“Shehram and I have worked together on many joint initiatives such as new product launches , GTM , marketing strategy, messaging, positioning, etc. and I have found him to be a collaborative, energetic, enthusiastic, and extremely customer focused. He spearheaded a new process ( Proof Of Value) of product adoptions for customers resulting in a pipeline of new customers and reference customers. He understands the customer viewpoint and has helpful insights on competitors' offerings . I strongly recommend Shehram. ”
About
Expert in Building - Launching New Products from Scratch to Scaled revenue. From…
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Education
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Duke University - The Fuqua School of Business
Recipient of a Duke Fuqua MBA Merit Scholarship for having outstanding professional & academic record.
SEE WHY DUKE FUQUA IS RANKED #1 BY BLOOMBERG BUSINESSWEEK!
http://www.bloomberg.com/bw/articles/2014-11-11/best-business-schools-2014-duke-is-top-full-time-mba-harvard-slips -
Languages
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English
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Portuguese
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Afrikaans
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Organizations
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U.S.SQUASH
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Recommendations received
7 people have recommended Shehram
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Dan Spellman
Love this new video from NVIDIA, on how OCI + NVIDIA are partnering to support enterprises and simplify generative AI adoption, to accelerate drug discovery, medical imaging, genomics and more! Enterprises can also generate up to 5x higher throughput of Llama 3 70B and connect directly to data inside Oracle database!
2 Comments -
Romuald Josien
Your onprem GPU server is nice...but...what if you had each year the newest GPU? Run with OCI AI ! L40S & H100 today, H200 tomorrow and B200 after tomorrow... 😎 The benefit of Cloud is still more true for GPU accelerated compute, and still more today, with now performance gap between NVIDIA GPU generations reaching 30X (B200 vs H100 for Inference), and with, in //, the GenAI models complexity growing exponential.
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Manik Patil
📢 NVIDIA aims to boost #developerproductivity with NIM (Nvidia Inference Microservices). ✔ Provides a simple and standardized way to add Generative AI to applications ✔ Provides models as optimized containers pre-built to speed model deployment for GPU-accelerated inference ✔ 40+ community models available incl Google’s open model Gemma, Meta's Llama 3, Microsoft's Phi-3, Snowflake's Arctic ✔ Allows enterprises to efficiently use infrastructure - bye, bye unnecessary infra costs #mindfulCIO #GenAI #AI 🍒 Share your thoughts in the comments. 👇 🍒 Like and share this post with your followers. 💓 🔗 See comments for the link
4 Comments -
Rimah Harb
OpenAI and Broadcom in talks about developing new AI chip OpenAI is in talks with Broadcom and other industry leaders to develop a new chip tailored for AI applications, potentially reducing reliance on NVIDIA #GPUs. Sam Altman has been instrumental in spearheading efforts to secure partnerships with #chipmakers, tech giants like Microsoft, and government bodies to enhance #compute capacity essential for #AI #innovation. This move underscores OpenAI's commitment to advancing artificial general intelligence (#AGI), aiming to push the boundaries of AI capabilities beyond current standards. Despite the formidable challenges and substantial financial requirements, including Microsoft's substantial investment, OpenAI remains focused on expanding access to AI benefits through strategic partnerships. For more information: https://lnkd.in/dYHej2Kc #AI #ArtificialIntelligence #OpenAI #TechInnovation #Semiconductors #Broadcom #Microsoft #AGI #AIHardware #TechPartnerships
1 Comment -
Raghavender ganti
Discover how #NVIDIAInception startup LiveX AI Inc. leveraged NVIDIA AI and GKE infrastructure to build #generativeAI agents that provide real-time, human-like customer experiences. 💡 Using NVIDIA A100 GPUs and NVIDIA NIM microservices, LiveX AI achieved a 6.1x acceleration in response generation speed for their AI agents.
1 Comment -
Elizabeth Press
What new questions can we ask? What answers do Large Language Models enable? 'How large language models enable network analysis' - a conversation with Sven Sewitz and Elizabeth Press from D3M Labs.🚀 Most organizations are still in the "Awareness" phase, where according to Gartner, interest in AI is sparked. Some advanced organizations have moved to the "Active" phase, where there are proof of concept projects, but those are few and far between. While infrastructure and tool chain remain barriers to feasibility 🚧, the questions persist: 🤔 What new inquiries can we make? How will this impact the culture and organization of data teams and their organizations? 🌐 Introduction: How did Sven become a computational biologist and what does a computational biologist do? 1:50 What is network analysis and why do you think it will be a new paradigm going forward? 3:17 Why are large languages an enabler to network analysis? 5:17 What are hurdles to implementing large language models for network analysis in an actual company? 7:32 There is a large amount of infrastructure investments that are crucial. What are some steps that companies can take? 9:04 Data education and cultural aspect that has to change. What new questions can you now ask? 9:52 How can organizations start along the journey? Follow D3M Labs to continue the conversation. Subscribe to the D3M Labs YouTube Channel. https://lnkd.in/e5Ms-sKt
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