Sat.Nov 05, 2016

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Swimming along a road in a flood of digital transformation

Paul Hobcraft

I am so caught up in transformation, no, actually I am swimming in it. No gentle backstroke for me lapping in the digital transformations that are being written about, this is a hard swim, one I’m not sure I can stay afloat and make headway, yet I must, well actually we all must. We all need to learn to swim along this new digital transformation road.

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Knowledge as a social process

HYPE Innovation

Walker’s Wagon Wheel tavern in the 1970s has a particularly important place in innovation history. Its name provides a great description of its role – like spokes on a wheel people and ideas converged on its centre and on a Friday night the air was full of conversation. Ideas flew around the place, colliding and often crashing in flames on the floor.

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The Six Sides of the So-Called Box

Idea Champions

Unless you've been in a coma for the past 20 years, I'm sure you're familiar with the phrase "get out of the box." It's everywhere. Whole industries have sprung up around it, including mine. No one can deny that getting out of the box is a good thing to do. Seems like a no-brainer, eh? Kind of like helping little old ladies cross the street. Or tearing down the Berlin Wall.

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How to turn around a failing program

HYPE Innovation

Not all enterprise innovation programs go well - sometimes they crash and burn, and sometimes they slowly degrade until they fall off the radar. As an innovation manager, you don’t want to see this happen, and ultimately you are in the driving seat when it comes to taking action to steer the program on track, others are unlikely to do it. In a recent webinar, my colleague Khattab Al-Ali, looked at ways to turn around a failing program, and also ensure new programs are set up to avoid failure.

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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.