A. Adam Wilson

The Forbes 2024 Cloud 100 List is live ☁ Congrats to all the honorees – the world's top 100 private cloud companies –including the 3 healthcare and life sciences companies featured this year: • Benchling - biotech R&D platform • Komodo Health - healthcare data analytics • Abridge - AI for clinical documentation For more on how AI is colliding with cloud computing, check out Bessemer Venture Partners's 2024 Cloud 100 report. Personally I'm focused on advancements in multi-modal AI, as applied to biomedical applications (Trend 3!): https://lnkd.in/euzurvQV

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Hard-coded model routing takes away intelligence from your system instead of adding to it! Interesting read below on how Ema Unlimited's Fusion model is a potent solution for the heterogeneous multi-model future of AI in the enterprise.

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Worth reading: How the Apache Arrow Format Accelerates Query Result Transfer by Ian Cook One of the hidden problems of intersystem communication is transcription of data formats. Ian does a wonderful job of explaining the "why" of Apache Arrow as well as the "how" of its advantages. Read on...

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If you have any interest in cloud marketplace distribution and strategy, then I highly recommend that you follow Roman Kirsanov. For Prolific this is another endorsement of our cloud partnership strategy and highlights the crucial role of high-quality human data in customizing foundational AI models to make them more representative of diverse applications, use cases, and ultimately, humanity itself. Exciting times ahead as we continue building a future grounded in responsible and impactful AI.

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🔍 When #Correlation Meets #Causality: Navigating the GTM Minefield 🔍 In the world of Go-To-Market (#GTM), we often find ourselves enamored with data. It’s like finding patterns in clouds—sometimes what you see is more about imagination than meteorology. Remember, just because two things happen together doesn't mean one caused the other. 🌥️=☔? Not always! For example, just because your ice cream sales spike the same month you launched a new ad campaign doesn't mean your ads are making everyone crave ice cream. Maybe it's just... summer. 🍦😂 But here’s the tricky part: in GTM—a blend of art, science, and social juggling— we are humans, and like everyone else : we love simplicity. 🤷‍♂️ We crave clear, predictable outcomes because, let’s face it, unpredictability can be daunting. Yet, the reality is that #sales, #marketing, and #customersuccess are far from deterministic. The same goes for #economics. It’s crucial to understand that data, while incredibly valuable, isn’t a crystal ball. 🔮 Data points does not equate to pure or applied science. ⛔️ Just because sales spiked in Q2 doesn't mean your new email template was the magical ingredient. Maybe the market was just ripe, or perhaps a competitor stumbled. So, next time you're tempted to declare victory based on correlational data, remember: correlation is not causation. 🚫 It’s insightful, yes, but it's not an ironclad guarantee of why things happen. Don't fall into the trap—it’s a tempting one because we all yearn for control and simplicity in the complex dance of GTM. #GTM #BusinessStrategy #DataDriven #Marketing #SalesStrategy #CustomerSuccess #CorrelationCausation Stay22 #tech #leadership #travel

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Oracle and Adobe just reported their latest quarter. ☁️ 𝐎𝐫𝐚𝐜𝐥𝐞 𝐂𝐥𝐨𝐮𝐝 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 (𝐎𝐂𝐈): Surging 52% Y/Y, OCI is rapidly scaling as it vies for the title of 4th hyperscaler. Top clients like Meta and TikTok are fueling AI-driven demand, but Capex is expected to double in FY25. 🎨 𝐀𝐝𝐨𝐛𝐞 𝐅𝐢𝐫𝐞𝐟𝐥𝐲 & 𝐆𝐞𝐧 𝐀𝐈: Adobe’s creative suite is being transformed by generative AI. Firefly has seen over 16 billion uses to date, but cautious FY25 guidance has raised questions about its ability to monetize this momentum amid intensifying competition from startups like OpenAI and Stability AI. Both companies face unique challenges, but they highlight the transformative power of AI in reshaping industries—from cloud infrastructure to creative workflows. Dive into the key takeaways and visuals breaking down their performance: https://lnkd.in/eU3bVAqd What do you think—are Oracle and Adobe positioning themselves as leaders in the AI era, or are the challenges too great?

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💡 Digital Adoption Reinvented with GenAI & Agentic Workflows Scaling digital adoption across a tech stack is no small feat—but game-changers like GenAI, AI agents, and agentic workflows are transforming the landscape. 🚀 What’s Different? Unlike static training modules, agentic workflows adapt in real-time. GenAI-powered agents: 👉 Provide contextual guidance and automate repetitive tasks. 👉 Act as on-demand coaches, making onboarding seamless. 👉 Ensure 24/7 support embedded within your software. The Impact: ✅ Faster user onboarding and reduced friction. ✅ Better tech utilisation—turning unused tools into must-haves. ✅ Higher productivity and quicker ROI on digital investments. This isn’t just about better training; it’s a new way for humans and technology to collaborate. Is your organization ready to unlock its digital potential? Let’s talk! #DigitalAdoption #GenAI #ProcessEfficiency #Innovation #ageticworkflows #AIagents

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Interesting notes from Intuit's recent webinar on LLMs. What evaluation processes do you deploy? at tasq.ai our approach is to integrate the AI models with diverse, global human guidance, to support #responsibleai faster and near real time.

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Snowflake and Anthropic have teamed up to bring Claude Models directly to the AI Data Cloud. They signed a multi-year partnership to make Anthropic's Claude models available to Snowflake customers through Cortex AI, a fully managed AI service on AWS. The Claude 3.5 Sonnet model will enhance Snowflake's AI products, like Snowflake Intelligence and Cortex Analyst, with advanced language processing capabilities. Christian Kleinerman from Snowflake said that the partnership expands their promise to offer trusted AI solutions for various enterprise needs. Michael Gerstenhaber from Anthropic mentioned that their collaboration with Snowflake helps businesses use advanced models securely within their data environments. Barry McCardel from Hex highlighted that with Claude, users can now leverage advanced AI models within Snowflake Cortex AI to make informed decisions. Enterprises can use Snowflake's Cortex Playground to compare different models and find the best fit for their use cases. Read more: https://lnkd.in/etasPK3C #ai #artificialintelligence #aistartup

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In 2013, Jay Kreps introduced the concept of the log as a fundamental abstraction for real-time data streaming, paving the way for platforms like #ApacheKafka. Over the past decade, the data streaming landscape has undergone a remarkable transformation, particularly with the rise of cloud-native environments and the integration of scalable object storage solutions like Amazon S3. This evolution has given rise to platforms like #ApachePulsar, each offering innovative approaches to log storage and data streaming. In our latest blog post, we explore the evolution of log storage implementations in data streaming and categorize this architectural journey into three distinct stages: 💡 Leader-Based Architecture Leader-based architectures form the foundation of most data streaming technologies used today. Traditional message queues rely on single-node brokers with primary-backup setups for high availability (HA). Kafka was the first distributed implementation, but it remains leader-based, where a designated leader manages replication. Pulsar advanced this by decoupling compute and storage, but it still follows the leader-based model. This approach works exceptionally well for scenarios requiring ultra-low latency (e.g., milliseconds). For such use cases, sending data through a leader remains unavoidable. 💡 Leaderless Architecture The emergence of S3 as a primary storage layer has triggered a shift toward leaderless architectures. Instead of treating S3 as just a tiered storage solution, it now serves as the main storage layer. In this model, brokers become leaderless, meaning any broker can handle reads and writes. Platforms like WarpStream, Confluent Freight Cluster, and StreamNative’s Ursa Engine are adopting this approach, reflecting the growing trend toward distributed and flexible architectures. 💡 Brokerless / Headless Architecture The next frontier is headless (or brokerless) architectures, where metadata and data are entirely decoupled: Data resides in S3, while metadata is managed by a separate metadata or catalog service. With a standard specification in place, operations no longer need to flow through brokers. Vendors can simply adhere to the standard and build their solutions accordingly. This approach can enable seamless scalability and interoperability. Our Ursa Engine is heading toward this exciting future. Explore the full blog post to dive deeper into these trends and the journey from leader-based to brokerless architectures: https://lnkd.in/gCcmv3rU You can also watch our keynote presentation at Data Streaming Summit: https://lnkd.in/g6a3wHrC

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While the MIT article correctly identifies the limitations of current AI progress measurements, the StrategyOps Framework 2.0 provides a structured solution that bridges the gap between AI technical capabilities and AI business value creation. By incorporating metrics for multi-dimensional technical capabilities, operational causality metrics, and customer outcomes, StrategyOps Framework 2.0 offers a more complete, practical, and meaningful way to measure the stages of AI competence's impact on business value. The framework's ability to identify, quantify, and measure different AI capabilities and business impact contexts while maintaining consistent measurement principles makes it particularly valuable for addressing the concerns raised in the article. StrategyOps Framework 2.0 provides a clear path forward for assessing and measuring AI business value in ways that are both technically sound and business-relevant. Follow me for the upcoming articles on StrategyOps 2.0. . #AI #agenticai #genai #generativeai #businessai #strategyops #strategyops2 #valtics #aibusinessvalue #aiagents Jaime Nelson - PVMP - StrategyOps Value Engineering Kate Garcia Anderson, PVMP Edmund (Ed) Ponce - PVMP - AI OMP - SVEP Jaime Nelson - PVMP - StrategyOps Value Engineering Edson Breton Bob Corbin José Alberto Gómez Moisés Ulises Alvarado Rodríguez Javier Bardon Dain Belyeu Alfredo Zayas Dr. Kimberly A. Moore Fernando Gaitán Salas Javier March Patrick Maroney

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🚀**Exploring 101 innovative AI use cases at Google Cloud Next '24**🚀 #AI #GoogleCloudNext #Innovation At the recent Google Cloud Next '24, a whopping 101 real-world AI use cases were put on display — a testament to the diverse and powerful capabilities that AI can offer various industries.([Link](https://lnkd.in/gzsh8pQP)) What was particularly fascinating is beyond the sheer variety of applications, it was the business-centric use of AI technologies. A hands-on, practical approach that underscores how AI can empower companies, boosting efficiency and engagement like never seen before. Remember, AI is not about replacing humans; It's about augmenting our capabilities. Making our lives easier and our businesses more streamlined. At Echomotion , we are perfectly positioned to help you navigate this new era of industry-leading AI technologies and implement them to fuelling your business growth. #Echomotion #AIConsulting #BusinessGrowt

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Perhaps lost in the news from OpenAI Google this past week was this new model from Microsoft Phi-4. Only 14B parameters but and on par with much larger Llama and Qwen models on MMLU. Out performing Gemini 1.5 Pro on math competition problems. https://lnkd.in/eUPFXERp

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Congratulations Sridhar, and Jensen, on your partnership to integrate NeMo into Cortex AI. This is a huge step to build custom AI apps. We have integrated #denodo platform with Snowflake #Arctic and #Cortex for building powerful #RAG applications, and are demoing this at our booth in the #datacloudsummit. As you know, relevant corporate #data is essential for #enterprise AI. To that effect, today, we proudly announced integrating NVIDIA NIM Interface Microservices with Denodo to accelerate and optimize #ai capabilities for enterprises. This integration will provide enterprise customers with faster, more secure, and fully scalable AI capabilities. https://lnkd.in/gqgwZ5Dh Looking forward to our partnership with Snowflake and NVIDIA to further the #ai innovation for our enterprise customers! #datavirtualization #logicaldatamanagement

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➰ APIContext's latest insights on cloud-based API performance have been featured on Nordic APIs! In the 2024 report, we delve into crucial aspects affecting API efficiency: 🔐 Authentication is key. Ensuring robust authentication mechanisms in APIs is crucial, yet offloading this function can introduce complex challenges. 📖 DNS configurations matter. How you handle DNS settings can significantly impact API performance, particularly when tied to authentication processes. 🌐 The role of third parties. Critical third-party services play a significant role in 🔗 API transactions, underscoring the need for careful integration and monitoring. ⛅ Not all clouds are created equal. Differences in cloud services can drastically affect API performance, an essential consideration as APIs account for over 80% of all internet traffic. #APIs #CloudComputing #TechInsights #APIContext

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23.9%. Let’s talk hyperscale. Grandview Research suggests the hyperscale computing market size was valued at $56.83 billion in 2022 and it is expected to expand 23.9% from 2023 to 2030. We see some companies are switching to #hyperscale #cloud computing for faster speeds, reduced downtime, and more. This is also driven by the rise of #AI (artificial intelligence), #bigdata, machine learning, and the #IoT (Internet of Things). What are you seeing? Is hyperscale skyrocketing? #digitaltransformation #GenAI #IBMPartner #IBM #Microsoft https://lnkd.in/eTCF5EDz Nikhil Patil Michal Ukropec Heathcliff Howland Arvin Parmar Tracy Holtz Alpesh Saraiya Sonu Khunkhun

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NeuBird, which is using generative AI to automate IT site reliability operations, raised a $22.5M seed extension led by M12, following a $22M seed in April (Marina Temkin/TechCrunch)​ 

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