Breakthroughs, discoveries, and DIY tips sent every weekday. Ancient Egyptians may have used opium a . Based on recent examinations, archaeologists now say the drug may even have been a near-daily recreational habit. Opium might have even been widely used across socio-economic classes as long as 3,000 years ago. The evidence is detailed in a study recently published in the, and offers a glimpse into the daily lives of regular Egyptians and royalty alike.

Science Archaeology The search for Cleopatra's long-lost tomb leads to sunken seaport A new documentary explores this 2,000-year-old mystery and a connection to the RMS'Titanic.' Breakthroughs, discoveries, and DIY tips sent every weekday. She's among the most famous leaders in world history, yet archeologists still don't know the location of Egyptian Queen Cleopatra's tomb. Now, National Geographic Explorer and archaeologist Dr. Kathleen Martínez and her team have uncovered a major clue in their 20-year-long hunt: the remains of a port off Egypt's Mediterranean coast. The previously unknown ancient port could have been used to keep the Egyptian queen's remains out of Roman hands.

We introduce the first watermark tailored for diffusion language models (DLMs), an emergent LLM paradigm able to generate tokens in arbitrary order, in contrast to standard autoregressive language models (ARLMs) which generate tokens sequentially. While there has been much work in ARLM watermarking, a key challenge when attempting to apply these schemes directly to the DLM setting is that they rely on previously generated tokens, which are not always available with DLM generation. In this work we address this challenge by: (i) applying the watermark in expectation over the context even when some context tokens are yet to be determined, and (ii) promoting tokens which increase the watermark strength when used as context for other tokens. This is accomplished while keeping the watermark detector unchanged. Our experimental evaluation demonstrates that the DLM watermark leads to a >99% true positive rate with minimal quality impact and achieves similar robustness to existing ARLM watermarks, enabling for the first time reliable DLM watermarking.

Large language models (LLMs) can be used to serve as agents to simulate human behaviors, given the powerful ability to understand human instructions and provide high-quality generated texts. Such ability stimulates us to wonder whether LLMs can simulate a person in a higher form than simple human behaviors. Therefore, we aim to train an agent with the profile, experience, and emotional states of a specific person instead of using limited prompts to instruct ChatGPT API. In this work, we introduce Character-LLM that teach LLMs to act as specific people such as Beethoven, Queen Cleopatra, Julius Caesar, etc. Our method focuses on editing profiles as experiences of a certain character and training models to be personal simulacra with these experiences. To assess the effectiveness of our approach, we build a test playground that interviews trained agents and evaluates whether the agents \textit{memorize} their characters and experiences. Experimental results show interesting observations that help build future simulacra of humankind.

We explore a knowledge sanitization approach to mitigate the privacy concerns associated with large language models (LLMs). LLMs trained on a large corpus of Web data can memorize and potentially reveal sensitive or confidential information, raising critical security concerns. Our technique fine-tunes these models, prompting them to generate harmless responses such as ``I don't know'' when queried about specific information. Experimental results in a closed-book question-answering task show that our straightforward method not only minimizes particular knowledge leakage but also preserves the overall performance of LLM. These two advantages strengthen the defense against extraction attacks and reduces the emission of harmful content such as hallucinations.

Let there be (ring) light. A British film editor is going viral for using artificial intelligence to imagine famous historical figures such as Jesus, Cleopatra, Queen Elizabeth I and Henry VIII taking selfies. "The results are hilarious, and everyone I've shared my work with can't believe how real the pictures really look," Duncan Thomsen, 53, told SWNS. He said he uses the AI software Midjourney through the Discord app, which responds to user-set prompts and commands to generate pictures by referencing billions of images online. Thomsen has recreated scenes from the Battle of Waterloo, the court of Cleopatra, and the Last Supper.

No living human can imagine what it was like to sit at the Last Supper or stand at Cleopatra's court, but artificial intelligence has given us a first-person look at these epic events. A freelance film editor recently shared a gallery of realistic images of historical figures taking selfies. He spent months developing a formula for clues, language and photographic elements. Duncan Thomsen, 53, used Midjourney software, which generates images from natural language descriptions. The images also show smiling soldiers at the Battle of Waterloo and the Battle of Agincourt, as well as a smiling Napoleon.

No living human can imagine what it was like to sit at The Last Supper or stand in Cleopatra's court, but AI has provided us with a look at these epic events - and from a first-person perspective. A freelance film editor recently shared a gallery of realistic images showing historical figures snapping selfies, which he spent months working out a formula of prompts, language and photographic elements. Duncan Thomsen, 53, used the software Midjourney, which generates images from natural language descriptions, also shows smiling soldiers at the Battle of Waterloo and the Battle of Agincourt, along with a grinning Napoleon. 'The results are hilarious, and everyone I've shared my work with can't believe how real the pictures really look,' said Thomsen. 'I've done Cleopatra, Queen Elizabeth I, Henry VIII, Jesus and many more.' AI is making waves in the image industry, letting anyone create realistic content just by telling the system what they want.

Researchers have developed a new method to detect rogue planets outside the solar system, worlds that wander their galaxies alone without a parent star. The technique, devised by NASA Goddard Space Flight Center scientist, Richard K. Barry, unites astronomy's future--in the form of the soon-to-launch Nancy Grace Roman Space Telescope--with its past, a method used by 19th-century astronomers to measure distances. The Contemporaneous LEnsing Parallax and Autonomous TRansient Assay (CLEoPATRA) mission will use parallax to measure distances, but the method will be bolstered by artificial intelligence (AI) developed by Dr. Greg Olmschenk. Olmschenk's program, RApid Machine learnEd Triage (RAMjET), will learn patterns through provided examples filtering out useless information and ensuring that of the millions of stars observed by CLEoPATRA per hour, only useful information is transmitted back to Earth. Recent research published in The Astronomical Journal suggests that exoplanets that exist in the Universe without a parent star could be more common than stars themselves, but until now spotting them has been difficult.

The Assassin's Creed series is known for its vast and richly detailed historical environments, and well... lots of murder. What you might not realize is just how much work goes into making these virtual windows into the past somewhat realistic. That's something Ubisoft is aiming to highlight with Assassin's Creed Origins' Discovery Tour. You can think of it as a museum-like experience set within the game's meticulous rendition of ancient Egypt. To turn one of the most popular gaming franchises in the world into a truly useful educational tool.