Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Deploying software to support the work of an enterprise is an increasingly complex job that's often referred to as'devops.' When enterprise teams started using artificial intelligence (AI) algorithms to more efficiently and collaboratively run these operations, end users coined the term AIops for these tasks. AI can help large software installations by watching the software run and flag any anomalies or instances of poor performance.

In a recent episode of Star Trek: Discovery, the crew struggled with the question of how to trust their newly sentient ship's computer Zora. The issue of trust came to a head when Zora made a unilateral decision the crew didn't like. In the face of such insubordination, is there any way the crew could trust Zora to follow the chain of command? Today's AI is many years away from suddenly waking up sentient, but the question of trust is front and center in every professional's mind. If there's a chance that some AI-driven software might get an answer wrong – either clearly incorrect or perhaps more perniciously, subtly biased – then how can we ever trust it?

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Databases have always been able to do simple, clerical work like finding particular records that match some given criteria -- say, all users who are between 20 and 30 years old. Lately database companies have been adding artificial intelligence routines into databases so the users can explore the power of these smarter, more sophisticated algorithms on their own data stored in the database. The AI algorithms are also finding a home below the surface, where the AI routines help optimize internal tasks like re-indexing or query planning. These new features are often billed as adding automation because they relieve the user of housekeeping work.

While interest in Machine Learning/Artificial Intelligence/ (ML/AI) has never been higher, the number of companies deploying it is only a subset, and successful implementations a smaller proportion still. The problem isn't the technology; that part is working great. What's missing is the attitude, appreciation, and approach necessary to drive adoption and working solutions. To learn more, join us for this free 1-hour webinar from GigaOm Research. Our panel members are seasoned veterans in the database and analytics consulting world, each with a track record of successful implementations.

In 2016, Microsoft released a chatbot designed to interact with people over Twitter. Enabled with an AI routine that analyzed speech, the bot was supposed to show how machines could mimic human communication. Unfortunately, Microsoft had to remove the bot when it began tweeting racist and sexist comments; its AI engine was flooded with hate speech from pranksters and other bad actors online. Now the AI routine itself was certainly not sexist or racist, it was merely imitating speech based on the data it received. I'm sure this incident led to a lot of jokes about how AI-enabled machines will become evil geniuses bent on subjugating humanity.

New concerns over how artificial intelligence videos could spread fake news and even prompt a war. Forget fake news for a moment. Artificial intelligence is now able to generate a convincing video of a celebrity or public figure. For illicit purposes, these videos are called deepfakes and show a celebrity superimposed into an adult movie. A programmer finds existing video and audio for a known figure, then the AI takes over and creates a brand new version.

AI is a technology on the cusp. While nothing actually new in itself, a recent convergence of increased computational power with a mushrooming of large datasets and the refinement of existing understanding of the techniques involved has seen it become an important differentiator in the industry. Following a breakthrough year in 2015 when its use, particularly by Google for image processing and translation, jumped markedly, 2017 has seen it rapidly spread into many different niches. Of all the zeitgeist-friendly products on the showfloor at IBC2017, TVU Networks would have won a buzzword bingo competition with its Smart Captions subtitling software. Since renamed TVU Transcriber, it marries AI routines with voice recognition -- another fecund key technology segment in Amsterdam -- to provide an audio to text transcribing service.

One night in Corvallis, with the Oregon State basketball team heading to its 14th straight loss of its season, the talk around the hotel bar moved from the television screen to a far different form of communication -- chatbots. No one used that word, of course. But the technology took front and center in a conversation about Alexa, the voice-activated digital assistant from Amazon that can do everything from play music to order groceries. Give Amazon credit: it's pushed hard to win the hearts and minds of U.S. consumers, teeing up more than 100 mini ads for just that purpose. Software that can respond to voice or text commands is a high-growth investment sector about to explode in scope and penetration worldwide. Look no further than the announcement by Mark Zuckerberg last year that Facebook Messenger will be opened to bot development.