Suresh Visvanathan

Insightful explanation of how do go channels work behind the scenes. Its all about yielding the ptocessor for other goroutines. https://lnkd.in/gbyQ4yH9

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Presenting at #MRCVegas2024 was a true pleasure and the response to our session, "Future of Strong Auth – Passkey" was fantastic. Shout out to Anand Bahety, Mahendar Madhavan, and the team for their invaluable contribution in enabling passkey capabilities for eBay users. Also, thanks to Kathryn Irwin and Julie Fergerson, CPFPP from #MRC for the opportunity and for making this conference possible. A few things to share on the topic of Passkey and its impact on payment risk management: 1. Passkey has significant potential as an option for 3DS, a standard currently in draft at EMVCo. If anyone is interested in learning or collaborating further, feel free to reach out to Ulrich Herberg, Ph.D. from eBay who has been actively involved in these discussions. 2. It would be particularly intriguing to see how EU regulations will classify passkey—whether as a two-factor or as a single-factor authentication method. 3. I learned from some of my friends about how some EU banks are already adopting mobile apps for verification over SMS. Similar innovations in the U.S. would be awesome! I'm eager to hear your thoughts on the following topics: 1. Has the widespread adoption of 3DS in the EU indeed resulted in lower chargebacks compared to the U.S.? 2. Given Passkey's potential, do you think it has the capability to not only safeguard accounts but also mitigate first-party chargebacks?

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The scale we deal with, the complexity it brings in and the impact we create for millions of customers across the globe, are defining moments for our teams at Amazon India. Every day, our tech teams invent and deliver things that were never thought as possible! #HearFromBuilders at Amazon on how they solve real-world problems with technology. #NationalTechDay #ItsStillDay1 #AmazonIndia #TechAtAmazon

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Our trajectory with Google Cloud epitomizes a transformative strategic pivot. What began as a challenging market positioning has evolved into a compelling narrative of operational resilience and technological leadership. Over seven pivotal years, we've fundamentally reimagined our enterprise value proposition—transitioning from a peripheral cloud solution to a mission-critical AI innovation partner. The financial metrics tell a powerful story: we've systematically converted recurring quarterly deficits into a robust framework for sustainable profitability. Buckle up the next 7 years are going to be epic @ Google Cloud! 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 🚀 #google #googlecloud #GCP #gcpcloud

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Looking to get started with in-database machine learning with MySQL HeatWave? This guide will help get you on the right path. https://lnkd.in/gPjuJU9g

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All conversations start with how my profile/ EB1 application looked. Here's a brief review of what I think worked. https://lnkd.in/g3pTgc4P More blog posts are on the way as I break down the conversations I have been having. And, as always, find a time to chat here: https://lnkd.in/gJ2eyCGP #EB1 #EB1A #immigration #profile

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WarpStream is a like 'Aurora Kafka' that is managed cloud native architecture reimplantation and no on-promise design of Kafka compatible. save cost by using S3 and reduce cross az data. But most people aren't aware or agree that, 99.99% of apps do not need any cross az high availability. They do need the same az HA and rapid DR recovery with lost control. Not bills. even if you do cross az, you should stop at 2. https://lnkd.in/gdMX-ZFb

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Check out how Meesho, one of India's leading e-commerce platforms, made the leap from Amazon ElastiCache to Redis Cloud on GCP! With Redis, they’ve scaled their operations to support 165M+ customers and 2.2M+ sellers, delivering blazing-fast performance, unmatched reliability, and seamless personalization during massive sales events (think Black Friday-level spikes!)

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Very interesting post on Intuit's use of LLMs to manage K8s, via Aditya Kulkarni at InfoQ: "Intuit Engineering's Approach to Simplifying Kubernetes Management with AI" https://lnkd.in/eRN6_sAK

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Great read on our journey to securing your AI investments from Steph Hay and Umesh Shankar #1 - AI opens up a world of possibilities. Be proactive in securing your AI investments - data, models, applications, and infrastructure. #2 - Make Google part of your security team, and Security Command Center - Enterprise as your default platform to help secure your AI investments. #3 - New capabilities in Notebook Scanner (private preview) and Model Armor (previewing soon) to secure your AI investments. Shout out to Amit Patil, Bharath Chandrasekhar, Matt Driscoll, Bhaskar Annadata, Cfir Cohen, Rahul Venkatraj and many more for these new capabilities.

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🔋 Amit Mishra, Engineering Manager II at Credit Karma, talks about how his team empowers developers focus on what they do best—coding—while JFrog Artifactory takes care of seamless dependency management. 👇🏼 Watch below to learn how Amit leverages Artifactory to streamline processes and empower developers!👇🏼 If you're looking for a similar outcome, get started on JFrog for free today: https://jfrog.co/3DfgPn3

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💡 Exploring Advanced RAG Together 💡 For those considering or already working on integrating RAG-powered GenAI assistants into your products or solutions, I’m excited to share some learnings in an upcoming talk. This session builds on the basics we explored sometime before (https://lnkd.in/dBw4UGA4) and dives into recent advancements like DRAGIN, ERAGent, and GraphRAG. These concepts are inspired by some fascinating research papers that I’ve been exploring, and I hope this discussion can spark ideas and conversations within the community. If this resonates with you, feel free to join in. I’d love to hear your thoughts and experiences as well! 🙌

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I am not sure Google’s primary duty should be to shareholders, including mass firings to pay for GPUs. As a shareholder, I am thankful to be able to own a few shares of Google in my retirement account. But Delaware Supreme Court case law serves unjustly as a faux federal loophole to maximize profits above all else, enabling amoral fiduciary duty to conventional shareholders. And it seems that employees are shareholders - should one class of shareholders be favored over another? It seems like the law needs to include stakeholders like the economy in which a company arises and the communities in which it does business. If a given government has a shrinking middle class, is it not true that eventually the corporate tax base will not be enough to pay for adequate national defense or safety nets? I happen to be pro-Google, especially because of their contribution to help so many businesses utilize the trackable ROI of Google Ads, and for many other reasons. As far as I know they obey the law - and it seems like the law needs to change. I also happen to believe it is good for the world to spread economic opportunity and jobs. But what makes up for all the money and tax these core Google employees were spending on the American economy, or the people who will lose out on a job opportunity because a Xoogler applied? Housing costs in SF are insane, what about their mortgages? Maybe they are millionaires, maybe not. I kind of doubt Google fired AI engineers, but maybe instead of hiring domestically they will hire wherever the AI labor is cheapest. I happen to be pro-immigration and my ancestors were immigrants. I don’t pretend to presume the right balance of domestic and offshore workers. I have been very pleased to collaborate with people and pay them out of pocket and be able to afford it because of the labor discount. But I am not a hugely profitable corporation either. I tend to believe in unfettered capitalism and that too much tax and regulation can stymie an economy and hurt everyone. Yet an economy needs to be sustainable, and not just for conventional shareholders. I am not sure there is a check and balance to the “duty to shareholders”. Public outcry used to be one, but not anymore, not after the massive tech hiring and layoffs. Maybe it is just competition. But it doesn’t seem biomimetic, as in natural balance between various forces in a biological system. If an economy was a body and large corporations were organs in the body, if money was water and employees are like blood, then the corporate organs seem to be growing abnormally and taking more moisture out of the system. In a normal body the organs would have limited growth but in this body the corporate organs are growing larger, while the rest of the body slowly dries out, and blood clots form from employees who are no longer needed. The corporate organs are less reliant on employees and are now making their own blood and selling it.

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Pranay Prateek from SigNoz shares his thoughts on Unified Observability and how Open Source Signoz can help you to harness OpenTelemetry (OTEL) for Traces, Metrics at Logs. This talk took place at Open Source Observability Day #opensource #observability #otel

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From a tech lead at FAANG to Senior Manager at a hyper growth scale-up. How my client transformed herself to land her dream role while following her heart 👇 My client came to me looking for a change... Her career at FAANG has stagnated. She did all she could. All the major problems were solved and there was little room for growth. But she was itching to take the next step in her career. To have a bigger business impact. To lead larger teams. (I see this story way too often) So we go to work... We got clarity on her next role. We found openings that could be a good fit. We overhauled her resume. Updated her LinkedIn. The interviews started rolling in. But she could not get over the final hurdle. She was not used to failure and the rejections hurt. Is pursuing career growth worth all this pain? She was about to give up... But then, she saw an opening for a health-tech org that solved problems close to her heart. Something she was super passionate about. Something that helps others. So she made a full-hearted decision: 𝗟𝗮𝗻𝗱𝗶𝗻𝗴 𝘁𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝘄𝗮𝘀 𝗺𝗼𝗿𝗲 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝘁𝗵𝗮𝗻 𝗵𝗲𝗿 𝗳𝗲𝗮𝗿 𝗼𝗳 𝗳𝗮𝗶𝗹𝘂𝗿𝗲. She was determined to truly give it her best. Even if it meant falling flat on her face yet again. So she extended our coaching. She took PTO.   She put in the time. In other words, she went all-in. And let me tell you - she is a changed person. The woman who first came to me that was terrified of making a mistake now oozes confidence. She speaks with certainty. She has authority. She believes she is worthy. And the offer she got? That was just a confirmation of the person she has become. She is now truly embodying a Senior Manager. A Senior Manager on a mission to make the world a better place. -- Deep down we all want to do something that matters. We're ingrained to help each other. To have a positive impact on society. My client found that job. She's passionate about the business. And the role is a fantastic for her career. That's what I call a win-win. So if your career has stagnated and you want a job that truly matters while growing your career, let's talk: https://lnkd.in/d_aGvXim

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Learn how to secure and govern your LLMs with UAPIM so that you can safely implement these powerful AI and LLM models into your business.

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Evaluating my fine tuned 3B model with LLM judge - many of you have asked so here goes :-). Tl;Dr - 91% accuracy vs 47% not-fine tuned; with only 140 examples and 3 minutes of training (https://lnkd.in/gHw993ZS) I started out with creating a new synthetic test data set that the fine tuned models haven't seen, using the same code from the training set (data here: https://lnkd.in/gcCSdT5e). I used Comet's Opik per Armand's recommendation (you should follow him if you aren't :-)). Then built my evaluations test for (1) JSON schema compliance, (2) distance from reference answer (3) the LLM Judge which scores first on json format, then on compliance with schema, then on entities being detected, then on not detecting more than necessary. I tried this out with a bunch of LLMs that could run on this laptop, as you can see the 3B fine tuned one performed the best, followed by the 1B, then all of the out of the box ones pretty similar and not so great. Code for you to enjoy: https://lnkd.in/guhzdUkf You'll need a Comet account, which is shockingly free. Enjoy :-) Next I'm going to try to beef up the data gen with Distilable and CrewAI, let me know if you find that interesting or have other ideas.

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AWS continues to add capabilities to Amazon Bedrock that make it the easiest way to build high quality, low latency, and cost-effective GenAI applications. Today the team announced:   - Custom Model Import, which lets customers easily bring their own models (from SageMaker and S3) to Bedrock to leverage its leading GenAI features, such as RAG, agents, Knowledge Bases (guardrails), inference deployment, and advanced customization to keep teaching and refining models.   - Model Evaluation, which lets customers quickly select predefined evaluation criteria (like accuracy and robustness) and run reports that help them understand which is the best model for them.   - Meta’s new Llama 3 models, now available on Bedrock and can support a wide range of use cases including text summarization and classification, sentiment analysis, language translation, and code generation.   - New Cohere Models, Command R and R+, are state-of-the-art FMs customers can use to build enterprise-grade generative AI applications with advanced RAG capabilities, in 10 languages, to support their global business operations. These will arrive on Bedrock in the coming weeks.   - New Amazon Titan models with Amazon Titan Image Generator (GA today) helping customers produce studio-quality images, at low cost, using natural language prompts (and applies an invisible watermark to help reduce the spread of disinformation)… along with Amazon Titan Text Embeddings V2 model, which reduces storage and compute costs, while out-performing other leading models on text embeddings.   Tens of thousands of customers are already building real-world production-ready GenAI apps and we're excited for even more customers to get started. https://lnkd.in/g4rkak47

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