LLMs

Prompt Experiments for Python Vulnerability DetectionPhoto by Alexander Sinn on UnsplashIf you are a software professional, you might dread opening the security scan report on the morning of a release. Why? You know that it’s a great tool for enhancing the quality and integrity of your work, but you also know you are going to spend the next couple of hours scrambling to resolve all the security issues before the deadline. If you are lucky, many issues will be false alarms, but you will have to manually verify the status…

How can an LLM be applied effectively for biomedical entity linking?Photo by Alina Grubnyak on UnsplashBiomedical text is a catch-all term that broadly encompasses documents such as research articles, clinical trial reports, and patient records, serving as rich repositories of information about various biological, medical, and scientific concepts. Research papers in the biomedical field present novel breakthroughs in areas like drug discovery, drug side effects, and new disease treatments. Clinical trial reports offer…

The computational complexity of AI models is growing exponentially, while the compute capability provided by hardware is growing linearly. Therefore, there is a growing gap between those two numbers, which can be seen as a supply and demand problem. On the demand side, we have everyone wanting to train or deploy an AI model. On the supply side, we have Nvidia and a number of competitors. Currently, the supply side is seeing earnings skyrocket, and the demand side is stockpiling and vying for access to compute. It's a…

Even when the two sentences had the same meaning, the models were more likely to apply adjectives like “dirty,” “lazy,” and “stupid” to speakers of AAE than speakers of Standard American English (SAE). The models associated speakers of AAE with less prestigious jobs (or didn’t associate them with having a job at all), and when asked to pass judgment on a hypothetical criminal defendant, they were more likely to recommend the death penalty.  An even more notable finding may be a flaw the study pinpoints in the ways…

A beginner-friendly introduction w/ Python codeThis article is part of a larger series on using large language models in practice. In the previous post, we fine-tuned Mistral-7b-Instruct to respond to YouTube comments using QLoRA. Although the fine-tuned model successfully captured my style when responding to viewer feedback, its responses to technical questions didn’t match my explanations. Here, I’ll discuss how we can improve LLM performance using retrieval augmented generation (i.e. RAG).The original RAG system. Image…

Predicting the future—or at least, trying to—is the backbone of economics and an augur of how our society evolves. Government policies, investment decisions, and global economic plans are all predicated on estimating what’s happening in the future. But guessing right is tricky.However, a new study by researchers at the London School of Economics, the Massachusetts Institute of Technology (MIT), and the University of Pennsylvania suggests that forecasting the future is a task that could well be outsourced to generative…

Language models (LLMs) have revolutionized the field of natural language processing (NLP) over the last few years, achieving state-of-the-art results on a wide range of tasks. However, a key challenge in developing and improving these models lies in extending the length of their context. This is very important since it determines how much information is available to the model when generating an output.However, increasing the context window of a LLM isn’t so simple. In fact, it comes at the cost of increased computational…

Combining LLMs with Human Judgement through Prediction-Powered Inference (PPI)Continue reading on Towards Data Science » Combining LLMs with Human Judgement through Prediction-Powered Inference (PPI)Continue reading on Towards Data Science » FOLLOW US ON GOOGLE NEWS Read original article here Denial of responsibility! Techno Blender is an automatic aggregator of the all world’s media. In each content, the hyperlink to the primary source is specified. All trademarks belong to their rightful owners, all…

Two years ago, Yuri Burda and Harri Edwards, researchers at OpenAI, were trying to find out what it would take to get a large language model to do basic arithmetic. At first, things didn’t go too well. The models memorized the sums they saw but failed to solve new ones.  By accident, Burda and Edwards left some of their experiments running for days rather than hours. The models were shown the example sums over and over again, and eventually they learned to add two numbers—it had just taken a lot more time than anybody…

The government's missive that all artificial intelligence (AI) and large language models (LLMs) must seek "explicit permission of the government" before being deployed for users on the Indian internet, has sent shock waves among companies developing LLMs, especially startups who feel it is "anti-innovation and not forward-looking".Several companies building LLMs, venture capitalists as well as experts told ET such directions can kill startups trying to build in this "hyper-active" space in which India is already late to…