Sat.Dec 27, 2014 - Fri.Jan 02, 2015

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Becoming More Innovative in 2015: Innovation Resolutions

Bill Fischer

What are you going to do this coming year to be more innovative? Innovative organizations deserve innovative leaders and members and if you’re not consciously thinking about how you might improve your own personal innovativeness, you’re abdicating on an important managerial responsibility. Since this is the time for New Year’s resolutions, [.

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Sustaining and Scaling Openness

100%Open

I was never a fan of the band Queen but I remember being moved to see the video to their song, The Show Must Go On, released at a time when their lead singer Freddie Mercury was in advanced stages of dying with Aids. Where others may have faded away quietly, the sheer necessity and inevitability of the need to keep on performing was striking. Whatever you think of their music I think you have to admire their tenacity.

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How to Design for Outcomes

Tim Kastelle

It’s always a bit dangerous to be “inspirational.” The problem is that inspiration doesn’t always lead to action – and that’s what we ultimately want. This is a lesson that Timothy Prestero and his organisation Design that Matters learned painfully. In 2010, DtM came out with an incubator designed for use in developing countries that won a ton of awards.

Design 270
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Becoming More Innovative in 2015: Innovation Resolutions

Bill Fischer

What are you going to do this coming year to be more innovative? Innovative organizations deserve innovative leaders and members and if you’re not consciously thinking about how you might improve your own personal innovativeness, you’re abdicating on an important managerial responsibility. Since this is the time for New Year’s resolutions, [.

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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.