Discovered in 1999 in Germany, the Nebra Sky Disc is the oldest known depiction of the cosmos. A recent examination of the Bronze Age artifact revealed the intricate methods used in its creation, which UNESCO described as “one of the most important archaeological finds of the twentieth century.”
The Nebra Sky Disc is a product of the Únětice culture, which originated in the Bronze Age of Central Europe. It reflects a sophisticated ancient understanding of both metalworking and astronomy and was created sometime between 1800 and 1,600 BCE. Clusters of stars, a sun, and a crescent moon are among the celestial bodies depicted by golden inlays covering the blue-green patina of the Nebra Sky Disc. The angle between the solstices is thought to be indicated by two golden arcs that run along the sides of the disc, one of which is now absent. It is thought that a boat is represented by another arc at the composition’s base. Only a few millimeters thick, the disc has a diameter of around 12 inches.
The Nebra Sky Disc is one of the best-investigated archaeological objects. The origin of the raw materials it is made of is well known The disc is made from copper, tin, and gold—materials whose origins have been traced to Cornwall, England. The rich blue-green patina of the disc’s bronze today results from chemical changes over time. Originally, it would have been a deep bronze hue.
The AI race is heating up! In this video, we delve into the competition between Nvidia’s Llama-3.1 and OpenAI’s GPT-4. Discover how these two AI giants are revolutionizing the field of large language models (LLMs) and reshaping AI performance benchmarks. From Nvidia’s groundbreaking Llama-3.1 Nemotron to GPT-4’s advanced video generation capabilities, we analyze their strengths, use cases, and potential to lead the AI revolution.
Topics covered:
Nvidia Llama-3.1 vs. OpenAI GPT-4: Performance benchmarks. How to use Nvidia Llama-3.1 Nemotron-70B AI in video generation: OpenAI’s GPT-4 and Nvidia AI animation. Nvidia AI benchmarks, GPUs, and requirements. OpenAI vs. Nvidia: Who’s winning the AI race? Llama GPU requirements and running Llama without a GPU Stay tuned to learn which of these tech titans might dominate the future of AI innovation!
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Thanks to CRISPR, medical specialists will soon have unprecedented control over how they treat and prevent some of the most challenging genetic disorders and diseases.
CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a Nobel Prize-winning gene-editing tool, already widely used by scientists to cut and modify DNA sequences to turn genes on and off or insert new DNA that can correct abnormalities. CRISPR uses an enzyme known as Cas9 to cut and alter DNA.
Engineers at the USC Alfred E. Mann Department of Biomedical Engineering have now developed an update to the tool that will allow CRISPR technology to be even more powerful with the help of focused ultrasound.
A pair of researchers, one with the Carnegie Institution for Science, the other with California Institute of Technology, has developed a possible solution to the Fermi Paradox. In their paper published in Journal of the Royal Society Interface, Michael Wong and Stuart Bartlett suggest that the reason that no aliens from other planets have visited us is because of superlinear scaling, which, they contend, leads to a singularity. (How do “Predator Civilizations” solve the Fermi Paradox?)
One of the most powerful assets of the brain is that it can store information as memories, allowing us to learn from our mistakes. However, some memories remain vivid while others become forgotten. Unlike computers, our brains appear to filter which memories are salient enough to store.
Researchers from Tohoku University have discovered that part of the memory selection process depends on the function of astrocytes, a special type of cell that surrounds neurons in the brain. They showed that artificially acidifying the astrocytes did not affect short-term memory but prevented memories from being remembered long-term.
Researchers at UC San Diego identify a key pathway leading to neurodegeneration in early stages of ALS, hinting at the potential for short-circuiting the progression of the fatal disease if diagnosed early.
What do motion detectors, self-driving cars, chemical analyzers and satellites have in common? They all contain detectors for infrared (IR) light. At their core and besides readout electronics, such detectors usually consist of a crystalline semiconductor material.
Such materials are challenging to manufacture: They often require extreme conditions, such as a very high temperature, and a lot of energy. Empa researchers are convinced that there is an easier way. A team led by Ivan Shorubalko from the Transport at the Nanoscale Interfaces laboratory is working on miniaturized IR detectors made of colloidal quantum dots.
The words “quantum dots” do not sound like an easy concept to most people. Shorubalko explains, “The properties of a material depend not only on its chemical composition, but also on its dimensions.” If you produce tiny particles of a certain material, they may have different properties than larger pieces of the very same material. This is due to quantum effects, hence the name “quantum dots.”
While the technology itself is impressive, its true potential lies in how leaders manage its adoption. Fostering a culture of innovation and continuous learning is crucial for success in this new industrial era. Leaders must ensure that their workforce is not only comfortable with automation but is also empowered to collaborate with AI-driven systems. Upskilling and reskilling employees to work alongside AI will create a workforce capable of leveraging technology to enhance operational efficiency.
It’s also essential for business leaders to prioritize cybersecurity and data privacy. The increased connectivity that comes with IIoT introduces new vulnerabilities, and safeguarding company and customer data must be a top priority.
AI, edge computing and IIoT represent a fundamental shift in the way industries operate. The future of manufacturing is not just automated. It is also intelligent, with systems that learn, predict and adapt in real time. For leaders, the challenge is not only implementing these technologies; it’s also fostering an environment of innovation where technology, data and human expertise work together to achieve operational excellence.
