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Builder. Investor. Board Member focussed on Modernization & Innovation using Emerging Technologies
Exploring the depth of human creativity and empathy in the face of AI's rapid advances in advanced reasoning... #HumanVsAI #CreativeIntelligence #AGI
ConceptVines reposted this
Builder. Investor. Board Member focussed on Modernization & Innovation using Emerging Technologies
With AI applications like ChatGPT having over 200 million weekly active users and emerging adoption across industries, cumulative water usage is enormous, raising sustainability concerns. This article calls for increased awareness of AI's hidden environmental costs #GenAI #Sustainability #Semiconductors #Datacentre
🔍 The question of whether AI leads us towards a dystopian or utopian future hinges so much on how we choose to shape its development and integration. 🧠. 🚀🔒 Great read! #AI #Technology #Future #ConceptVines
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🚀 **Exciting News from ConceptVines!** 🚀 We're thrilled to announce that **SpeedX Workshops** are now available in the **AWS Marketplace**! 🎉 SpeedX is designed to fast-track your journey to innovation with AWS by delivering hands-on, immersive workshops that help you: ✅ Discover new **Generative AI** and **Cloud Solutions** ✅ Develop a clear path to **cloud transformation** ✅ Build a Proof of Concept (PoC) with expert guidance ✅ Leverage AWS credits to reduce costs! Whether you're looking to optimize your cloud infrastructure, adopt Gen AI, or explore new revenue-generating services, SpeedX provides the perfect platform for businesses to accelerate success. 🌐 Find us in the AWS Marketplace today: https://lnkd.in/gt6XYZBM 🔗 Learn more about how SpeedX can transform your business at https://lnkd.in/gqXC7PPe #ConceptVines #AWSMarketplace #ConceptVines #CloudTransformation #GenerativeAI #SpeedX #DigitalInnovation #CloudConsulting #AWS
Great post, Senthil ! Your insights on Open Source LLM's truly reflect the innovative approach we strive for at ConceptVines
Builder. Investor. Board Member focussed on Modernization & Innovation using Emerging Technologies
Should you care about Open Source LLMs ? LLMs (Large Language Models) are a complex beast to manage. More often than not, they are nice to you, they hallucinate, and provide answers to big questions but struggle with basic mathematics, and so on. The problem with most LLMs is that they don’t fully reveal their data sources, they don’t provide transparency on how they are trained, and they are mostly happy to charge you on a subscription fee/token-based pricing model. This is the case with OpenAI LLMs. But why should we care? Shouldn’t we all be happy about what we could do with ChatGPT, Gemini, Claude, etc? With the increased adoption of large language models by every industry (at varied speeds), with activities ranging from Customer Support to product Eligibility and several aspects of operations, it is very important that we, as consumers of these services, understand what goes into the models (remember NYTimes suit on OpenAI & Microsoft), how they are trained, and how the outputs arrived. This is a big area for policymakers to be concerned about as well. Economic Viability - A key trap here is that a large corporation is incentivized to build nontransparent models (“secret sauce”) that generate higher valuations for their investors and themselves rather than be bothered about the hassles of developing Safe AI - of course not exactly saying so. Safe AI requires absolute transparency and, hence, an open-source approach. Looking at the Capex (more than $400B across the globe in 2023) spent by the NVDA, BigTech, and leading AI firms, a fully transparent approach is not often economically viable for large corporations. Who will bell the cats? The problem here is that unlike developing open source software say Linux, LLMs require several million dollars upfront investment. This is where OLMo shines. OLMo stands for Open Language Model, from Allen Institute, which was founded by Microsoft Co-Founder Paul Allen. (Eerily Open AI was founded as a non-profit organization that drifted later) OLMo shares the data that went into the model, training/evaluation code, model weights, inference code, etc. Most of the models that claim to be open source do not do most of the above. They are, in fact,, quasi-open-source models. This is a crucial pivot from the profit-driven models of most large AI developers, where the specifics of model training and data handling often remain shrouded in confidentiality to maintain competitive advantages. The future will definitely be a hybrid of these models: closed, open, quasi-open, etc, as the gold rush settles down. Till then we can continue to enjoy the poems that ever-jubilant ChatGPT writes for us with a mild sense of grumpiness for the cost we have to pay for accessing GPT-4o Out of the several LLMs, what is your favorite and why? For a detailed coverage of OLMo please check out :
Happy International Women's Day! Celebrating the unwavering strength, courage, and contributions of women worldwide - here's to breaking barriers and building a brighter, more equal future together. #ConceptVines #InternationalWomensDay #IWD2024 #Empowerment #EqualityForAll #inspireinclusion
Wishing everyone a Happy Valentine's Day filled with love and happiness from all of us at ConceptVines! #ConceptVines #ValentinesDay
Wishing you a year filled with joy, laughter, and endless possibilities in 2024! 🎉✨ #ConceptVines #HappyNewYear #NewBeginnings #2024