Search results
Results from the WOW.Com Content Network
Prompt injection is a family of related computer security exploits carried out by getting a machine learning model which was trained to follow human-given instructions (such as an LLM) to follow instructions provided by a malicious user. This stands in contrast to the intended operation of instruction-following systems, wherein the ML model is ...
Prompt injection is a family of related computer security exploits carried out by getting a machine learning model (such as an LLM) which was trained to follow human-given instructions to follow instructions provided by a malicious user. This stands in contrast to the intended operation of instruction-following systems, wherein the ML model is ...
Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.
Code injection is the malicious injection or introduction of code into an application. Some web servers have a guestbook script, which accepts small messages from users and typically receives messages such as: Very nice site! However, a malicious person may know of a code injection vulnerability in the guestbook and enter a message such as:
There is free software on the market capable of recognizing text generated by generative artificial intelligence (such as GPTZero), as well as images, audio or video coming from it. [99] Potential mitigation strategies for detecting generative AI content include digital watermarking , content authentication , information retrieval , and machine ...
Prompt injection, a technique by which malicious inputs can cause AI systems to produce unintended or harmful outputs, has been a focus of these developments. Some approaches use customizable policies and rules to analyze both inputs and outputs, ensuring that potentially problematic interactions are filtered or mitigated. [ 145 ]
OpenAI researchers found that Codex struggles with multi-step and higher-level [clarification needed] prompts, often failing or yielding counter-intuitive behavior. Additionally, they brought up several safety issues, such as over-reliance by novice programmers, biases based on the training data, and security impacts due to vulnerable code.
Ernie Bot is based on particular Ernie foundation models, including Ernie 3.0, Ernie 3.5, and Ernie 4.0. The training process starts from pre-training, learning from trillions of data points and billions of knowledge pieces. This was followed by refinement through supervised fine-tuning, reinforcement learning with human feedback, and prompt. [19]