Remove 2017 Remove Algorithm Remove Deep Learning
article thumbnail

Inching towards AGI: How reasoning and deep research are expanding AI from statistical prediction to structured problem-solving

Flipboard

Back in 2017, my firm launched an AI Center of Excellence. AI was certainly getting better at predictive analytics and many machine learning (ML) algorithms were being used for voice recognition, spam detection, spell ch… Read More GUEST: AI has evolved at an astonishing pace.

article thumbnail

Understanding and coding Neural Networks From Scratch in Python and R

Analytics Vidhya

Note: This article was originally published on May 29, 2017, and updated on July 24, 2020 Overview Neural Networks is one of the most. The post Understanding and coding Neural Networks From Scratch in Python and R appeared first on Analytics Vidhya.

Python 400
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

[AI/ML] Keswani’s Algorithm for 2-player Non-Convex Min-Max Optimization

Towards AI

Keswani’s Algorithm introduces a novel approach to solving two-player non-convex min-max optimization problems, particularly in differentiable sequential games where the sequence of player actions is crucial. Keswani’s Algorithm: The algorithm essentially makes response function : maxy∈{R^m} f (.,

Algorithm 103
article thumbnail

DeepMind

Dataconomy

is dedicated to creating systems that can learn and adapt, a fundamental step toward achieving General-Purpose Artificial Intelligence (AGI). Technology and methodology DeepMind’s approach revolves around sophisticated machine learning methods that enable AI to interact with its environment and learn from experience.

article thumbnail

First Step to Object Detection Algorithms

Heartbeat

How do Object Detection Algorithms Work? There are two main categories of object detection algorithms. Two-Stage Algorithms: Two-stage object detection algorithms consist of two different stages. Single-stage object detection algorithms do the whole process through a single neural network model.

article thumbnail

Tensor Processing Units (TPUs)

Dataconomy

Tensor Processing Units (TPUs) represent a significant leap in hardware specifically designed for machine learning tasks. They are essential for processing large amounts of data efficiently, particularly in deep learning applications. TPUs are specialized hardware designed to accelerate and optimize machine learning workloads.

article thumbnail

TensorFlow

Dataconomy

TensorFlow has revolutionized the field of machine learning and deep learning since its inception. TensorFlow is an open-source framework designed for machine learning and deep learning applications. in early 2017. What is TensorFlow? Released as open-source in 2015 under the Apache 2.0