Tag: detect
Cosmic-Ray Muons Used to Detect Underground Tombs In Naples
Cosmic rays and lasers have revealed that deep underneath the city streets of Naples, Italy, lie the remains of the Greeks who originally settled the area, as well as the catacombs of Christians who lived there during the Roman era nearly two millennia ago, a new study finds…
The layers of contemporary buildings make it difficult to access ancient sewers, cisterns and tombs 33 feet (10 meters) underneath the streets, so a group of Italian and Japanese researchers hypothesized that they could identify previously unknown burial hypogea from the Hellenistic period using 21st-century techniques. Their study, published April 3 in the journal Scientific Reports, details how they used muography to detect underground voids that were unknown to archaeologists… In 1936, scientists discovered that muons are produced by cosmic rays in Earth’s atmosphere, and that these tiny particles can easily penetrate walls and rocks, scattering in open spaces. In this study, the muons’ tracks were recorded using nuclear emulsion technology, in which extremely sensitive photographic film is used to capture and visualize the paths of the charged particles.
By measuring muon flux — how many muons arrive in a particular area over time — and direction using a particle detector, researchers can peer into volcanoes, underground cavities and even the Egyptian pyramids through muography… Valeri Tioukov, a physicist at Italy’s National Institute for Nuclear Physics, and his colleagues placed the muon tracking devices 59 feet (18 m) underground, in a 19th-century cellar that was used for aging ham, where they recorded the muon flux for 28 days, capturing about 10 million muons… 3D laser scans of the accessible structures can then be compared with the measured muon flux. Anomalies in the muon flux images that are not visible in the 3D model can be confidently assumed to be hidden or unknown cavities.
Muography revealed an excess of muons in the data that can be explained only by the presence of a new burial chamber. The chamber’s area measures roughly 6.5 by 11.5 feet (2 by 3.5 m), according to the study, and its rectangular shape indicates it is human-made rather than natural.
Read more of this story at Slashdot.
Firefox might one day be able to detect fake reviews written by ChatGPT
Microsoft explains how to detect a BlackLotus UEFI bootkit infection
BlackLotus is an all-powerful UEFI bootkit recently discovered “in the wild,” a security threat equipped with very advanced capabilities and designed to turn itself into an invisible ghost within a fully updated Windows machine. Even though the infection is effectively transparent to normal usage, researchers and analysts have now enough…
Meta shares AI model that can detect objects it hasn’t seen before
AI normally needs to be trained on existing material to detect objects, but Meta has a way for the technology to spot items without help. The social media giant has published a “Segment Anything” AI model that can detect objects in pictures and videos even if they weren’t part of the training set. You can select items by clicking them or using free-form text prompts. As Reutersexplains, you can type the word “cat” and watch the AI highlight all the felines in a given photo.
The model can also work in tandem with other models. It can help reconstruct an object in 3D using a single image, or draw from views from a mixed reality headset. Effectively, Segment Anything can limit the need for additional AI training.
Both the AI model and a dataset will be downloadable with a non-commercial license. That is, creators can’t use it for products. This is primarily for research and expanding access to the technology. Right now, Meta uses somewhat similar tech to moderate banned content, recommend posts and tag photos.
The developers acknowledge that the existing model is flawed. It might miss finer details, and isn’t as accurate at detecting the boundaries as some models. And while Segment Anything can handle prompts in real-time, it bogs down when demanding image processing is involved. Some more specialized AI tools are likely to outperform this model in their respective fields, Meta says.
You aren’t about to see this AI in robots or other devices where fast, accurate object detection is (usually) vital. However, models like this may still help in situations where it’s impractical to rely exclusively on training data. A social network could use the tech to keep up with a rapidly growing volume of content. If nothing else, this shows that Meta wants to generalize computer vision.
Meta is no stranger to sharing AI breakthroughs, such a translator for unwritten languages. With that said, there’s pressure on the company to show that it’s as much of a powerhouse in the category as tech heavyweights like Google and Microsoft. It’s already planning generative AI “personas” for its social apps, and inventions like Segment Anything show that it has a few advantages of its own.
This article originally appeared on Engadget at https://www.engadget.com/meta-shares-ai-model-that-can-detect-objects-it-hasnt-seen-before-210002471.html?src=rss
US national lab is using machine learning to detect rogue nuclear threats
The Pacific Northwest National Laboratory (PNNL) is trying to hunt for unknown nuclear threats by using machine learning (ML) algorithms. PNNL, which is one of the United States Department of Energy national laboratories, said that ML is everywhere now, and that it can be used to create “secure, trustworthy, science-based…
Google’s Pixel Watch can now detect if you fall: How to turn it on
How to Detect AI-Generated Text, According to Researchers
OpenAI says “AI classifier” tool can detect AI-written text
ChatGPT and other algorithms capable of producing seemingly correct textual content have quickly become a growing concern for educators, schools and universities, so much so that there is now a market for anti-AI tools like GPTZero. Another such tool has now been released by OpenAI, the very same company that…
OpenAI Releases Tool To Detect Machine-Written Text
Users copy a chunk of text into a box and the system will rate how likely the text is to have been generated by an AI system. It offers a five-point scale of results: Very unlikely to have been AI-generated, unlikely, unclear, possible or likely. It works best on text samples greater than 1,000 words and in English, with performance significantly worse in other languages. And it doesn’t work to distinguish computer code written by humans vs. AI. That said, OpenAI says the new tool is significantly better than a previous one it had released.
Read more of this story at Slashdot.