LLMOps in action: How we move GenAI from prototype to production
Struggling to get your GenAI prototype into production? Discover how LLMOps helps streamline deployment – fast, scalable, and reliable.
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Implementing an AI-augmented product development cycle
Product administration requires a product supervisor to juggle a number of elements of assorted product options, starting from discovery to launch. Artificial intelligence is quick changing into a product supervisor’s new sidekick. From the spark of a product thought to refining a mature product, AI is altering how product managers (PMs) work at each step. This doesn’t…
Case study: OpenAI
OpenAI: The $300 billion frontier, anchored within the UK The world AI panorama in 2025 is outlined by an intense, multi-front conflict for supremacy amongst foundational mannequin builders: OpenAI, Google DeepMind, Anthropic, and Mistral AI. While OpenAI continues to steer in general scale, person base, and income (projected close to $12 billion in 2025), its…
How TigerEye is redefining AI-powered business intelligence
At the Generative AI Summit in Silicon Valley, Ralph Gootee, Co-founder of TigerEye, joined Tim Mitchell, Business Line Lead, Technology at the AI Accelerator Institute, to discuss how AI is transforming business intelligence for go-to-market teams. In this interview, Ralph shares lessons learned from building two companies and explores how TigerEye is rethinking business intelligence…
- IBM & Oracle debut watsonx agentic AI on OCI
Unlike traditional AI systems that rely on step-by-step human input, agentic AI represents the next evolution: autonomous agents capable of ingesting information, executing tasks, and independently delivering end-to-end outcomes. These agents can undertake multistep processes, linking APIs, databases, and workflows, to tackle complex problems without constant oversight. As businesses aim to streamline operations and cut…
Human + AI: Rethinking the roles and skills of knowledge workers
Artificial intelligence is not just another gadget; it’s already shaking up how white-collar jobs work. be important. Critical and strategic thinking When routine tasks are automated, the human side of problem framing, strategy, and design can shine through. This means developing, along with domain expertise, long-term thinking: choosing the right technology tools, architecting resilient systems,…
Copilot vs Claude for Excel: Which AI assistant wins for formula building?
Copilot presents seamless integration immediately in Excel, however requires OneDrive auto-save, responds slower, and offers restricted formula alternate options. Claude delivers quicker responses with a number of formula choices and excels at Power Query M code, however requires copying/pasting between home windows. For primary customers, Copilot’s integration wins regardless of its limitations. For superior customers or these preferring…
