Sascha: Welcome back to another episode of The Process & Automation podcast, with The Automation Guys. In today's episode, we will go through a list of questions, questions we often get asked by our audience, on the topic of low code. And hopefully with our answers on these questions, we can break down some of the technical blur which is associated with our industry and automation. So let's kick it off with the first question we have received, um, yeah. Arno, do you like to take the first one?

Marc is yet another techie who has made a successful transition to being an entrepreneur. In this interview, he discusses his journey, as well as a lot of the nuances of positioning his venture, Starmind, for success. Sramana Mitra: Let's start by introducing our audience to yourself as well as to Starmind. Marc Vontobel: I'm the Co-Founder and CEO of Starmind. I have a background in Computer Science specializing in AI. That's also the origin of Starmind. I met my co-founder at the artificial intelligence laboratory in Zurich. We were supposed to work on humanoid robots, and we were totally lost. The initial idea of Starmind came up to build an eBay for knowledge. Instead of learning all the different disciplines ourselves, we envisioned having a platform where we can ask any question and put a price tag on it. That's how Starmind started. The problem was it was a one-sided market. No one really wanted to pay a colleague for their knowledge. It took us some time to

According to a recent McKinsey survey, a majority of enterprises of all sizes are actively embracing AI. The areas seeing the biggest boost from AI adoption include service-operations optimization, AI-based enhancement of products and contact-center automation. When the general American populace is asked about AI, most have a positive view on AI's potential. But if you ask the more engineering-centric, IEEE Spectrum crowd, AI has a long, long way to go before they're willing to stand and applaud. IEEE Spectrum "members are involved with hard-to-penetrate vendor decision teams, usually in management capacity," according to the 2020 media kit.

With such a broad definition, it's no wonder that AI is everywhere. We can basically stretch the definition of AI to fit any system that replaces human behaviour/intervention in any way. Since the 1950s people have been developing systems and calling it artificial intelligence (it goes further back, but that's when computer AI started). When it started it was based on the human brain and how digital signals are passed around the brain. This was the first attempt at a system that thinks humanly. But the problem is as far as we know, there's more to thinking than just electrons firing.

It is said that a successful product is a reflection of who we are. Usually, our unique perspective is what leads to the initial discovery. As the product acquires feedback, our keen desire to respond is what drives further innovation. Time and time again I see technology products starting on the right footing only to deteriorate as companies push them to scale. The internet now is quite mature, so this is becoming to stop using emojis finally experience.

IBM today made a major announcement about new products and services aimed at helping alleviate the roadblocks to AI (artificial intelligence) adoption in the enterprise. It is only a beginning, but it's very interesting in the breadth and comprehensiveness of IBM's plan. On the infrastructure front, they announced enhancements to the AC922 Server, primarily be improved integration of NVIDIA V100 GPUs and NVLink for faster system communications. This server is for the heavy lifting, training of AI models and processing in HPC (High Performance Computing) systems. They also announced the LC921 and LC922 servers aimed at data intensive applications.

I recently asked Desiree Garcia, designer at IBM, to discuss her experiences in designing for bots, balancing listening to your gut versus listening to stakeholders, and why content-first design is a must. At the O'Reilly Design Conference, Desiree will be presenting a session, Bots may solve some of our problems; here's how they'll put us on the hook for others. What are some of the new challenges bots present for designers? We designers love to talk about empathy all the time and what that means. For creating AI bot technology and bots using AI, I think there's more to building empathy for the user than creating a convincing dialogue, or coming up with ways to help with user frustration if the bot isn't perfect.