40,000-year-old Stone Age symbols may have paved the way for writing, long before Mesopotamia

Over 40,000 years ago, our early ancestors were already carving signs into tools and sculptures. According to a new analysis ...
EurekAlert!

Signs on Stone Age objects: Precursor to written language dates back 40,000 years

Over 40,000 years ago, our early ancestors were already carving signs into tools and sculptures. According to a new analysis by linguist Christian Bentz at Saarland University and archaeologist Ewa ...

Writing May Have Begun 40,000 Years Ago

Ancient carvings once thought decorative may actually be early attempts to record information. Their statistical complexity matches that of proto-cuneiform, pushing the origins of writing-like systems ...
Scientific Research Publishing

An Empirical Study Based on Big Data Analysis to Analyze Social Media Group Sentiment and Its Impact on Consumer Psychology ()

As social media becomes the core domain of information interaction in the era of big data, the emotional information contained in the vast amount of user-generated content provides an unprecedented ...
La Brújula Verde

Engraved signs on the Adorant and other Stone Age artifacts constitute a 40,000-year-old writing system predating the Mesopotamian one

A team of researchers has determined that the sequences of engraved marks on Stone Age objects, dating back as much as 40,000 ...
Unite.AI

Why Data Labeling Is Critical to Building Accurate Machine Learning Models

Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...

AI Is Unlocking a New Way of Doing Math

Over the past couple of months, several researchers have begun making the same provocative claim: They used generative-AI tools to solve a previously unanswered math problem. The most extreme promises ...

Manifold-Constrained Hyper-Connections: The Architectural Breakthrough That Might Redefine LLM Training

If mHC scales the way early benchmarks suggest, it could reshape how we think about model capacity, compute budgets and the ...

Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...