Lobe’s ridiculously simple machine learning platform aims to empower non-technical creators
Originally shared by Ward Plunet
Lobe’s ridiculously simple machine learning platform aims to empower non-technical creators
Machine learning may be the tool de jour for everything from particle physics to recreating the human voice, but it’s not exactly the easiest field to get into. Despite the complexities of video editing and sound design, we have UIs that let even a curious kid dabble in them — why not with machine learning? That’s the goal of Lobe, a startup and platform that genuinely seems to have made AI models as simple to put together as LEGO bricks. I talked with Mike Matas, one of Lobe’s co-founders and the designer behind many a popular digital interface, about the platform and his motivations for creating it. “There’s been a lot of situations where people have kind of thought about AI and have these cool ideas, but they can’t execute them,” he said. “So those ideas just like shed, unless you have access to an AI team.” This happened to him, too, he explained. “I started researching because I wanted to see if I could use it myself. And there’s this hard to break through veneer of words and frameworks and mathematics — but once you get through that the concepts are actually really intuitive. In fact even more intuitive than regular programming, because you’re teaching the machine like you teach a person.” But like the hard shell of jargon, existing tools were also rough on the edges — powerful and functional, but much more like learning a development environment than playing around in Photoshop or Logic. “You need to know how to piece these things together, there are lots of things you need to download. I’m one of those people who if I have to do a lot of work, download a bunch of frameworks, I just give up,” he said. “So as a UI designer I saw the opportunity to take something that’s really complicated and reframe it in a way that’s understandable.”
https://techcrunch.com/2018/05/05/lobes-ridiculously-simple-machine-learning-platform-aims-to-empower-non-technical-creators/
Lobe’s ridiculously simple machine learning platform aims to empower non-technical creators
Machine learning may be the tool de jour for everything from particle physics to recreating the human voice, but it’s not exactly the easiest field to get into. Despite the complexities of video editing and sound design, we have UIs that let even a curious kid dabble in them — why not with machine learning? That’s the goal of Lobe, a startup and platform that genuinely seems to have made AI models as simple to put together as LEGO bricks. I talked with Mike Matas, one of Lobe’s co-founders and the designer behind many a popular digital interface, about the platform and his motivations for creating it. “There’s been a lot of situations where people have kind of thought about AI and have these cool ideas, but they can’t execute them,” he said. “So those ideas just like shed, unless you have access to an AI team.” This happened to him, too, he explained. “I started researching because I wanted to see if I could use it myself. And there’s this hard to break through veneer of words and frameworks and mathematics — but once you get through that the concepts are actually really intuitive. In fact even more intuitive than regular programming, because you’re teaching the machine like you teach a person.” But like the hard shell of jargon, existing tools were also rough on the edges — powerful and functional, but much more like learning a development environment than playing around in Photoshop or Logic. “You need to know how to piece these things together, there are lots of things you need to download. I’m one of those people who if I have to do a lot of work, download a bunch of frameworks, I just give up,” he said. “So as a UI designer I saw the opportunity to take something that’s really complicated and reframe it in a way that’s understandable.”
https://techcrunch.com/2018/05/05/lobes-ridiculously-simple-machine-learning-platform-aims-to-empower-non-technical-creators/
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