Imran Moin

Google Cloud Vertex AI is rolling out multiple updates to make AI accessible for every enterprise. Up to 85% lower input costs and 80% lower output costs, and 100+ new languages coming to Gemini 1.5. #GoogleCloud #VertexAI #Gemini

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Super excited about this talk! I'm going to dive into some of the work we've done under the covers in AWS, in services like Lambda, Aurora, and DynamoDB, to make them even more resilient, and how to apply those same techniques in your own systems.

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Last April I gave a talk at Palo Alto Networks about AI's impact on enterprise software. I didn't know Satyam Sinha, their VP of Engineering, was in the audience—and he'd been thinking about this for months. He soon resigned and shifted focus to building a startup that would push AI innovation forward instead of simply adapting to it. Fast forward to today: My partner Jaya and I are thrilled to announce that Acuvity, the company born from Satyam's vision, has raised a $9M seed round led by Foundation Capital, with participation from Jonathan Siddharth (CEO of FC portfolio company Turing) and other angels. Acuvity tackles one of the most pressing issues in enterprise AI adoption—security. Companies rushing to leverage AI are exposing themselves to unprecedented risks of data leaks and compliance violations. Samsung's recent AI-related data breach is not an anomaly. Satyam and his co-founder Antoine Mercadal have developed a novel approach using AI models to monitor AI usage, combining elements of classical machine learning with LLMs. It's an elegant solution to a complex problem, providing enterprises with the visibility and control they desperately need. This investment combines two of Foundation's deep convictions: the transformative power of AI and the critical importance of data security. We've been investing at this intersection for over a decade, from MobileIron to Fortanix to Skyflow. We're excited to lead this round and partner with Satyam, Antoine, and the entire Acuvity team on their journey to secure AI-powered enterprise! Read more: https://lnkd.in/gPiiutpD

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Kapil Khangaonkar, CEO of Clodura.AI, shares how Google Cloud fueled their growth: 71% less tech debt, 12x faster app delivery, & significant customer growth. 🚀 Ready to transform your startup? The Google for Startups Cloud Program now offers new benefits for AI startups, giving you the technology and resources to build easily. Take advantage of our open AI ecosystem and tap into the best of Google’s infrastructure, AI products, and foundation models.   Sign up today and unlock your startup's potential! #startups #cloud #GoogleCloud #CloduraAI #techstartup #startuplife #AI #buildwithAI #GoogleAI #GoogleforStartups #GoogleCloudforStartups https://goo.gle/GFSCP_CS Clodura.AI Google for Startups

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Uddhav Gupta, President of CloudBlue, joined me for an exclusive interview as his company 🎯 launched a new offering designed to help ISVs leverage hyperscaler marketplaces. CloudBlue has a proven track record of enabling ISVs to sell through various marketplaces. Uddhav emphasized, “There are over 200+ ISVs…that are using us to basically go through a multi-tier marketplace whether it's the distributor's marketplace, whether it's a reseller's marketplace, whether it's a telcos marketplace.” 🔁 A Tectonic Shift in Go-to-Market The emergence of hyperscaler marketplaces marks a profound shift in ISVs' GTM strategies. These platforms are quickly becoming “one of the most important routes to market that's coming up these days,” stressed Uddhav. He highlighted that rapid customer adoption of the #cloud and changing buying preferences are key drivers of this trend. “Customers on the other end are also adapting the cloud more aggressively. And they are also seeing the hyperscaler marketplace as a procurement vehicle for them to basically buy products.” 📊 In Today's Multi-Marketplace Environment, ISVs Need to Be Everywhere Uddhav explained, “Every technology vendor out in the market is creating their own ecosystem marketplaces, their own app stores, their own app exchanges, and then also creating really strong bundled offerings on the hyperscaler marketplaces.” This complexity requires ISVs to orchestrate multiple routes to market efficiently. “You need to centrally manage all the subscriptions across these multiple routes to market. You need to onboard a product once and be able to take a flavor of that product and push it through any of these marketplaces,” he emphasized. 💡 One Platform & Framework for ISVs CloudBlue’s new offering aims to simplify this process. “We are very excited to announce that taking all of this knowledge that we have in helping ISVs get onboarded to several hundred marketplaces, we've now created the knowledge base that's needed and the technologies that's needed to make onboarding to hyperscaler marketplaces extremely seamless,” highlighted Uddhav. 📈 GTM Strategy Comes First, Before the Orchestration Platform Often, ISVs believe that for successful Cloud GTM they need to start with a platform first, but Uddhav advises otherwise. “And as much as I love the thought, but as a true design partner, I would say creating this strategy comes first. You need to put together a team that can execute on that strategy, right? And the strategy is basically all about how are you gonna create a demand in whatever hyperscaler marketplace you take?” The good news is that hyperscaler #marketplaces “they've created enough incentives for ISVs, they've created enough incentives for their customers, and they've created enough incentives for even their field to basically draw you in.” Watch the entire interview to learn more insights from Uddhav Gupta on the new CloudBlue offering https://lnkd.in/ejv5G4YP

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Llama 3 70B is already in the top 6 of all LLMs, showcasing better accuracy than much larger, proprietary models. It’s a testament to the power of data quality and showcases that open, small models can deliver leading performance – perfect for #edge deployments. With the release of new models like Phi-3 (mini 4B, small 7B and medium 14B), this trend is clearly accelerating.   Open-source small-to-medium sized models trained on high quality data can deliver market leading performance comparable to the largest proprietary models – great news for bringing #AI everywhere at the edge.   View the public leaderboard below.   #IAmIntel #OpenSource #LLM   https://lnkd.in/g5K_7P5d

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Data marts, warehouses, lakes, whatever the name, the pattern of consolidating data across an enterprise for comprehensive analytics is a familiar one. Every enterprise has many data sources, some operational, some analytics, some telemetry, and bringing them together has always been a challenge. Cleaning the data, curating for consistency, exploring, doing data science, building reports, monitoring, is another series of challenges in bringing a range of tools to bear on the data, thanks to diverse data formats and tooling. With Gen AI, the requirements (e.g., vector indexing for RAG) and potential value of the data have both gone up. And the pressure to ensure right use of the data, to comply to a broad range of regulations, to secure the data has never been higher. We believe the time has come to come together around open data standards to ensure that data is easy to consolidate and easy to plug into a wide variety of tools, all in a properly governed way. Josh and I describe the approach we are taking at Microsoft with Fabric and Purview. We are building on open Parquet-based updatable table formats such as Delta, Iceberg and Hudi, and interop across them with XTable. We are making it easy to consolidate data with mechanisms like mirroring and shortcuts. Ultimately, users should be able to use their tool of choice for a given task with the least friction.

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Join me and @Vishal Srivastava from @Amazon Web Services (AWS) tomorrow for our webinar "Bringing the Power of #GenerativeAI to the Denodo Platform with #AWS." This session will delve into how the #DenodoPlatform uses #genAI to support users across technical and non-technical spectrums. Register now totally free! https://buff.ly/3UMQh2t

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Catch our top Solutions Architects Sri and Rita in this session at AWS Innovate. Learn the latest approaches to rapidly modernize your .NET Applications using GenAI and the power of the AWS Cloud.

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This is a major strategic announcement for both Google and Oracle and a huge market expansion opportunity for both. Most #enterprises continue to adopt a #multicloud strategy, powering #apps on the best fit solution for their needs. Google Cloud has been making major inroads into enterprises, and Oracle solutions and increasingly Oracle Cloud remains a strategic imperative for many organizations where their key data assets remain and where mission critical apps run. By enabling the Oracle Cloud Infrastructure suite to run on Google Cloud, and without charging any data transfer fees, Oracle is greatly expanding its potential market and scale, while Google gains an installed base to expand its presence against Amazon Web Services (AWS) and Microsoft Azure . This partnership also enables Oracle to add leading #AI capabilities to their solution through Google #Gemini which will continue to expand its capabilities over time and enable Oracle to not have to develop its own AI infrastructure, allowing it to concentrate on its enterprise grade business solutions. This is a win-win for both companies and a major opportunity for expansion as enterprises already operating on Google Cloud have a clear incentive to adopt and/or expand the use of Oracle capabilities without the need to implement another cloud instance. It's also a major opportunity for those companies that are still on-prem with Oracle solutions to have a #cloud upgrade path they may already be familiar with.

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Challenges of AI Networking for hyperscalers and enterprises Sept 27, 2024 I had the opportunity to meet with Manohar Paluri, VP of AI at Meta, this evening at the AI Tech Leaders Club, just under 24 hours before the AI Infra Summit on September 27, 2024. It’s been confirmed that the large training cluster at 500K GPUs is the next frontier for the hyperscaler industry. Meanwhile, on the enterprise side, standalone cluster sizes typically range from 20K to much smaller setups for retraining and inference. From my experience, while the challenges in these two sectors are intertwined, they can still be stated separately. 1) Checkpointing Challenges: Large GPU clusters require numerous checkpoints to maintain system reliability. The industry has recently implemented networking and checkpointing solutions for clusters with around 20K GPUs. Imagine the challenges we’ll face at the scale of 500K GPUs! 2) GPU Utilization: Typical GPU utilization hovers around 20%. While hyperscalers may achieve better numbers, overall utilization remains low. For this, a startup came up a clever solution to power down the idle GPUs dynamically to save up to 60% of power consumption from a GPU cluster. This approach could either reduce power usage from idle GPUs or, in conjunction with increased GPU utilization through further resources sharing—like memory, network, and model partitioning/parallelization—enhance overall efficiency. 3) Deployment Flexibility: The deployment of data center networks (hyperscaler cloud) or private networks (on-premises) for enterprises often lacks the necessary flexibility. For more insight, I recommend reading the justification for Google’s Optical Circuit Switching (OCS) network. Following conventional practices without innovative solutions can lead to over-investment in AI and cloud infrastructure. 4) ROI Optimization: Classic cloud infrastructure is often not optimized for ROI in AI networking, which leads to operational challenges for enterprises. To understand this, a little involved discussion is needed. Once understood, it becomes part of your instinct. Consider the competitive disadvantage faced by businesses that optimize ROI in their AI networks. Free Takeaway from me: Conversations about the challenges of AI infrastructure and networking are very welcome at the AI Infra Summit, and participants will receive the latest AI networking problem slide! 😊

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The International Electrotechnical Commission (IEC) produces standards worldwide and it's members, in their wisdom, introduced IEC 61499. The IEC 61499 standard is a system-level design language for distributed information and control systems. It starts with event-driven function blocks and the behavior of a function block is defined as an event-driven state machine known as the Execution Control Chart.   This international technical commission, made up of technical experts worldwide, says events and state machines should be used to design automation systems.   DADA X uses events and state machines(with causal tracking) to control systems. The future is Event Computation, click on the video link below to see why!

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IBM THINK is happening now in Boston…. Enterprise Customers are firmly supporting a number of key priories regarding AI. 1). TRUST is critical. Both the data used to train models and the governance used to ensure they act consistently in accordance with policies, intent and regulatory environments. 2) OPEN provides critical flexability to use the right model - for the right use-cases. 3) ECONOMICS matter - to go from pilot to production requires both a compelling aggregate business case and efficient inferencing unit-costs.

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Indraneel Shah and I are super excited for our investment in Atomicwork. Great to work with Vijay Rayapati again (successful exit of Botmetric with Nutanix). With this round of investment Atomicwork now has the backing of leading funds and 40+ enterprise CxOs 🚀 for a total funding of ~$14M. As a digital advisor to enterprises, we deal with the fragmentation of applications and workflows. We see an need to modernize service management for businesses to unlock growth, productivity, and profitability without letting complexity interfere while accelerating the adoption of Agentic AI and AI Agent OS. Shifting service management to tools like Slack or Microsoft Teams can help organizations move from being: ✨ Portal-centric —> People-centric ✨ Ticket-based —> Context-based ✨ Process-focused —> Productivity-focused Priya Modh Nidhi Shah Troy Wyatt Andrew Haggard, MBA Ty Panagoplos Frederic Dussart Bhuvaneswari Subramani Natallia Beliakova Mukesh Singh Anand Kumar (AK) Intuitive.Cloud Intuitive.VC Parsuram Vijayasankar Kiran Darisi https://lnkd.in/g_UK6yAk

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Steven Karachinsky “gets it”. His recap on how we all need to adapt to the #ITprocurement ecosystem is spot on. #ISV’s and customers alike need a solid multi-cloud #Marketplace strategy. Proud to partner with ZIRO for Microsoft Teams voice solutions. They understand UCaaS and CCaaS, and are relentless in the pursuit for a positive multi-cloud customer experience, regardless of how the customer prefers to buy.

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