We are thrilled to announce the launch of our revolutionary new product, “Drive”. A testament to our commitment to innovation, “Drive” sets a new standard in financial technology by allowing users to interact directly with SEC filings using LLMs (Large Language Models). Interact with SEC Filings Like Never Before Drive empowers users to explore SEC filings through a chat interface that leverages state-of-the-art Language Models. This groundbreaking technology translates dense financial texts into understandable insights.

In our quest to find ways to maximize our positive impact on society, I’ve developed a Python script that helps us calculate the potential societal utility of a career or business idea. The script asks for the number of people potentially impacted per year by the new idea, and the total number of opportunities per year for both the current (“baseline”) and potential new career or business. Here’s the Python code:

Welcome back, savvy investors and AI enthusiasts! 🚀 Our journey into Temporal Fusion Transformers (TFTs) and their application in stock market prediction continues. In this installment, we’ll demystify the key components of TFTs, and discuss how they can be implemented using renowned machine learning libraries such as TensorFlow and PyTorch. Let’s dive in! Unfolding the Secrets of Temporal Fusion Transformers A TFT is composed of several critical components: Data Input Layer: This is the entry point of your time series data into the model.

Hello there, future AI enthusiasts and stock market wizards! 🧙‍♂️ Welcome to the first part of our deep dive into the world of AI, machine learning, and time series forecasting. We’re going to explore a powerful machine learning model called Temporal Fusion Transformers (TFT). If that sounds like a mouthful, don’t worry, we’ll break it down together. By the end of this series, you’ll be using AI to predict stock prices like a pro!

Today, we have an exciting topic on our hands. We’re going to delve deep into the world of deep learning by exploring one of the most versatile and dynamic libraries available - PyTorch. This library, developed by Facebook’s artificial intelligence research group, has been making waves in the AI community. It offers a flexible platform for both building and training a vast range of neural network architectures. PyTorch is used by researchers and engineers worldwide, spanning across startups and tech giants.

Introduction Artificial Intelligence (AI) is a term that’s been buzzing around a lot lately. Amidst all the buzzwords like ‘machine learning’, ‘deep learning’, ’tensorflow’, and ‘pytorch’, one term stands out as the cornerstone of many AI technologies - ’neural networks’. But what exactly are these neural networks, and why are they so central to AI and machine learning? Let’s take a closer look. What is a Neural Network? Neural networks, also known as ‘artificial neural networks’, are a type of machine learning model inspired by how our brains work.

Today, we’re taking a dive into automating summarization of online articles using Python, and the BART model from Hugging Face. Let’s dive right in! Getting Started Make sure you have the transformers and torch libraries installed. You can do this by using pip: pip install torch pip install transformers pip install coloredlogs Initializing the Summarizer and setting up our logger We begin by clearing our CUDA cache, then determining if we can run our operations on a GPU or if we need to use a CPU.

Source Today, I have an exciting piece of research to share, which plunges us into the intriguing world of smart robots, a place where the marvels of high technology intersect with unexpected vulnerabilities. In a recent groundbreaking study, an adept team of researchers has unlocked new insights into the functioning of our robotic counterparts. It’s an exciting prospect—we now have the means to delve deep into their ’thought’ processes!

Disclaimer: This blog post is created for demonstration purposes. Have you ever wondered if you could predict stock market trends and make profitable investments? Well, I recently embarked on an exhilarating journey, using an incredible program called SuperAGI, to delve into the realm of predictive stock market analysis. Buckle up as I share my experience, the agent template I fed into SuperAGI, and the intriguing results that unfolded. Unveiling SuperAGI’s Impressive Features SuperAGI is not your ordinary tool; it’s a game-changer in the world of stock market prediction.

Unleashing the Power of Code: WizardCoder Takes Code Language Models to New Heights Source | HF Model Introduction Diving into the universe of Artificial Intelligence and Machine Learning, we stumble upon a riveting sub-field known as Code Large Language Models (Code LLMs). These are sophisticated engines that have been trained extensively on myriad lines of code, giving them the ability to both understand and create programming scripts. Enter WizardCoder - an exciting leap forward that ups the ante for Code LLMs.