Instacart and OpenAI partner on AI shopping experiences
OpenAI and Instacart are deepening their longstanding partnership by bringing the first fully integrated grocery shopping and Instant Checkout payment app to ChatGPT.
OpenAI and Instacart are deepening their longstanding partnership by bringing the first fully integrated grocery shopping and Instant Checkout payment app to ChatGPT.
Genuinely curious, what stops roving gangs from taking over communities and driving folks from their homes with no government or public safety force of any kind? submitted by /u/personofinterest1986 [link] [comments]
Author(s): Sayan Chowdhury Originally published on Towards AI. Understanding the OG Perceptron Neural networks look complex from the outside, but at their core they are built from one simple unit. This unit is called the perceptron. The OG 😀The article explains the perceptron, the simplest form of a neural network, which serves as a tiny decision maker by taking a set of inputs to decide between two outcomes. It discusses how perceptrons inspired modern deep learning systems, focusing […]
Annotating regions of interest in medical images, a process known as segmentation, is often one of the first steps clinical researchers take when running a new study involving biomedical images. For instance, to determine how the size of the brain’s hippocampus changes as patients age, the scientist first outlines each hippocampus in a series of brain scans. For many structures and image types, this is often a manual process that can be extremely time-consuming, especially if the regions […]
This article introduces the Gaussian Mixture Model as a natural extension of k-Means, by improving how distance is measured through variances and the Mahalanobis distance. Instead of assigning points to clusters with hard boundaries, GMM uses probabilities learned through the Expectation–Maximization algorithm – the general form of Lloyd’s method. Using simple Excel formulas, we implement EM step by step in 1D and 2D, and we visualise how the Gaussian curves or ellipses move during training. The means shift, […]
Large language models (LLMs) are based on the transformer architecture, a complex deep neural network whose input is a sequence of token embeddings.
As has been said by many commentators, rare earths are not particularly rare. Via source, here is an estimate of their abundance in the Earth’s surface: Note by the way the Y-axis is logarithmic so small changes in vertical position can mean a factor of 10 or more difference in concentration. But the rare earths are not unreasonably far off fairly common industrial metals like lead, nickel, copper, and molybdenum and well more common than gold, silver, and […]
Today, we are celebrating the extraordinary impact of Nobel Prize-winner Geoffrey Hinton by investing in the future of the field he helped build. Google is proud to supp…
I just got a $15 tip to deliver a $1 soda in a rich neighborhood. This is just one silly example, but rich people, or just wealth in general obviously creates more opportunities and jobs for all of us submitted by /u/Crafty_Jacket668 [link] [comments]
Large language models (LLMs) sometimes learn the wrong lessons, according to an MIT study. Rather than answering a query based on domain knowledge, an LLM could respond by leveraging grammatical patterns it learned during training. This can cause a model to fail unexpectedly when deployed on new tasks. The researchers found that models can mistakenly link certain sentence patterns to specific topics, so an LLM might give a convincing answer by recognizing familiar phrasing instead of understanding the […]