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A new AI test is outwitting OpenAI, Google models, among others

Mashable Tech

The Arc Prize Foundation, a nonprofit that measures AGI progress, has a new benchmark that is stumping the leading AI models. The test, called ARC-AGI-2 is the second edition ARC-AGI benchmark that tests models on general intelligence by challenging them to solve visual puzzles using pattern recognition, context clues, and reasoning.

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Technology Has Shaped Human Knowledge for Centuries. Generative AI Is Set to Transform It Yet Again.

Singularity Hub

We stand on the brink of the next knowledge revolution. Where would we be without knowledge? Everything from the building of spaceships to the development of new therapies has come about through the creation, sharing, and validation of knowledge. Today, we stand on the brink of the next knowledge revolution.

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AI firms follow DeepSeek’s lead, create cheaper models with “distillation”

Ars Technica

Leading artificial intelligence firms including OpenAI, Microsoft, and Meta are turning to a process called distillation in the global race to create AI models that are cheaper for consumers and businesses to adopt. Read full article Comments

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Meta will start using data from EU users to train its AI models

Engadget

As for why the company wants to start using EU data now, it claims the information will allow it to fine tune its future models to better serve Europeans. "We "That means everything from dialects and colloquialisms, to hyper-local knowledge and the distinct ways different countries use humor and sarcasm on our products.

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What Are Foundation Models?

NVIDIA AI Blog

Like the prolific jazz trumpeter and composer, researchers have been generating AI models at a feverish pace, exploring new architectures and use cases. In a 2021 paper, researchers reported that foundation models are finding a wide array of uses. Earlier neural networks were narrowly tuned for specific tasks. See chart below.)

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Larger language models do in-context learning differently

Google Research AI blog

In general, models’ success at in-context learning is enabled by: Their use of semantic prior knowledge from pre-training to predict labels while following the format of in-context examples (e.g., Flipped-label ICL uses flipped labels, forcing the model to override semantic priors in order to follow the in-context examples.

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Young Coders Are Using AI for Everything, Giving "Blank Stares" When Asked How Programs Actually Work

Futurism

That's according to Namanyay Goel, an experienced developer who's not too impressed by the new generation of keyboard-clackers' dependence on newfangled AI models. The foundational knowledge that used to come from struggling through problems is just missing," he added. Crickets,"he wrote. Ask about edge cases? Blank stares." "The

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