What will drive NLP growth in the coming year?

A Look Ahead to NLP in 2022

The world is facing a global AI talent shortage, so while there’s a great demand for NLP implementations, the supply of data scientists needed to bring these projects to life are limited. But what if we could democratize NLP, reducing the need for data scientist intervention?

Chatbots are getting smarter

6 common mistakes agencies make when first deploying chatbots

We’ve all had our fair share of experiences with a bad chatbot, but chatbots are getting smarter and research shows that they will reach a 90% customer interaction success rate by 2022. Here are some key chatbot mistakes you don’t want to make and how to avoid common pitfalls.

Examining the dangers of intelligent machines

Will AGI Be a Friend or Foe?


Some believe that artificial general intelligence (AGI) will wipe out the human race, while others are confident it will lead to a utopian society. Between these extremes, most people anticipate major changes as AGI becomes more prevalent. What are the risks and dangers that will emerge?

Making the next-generation voice assistant

How a Data API Enables the MeetKai Next-Generation Voice Assistant

To be the next-generation voice assistant, you need to be a concierge that truly understands your user’s preferences, learns them, and keeps track of context for personalized results. How do you keep track of preferences and other relevant activities such as recent searches?

Developer and tester tips

Chatbot Testing: How to Get it Right in the First Go

Chatbots do more than just messaging. They are rapidly adding value to conversations and have context-driven intelligence that aims to solve customer problems in a convenient matter. This is just the tip of the iceberg. In this article, we will talk about the must-haves in your chatbot testing checklist.

Creating Artificial General Intelligence

Developing AGI: Where We Are and What the Future Holds


How do you create Artificial General Intelligence (AGI)? No one precisely knows. If we wait for a complete understanding with robust mathematical models of AGI, we may never get started. Given that, a more experimental and iterative development approach is in order.

Automate test writing

How AI (Reinforcement Learning) Can Help Spring Developers Write Better Java Unit Tests

Overall, Java developers love Spring/Spring Boot because it saves them time and supports their testing experiences. The Diffblue Survey found that Spring’s standardized testing approach makes it easier to apply a technique from artificial intelligence (AI) called Reinforcement Learning to automate test-writing. Making this work for Java developers can slash development time as well as improve code coverage.

Key aspects in the fight against bias

The fight against AI bias


The rapid growth of AI also means that technology is making more and more decisions without us questioning them. Whether it is loan approvals, job recruiting or facial recognition, companies now more than ever need to make sure their AI applications do not discriminate against humans. To minimize the risk of AI bias – the unintended distortion of decisions by artificial intelligence – developers must keep a number of things in mind.

Avoiding DIY disaster

Building Your Own AIOps Platform is a Bad Idea

Why does DIY AIOps fail and what is the root cause? In many cases, all the time and effort put into a do-it-yourself project simply winds up being wasted. This article looks at how to safely encourage AIOps exploration and measure ROI from AIOps without the risk of failure.

The fifth form of matter

Introducing software fuzzing – part of AI and ML in DevOps

Justin Reock, Chief Architect for OpenLogic at Perforce Software, describes what is software fuzzing and why it is needed. Justin is the author on a chapter about fuzzing in a new book from Perforce Software: “Accelerating Software Quality: Machine Learning & Artificial Intelligence in the Age of DevOps”.

Reliable and secure

Why Artificial Intelligence Should be Deployed For Enhanced Data Centers


AI makes it possible to process and interpret huge quantities of data far more quickly and efficiently, potentially unlocking a whole host of new insights. In this article, we’ll take a look at what AI is doing for data centers and why you need to make the most effective possible use of this transformative technology.