Man goes viral after revealing he's been married for 15 years and never had a single argument with his wife.

Scientists working on the Beyond EPICA – Oldest Ice project have successfully drilled nearly 2 miles (3,000 meters) into the East Antarctic ice sheet, specifically at a site called Little Dome C, to extract ancient ice cores. The mission is part of an international effort to recover the oldest possible continuous record of Earth's climate, and this recent core is believed to be around 1.2 million years old. Ice cores are natural time capsules containing air bubbles and particles trapped in ancient snowfall. These records help scientists analyze greenhouse gas levels, temperature variations, and atmospheric conditions from Earth's distant past. This drilling effort is essential for understanding the transition between the Mid-Pleistocene Transition (about 900,000 years ago), a key climatic shift in Earth's ice age cycles. Previously, the oldest continuous ice core record was about 800,000 years old, recovered from Dome C in the early 2000s. The new 1.2-million-year-old core marks a major step forward in paleoclimate research, potentially revealing what triggered the change in Earth's glacial rhythms.

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Apple's latest AI research challenges the hype around Artificial General Intelligence (AGI), revealing that today’s top models fail basic reasoning tasks once complexity increases. By designing new logic puzzles insulated from training data contamination, Apple evaluated models like Claude Thinking, DeepSeek-R1, and o3-mini. The findings were stark: model accuracy dropped to 0% on harder tasks, even when given clear step-by-step instructions. This suggests that current AI systems rely heavily on pattern matching and memorization, rather than actual understanding or reasoning. The research outlines three performance phases—easy puzzles were solved decently, medium ones showed minimal improvement, and difficult problems led to complete failure. Neither more compute nor prompt engineering could close this gap. According to Apple, this means that the metrics used today may dangerously overstate AI’s capabilities, giving a false impression of progress toward AGI. In reality, we may still be far from machines that can truly think. #AppleAI #AGIRealityCheck #ArtificialIntelligence #AIResearch #MachineLearningLimits

Apple’s latest AI study is stirring the pot by exposing serious cracks in the perceived reasoning power of today’s top language models. Researchers put major players like DeepSeek-R1 and OpenAI’s O3 to the test using classic logic puzzles, revealing that while these models handle easy tasks and short chains of logic, they falter hard as complexity increases. It’s not that they lack knowledge—but that they fail to plan ahead when it counts most. The team observed a dramatic “reasoning collapse” once tasks became too intricate, suggesting these models are excellent imitators, not problem-solvers. Despite having plenty of memory and token space left, the models would abandon mid-task thinking or repeat patterns without adapting. Apple’s paper warns that today’s “reasoning models” may be more illusion than innovation—highlighting the gap between surface-level competence and true cognitive ability. #AIresearch #AppleAI #OpenAI #DeepSeek #ArtificialIntelligence