Researchers can mass-produce these cyborg cockroaches for disaster relief, surveillance, and environmental monitoring.
Researchers from Singapore have developed a new machine to automatically turn cockroaches into cyborgs in 68 seconds flat.
Continue reading “Cockroaches turned into cyborgs in 68 secs with new automated machine” »
Apple is reportedly developing a custom server processor to power its AI services. Codenamed “Project Baltra,” the initiative aims to bolster the AI capabilities integrated into Apple’s operating systems, with production expected to begin in 2026, according to The Information, which cites three unnamed sources familiar with the matter.
These sources indicate that Apple is partnering with semiconductor giant Broadcom for this endeavor. Apple now possesses a strong history and experience designing its own Arm-based silicon and already maintains an existing relationship with Broadcom in 5G component development.
While specific details remain scarce, it is speculated that Broadcom’s recent unveiling of its 3.5D eXtreme Dimension System in Package (3.5D XDSiP) technology could play a role in the project’s development.
Author(s): Yuki Shizuya Originally published on Towards AI. Photo by gilber franco on UnsplashRecently, I needed to research image similarity search. I wonder if there are any differences among embeddings based on the architecture training methods. However, few blogs compare embeddings among several models. So, in this blog, I will compare the vision embeddings of EfficientNet [1], ViT [2], DINO-v2 [3], CLIP [4], and BLIP-2 [5] for image similarity search using the Flickr dataset [6]. I will mainly use Huggingface and Faiss libraries for implementation. First, I will briefly introduce each deep learning model. Next, I will show you the code implementation and the comparison results.
With the approach of a new year, and the prospect of accelerating technological advancement, all eyes are on AI. The new best-selling book \.
Precision agriculture leverages cutting-edge machine learning algorithms to transform farming, boosting productivity and sustainability. From Random Forest for crop classification to CNNs for high-resolution imagery analysis, these tools optimize resources, detect diseases early, and improve yield prediction. Discover the top algorithms shaping modern agriculture and how they empower smarter, data-driven decisions.
There’s No Turning Back
Not long ago, solving the crystal structure of a protein required an entire PhD.
Growing crystals, collecting X-ray diffraction data, and interpreting electron density maps often took years of optimization and expensive instruments. Even then, solving all protein structures was a challenge, further compounding the “protein folding problem” in biology.
AIs that generate answers to user queries could transform search, but only if someone can get the tech and the business model right.
Data is the new oil, as they say, and perhaps that makes Harvard University the new Exxon. The school announced Thursday the launch of a dataset containing nearly one million public domain books that can be used for training AI models. Under the newly formed Institutional Data Initiative, the project has received funding from both Microsoft and OpenAI, and contains books scanned by Google Books that are old enough that their copyright protection has expired.
Wired in a piece on the new project says the dataset includes a wide variety of books with “classics from Shakespeare, Charles Dickens, and Dante included alongside obscure Czech math textbooks and Welsh pocket dictionaries.” As a general rule, copyright protections last for the lifetime of the author plus an additional 70 years.
Foundational language models, like ChatGPT, that behave like a verisimilitude of a real human require an immense amount of high-quality text for their training—generally the more information they ingest, the better the models perform at imitating humans and serving up knowledge. But that thirst for data has caused problems as the likes of OpenAI have hit walls on how much new information they can find—without stealing it, at least.
Researchers at the University of Sydney Nano Institute have made a significant advance in the field of molecular robotics by developing custom-designed and programmable nanostructures using DNA origami.
This innovative approach has potential across a range of applications, from targeted drug delivery systems to responsive materials and energy-efficient optical signal processing. The method uses ‘DNA origami’, so-called as it uses the natural folding power of DNA, the building blocks of human life, to create new and useful biological structures.
Continue reading “‘Velcro’ DNA origami helps build nanorobotic Meccano” »
