Jake Makler

❄️ Come and hear how Snowflake uses DataOps.live for massive productivity gains for all its engineers. #data #dataops #analytics #dataproducts

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At Davos 2024, industry leaders sent a clear message: embrace AI or risk falling behind in today's rapidly evolving world. 🚀 AI is not just a trend; it's a transformative force that will shape nearly every aspect of our society. 🤖💼 As IBM CEO Arvind Krishna pointed out, AI will be a significant driver of economic competitiveness, with an estimated $4 trillion in productivity gains by the end of the decade. 📈💰 This is a wake-up call for businesses and professionals alike. We must be proactive in understanding and adopting AI to stay ahead of the curve and reap the benefits of this powerful technology. 💪📚 If you're wondering how AI can benefit your business, our latest blog post, "7 Ways Predictive And Generative AI Can Benefit Your Business," is a must-read! 📑 Click the link below to discover how you can harness the power of AI to drive growth, increase efficiency, and stay competitive in your industry. 🔗7 Ways Predictive And Generative AI Can Benefit Your Business https://lnkd.in/gPH-ywpf #DataScience #InnovationTechnology #FutureOfWork

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Nate Nichols has been researching, building and deploying AI systems for 15 years. He does a great job breaking down the basics to help you with an AI roadmap to get started in your organization. Watch Nate and reach out if you want to learn more!

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This hesitancy is one thing I hear from both customers and prospective customers alike. As Shubham states, it's a legitimate concern, but there are solutions that should put compliance and risk officers at ease. If you're considering incorporating LLMs, check out the below.

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Your enterprise tech stack is about to get transformed by AI. How would you rethink your tech, knowledge work, and operations for the exciting new world unfolding before us? Recommended reading for everyone interested in how gen AI is reshaping the enterprise software space. https://lnkd.in/g3J2A5Qt 🚀 Generative AI: Redefining Enterprise Software 🤖 AI is revolutionizing the very core of our enterprise data systems, workflows, and applications. 🌐 Here’s how: 🔗 Connecting the Dots: Generative AI is a master at linking disparate data sources—structured, unstructured, and multimodal—from both inside and outside the enterprise. Imagine effortlessly piecing together a puzzle 🧩 with data from emails, audio conversations, video meetings, customer records, social media, and beyond! 📚 Evolving Systems of Record: Traditional systems of record have primarily focused on structured data. As generative AI’s ability to connect the dots across disparate data sources and more complex data types becomes more apparent, the underlying systems of record need to adapt or risk displacement. ⏱️ 📊Data-Centric & Model-Centric Platforms: As AI takes center stage, data-centric and model-centric platforms are becoming more prominent. Beyond traditional data warehouses and lake houses, there’s an emerging category of platforms that prepare data, enrich context, improve quality, observe, and boost the reliability of gen AI systems. 🌍 🧠 Redefining Knowledge Work: The pervasive use of gen AI is set to transform knowledge work and related workflows. Routine tasks? Automated! 🤖 Complex decision-making? Simplified with interactive insights! 📈 This in turn is likely to reshape the applications we use today. 💡 Generative AI is more than just a tool—it's a catalyst for a data revolution, making our systems smarter, our workflows smoother, and our businesses more agile. 💼✨ #GenerativeAI #EnterpriseSoftware #EnterpriseAI #DataRevolution #AI #Innovation #DigitalTransformation

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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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When engines compete, customers win. The biggest story in data this summer was that Iceberg established itself as the de facto standard for how customers store their data for decades to come. What comes next? Listen to Alex Woodie and I cover this and a wide range of other topics on his interview series here:

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For those who missed the Snowflake Data Summit keynote; here’s my GeneAI summarization :-) 1) Sridhar the new Snowflake CEO is smart as a pup and amazing academic and career pedigree, but has very little charisma or public speaking skills. Hope he improves on the latter over time. 2) Jensen zoomed in for his Keynote because he is still in Taiwan for Compudex. Jensen has labeled Taiwan the heart of GenAI Compute, all of Nvidia (and AMD)’s major suppliers are in Taiwan. It’s amazing this little island the size of California holds the future to AI. 3) Snowflake and Nvidia announced their partnership. Basically it’s combining Snowflake LLM Datastore with Nvidia LLM training and inference/generate. This is revolutionary. Snowflake pioneered the separation of compute from storage in massive EDWs, and now the circle is completely with bringing Nvidia compute training and inference/generation close to storage, eliminating bandwidth cost, latency and data policy/privacy issues. And as someone with Information Retrieval background, I see GenAI has come full circle with RAG - it’s just Precision/Recall, attributes vectorization as “embedding”, K-Nearest Neighbor, User Search Intent, DAG, ML algorithms, etc all over again. Except this time with supercharged GPU SoC that is improving at 16x Moore’s Law. We live in exciting times.

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Steve Jobs✨ One of the things that hurt apple was thinking thinking that a really great idea is 90% of the work. Great Ideas vs. Great Products - Steve Jobs emphasizes that many people have great ideas, but it's the meticulous execution that transforms those ideas into groundbreaking products. #SteveJobs #Innovation #ProductDevelopment #TechInspiration #GreatIdeas #ExecutionMatters

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I had a great time speaking at Silicon Valley Leadership Group's Tech & Innovation Summit at the Amazon offices in Palo Alto earlier this month. I shared some of the highlights from Microsoft and LinkedIn’s 2024 Work Trends Index report, which showed how AI is influencing the future of work. My call-to-action slide was a reminder that inaction on the part of leadership isn’t an option. Leaders need to lean into AI to help their organizations best leverage the benefits of AI. This really comes down to three things: identify a business problem and apply AI to solve it; encourage top-down, bottoms-up conversations about AI; and prioritize AI training.  #AI #SVLG #Microsoft #FutureOfWork #WTI

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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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Our Call Score API - a very successful, business-ready application of GenAI techniques to measure and evaluate conversations - has a new set of features! You can try it out now, explainer and technical documentation below... We just launched the ability to define 'Custom Criteria' to evaluate any given conversation, and a 'Scorecard' that combines all these criteria together. This release continues our efforts to go beyond just the hype of Generative AI, and to build products that our customers need, want to use, and can integrate into their businesses and products from Day 1. Give it a try today! Blog: https://lnkd.in/gEvubpVt API Reference: https://lnkd.in/gmneKYCK.. Documentation: https://lnkd.in/gn_mr8VK.. #SymblDotAI #CallScore #CallScoring #ConversationUnderstanding #NLP #NLU #Conversation #ConversationAI #GenAI #GenerativeAI #NebulaLLM

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Salesforce CEO Marc Benioff has been promoting the concept of the ‘𝗔𝗴𝗲𝗻𝘁-𝗙𝗶𝗿𝘀𝘁’ 𝗼𝗿𝗴𝗮𝗻𝗶𝘀𝗮𝘁𝗶𝗼𝗻 recently (https://lnkd.in/e8iTUuG2), but its relevance extends far beyond any single vendor's vision—it represents a fundamental shift in how enterprises operate in an AI-driven world. Most organizations who are using AI today are doing so in isolated pockets: perhaps a chatbot for customer service, predictive analytics for sales, or automation for specific back-office tasks. The Agent-First Organization is like an 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗲𝗱 𝘁𝗲𝗮𝗺 𝗼𝗳 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝗲𝗺𝗽𝗹𝗼𝘆𝗲𝗲𝘀, handling complex processes end-to-end. Less "chatbot" and more "augmented organisation" that scales instantly without proportional costs. AI agents are like digital employees with specific roles and responsibilities. They can understand context, make decisions, and work together. Let’s take a 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: • Traditional AI: A chatbot handles basic queries and escalates everything else to humans • Agent-First: An integrated team of AI agents manages the entire customer journey:  o One agent understands the customer's history and current needs o Another checks inventory and delivery systems o A third coordinates with billing and payments o A fourth schedules technical support if needed o All working together seamlessly, only escalating truly complex issues 𝗞𝗲𝘆 𝗯𝗲𝗻𝗲𝗳𝗶𝘁𝘀 𝘁𝗼 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲𝘀 📈 Scalable Growth Without Linear Costs 💰 Dramatic Cost Base Reduction 🎯 Enhanced Customer Experience 🚀 Accelerated Revenue Growth 𝗘𝗮𝗿𝗹𝘆 𝗽𝗿𝗼𝗼𝗳 𝗽𝗼𝗶𝗻𝘁𝘀 Think of it like the early days of autonomous vehicles: we've moved from basic driver assistance to fully autonomous Waymo fleets But the future’s already here. See this groundbreaking case study from a European insurer: https://lnkd.in/eeU3Ti-m The question isn't whether to embrace agent-first approaches, but how to implement them effectively while managing associated risks. #agenticAI #aiagents #agentfirstorganisation #augmentedworkforce #augmentedorganisation

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How open will open source data architecture remain as Databricks, Snowflake, Meta et al make it core to their business models and the future of AI? Looking forward to hearing from the community of practitioners and contributors themselves at Chill Data Summit https://rb.gy/2fccp7 #upsolver #futureofAI #apacheiceberg #opentableformats #dataengineering

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Gain exciting insights from Thomas Been, CMO at Domino Data Lab, on the evolving landscape of AI and data science! In this short video from his interview on The Ravit Show, Thomas discusses the shift towards maximizing value in AI initiatives and the growing focus on enterprise AI. He mentions key observations from Gartner Research VP, Business Analytics, Rita Sallam and highlights Domino's roadmap for empowering data scientists.

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Some really provocative ideas in this article that challenge us to reimagine leadership for the AI era. AI expert Nell Watson prompts us to imagine a future where AI takes on leadership roles in business and beyond. But don't picture a robot manager just yet. AI's superhuman ability to process vast amounts of data and spot hidden patterns makes it an attractive candidate for high-level decision-making. But who's accountable when an AI makes a costly mistake? How do we ensure these leaders align with our values? Can AI generate the kind of contrarian, innovative thinking we need in a leader? What do you think? Can you imagine an AI leader in the C-suite? #artificialintelligence #leadership #empathy

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Snowflake jumps into the Generative AI arena with its latest LLM announcement. The Arctic LLM. But, Do we need another LLM? Snowflake talks about unprecendent performance, unparalleled efficiency, etc. Typical sales jargon associated with a new product. But, Here is my take in English. Ecosystems of LLMs are evolving.  Models are being built across a wide array of use cases. GPT- 3: focus on Q&A, and content creation. DALL-E: Image generation LLaMA - summarization, transition, code generation T5: converting text from one form to another and a host of AWS LLMs. Each model and its iteration improves efficiency and performance.  So, Demand for specialized and effective LLMs will only grow from here. I made an example of how Snowflake may gain momentum with this investment, more importantly, how this will help a customer. Consider RetailSM, a retailer invested in a data-led journey. they are seeking to understand customer sentiment. In the past or current, their options are as follows. • Build a data lake. • Build a data mesh. • Unify all data. send Data scientists to town to build models. • Hope the models can drive the use case, and no one says your data is trash after 6 months of burning money. • Pray, the use case implementation (Sentiment analysis) journey yields results in under 6 months, with some $$$ returns. With this LLM model natively within Snowflake's realm, several benefits should come fast. #1 of that is to cut down a significant amount of time. Here are some others: 💡Gain deep insights from social media, customer interactions, and reviews through sentiment analysis. 💡 Tailor marketing campaigns with personalized recommendations and promotions.  💡Drive product development strategies based on customer feedback.  💡Enhance customer service by proactively addressing concerns. This mirrors an advance like Microsoft's Copilot. MS Copilot has the potential to revolutionize the modern workplace. Because Microsoft is the OG of the modern workplace. Snowflake is deep into the Enterprise data ecosystem. It can wield its analytics wizardry to empower businesses. In the end, Snowflake's Arctic LLM represents a powerful tool to harness the power of Gen AI. #SnowflakeArctic #GenerativeAI #DataAnalytics What do you think? Sridhar Ramaswamy

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