Siddharth T.

Interesting paper; if the interaction between layers is linear, there are possibly new ways of optimizing them. We have just started with these.

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Grateful for the enlightening discussions on Data Lake vs Data Warehouse during our panel session at #DES2024 by AIM Events! Exciting times are ahead as AI and ML advancements promise to revolutionize storage practices.  Here are some key points and future predictions from our talk. 1️⃣ We talked about how to achieve incremental ROI with both storage approaches, considering specific goals. The rise of ML and AI will dramatically change data storage practices. With data volume, user base, and use cases expected to grow, big changes are coming. 2️⃣ AI capabilities are changing data engineering, making data preparation, pipeline management, and data movement faster and more automated. Future strategies need to focus on cost-effectiveness, flexibility, security, and governance. Hybrid approaches like the Data Lakehouse, which combine the best of Data Warehouses and Data Lakes, are becoming popular. 3️⃣ Edge computing will increase the need for better compute power in storage management. Real-time analytics will continue to improve storage practices. AI and ML integration will make data modeling and discovery easier. Additionally, data virtualization and federated queries will allow seamless data access across different sources without needing to move data physically. As we navigate this evolving landscape, it's important to stay updated on these changes and embrace innovative solutions for success. 🚀 How do you see AI and ML influencing your data management strategies? Let me know in the comment section below! #DataManagement #AI #ML #DataStorage #Innovation #DES24 #DES #AIM #ThinkAIThinkAIM #Datewarehouse #DataLake #DataLakehouse #GENAI

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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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An apt representation …and that’s true for any technology innovation. However risks are much higher and its impact is much broader in case of ai #aiforgood #artificialintelligence #ai

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As you consider the more operational facets and best practices, of your AI program roll-outs.

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Please join me on June 25th San Francisco, CA, USA for a panel titled "A BLUEPRINT FOR SCALABLE & RELIABLE ENTERPRISE AI/ML SYSTEMS" w/ moderation by Hira Dangol from Bank of America and my fellow panelists Rama Akkiraju from Nvidia and Nitin Aggarwal from Google. Recent breakthroughs in AI technology have captured the world's attention, and now it's time to address the challenge of creating truly robust and reliable AI systems. AIQCon's mission is to harness the power of our community to develop new GOLD STANDARDS for AI quality. The global movement is bringing together renowned leaders and professionals from across the industry to establish reliable AI quality solutions and standards. If you're working on AI systems, you won't want to miss this one! Use the discount code "Community" for a 15% discount on registration. Register at https://lnkd.in/gqRE48fC. #AI #EnterpriseAI #AIQuality #AIQCon https://lnkd.in/gqRE48fC

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Madhav Kumar, Ph.D. Student at MIT Sloan School of Management on AI: “I think the technology substantially lowers the barrier of entry for a lot of people, as well as organizations, to compete at every level. I'm quite excited about that. I think one of the big changes it allows is it pushes out our production frontier where we can do more with less, or at the same cost." https://lnkd.in/g9v2pqAm #MITCIO #AI #ArtificialIntelligence https://lnkd.in/gF8_YrMK https://lnkd.in/gNVHW_Mm

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I'm thrilled to announce my participation as a speaker at the highly anticipated 3AI #SPECTRA event, a confluence of cutting-edge AI and GenAI discussions with over 150+ renowned speakers across 3 insightful days. 🌟 During my session, I'll be delving into the best practices to maximize ROI for Generative AI initiatives within enterprises. Drawing from my hands-on experience driving multiple large-scale GenAI projects, I'll share valuable insights and strategies to unlock the true potential of this transformative technology. 🚀 Get ready to uncover: ✅ Key considerations for successful GenAI adoption and implementation at an enterprise scale. ✅ Proven methodologies to measure and optimize GenAI's impact on business outcomes. ✅ Real-world case studies and lessons learned from driving GenAI initiatives across diverse industries. ✅ Actionable tips to navigate challenges and accelerate time-to-value for your GenAI investments. Whether you're an AI leader, technology enthusiast, or a business decision-maker exploring the power of GenAI, this session promises to be an invaluable opportunity to gain practical knowledge and stay ahead of the curve. 🔍 Don't miss this chance to witness the live event and engage with industry experts pushing the boundaries of AI and GenAI. Join me at 3AI SPECTRA, where we'll collectively shape the future of intelligent systems and drive transformative change. 🌐 Mark your calendars and secure your spot today! Let's unlock the full potential of GenAI together. 💪 #3AISPECTRA #GenerativeAI #EnterpriseAI #AIAdoption #ROIOptimization #TechnologyLeadership

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Totally agree with you, Anthony. The name of the game is to get the right context as tight as possible to the question or task on hand. Graphs are one good way to do this, but you should use all the tools in your belt. With our solution, we use graphs, tables, key value pairs, geospatial information, regular search, vectors, and so on. When you combine all these things, the probability of getting the right context as much higher.

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Integrating systems and data continues to be a massive challenge in Banking. There is no lack of flashy Fintechs promising a silver bullet to solve the problem. But banks and credit unions need thoughtful, reliable experts with fit for purpose technology solutions. Enter Sandbox Banking iPaaS. Their use of ML and AI is targeted at the specific systems, data libraries and functional problems you are trying to solve, delivering real efficiencies and scale. If you are considering iPaaS solutions, you should get to know Ravi, Skye and the dedicated Sandbox team. #iPaas, #AI

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A recent #HBR article gives real-world examples showcasing how #GenAI is leveling the playing field. It's interesting to see the various ways where this transformative tech is being used. In this context, I often hear how GenAI is enabling skill democratization. It though doesn't level the playing field by enabling anyone to perform tasks across various domains without background or training. Instead, as the examples in the article point out, it augments existing skills, making it easier to accomplish tasks by lowering the barrier. HBR article - https://lnkd.in/eiSQVJBv

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Reading through Menlo Ventures' article on #GenAI application winners, the rise of Compound AI systems driving enterprise adoption caught my attention. It's not just about the foundational #LLM models. Compound AI systems are an evolving paradigm, exploring efficient and specialized architectures needed for implementing enterprise use cases. By engineering an end-to-end system, they are a refined approach to GenAI development. These systems combine and integrate multiple components such as LLM models, content retrieval systems, databases, knowledge graphs, and external tools- improving inference quality, control behavior, restrict access, and more. https://lnkd.in/gUYU_qTF

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While Linkedin Space is overwhelmed with GenAI contents , there has been an excellent drive going on by Scientific community on how AI (Neural Net and other DL/ML s) can help solving science probems of solving equations and simulations. It opened my eyes on vast opportinuty of possibilities. For further, please read Physics Inspired Neural Net, Neural Operator ... More here .. https://lnkd.in/eNRtswmr (X page of Anima Anandkumar ) https://sciml.ai/ #sciml #aiforscience

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#GenAI at Scale needs strong Foundations - To date only 4% of #Banks have full readiness from a technology and business point of view to embed #GenAI across their organization at scale, based on the recently released Retail Banking Report from Capgemini. ● 80% of banking executives see Generative AI as a significant leap in advancing Artificial Intelligence. Enhancing existing AI solutions with GenAI is seen as having substantial potential to boost both Customer Experience and Efficiency. For instance, enhancing customer acquisition, retention as well as risk management. #GenAI #Copilots are a specific focus, as they can help bank employees struggling with mundane operational tasks, which consume about 71% of their time, leaving only 30% to customer facing activities. ● However, most banks lack GenAI readiness. On the technology side, they struggle with fragmented data and often lack robust Machine Learning Operations (MLOps) to ensure drive #ResponsibleAI. On the business side, banks face challenges esp. in effectively tracking and measuring the impact of Generative AI initiatives and struggle to rapidly identify use-cases to kick-start adoption. As a result, among the CXOs surveyed, only 6% reported they are ready with a roadmap for enterprise wide (Gen)AI-driven transformation at scale, 28% said they are actively exploring a suitable roadmap for their bank’s needs and 34% have developed AI adoption strategies for specific lines of business but not integrated within the enterprise. ● Responding to the challenge, 70% of banks plan to increase their investment in digital transformation in 2024 by up to 10%. Key will be to also re-balance investments. The report highlights to date 56% of technology budgets are spent on front-end transformation, compared to 44% on back-end improvements. Banks have a lot to improve in their front-ends, no doubt. However, back-end transformation is essential to building the strong foundations necessary to scale AI and GenAI. Great insights from Capgemini Financial Services' Vaibhav Pandey & Bipin Jose (Link to full report in comments) CC: Richard, Arjun Vir, Theodora, Dr. Martha, Prof. Dr. Ingrid, Dr. Debashis, Alvin, Efi, Sanjeev, Enrico, Aditya Ranjan, Dinis, Zvonimir, Matt, Alex, Conor, FRANKI, Noelle, Tarja, Pablo, Medo, Fabio, Kamales, Tyler, Dr. Marcell, Chuck, Ravit, Joy, T. Scott. Ravi, Paul

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At the moment, intense competition drives large language model (LLM) advancements. Tech giants and startups are pushing boundaries to enhance model capabilities and accessibility with open-source and closed-source strategies. All are racing towards language model parity in quality, speed, and capabilities. LLM as a technology, will not be an enterprise differentiator.

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NVIDIA NIM Revolutionizes Model Deployment, Now Available to Transform World’s Millions of Developers Into Generative AI Developers The world’s 28 million developers can now download NVIDIA NIM™ — inference microservices that provide models as optimized containers — to deploy on clouds, data centers or workstations, giving them the ability to easily build generative AI applications for copilots, chatbots and more, in minutes rather than weeks. NIM enables enterprises to maximize their infrastructure investments. For example, running Meta Llama 3-8B in a NIM produces up to 3x more generative AI tokens on accelerated infrastructure than without NIM. #NIM #NVIDIA #GPU #ArtificialIntelligence #Llama3

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AI Reading for Sunday May 12! Speculating about OpenAI's Monday announcement. https://lnkd.in/e4nA2xKd More rumors of what ChatGPT might show. - THE DECODER Top guesses according to Perplexity, others, and yours truly - Project Q* which possibly learns to solve complex multi-step reasoning problems with something like Q-learning and tree search. - Something with agents and improvements to Assistants API which Sam Altman has been hyping - Better voice assistant - Not GPT-5 per Sam Altman, but maybe 4.5 with a long context and multimodality to catch up to Google, and price reductions for GPT-4 matching cheaper startups - Improved AI studio dev tools. - Maybe OpenAI should release a small local open source model and runtime environment for finetuning it. That space is buzzing but the technical bar to get into it is high for most people. Or maybe, a sarcasm detector. Wow, a true leap for mankind. Great job, Einsteins. - PCMAG OpenAI removed 'our most advanced' from the description of GPT-4 ... a more advanced 4.5 or something coming? Either they have poor opsec or are good at getting attention with headfakery. - Reddit ARM to launch AI chips to compete with Nvidia. But their business model is they don't sell chips, they license designs to vendors like Apple and Amazon and Nvidia, so this is new for them. ARM might have pricing power and a roadmap to capture more of the value chain, also might push customers to e.g. RISC-V. - Nikkei Asia WSJ covers NYC AI startups in NYC like HuggingFace, Runway, Pinecone, which are raising money at 1/2 the pace of Bay Area - WSJ Pro Alibaba leverages cloud business to become leading AI startup investor in China. - FT Wikipedia adds an LLM-powered Chrome extension for fact-checking. - Chrome Store How did that robot commencement speaker work out? Looks kinda weird and creepy. - YouTube Researchers test AI systems' ability to solve the New York Times' connections puzzle Tesla exec leaves, suggests it's a toxic work environment and "The recent layoffs that are rocking the company and its morale have thrown this harmony out of balance and it's hard to see the long-game." - Futurism Videos of cheerleaders engaging in off-limits activities were circulated. The cheerleaders and cops said they were deepfakes. A woman was accused of deepfaking them. Not deepfakes, although possibly underhanded shenanigans of unclear motivation. - the Guardian

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Capital One and USC partnered to establish the Center for Responsible AI and Decision Making in Finance (CREDIF). CREDIF will explore how AI and analytics can be responsibly applied at scale to drive innovation in finance and technology. Learn more 🔗

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