Long before humans built cities, made tools, or even appeared on Earth, the planet was already leaving behind clues to its earliest history. Some are tiny crystals almost as old as Earth itself.

Others are fossils, ancient rocks, mountain ranges, and tools that reveal when life began, how early humans evolved, and how our world changed over billions of years. These seven discoveries are among the oldest things ever found on Earth.

1. UR 501 jawbone

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The UR 501 jawbone is considered one of the oldest known human fossils. Found in Malawi, it is estimated to be around 2.5 to 2.3 million years old. The fossil belongs to the Homo rudolfensis group, an early human relative.

Its discovery was important because early Homo fossils had not been found in Central Africa before. The jawbone suggests that early humans or their close relatives may have moved through the East African rift system, offering clues about how early Homo spread across the continent.

2. Lomekwi stone tools

The Lomekwi stone tools, discovered in West Turkana, Kenya, are around 3.3 million years old. They are considered the oldest known tools ever found. Archaeologists uncovered anvils, cores, and flakes at the site.

What makes these tools remarkable is that they are older than the earliest known humans by about 500,000 years.

This means they may have been made by early human relatives such as Australopithecus or Kenyanthropus. Their discovery changed the idea that toolmaking was only a human trait.

3. Lake Zaysan

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Lake Zaysan in Kazakhstan is believed to be around 65 million years old. While Lake Baikal is often called the world’s oldest lake, Lake Zaysan may be even older.

The lake is thought to have formed during the Cretaceous period, though its exact age is difficult to confirm. Today, it is located near artificial reservoirs and the Bukhtarma dam. The dam raised the lake’s water level, increasing its area and causing some sources to group it with nearby reservoirs.

4. Makhonjwa Mountains

The Makhonjwa Mountains, located in South Africa and Eswatini, are about 3.6 billion years old. They are widely known as the oldest mountain range in the world.

The mountains are part of the Barberton Greenstone Belt, one of Earth’s oldest geological structures. They also contain some of the oldest known signs of life and ancient gold deposits. In 2018, the Makhonjwa Mountains were added to UNESCO’s World Heritage List.

5. Stromatolites

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Stromatolites are layered rock structures formed by ancient cyanobacteria. Some of the oldest stromatolites are about 3.5 billion years old, making them among the earliest visible evidence of life on Earth.

These organisms once existed in large numbers around the planet. Although they became less common in the fossil record about a billion years ago, stromatolites still grow in some places today. They remain one of the clearest records of early life.

6. Hematite tubes

Hematite tubes found in Quebec, Canada, may be between 3.7 and 4.2 billion years old. Researchers have suggested that these tiny structures could be some of the oldest fossils ever discovered.

The tubes resemble structures made by modern microbes near hydrothermal vents. They also contain chemical signs often linked with life, including carbon and phosphorus.

However, some scientists remain cautious, arguing that the structures may have been misread or may not be as old as claimed.

7. Jack Hills zircon

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The Jack Hills zircon crystals from Australia are believed to be the oldest known material found on Earth. They have been dated to about 4.375 billion years old.

These tiny crystals formed only around 165 million years after Earth itself. Their chemistry suggests that early Earth may have cooled quickly enough to have surface water and continental-type rocks. That means the young planet may not have been as hostile as once believed.

Natural disasters are usually remembered for the destruction they leave behind. But some disasters do more than destroy cities, villages, or coastlines. They change the direction of history.

Across centuries, earthquakes, floods, eruptions, and storms have weakened empires, stopped invasions, changed belief systems, and forced societies to rethink how they build and survive.

Here are five of the deadliest natural disasters that changed human civilization.

1. The Minoan eruption

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Around 1600 B.C., a massive volcanic eruption struck Thera, now known as Santorini in Greece.

The eruption was one of the most powerful volcanic events of the ancient world. It sent ash into the sky, buried settlements, and triggered tsunamis across the Aegean Sea. One of the societies most affected was the Minoan civilization, based on Crete.

The Minoans were among the most advanced people in the ancient Mediterranean. They had large palaces, strong trade routes, and a powerful seafaring culture. But the eruption disrupted their economy and weakened their influence.

The disaster did not destroy the Minoans in one moment. However, it likely accelerated their decline and helped shift power toward the Mycenaeans. Some scholars have also linked the event to later stories about Atlantis, the lost island civilization described by Plato.

2. The typhoons that stopped the Mongols

In the 13th century, the Mongol Empire was one of the most powerful forces in the world. After conquering large parts of Asia and Europe, the Mongols turned toward Japan.

They launched two major invasions, first in 1274 and again in 1281. Both campaigns involved large naval fleets carrying troops across the sea.

But both invasions were struck by massive typhoons. The storms destroyed many Mongol ships and scattered the invading forces before they could take control.

In Japan, these storms became known as kamikaze, or “divine winds.” They helped preserve Japan’s independence and stopped Mongol expansion further east.

The storms also became an important part of Japanese memory, reinforcing the belief that the country was protected by divine forces.

3. The 1556 Shaanxi earthquake

The 1556 Shaanxi earthquake remains the deadliest earthquake in recorded history.

It struck China during the Ming Dynasty and killed an estimated 830,000 people. The death toll was so high partly because many people lived in cave dwellings carved into soft loess soil. When the earthquake hit, these homes collapsed almost instantly.

The disaster destroyed villages, farmland, roads, and local administrative systems. Entire communities were wiped out.

The earthquake showed that the impact of a disaster depends not only on nature’s force but also on how people live. It pushed later discussions around safer buildings, better settlement planning, and disaster response.

4. The 1755 Lisbon earthquake

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On November 1, 1755, a massive earthquake struck Lisbon, Portugal. It happened on All Saints’ Day, when many people were inside churches.

The earthquake was followed by a tsunami and fires that destroyed much of the city. Tens of thousands were killed, with some estimates reaching up to 100,000.

But the disaster did not only reshape Lisbon. It changed European thinking.

At the time, many people saw disasters mainly as acts of divine punishment. Lisbon’s destruction forced philosophers, scientists, and leaders to ask new questions. Could earthquakes be studied? Could cities be built to survive them?

The event influenced Enlightenment thinkers such as Voltaire and helped push early ideas in seismology. Lisbon was later rebuilt with stronger planning and more resilient design.

5. The 1931 China floods

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The 1931 China floods are among the deadliest natural disasters in human history.

They were caused by heavy snowmelt, extreme rainfall, and overflowing rivers, including the Yangtze and Huai. Vast areas of China were submerged.

The disaster killed an estimated 1 million to 4 million people through drowning, famine, disease, and the collapse of basic services. Crops were destroyed, communities were displaced, and cities and villages remained underwater for long periods.

The floods forced China to rethink flood-control policies, river management, urban planning, and agriculture. They showed how deadly extreme weather can be when it meets densely populated areas and weak infrastructure.

Conclusion

History shows that natural disasters are never just moments of destruction. Their impact depends on how societies prepare, respond, rebuild, and learn from what went wrong.

In many cases, the real legacy of a disaster is not the damage it causes, but the changes it forces into the future.

A Unitree G1 humanoid robot is being prepared for a planned Mount Everest expedition later this year after taking part in a high-altitude test on Mount Chimborazo in Ecuador.

The robot, named Pemba, was provided by Eastworlds Labs, the AI robotics initiative of Virtuals Protocol. It was part of a Geologic Dome expedition that placed the robot at 20,312 feet on June 5, 2026.

The Chimborazo mission is being treated as an early test before the planned Everest trek in the fall. Mount Chimborazo is known for a unique geographical fact. Its summit is the farthest point from Earth’s center and the closest point to the Sun on Earth.

Eastworlds Labs said the expedition supports its larger goal of bringing autonomous AI agents into the physical world.

The team also documented the mission and plans to create a trailer for the Everest expedition. The project is working with the production crew behind Netflix’s 14 Peaks: Nothing Is Impossible.

Everest is the next challenge

The planned Mount Everest trek will take the project into one of the world’s most difficult mountain environments.

For Eastworlds Labs and Geologic Dome, the aim is not only to place a robot in extreme terrain.

The larger goal is to test whether humanoid robots can support conservation, research, and monitoring in places that are hard or dangerous for people to reach often.

According to Eastworlds Labs, the Unitree G1 robot will be donated to the local Sherpa community for the Everest expedition. The company said this will connect the project’s legacy to the region where the next mission will take place.

The Everest plan follows the Chimborazo expedition, where Pemba was the only humanoid robot used. The Unitree G1 weighs 77 pounds (35 kg) and can fold down to 690 mm, which made it easier to transport through difficult terrain.

During the Ecuador mission, the team disassembled the robot and carried it between camps. It was then reassembled at different stages of the journey.

Chimborazo test pushed the robot

Mount Chimborazo gave the team a difficult test before Everest.

Temperatures on the mountain can fall to 5 degree Fahrenheit (-15°C), while wind gusts can reach 55 miles per hour (90 km/h). To help the robot handle these conditions, the Unitree G1 was fitted with custom cold-weather jackets, gated enclosures, and composite feet.

The robot’s autonomy system was trained in NVIDIA Isaac Sim at 1,620 times real-time speed. Eastworlds Labs said the system achieved 85 percent sim-to-real transfer on uneven terrain.

The robot was also pretrained to respond to wind turbulence and recover its balance on technical alpine terrain.

Communication during the expedition was supported by a proprietary mesh relay across camps. Satellite internet at each camp delivered 25 ms latency. This stayed below the 50 ms limit needed for live teleoperation with Reflex’s latency software.

Conservation goal behind the mission

The Everest plan is part of Geologic Dome’s broader conservation work.

The organization is building autonomous infrastructure for conservation zones. This includes communication relays, AI-powered ecological monitoring, and energy-independent robotic platforms.

Eastworlds Labs said it sponsored the Chimborazo expedition and is also contributing funding toward Geologic Dome’s nature conservation work.

Geologic Dome is currently testing its approach across three sites. These include equatorial forest in the Democratic Republic of Congo, montane cloud forests in Ecuador, and the full Himalayan altitude gradient in Nepal.

Researchers at Los Alamos National Laboratory have developed a new tool called the Prelim Attention Score, or PAS, to help detect when a vision-language model’s output is grounded in the image and when it may be relying too heavily on its own generated text.

The system is being viewed as a means to enhance vision-language model safety and trustworthiness.

“The PAS is a real-time, plug-and-play metric that acts as an internal monitor for the AI,” said Manish Bhattarai, a Los Alamos computer scientist.

“The system works with major existing vision-language models and requires minimal additional computational overhead, making it an efficient way to detect potential hallucinations. PAS achieves state-of-the-art accuracy in catching hallucinations, offering developers a practical path toward safer and more trustworthy multimodal AI systems,” he added.

Tracking where the model gets its answer

Most commonly used vision-language models are autoregressive. They generate each new token, or word, partly by relying on the words they have already produced.

While this process helps the model form coherent responses, it can also cause the system to lean too strongly on its own previous output rather than the image itself.

PAS monitors a vision-language model’s prediction of each token. By doing so, it helps identify where the model is drawing information from and where hallucinations are likely to occur. The tool then presents a score that alerts users to the possible presence of hallucinations in the output.

A low-overhead hallucination detector

Many autoregressive vision-language models are based on transformer architectures, a class of deep-learning neural networks that use attention patterns to weigh information as they generate an output.

The Los Alamos team studied how these models attend to the image, the text prompt and the model’s own preliminary generated words.

When PAS is integrated into a vision-language model workflow, it can run alongside the model as it handles a request.

For object mentions in the response to an image and text input, PAS computes an attention-based score showing how strongly the model relied on its own previously generated words.

The closer the PAS score is to zero, the less likely it is that the model has produced a hallucination.

“By understanding the way a vision-language model pays attention to preliminary information, PAS can help identify the exact instance where a model begins to over-rely on its own words,” said Xuan Nhat Hoang, Los Alamos intern.

“Our tool reads signals the AI is already producing, representing a low-overhead way to help ensure that information is reliable and useful,” he added.

Reliability checks for visual workflows

PAS could be used in applications where images, documents, diagrams and text are analyzed by vision-language models.

The researchers say it could eventually support reliability checks in areas such as medical imaging, scientific document analysis, engineering diagrams, remote sensing and other visual workflows where unsupported claims could affect downstream decisions.

The Los Alamos team is presenting PAS at the Computer Vision and Pattern Recognition 2026 conference, sponsored by the IEEE and Computer Vision Foundation, in Denver this month.

The work was supported by the Laboratory Directed Research and Development program at Los Alamos.