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Undoubtedly OpenAI's Neural Network for deep text generation was built with good intentions, but can its sheer power become a recipe for disaster? GPT2 started life as a what word follows next predictor, just as Gmail or the virtual keyboards in our mobile devices do. For that purpose it was trained with a massive 40GB dataset, a database collected from sites around the web heavy in text, mostly news sites. The dataset was fed into the Neural Network in order to build a linguistic model as a basis for predicting the next word. That, of course, means that it can generate text, well as far as the next word goes. However, it turns out that the model became so good at it that it also learned to generate complete meaningful sentences: full article on i-programmer

Open Source vs. Commercial, Public Cloud vs. On-Premise vs. Hybrid Cloud? Which one? Last month ScaleGrid attended Percona's Live event, got the insight on the most used "databases" by Percona's clients in 2019 and made a report out of it. I'll ignore the fact that the report mistakenly uses the term "database" in place of (R)DBMS, so that I can just focus on the juicy stuff. The popularity categories are broken down into: Top Databases Used: Open Source vs. Commercial Cloud Infrastructure Analysis: Public Cloud vs. On-Premise vs. Hybrid Cloud Polyglot Persistence Trends: Number of Databases Used & Top Combinations So first of all, the lowdown on the top Open Source "Databases". full article on i-programmer

Software development is flooded with IDE's and text editors, the general consensus being that VSCode is the most popular. What about Vim? Hardcore Linux devs who like to get their hands dirty still prefer the timeless and venerable Vim. Personally, I think that anyone working with a Linux shell should first learn to use Vim. I use it for writing Perl, shell scripts or manipulating text without craving the bells and whistles that VSCode offers. When I started out with Vi(m), there were just a few text-based tutorials, but now they come in a variety of formats, and certainly when I was starting out I would have found such a good flashy and interactive guide most helpful. full article on i-programmer

The new distribution of ROS2, code named "Dashing Diademata", is the first Long Time Support release following last year's "Crystal".  Along with it, there are many new features that aim to establish ROS as an industry wide standard, to be used safely in commercial applications. But Diademata also breaks ties with its ROS1 predecessor, a move that signifies time to upgrade. full article on i-programmer

Who said that only humans can collaborate? AI not only managed to break this barrier too, but it also managed to beat humans at their very own game. Fun aside, Capture the Flag competitions are difficult to win even for humans. In a competition like this, each competing team comprising of two or more teammates occupies a basecamp identified by a distinct flag. The team has to protect its flag at all cost, but at the same time capture and hold the other teams' flags in order to win the competition. It's the exact same thing happening when a country gets conquered, the winner folding the home flag to replace it with its own symbol. In tech slang, that's the definition of 'owned'. full article on i-programmer

The AI for K-12 Initiative wants to kick-start the discussion on how to incorporate learning about AI in the United States school curriculum, ultimately leading to national guidelines.  The AI for K12 working group led by Professor David Touretzky, an AI researcher at Carnegie Mellon University was announced a year ago by the AAAI (Association for the Advancement of Artificial Intelligence, formerly the American Association for Artificial Intelligence). The project is in collaboration with the Computer Science Teachers Association and AI4All, a nonprofit that works to increase diversity and inclusion in artificial intelligence.  full article on i-programmer.info