Amitabh Patil

We are excited to back Morphing Machines. As Dr. Ranjani, CTO and co-founder says: “For the first time in India and globally, we have a processor that is truly runtime reconfigurable, catering to emerging workloads.” While Nvidia’s growth and high valuation are driven by robust demand for “infra-compute” in high-performance GPUs, spurred by Gen AI, there is a distinct need for innovative solutions tailored to a new wave of reactive applications. Enter Morphing Machines. It addresses this demand with its unique product designed for next-gen telecom, autonomous vehicles, collaborative robots, avionics, and online data analytics. This product is specifically engineered to handle heterogeneous workloads and diverse tasks with varying performance demands simultaneously, ensuring a high level of scalability. As we move from an institutionally-backed research team at IISC to productization, Golden Sparrow is collaborating with Speciale Invest and others to support Deepak Shapeti, who joined as CEO three years ago after earning his Masters at Stanford. He brings not only technical expertise but also the business acumen necessary to guide the product to commercial success. Venkat Raju Afreed Faizan Anand Rao Ritik Singh Michael Marmor

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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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Advancing multilingual AI in Asia : the topic of my talk in the recently concluded NVIDIA AI summit in Mumbai really talks about how Tech Mahindra and NVIDIA together are taking LLMs for the new world order Yes there are multiple LLMs but as you all know foundation models do very well in a generic space but fail when its verticalized domain based space . They have to be fine tuned . Data has to be curated well and above all it’s not science but sort of a dark art to attain resonance of models which are guardrailed , and are ethical for an organisation. The future is just not verticalized LLms but genetic workflows as well , but the biggest area of work today is how to give reasoning and context to these models so that they establish a world model in their dreams to answer correctly. Stay tuned …. https://lnkd.in/dacH_r2Y

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Bias in Machine Learning with EQengineered's Chief Data Officer, Ranjan Bhattacharya #datagovernance #ML #machinelearning #AI #artificialintelligence #ethicsinAI #dataengineering #digitaltransformation #EQengineered

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The need for Application defines the standard of Learning!

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Clean data is very crucial for any AI/ML product to succeed. Sounds like Same Old Gyan and more than a decade old problem. More often than not Source DQ, Master Data Management, Data Integrity in a large scale enterprise are top problems that can impact quality of Pred/Gen AI solutions !!! Cutting edge data "foundation" is an undeniable key to the success of bleeding edge AI :) 2 hours of video processing ability may not be the ultimatum to solve this classic :p PC: LLAMA3.1 #ai #genai #datafoundation

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

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Ola Krutrim , India’s first AI unicorn, recently launched its LLM, Krutrim-7B-chat. This new model is trained in 10 Indian languages and is available on Databricks Marketplace. It can generate text in Hindi, English, Tamil, Telugu, Marathi, Malayalam, Gujarati, Bengali, and Kannada. This is the first of several India-specific models trained by Ola Krutrim. It has been trained on a massive dataset of Indic languages— “Krutrim delivers text infused with Indian sensibilities and cultural awareness.” Check out the model here. The announcement came to light at the Data Intelligence Day in Mumbai on May 10, 2024, by Gautam Bhargava, VP & Head of AI Engineering at Krutrim. “We’re excited to be at the forefront of building foundational LLMs trained on Indian languages to better serve our customers in India. We have been working very closely with the Databricks team to pre-train and finetune our foundational LLM,” said Bhargava. He added, “We are confident that Krutrim, our base model, will be able to provide high-quality responses in Indian languages and dialects.” According to Bhargava, Krutrim was trained using Databricks Mosaic AI Training’s GPU orchestration and system optimisations, enabling state-of-the-art generative AI solutions for customers globally. The model is now available on the Databricks Marketplace.

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Honored to have led a session on "Accelerating AI Innovation: Building Successful Startup-Corporate Partnerships" in collaboration with Microsoft! As Head of Data & AI Practice at e& enterprise, I shared frameworks and real-world strategies on how startups and corporations can build lasting partnerships that drive AI innovation. We delved into practical approaches for successful collaborations, discussing key success factors and common pitfalls to avoid when building AI partnerships. Special thanks to Microsoft for Startups, Abu Dhabi Investment Office, and Plug and Play Tech Center for the opportunity to contribute to this important conversation. As AI continues to reshape industries, effective collaboration will be key to staying ahead! Looking forward to seeing more transformative partnerships emerge in our ecosystem. #eAnd #eAndenterprise #StartupSuccess #CorporatePartnerships #TechLeadership #MicrosoftStartups #AI #GrowthXAccelerator

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Sanjay Jha is moderating an intriguing panel discussion at GSA (Global Semiconductor Alliance ) executive forum now Rene Haas : insatiable demand driven by AI speed up our roadmap. Software does not die, AI is an additional demands for hardware. Life science and drug development will be the next big thing. Anirudh Devgan : AI is in the phase 1 of infrastructure and phase 2 of AI in existing application, 3rd phase is AI new application. Cadence is engaging phase 1 by enabling AI Chips, and phase 2 which drive design automation. 3DIC is natural extension of Moore's law. Optimistic about power, as new Innovation along the way will bend the straight line projection usually seen in the early inning of technology like AI. Real value realization will mostly be vertical based, not the horizontal LLM. AI will move from infrastructure AI, physical AI(automotive, robotics) to the horizon 3, that is likely AI biggest apps such as AI for science, particularly life science Sandra Rivera : AI impact is multi facets. First it is a TAM expansion for FPGA, which is needed as co-accelerator. AI is also embedded in placement tool and in even in basic fabrics, which will be making FPGA better. Power is the single Largest limiter for AI deployment. Also, Should AI be better regulated than what happened in social media, leading to the data security and privacy. Tien Wu : AI has driven ASE to increase capex to 4B This year from 2B last year due to systematic complexity, not just technology but the more players in ecosystem, which breaks the traditional pricing. AI has made us seeing the first time that Hardware is the bottleneck in term of improvement and return in profit. US has the data and economic scale to deploy AI across all sectors in term of efficiency improvement, given US also has been a highly "wasteful" nation.

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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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Taking GenAI and LLMs from POCs to Production 🚀 Join us for an enlightening webinar hosted by CrossML Pvt Ltd and presented by Ankit Aggarwal, as we dive deep into the journey of taking Large Language Models (LLMs) from Proof of Concept (POC) to full-scale production. This webinar is perfect for CTO, AI enthusiasts, data scientists, product managers, and anyone interested in harnessing the power of LLMs to transform business operations. #LLM #AIWebinar #MachineLearning #GenerativeAI #TechnologyEvent

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If you are still thinking that AI is just a hype, you should listen the conversation between Mukesh Ambani and NVIDIA CEO Jensen Huang. Why ? Mukesh Ambani bullishly talks about Generative AI models, GPUs, need of open source models etc. He takes up the challenge to surprise world with AI capabilities in coming years. He is not someone who has been leading IT/Software companies day in day out like Narayan Murthy/ Shiv Nadar/Bill Gates etc. What it means? AI has already arrived and every big firm, irrespective of their traditional business, wants to build business and create impact using this. AI is not just another cool tech anymore. It is the industrial revolution changing every facet of our life. Embrace it or get ready for classic "Kodak Case study" in your career and business. Watch here: https://lnkd.in/ejvnCMHZ

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#videopodcastseries - weekend watching and listening into the deep dive of #episode84 of XTraw AI conversations with the CPMO, Rahul Singhal from Innodata Inc. on harnessing the power of AI to transform businesses. We delved into key strategies that are shaping the future such as enhancing efficiency, driving innovation and more in the context of AI and data engineering. 👉Don’t forget to subscribe if you haven't yet! #AI #GenAI #Data #Analytics #Innovation #DataEngineering https://lnkd.in/giyaRfj5

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Unleashing GenAI Innovation: Insights from the 3AI #SPECTRA Roundtable I had the pleasure of moderating the roundtable discussion on "RAG Strategies: Leveraging Diverse Techniques for GenAI Innovation" at the recent 3AI SPECTRA event. As the moderator, I posed these thought-provoking questions to our esteemed panelists: 1. How do enterprises prioritize their strategies to drive business growth and efficiency — focusing on increasing revenue or reducing costs through improved productivity? 2. what is the typical preference for optimizing processes — agentic workflow, RAG approach, or a combination of both? 3. What do enterprises value more when interacting with systems — achieving high-quality responses, low-latency per request, or finding a balance between to meet business expectations? 4. What is the prevailing preference for an enterprise — utilizing open-source models or investing in commercial models for implementing Gen AI solutions? 5. When enterprises kickstart Gen AI projects, what approach do they often take— starting with one Proof of Concept and then scaling it up, or experimenting with 2-3 POCs and then deciding which one to scale based on outcomes and feasibility? 6. What priorities do enterprises have when it comes to system performance —minimizing costs per request, delivering high-quality responses consistently, or achieving a blend of efficiency and effectiveness? 7. Which type of models, small domain-specific or large general models typically deliver better results and value for enterprises in terms of accuracy, scalability, and adaptability to business needs? Listen to the playback video for key takeaways and the insightful conversation with our esteemed panelists. A huge thank you to my co-moderator Shibaji Chatterjee and our esteemed panelists Ashok Kalra, Karan Makim, Kiranjit Pattnaik, Prashant Kumar Jha, and Shivani Sharma for sharing such valuable insights. My deepest gratitude to Sameer Dhanrajani, Nandakumar Ramaiah, and Kapil Gandhi for organizing this incredible event and providing me with this amazing opportunity. #GenAI #AI #3AISpectra #Innovation

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On AI Appreciation day, I shared my views with The Economic Times on how Artificial Intelligence, grounded in contextually-relevant information, is reshaping business dynamics. AI's ability to uncover real-time insights and democratize complex data is revolutionizing decision-making across all levels of organizations. However, to harness AI's full potential responsibly, businesses must invest in robust data integration and governance frameworks. Read more here: https://lnkd.in/gFAUbtaN

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The competition to develop the most advanced Large Language Models (LLMs) has seen major advancements, with the four AI giants, OpenAI, Meta, Anthropic, and Google DeepMind, at the forefront. These LLMs are reshaping industries and significantly impacting the AI-powered applications we use daily, such as virtual assistants, customer support chatbots, and translation services. As competition heats up, these models are constantly evolving, becoming more efficient and capable in various domains, including multitask reasoning, coding, mathematical problem-solving, and performance in real-time applications.

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A crisp and enriching framework by McKinsey & Company to help us all understand #genAI #adoption strategies better. With #humans and #humanity as the anchor of technological advancements using #GenAI, we are in for an exciting and promising journey ahead. #IBelongHere #AIinnovation

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Looking forward to this panel where Divakar Tantravahi, Meduri Ravi Kumar, and Cosimo Spera will talk about the latest AI technologies that are changing product and customer support, along with their real world examples and practical strategies. If you have not registered, use this link - https://lnkd.in/gdTMgryA #ai #businessoutcomes #product #customer

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