Integrated Wi-Fi is the major upgrade in this revamp of Lockly's well-aged Secure Pro lock, making it a winner on all fronts. The Lockly Secure Pro isn't a new lock, but rather an upgrade to an old one: The original Lockly Secure Pro came out way back in 2019, hence this release's full (and rather awkward) name: Lockly Secure Pro 2025 Version. The two locks have roughly the same industrial appearance (though the new lock is reportedly 25 percent smaller), so you'll need to pay close attention when shopping to ensure you're getting the current version. While Lockly's website includes the 2025 indicator in the name, many vendors, including Amazon, do not. Look for Lockly model number PGD728WMBE1 to be sure.

The instruction hierarchy, which establishes a priority order from system messages to user messages, conversation history, and tool outputs, is essential for ensuring consistent and safe behavior in language models (LMs). Despite its importance, this topic receives limited attention, and there is a lack of comprehensive benchmarks for evaluating models' ability to follow the instruction hierarchy. We bridge this gap by introducing IHEval, a novel benchmark comprising 3,538 examples across nine tasks, covering cases where instructions in different priorities either align or conflict. Our evaluation of popular LMs highlights their struggle to recognize instruction priorities. All evaluated models experience a sharp performance decline when facing conflicting instructions, compared to their original instruction-following performance. Moreover, the most competitive open-source model only achieves 48% accuracy in resolving such conflicts. Our results underscore the need for targeted optimization in the future development of LMs.

While Large Language Models (LLMs) are increasingly being used in real-world applications, they remain vulnerable to prompt injection attacks: malicious third party prompts that subvert the intent of the system designer. To help researchers study this problem, we present a dataset of over 126,000 prompt injection attacks and 46,000 prompt-based "defenses" against prompt injection, all created by players of an online game called Tensor Trust. To the best of our knowledge, this is currently the largest dataset of human-generated adversarial examples for instruction-following LLMs. The attacks in our dataset have a lot of easily interpretable stucture, and shed light on the weaknesses of LLMs. We also use the dataset to create a benchmark for resistance to two types of prompt injection, which we refer to as prompt extraction and prompt hijacking. Our benchmark results show that many models are vulnerable to the attack strategies in the Tensor Trust dataset. Furthermore, we show that some attack strategies from the dataset generalize to deployed LLM-based applications, even though they have a very different set of constraints to the game. We release all data and source code at https://tensortrust.ai/paper

The Internet of Things (IoT) is defined as a source connecting any electric device to the internet. The smart world has obtained devices like mobile, computer or tablets to stay at the electronic hype. Henceforth, IoT is no longer a part of some sci-fi movie or drama. The collection of usage and data by the IoT devices provides valuable insights into users' behaviours, interests and preferences, something which has been coined as the Internet of Behaviour (IoB). The emerging technology is expected to open numerous possibilities in business, personal finance, workplace and much more. Gartner has predicted that IoB will become more as a part of human life with over 3 billion people being under its influence by 2023.

The microchip is about the size of a grain of rice and usually inserted in the webbing between the thumb and forefinger using a needle the same thickness as used in body piercing. It feels, says insertable technology expert Kayla Heffernan, like getting a drip. Once the needle is removed the incision heals in a few days and the microchip remains, allowing the wearer to open doors with the brush of a hand – provided they only wish to access one particular place. Commercially available insertable microchips are only large enough to hold one access code and a small amount of other information, so the days of replacing an entire wallet and keychain with a tiny computer under the skin are not yet upon us. The future is coming, but it's not in a rush.