Sun.Sep 30, 2018

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Winners Of The 2019 Forrester And InfoWorld EA Awards Contest Show EA’s Role In Digital Transformation

Forrester IT

In past Forrester and InfoWorld Enterprise Architecture Awards competitions, we had named themes to align entries and winners to the current needs of modern enterprise architecture (EA) programs. This year, we went themeless to simply find the most dramatic stories of EA’s strategic leadership. But the winners of the 2018 Forrester/InfoWorld Enterprise Architecture Award show […].

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Three Aspects Of How Collective Learning Fosters Innovation

Future of CIO

We live in the information and knowledge economy, today’s digital professionals are hard workers, knowledge workers, and creative workers, who are exploring, innovating and evolving to new digital paradigms. To create the new requires not just one skill, but many, not just old experience, but new perspectives. Collective learning rejuvenates the organizational culture and foster innovation.

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Intern Life at Nutanix

Nutanix

When I first started the daunting task of finding a summer internship, I was nervous about making the wrong decision and spending my summer making photocopies or going on coffee runs.

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The New Book “The Change Agent CIO” Introduction Chapter 3 The Digital IT Change Agenda

Future of CIO

Crafting an IT change agenda is important to ensure that IT is strategically positioned to be ahead of where the business is moving next. With change as the new normal with the faster pace and high velocity, IT faces an unprecedented opportunity to refine its reputation, also needs to take more responsibility as a true business partner. Change is a dance between the top management and the affected parts of the organization, the CIO needs to take the logical scenario to gain change curve awarenes

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.