State of AI technology in 2020: Comprehensive Guide

AI technology can be divided into 3 layers. While we will likely see incremental improvements in algorithm design and application of those algorithms to specific domains, step change is possible in computing if breakthroughs can be achieved in quantum computing.

  • Algorithms that enable machine decision making including artificial neural networks (ANN), Bayesian inference and evolutionary computing. ANNs can be categorized by their depth (i.e. number of layers) and structure (i.e. how nodes are connected). Most recent progress in AI was due to deep neural networks (also called deep learning).
  • Computing technology to run those algorithms: Computing is key in AI, advances in computing power enabled the wave of AI commercialization thanks to deep learning since the 2010s.
  • Application of those algorithms to specific domains including reinforcement learning, computer vision, machine vision, natural language processing (NLP), recommendation systems.

AI Algorithms

Algorithms are like recipes for AI systems to learn from data or to make decisions. Advances in algorithm design are key for advancement for AI.

Artificial Neural Networks (ANNs)

The neural network is a popular machine learning technique that is inspired by the human brain and the neural network in our brains. Read more

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Future of AI according to top AI experts of 2020: In-Depth Guide

Investment and interest in AI is expected to increase in the long run since major AI use cases (e.g. autonomous driving, AI-powered medical diagnosis) that will unlock significant economic value are within reach. These use cases are likely to materialize since improvements are expected in the 3 building blocks of AI: availability of more data, better algorithms and computing.

Short term changes are hard to predict and we could experience another AI winter however, it would likely be short-lived. Feel free to jump to different sections to see the latest answers to your questions about the future of AI: Read more

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AI-Powered Mobile Apps: A Brief Introduction

Are you looking to transform your mobile app with AI solutions? You can improve your user experience by integrating AI technologies to your app. We have compiled an introduction to AI-powered mobile apps to help you to understand how you can benefit from AI to improve your mobile apps.

How is AI impacting the mobile experience?

AI enables personalized mobile apps which helps improve user experience. This is the most common use case of AI in mobile apps. These apps can store many information about us such as our age, gender, location, hobbies, photos we like, the products we buy and much more. Read more

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AI in Business: Guide to Transforming Your Company [2020 Update]

You probably read tens of articles on AI in business indicating numerous AI applications or exotic-sounding algorithms like deep learning or support vector machines. But you don’t know what you can do with AI for your own business today. We have a solution:

First, AI is a tool and writing in general about AI in business is like writing about computers in business. It helps to be a lot more specific so we will break down AI applications by industry and business function to give you an overview of what AI can achieve. Read more

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2018 AI predictions: Summary of top AI experts’ predictions

Since the beginning of the year, PwC, CEO of pymetrics, Gil Press  from Forbes published predictions on the direction AI will take. We read them all and couldn’t resist adding our predictions and categorizing the predictions:

Mega-trends that will shape AI in 2018

The news cycle is full of AI, research centers being opened, re-organizations, new research findings and tabloids peddling that robots will kill us all tomorrow. Reading a different type of news everyday, it is easy to lose track of what is really happening. What are the major trends? Read more

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