Jason Burchell’s Post

🌐 Technology is revolutionizing government management, automating processes, reducing costs, and improving efficiency. By 2026, over 70% of government agencies will use AI to enhance administrative decision-making, according to Gartner. Discover how Microsoft solutions are driving change and improvement for governments and their citizens, addressing their needs and challenges! 👩💻 #IndustryInnovation https://lnkd.in/edJ9cg-b #MicrosoftCanada #MSFTAdvocate #AI

Google’s #AI announcements at Google Cloud Next ‘24 were quite impactful. The event was not just a showcase of Google's commitment to pushing the boundaries of AI but also a testament to the company's leadership in driving advancements that resonate with developers and businesses alike. The introduction of like Gemini Code Assist and Vertex AI Agent Builder underscores Google's strategic goal of equipping developers with cutting-edge AI solutions to enhance code quality, productivity, and workflow efficiency. Moreover, the improvements in #MLOps capabilities demonstrate Google's dedication to simplifying AI model development and deployment, paving the way for seamless integration into production environments. As Google continues to expand its AI portfolio and make strides in various domains such as databases and generative media capabilities, developers are presented with new opportunities to innovate and drive value creation. Read more in this research note by Paul Nashawaty of The Futurum Group

Google's AI keynote was exciting! It's clear that their massive infrastructure is the ace up their sleeve in the AI race. By leveraging their unparalleled scale, Google is transforming large language models from creative novelties into reliable, enterprise-ready powerhouses. What really got me excited was the potential of "grounding" – integrating LLMs with company data and knowledge to ensure trustworthy outputs. It's already a huge step forward, but combined with Gemini 1.5 Pro's million-token context window? Game-changer. Just think about the possibilities this opens up! Imagine being able to surface critical business insights from thousands of pages of documents with a simple query. Or updating code while automatically adhering to security standards and best practices. Even creative tasks could be supercharged by an AI that truly understands your brand's unique style and voice. That's the future Gemini 1.5 promises, and Google's sheer scale makes it achievable. Can't wait to see how this unfolds. The companies that harness these advanced AI capabilities effectively are going to have a massive competitive advantage. https://lnkd.in/eRezp3AT #AGI #aiandsociety #artificalintelligence #aiandlaw #ml #machinelearning #ai #responsibleaibydesign #bigdata #deeplearning #technology #datascience #tech #futureoftech #AIandBusiness #innovation #digitaltransformation #businesstransformation #automation #productmanagement #productinnovation #chatgpt #openai #databricks #aiproducts #digitalmarketing #dataanalytics #softwareengineering #softwareengineer #dataengineering #aimarketing

How to run dozens of AI models locally

Planet Technologies knew this was coming but it's available sooner than expected. #OpenAI is now available in #Azuregov. Planet is uniquely positioned to assist with your AI requirements. We have some of the top experts focused on AI and ML in the market today. #Microsoft has announced the availability of Azure OpenAI Service for Azure Government, providing advanced AI capabilities for government agencies with strict security and compliance requirements. This service aims to streamline processes, enhance productivity, and accelerate innovation for mission-critical workloads. It offers features like automating tasks, augmenting personnel capabilities, and simulating complex situations. Agencies can experiment with generative AI across various scenarios, ensuring faster time to innovation. Notably, Microsoft emphasizes data protection, ensuring that agency data remains secure and private. The initiative aligns with the White House Executive Order on AI, reflecting Microsoft's commitment to responsible AI deployment in government settings. #experiencematters #goplanet https://lnkd.in/g3EqDX5Y

AI researchers and developers have been exploring numerous RAG technologies, including text chunking, query expansion, hybrid search, knowledge graph, reranking, and others. In short, an LLM needs the right data so that it doesn't have to make things up, and you need the best search technology to get the best data. Google Search technologies, backed by over two decades of experience pioneering information retrieval at scale, offer powerful information retrieval capabilities for RAG solutions. With Vertex AI Search, for instance, developers can easily combine LLMs with Google Search technology, letting them focus on building innovative AI apps instead of taking months to design and build their own advanced search engine for RAG systems.

Google claims to have the best infrastructure for AI. Its deep investments into AI have helped customers train and serve cutting-edge language models and put the company at the forefront of the AI platform shift. This article looks at how Google's infrastructure helps companies transform their operations and what that says about Google's ability to compete. Google may have to shift to a different business model, but its reliance on scale and overwhelming infrastructure advantage won't change - because it's the company's nature. #ai #technology #innovation https://lnkd.in/gJ_vT9sz

#Microsoft is making it easier for the #AI systems to retrieve information at scale. Customers can #innovate with confidence with state-of-the-art retrieval technology in #Azure AI Search and an #enterprise-ready foundation.

Keeping your #GenAI on prem and brining AI to your data with Dell Technologies is the most cost effective way to go. Check out this paper from ESG. #iwork4dell https://lnkd.in/eHNkp8CX

When a large language model (LLM) doesn’t have enough information or has no contextual knowledge of a topic, it is more likely to hallucinate and provide inaccurate or false responses. Developers are increasingly excited about generative AI and Retrieval Augmented Generation (RAG) — an architecture pattern that combines LLMs with backend information retrieval from other information sources. Check out this article that talks about how Google Search technology can help improve results with RAG. #googlecloud #LLM #GenAI #AI https://lnkd.in/euFc6pYe