How Disappearing Giant Animals May Have Triggered the Stone Tool Revolution

Early Humans Tool Evolution

Evolution of Tools: Early Humans Innovate for Smaller Prey

Raul Martin/MSF/Science Photo Library

A notable decline in megafauna populations approximately 200,000 years ago prompted ancient humans to pivot from robust stone tools to lighter, more versatile hunting kits for capturing smaller animals, according to a groundbreaking study. This research bolsters the theory that the shift to hunting smaller prey played a pivotal role in enhancing the cognitive abilities of early humans.

For over a million years, diverse early human species relied on heavy stone toolkits, including axes, kitchen knives, scrapers, and stone balls. Evidence indicates these tools specifiably targeted large herbivores, such as now-extinct relatives of elephants, hippos, and rhinos.

Between 400,000 and 200,000 years ago, the emergence of smaller, advanced tools coincided with the disappearance of heavier implements. Our species, Homo sapiens, emerged during this transformational period.

About 200,000 years ago, heavy tools vanished from archaeological records across the Levant, while the quantity of sophisticated, lightweight stone toolkits—such as blades and precision scrapers—increased significantly.

Research led by Vlad Litov, a professor at Tel Aviv University, establishes a compelling connection between these technological advancements and the dramatic decline of large herbivorous mammals, likely caused by overhunting.

Researchers meticulously cataloged archaeological evidence from 47 Paleolithic sites—covering 3.3 million to 12,000 years ago. Cross-referencing stone artifacts with animal remains revealed a distinct pattern.

The findings show a marked decline in large herbivores exceeding 1,000 kilograms, coinciding with the disappearance of fundamental stone tools 200,000 years ago. Conversely, the presence of smaller prey and innovative small tools rose significantly.

Supporting the correlation between tool types and prey availability, previous research indicates durable stone tools persisted in areas like southern China—where large game remained abundant—until about 50,000 years ago.

Comparative Analysis: Heavy Stone Tools vs. Lightweight Tools

Vlad Litov et al., Institute of Archeology, Tel Aviv University

Previously, it was posited that technological advancements were driven by an inherent rise in intelligence among humans, potentially influenced by unknown evolutionary pressures. However, Litov and his colleagues suggest that the reliance on smaller prey may have been a significant factor in the brain’s evolution across modern humans.

“As megaherbivores dwindled, humans increasingly turned to smaller prey, demanding novel hunting methods, enhanced planning capabilities, and the use of more intricate, lighter toolkits,” states Litov. “This cognitive evolution was thus a response to new adaptive needs, rather than its initial driver.”

“It’s essential to consider more than just prey size,” states Seri Shipton from University College London. He mentions evidence suggesting mass hunts of medium-sized ungulates like horses and bison, indicating that cognitive developments and advanced planning were already occurring during the Middle Paleolithic period.

Nicolas Tessandier from the French National Center for Scientific Research adds a critical perspective. “Human adaptations to new fauna reflect resourcefulness rather than sheer intelligence,” he explains. “The development of effective technologies for hunting large herbivores was equally strategic.”

Litov acknowledges that earlier studies demonstrate cognitive abilities in ancient hominins, particularly Homo erectus specimens dating back around 2 million years. However, he contends that the transition from large to small prey had far-reaching implications for human development. An ancient elephant carcass could have sustained about 35 hunter-gatherers for an extended period. With this high-calorie resource’s disappearance, relying solely on smaller prey could drastically reduce caloric returns.

“To match the energy yield of one elephant carcass, we had to acquire numerous smaller ungulates, like fallow deer,” Litov explains. This necessity may have spurred cognitive and behavioral transformations, such as enhanced cooperative hunting strategies and better planning, laying the groundwork for increased brain sizes in later hominins like Neanderthals and Homo sapiens.

“In my view, the decline of large prey likely escalated inter-group competition,” notes Shipton. “It’s possible this dynamic created a feedback loop where diminishing large prey spurred cognitive advancements, allowing access to diversified smaller prey.”

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Artificial Intelligence could assist in preserving historical scents that are in danger of disappearing

Some scents are at risk of disappearing forever. Can AI reproduce them?

Brickwinkel/Alamy

Artificial intelligence can assemble formulas to recreate perfumes based on their chemical composition. One day, a single sample may be used to recreate rare scents that are at risk of being lost, such as incense from culturally specific rituals or forest scents that change as temperatures rise.

Idelfonso Nogueira Researchers at the Norwegian University of Science and Technology profiled two existing fragrances and determined their scent families (subjective words such as “spicy” and “musky” commonly used to describe perfumes); They classified them by a so-called “odor value” scale. About how strong certain smells are. For example, one of our fragrances received the highest odor value for ‘coumarin’, a group of scents similar to vanilla. The other received the highest odor value for the scent family “alcohol.”

To train the neural network, the researchers used a database of known molecules associated with specific fragrance notes. The AI ​​learned how to generate a set of molecules that match the odor score of each scent family in the sample fragrance.

But simply producing those molecules isn’t enough to recreate the desired scent, Nogueira says. That’s because the way we perceive smells is influenced by the physical and chemical processes that molecules go through when they interact with the air and skin. Immediately after spraying, the “top note” of a perfume is most noticeable, but it disappears within minutes as the molecules evaporate, and the “base note” can remain for several days. To address this, the team selected molecules produced by AI that evaporate under conditions similar to the original fragrance.

Finally, they again used AI to minimize the discrepancy between the odor value of the original mixture and the odor value of the AI-generated mixture. Their ultimate recipe for one of the fragrances showed a slight deviation regarding its “coumarin” and “sharp” notes, but the other appeared to be a very accurate replica.

Predicting the smell of chemicals is notoriously difficult, so the researchers used a limited number of molecules in their training data. But the process could become even more accurate if the database could be expanded to include more, more complex molecules, Nogueira says. He suggests that the perfume industry could use his AI to create recipes that create cheaper, more sustainable versions of fragrances.

richard gerkin Arizona State University and OsmoThe startup, which aims to teach computers how to generate smells the way AI does for images, says that combining AI with physics and chemistry is the strength of this approach, and that it understands how smells are generated. He says that this is because it can explain subtle points that are often overlooked, such as whether the image evaporates into water. But the effectiveness of this process still needs to be confirmed in human studies, he says.

Nogelia and his colleagues are already almost there. In a few weeks, he plans to travel to his colleague’s lab in Ljubljana, Slovenia, to experience the AI-generated scents for himself. “I’m really looking forward to smelling it,” he says.

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Source: www.newscientist.com