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Top Ten Data Challenges (And Solutions) for Associations

Association Analytics

Here are the top 10 data challenges associations like yours are running into – and solutions on how to overcome them. 10: Your Data Volume and Complexity Challenge : If you’re overwhelmed by the sheer amount of data your association collects, you’re certainly not alone. Solution : Solve this challenge by creating a data capture policy.

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Soft Skills Support Hard Leadership Challenges

.orgSource

What can we do to ensure they have the skills to understand a challenging landscape and make the wise decisions needed for success? Collegiality and teamwork among directors are critical to effective problem-solving. it’s essential to have a strategic governance model,” she says. How do we bring novice players up to speed?

Skills 221
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Announcing the first Machine Unlearning Challenge

Google Research AI blog

Posted by Fabian Pedregosa and Eleni Triantafillou, Research Scientists, Google Deep learning has recently driven tremendous progress in a wide array of applications, ranging from realistic image generation and impressive retrieval systems to language models that can hold human-like conversations.

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Sam Altman announces GPT-5 timeline update, cancels o3 as standalone model

Mashable Tech

OpenAI will ship GPT-5 in a matter of months and streamline its AI models into more unified products, said CEO Sam Altman in an update on Feb. as its "last non-chain-of-thought model" and integrate its latest o3 reasoning model into GPT-5. Specifically, Altman says the company plans to launch GPT-4.5

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Watch these Excel pros duke it out in a financial modeling competition

The Verge

Diarmuid Early competes in the second round of the Financial Modeling World Cup. Image: Financial Modeling World Cup | YouTube. from around the world face off in the Financial Modeling World Cup (FMWC) (via PCWorld ). Microsoft is sponsoring an esports competition with prizes totaling $10,000.

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Google Research, 2022 & Beyond: Language, Vision and Generative Models

Google Research AI blog

We want to solve complex mathematical or scientific problems. I will begin with a discussion of language, computer vision, multi-modal models, and generative machine learning models. Transform modalities, or translate the world’s information into any language. Diagnose complex diseases, or understand the physical world.

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Data-centric ML benchmarking: Announcing DataPerf’s 2023 challenges

Google Research AI blog

The key to both is a deeper understanding of ML data — how to engineer training datasets that produce high quality models and test datasets that deliver accurate indicators of how close we are to solving the target problem. Despite the importance of data, ML research to date has been dominated by a focus on models.