This advisory examines the challenges and considerations for implementing and scaling graph AI databases, with a focus on hyperscaler Cloud options and necessary skills.
Technological advancements follow a compressed four-stage market cycle, creating a corresponding value cycle. Early movers in digital sectors secure disproportionate value, challenged by regulation. Intangible assets drive modern value, demanding revised B2B procurement for ecosystem navigation and value capture.
Google’s Ironwood TPU targets AI inference cost/efficiency, vital for scaling complex models amidst fierce competition.
Google’s GDC now hosts Gemini, Vertex AI on-premises, enabling sovereign AI for regulated sectors, strengthening hybrid cloud offerings.
Generative AI mimics reasoning through data-driven pattern matching, diverging fundamentally from human cognitive reasoning. The misconception leads to costly mistakes in how businesses apply AI.
A comprehensive analysis of safe AI models, how current LLM products such as OpenAI, Microsoft, Google, and Deepseek stack up and testing recommendations.
AI video generation tools offer rapid content creation; however, strategic alignment, skilled users, and clear guidelines are crucial for realising tangible business value.
Canva’s integrated platform challenges established suites by unifying design, data, and AI, but enterprise governance and the implications of AI-driven job roles warrant careful consideration.
Canva’s expanded platform integrates design, data, and AI, targeting enterprise-wide visual content creation and potentially challenging established productivity suites.
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