FL in the pursuit of AGI. We believe these insights will catalyze further innovations and collaborations in the AI community. #ArtificialGeneralIntelligence #ReinforcementLearning #FederatedLearning #AIResearch #CorgnitResearchLab #PrivacyPreservingAI #ScalableAI #EthicalAI Corgnit, Corgnit Research India, Reinforcement Learning, Federated Learning Consortium

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More app development news from #GoogleCloudNext: Gemini in Firebase for mobile and web app development is GA! Gemini serves as an in-code assistant—providing answers to Firebase-related Qs, generating code snippets, and offering troubleshooting guidance.

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