“Kartik and I worked together on many of the strategic initiatives for Amazon Advertising, and I admired Kartik's ability to maintain balance and a level head in situations that were often very contentious. People/I like working with Kartik, he has a very easy going nature that makes him a please to work with. Kartik brings a wealth of technical knowledge and interpersonal skills that really benefits the organizations and cultures he is a part of.”
About
With over 15 years of experience leading engineering programs and driving product…
Contributions
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What is the pitch funnel and how can you use it to create a winning pitch?
The final step of the Funnel involves negotiations and deal closure. Critical things to lookout for: - The terms of the investment - Valuation - Legal considerations. Remember, most of us in tech sphere are not black suites, always get a legal counsel to fully understand the implications of the terms being offered.
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What is the pitch funnel and how can you use it to create a winning pitch?
Having meticulously narrowed your options down to 1-2 potential sponsors, it's crucial to approach the final step with clarity and precision. This is the moment to provide a compelling rationale for your investors to commit. Your pitch at the bottom of the funnel must be succinct and laser-focused. A clear, unambiguous call to action, whether for investment, a purchase, or project approval, is essential for driving decisive action from your sponsors.
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What is the pitch funnel and how can you use it to create a winning pitch?
In the dynamic landscape of product acceptance, the pitch funnel framework helps not only to bring your ideas to the audience but also helps get the sponsor that is best suited for your product. In my experience you often get the right sponsor through a well-structured journey from awareness to interest, and finally to commitment. This helps ensures a mutual fit between your product's vision and the sponsor's objectives.
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How can you demonstrate your ability to manage change in a project?
Effective change management is all about being simple, flexible, and be ready to evolve Before you start, defining an effective process helps guide the change process without derailing your project's train. Below are some key steps: 1. Early identification of potential changes through stakeholder feedback and retros. Start by Asking Why do we need this. 2. Approving only beneficial changes, based on timeline, resources, costs and non-tangible (culture, people dynamics). 3. Maintaining clear communication about changes, reasons, and impacts. 4. Assigning roles like change managers and project managers for accountability. 5. Evaluating, documenting, and tracking changes using tools. 6. Continuously reviewing and adapting based on feedback.
Activity
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About 3 years ago after 9 years at Amazon I decided to leave Amazon to try something different. 8 months later Alan Lewis called me up and asked if…
About 3 years ago after 9 years at Amazon I decided to leave Amazon to try something different. 8 months later Alan Lewis called me up and asked if…
Liked by Kartik M.
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Hitchhiker's guide to rebranding: - Machine learning -> statistical mechanics - Loss function -> energy functional - Optimize the model -> minimize…
Hitchhiker's guide to rebranding: - Machine learning -> statistical mechanics - Loss function -> energy functional - Optimize the model -> minimize…
Liked by Kartik M.
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GB200 - love the progress we’ve made with our Nvidia partners on this awesome new system :)
GB200 - love the progress we’ve made with our Nvidia partners on this awesome new system :)
Liked by Kartik M.
Experience
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Education
Licenses & Certifications
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Supervised Machine Learning: Regression and Classification
DeepLearning.AI, Stanford University
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1 person has recommended Kartik
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And the badge turns Red. It's been a tremendous decade contributing to flagship zero-to-one products like FireTV, Alexa Skills & Alexa Shopping and…
And the badge turns Red. It's been a tremendous decade contributing to flagship zero-to-one products like FireTV, Alexa Skills & Alexa Shopping and…
Liked by Kartik M.
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As the days grow shorter and the Seattle skies fill with clouds, Diwali brings a warm glow to our hearts. Celebrating Diwali here is unique – while…
As the days grow shorter and the Seattle skies fill with clouds, Diwali brings a warm glow to our hearts. Celebrating Diwali here is unique – while…
Shared by Kartik M.
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NVIDIA AI silently released the Llama 3.1 70B Instruct Nemotron model which is topping the leaderboards. You can try it for yourself…
NVIDIA AI silently released the Llama 3.1 70B Instruct Nemotron model which is topping the leaderboards. You can try it for yourself…
Liked by Kartik M.
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🔜 NVIDIA GB200 GPUs on Google Cloud Watch a sneak peek at how Google Cloud is preparing to bring the power of NVIDIA GB200 NVL72 GPUs to our…
🔜 NVIDIA GB200 GPUs on Google Cloud Watch a sneak peek at how Google Cloud is preparing to bring the power of NVIDIA GB200 NVL72 GPUs to our…
Liked by Kartik M.
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I had so much fun discussing eval with Chip Huyen and Atindriyo Sanyal at Productionize this week! Thanks again for inviting me Yash Sheth, Atindriyo…
I had so much fun discussing eval with Chip Huyen and Atindriyo Sanyal at Productionize this week! Thanks again for inviting me Yash Sheth, Atindriyo…
Liked by Kartik M.
Other similar profiles
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Himanshu Kohli
During his Q&A at 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 today, 𝗦𝗮𝗺 𝗔𝗹𝘁𝗺𝗮𝗻 mentioned an interesting thing - “𝗜𝘁𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗱𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁” Interestingly, earlier this month, in one of the blogs, OpenAI explained how they are improving AI safety by learning from real-world use to improve safeguards via Iterative deployment. And apparently, this is very similar to what Meta CEO Mark Zuckerberg said earlier this month - 𝙛𝙚𝙚𝙙𝙗𝙖𝙘𝙠 𝙡𝙤𝙤𝙥𝙨 𝘸𝘪𝘭𝘭 𝘣𝘦 𝘮𝘰𝘳𝘦 𝘷𝘢𝘭𝘶𝘢𝘣𝘭𝘦 𝘧𝘰𝘳 𝘵𝘳𝘢𝘪𝘯𝘪𝘯𝘨 𝘈𝘐 𝘮𝘰𝘥𝘦𝘭𝘴 𝘵𝘩𝘢𝘯 𝘵𝘩𝘦 𝘥𝘢𝘵𝘢 𝘰𝘳 𝘢𝘯𝘺 𝘬𝘪𝘯𝘥 𝘰𝘧 𝘶𝘱𝘧𝘳𝘰𝘯𝘵 𝘤𝘰𝘳𝘱𝘶𝘴 I totally agree with this view point. It is critical to leverage real-world customer usage, understand how customers are using AI tools, and then improve from there. This is going to be more differentiating than just training models with the existing, non-real world data. I think we are heading towards a world where we will start having very use-case and scenario specific trained AI tools. And to achieve this, organizations need to incorporate iterative deployment or feedback loops, while building their AI tools. If you haven't, do read the following: OpenAI blog: https://lnkd.in/gwy2jhqR Mark's interview: https://lnkd.in/gkEtR7bb #genAI #openAI #LLM #Meta #llama #AI
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Jess Nall
From where I sit in the SF Bay Area, cradle of innovation for at least the last 30 years, I'm a true believer in the promise of the #AI revolution. That said, I find it fascinating to consider views on the opposing side. I'm sharing below two opinion pieces from the last two weeks suggesting that the AI revolution is fundamentally overhyped and a bubble ripe for bursting, and that AI tools are actually not useful or transformative. Contrast this with venture capitalist Kai-Fu Lee's prognostication that 50% of white collar jobs will be displaced by #AI within three years, and that OpenAI and the other cutting edge movers in the space are headed to a trillion+ dollar valuation. Which side will win out? Where will we be by 2030 in the AI race? I'd love to hear your thoughts in the comments.
3 Comments -
Candace Gillhoolley
Google Cloud and Highmark Health are pioneering efforts to use generative AI to customize the patient intake experience. Similarly, Amazon’s AWS is exploring how generative AI could sift through medical databases to identify social health determinants. Microsoft Azure, on the other hand, is aiding in the creation of a system to manage patient-provider communications more efficiently. In the startup arena, companies like Ambience Healthcare, Nabla, and Abridge are at the forefront, developing AI-driven tools for clinical and administrative support. These ventures have attracted significant venture capital, indicating strong investor confidence in the potential of generative AI in the health sector. What do you think? #EthicalConcerns #PublicPerception #ProfessionalSkepticism #Consumers #generativeai
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Sal Huante
AI played a pivotal role in Google Cloud’s impressive performance, nearly 90% of generative AI unicorns (start-ups valued at $1 billion or more) are leveraging Google Cloud for their model development. Boasting robust data center infrastructure, Google Cloud provides a powerful environment for AI training, alongside offering a diverse array of over 130 pre-built AI models, including Google DeepMind’s Gemini, to expedite application development for customers. Access to such cutting-edge models influences developers' preferences for Google Cloud over other platforms, underscoring the importance of continuously enriching the platform's AI offerings. #AI https://lnkd.in/gvqdTEGf
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Satish Nanduri
Is Gen AI hype or real? Hosting a panel of experts from Amazon ( Thank you- Muthu Muthukrishnan, Jeetu Mirchandani, Mukesh Karki, Anand Rathi) in AWS Fintech summit to talk about building enterprise Gen AI solutions and applying Gen AI at scale was an honor. We discussed potential, technological challenges, including hallucinations and accuracy, cost, and go-to-market plans for AWS, Advertising, Stores, and the AGI space. #GenAI #ArtificialIntelligence #AWS #FintechSummit
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