InfoQ Homepage Artificial Intelligence Content on InfoQ
-
Q&A on the Book Techlash
The book Techlash by Ian Mitroff and Rune Storesund explains why companies need to become socially responsible by considering the potential negative outcomes of technology. It explains how proactive crisis management can help prevent a crisis by the early detection and correction of deviations from expected conditions.
-
The First Wave of GPT-3 Enabled Applications Offer a Preview of Our AI Future
The first wave of GPT-3 powered applications are emerging. After priming of only a few examples, GPT-3 could write essays, answer questions, and even generate computer code! Furthermore, GPT-3 can perform algebraic calculations and language translations despite never being taught such concepts. However, GPT-3 is a black box with unpredictable outcomes. Developers must use it responsively.
-
State of the Art in Automated Machine Learning
InfoQ caught up with experts Francesca Lazzeri, machine learning scientist lead at Microsoft; Matthew Tovbin, co-founder of Faros AI; Adrian de Wynter, applied scientist in Alexa AI’s Secure AI Foundations; Leah McGuire, principal member of technical staff at Salesforce; and Marios Michailidis, data scientist at H2O.ai, about the state of the art in automated machine learning (AutoML).
-
The Road to Artificial Intelligence: a Tale of Two Advertising Approaches
Artificial Intelligence startups received a record $26.6bn in funding last year, yet a litany of stakeholders continue to demonstrate a lack understanding and education around the discipline. It is critical that entrepreneurs, investors, regulators, and consumers all remain vigilant in properly assessing advertising claims as relates to powerful, constantly-evolving technology.
-
What Do AI and Test Automation Have in Common?
These days AI is a big buzzword. While it rises in popularity, the controversy surrounding it flourishes as well. We will demystify AI, and see how it is already embedded in our everyday life, and then you are going to learn about how we (the folks at Testim.io) utilised this kind of groundbreaking technology to bring test automation to the next level.
-
What’s Next in DevOps?
The DevOps movement continues to grow and gain influence in the IT world and the business world at large. As the organisations become increasingly digital, the agility of our IT systems becomes critical to the life and health of the companies.
-
Q&A on the Book AI Crash Course
The book AI Crash Course by Hadelin de Ponteves contains a toolkit of four different AI models: Thompson Sampling, Q-Learning, Deep Q-Learning and Deep Convolutional Q-learning. It teaches the theory of these AI models and provides coding examples for solving industry cases based on these models.
-
Has an AI Cyber Attack Happened Yet?
AI cyber attacks have happened and are happening, with increasing regularity. This article looks at recent attacks, the role of bots, and defense strategies you can employ.
-
The Road to Artificial Intelligence: An Ethical Minefield
Increasingly-rapid developments in the field of AI have offered society profound benefits, but have also produced complex ethical dilemmas. Many of the most nefarious issues are often overlooked, even in the engineering community. There also exists the meta-ethical question of who ought to be the ones making decisions concerning the encoding of values into autonomous systems.
-
How King uses AI to test Candy Crush Saga
To be able to improve features in games which are constantly evolving, the challenge will be to scale tests to be on a par with new feature development. Automated tests are vital for King to keep up testing Candy Crush, therefore they are constantly looking for new improved ways to test.
-
Q&A on the Book Rebooting AI
The book Rebooting AI explains why a different approach other than deep learning is needed to unlock the potential of AI. Authors Gary Marcus and Ernest Davis propose that AI programs will have to have a large body of knowledge about the world in general, represented symbolically. Some of the basic elements of that knowledge should be built in.
-
Building Intelligent Conversational Interfaces
Authors discuss how to build intelligent conversational applications and skills using the conversational AI technology and its three components: interaction flow, natural language understanding (NLU) and deployment.