MuleSoft CTO: API-based infrastructures helped company and customers adapt to the new normal

Agile, API-based systems are helping both MuleSoft customers and Salesforce react to the new business reality of increased remote work and rapid digital transformation.

In conjunction with Salesforce’s
TrailheaDX 2020

developer event, which was completely virtual this year, I had a chance to speak with MuleSoft CTO Uri Sarid for out
Dynamic Developer

podcast. Sarid discussed a variety of topics, including the company’s continued efforts to help companies build API-based infrastructures and capabilities, how these API-based systems are helping both customers and Salesforce adapt to the new normal of the COVID-19, and what’s on the horizon for MuleSoft, such as a new feature they’ll be releasing later this year called API Federation. The following is a transcript of our interview, edited for readability.

Bill Detwiler: So, when you and I spoke last at Dreamforce last year, we had a great conversation about how MuleSoft, and how you, really see the

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The field of natural language processing is chasing the wrong goal

At a typical annual meeting of the Association for Computational Linguistics (ACL), the program is a parade of titles like “A Structured Variational Autoencoder for Contextual Morphological Inflection.” The same technical flavor permeates the papers, the research talks, and many hallway chats.

At this year’s conference in July, though, something felt different—and it wasn’t just the virtual format. Attendees’ conversations were unusually introspective about the core methods and objectives of natural-language processing (NLP), the branch of AI focused on creating systems that analyze or generate human language. Papers in this year’s new “Theme” track asked questions like: Are current methods really enough to achieve the field’s ultimate goals? What even are those goals?

My colleagues and I at Elemental Cognition, an AI research firm based in Connecticut and New York, see the angst as justified. In fact, we believe that the field needs a transformation, not just in system

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KDE Plasma Desktop review: I’m still not switching from GNOME

Jack Wallen shares what he likes and dislikes about KDE Plasma and reveals who might be best suited to use the open source desktop.

Image: Jack Wallen

I have to confess: I don’t give KDE a fair shake. It’s not because I don’t believe it to be a strong take on the Linux desktop, it’s just that I prefer a much more minimal desktop. Also, I was never a big fan of the old taskbar/start menu/system tray combo. I leaned more toward the GNOME way of thinking and doing things.

Recently, a reader called me out on my lack of KDE coverage, so I thought it was time to offer up my take on where KDE Plasma stands, and who might be best suited to use this open source desktop. Comparing Plasma to my usual GNOME desktop is really quite challenging, given these two desktops are night and day. It’s

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Three AI companies join a business development group built by the London Stock Exchange

The cohort will get help refining their investment pitches as well as access to the group’s network of institutional investors.

Image: elenabs, Getty Images/iStockphoto

Three companies building artificial intelligence products and services have a fast track to funding as the newest members of the ELITE Group. This private business development program developed by the London Stock Exchange and Global Accelerated Ventures provides entrepreneurs with business coaching and access to institutional investors. 

ELITE announced Friday three new companies that will be in the organization’s latest cohort:

  • ModuleQ: An artificial intelligence (AI) platform that analyzes data from calendars, email, and Microsoft Teams to make business recommendations for individuals.
  • Covex 2020:  An AI company that combines and analyzes multiple data sets to support decision making.
  • vElement: A service provider that specializes in robotic process automation, data science, and artificial intelligence. 

Thomas Tyler, global head of ELITE Americas and global head

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A new neural network could help computers code themselves

That’s why some people think we should just get machines to program themselves. Automated code generation has been a hot research topic for a number of years. Microsoft is building basic code generation into its widely used software development tools, Facebook has made a system called Aroma that autocompletes small programs, and DeepMind has developed a neural network that can come up with more efficient versions of simple algorithms than those devised by humans. Even OpenAI’s GPT-3 language model can churn out simple pieces of code, such as web page layouts, from natural-language prompts.

Gottschlich and his colleagues call this machine programming. Working with a team from Intel, MIT and the Georgia Institute of Technology in Atlanta, he has developed a system called Machine Inferred Code Similarity, or MISIM, that can extract the meaning of a piece of code—what the code is telling the computer to do—in

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