Yesterday we wrote about the highlights of TechCrunch Disrupt London. One of them was Startup Battlefield, a startup competition consisting of short presentations followed up by Q&A session between the judges and the participants. As always, the competition was fierce and we got to know many fascinating projects. Two of them drew our attention the most. Meet Aiden & Iris, new AI assistants on the market.
The goal of Aiden is to make marketing data easier to digest. Currently, digital marketers depend on various information sources. Compiling all of it together takes time. What’s more, the conclusions they get might be outdated by the time they finish the analysis as users’ behaviors can change pretty fast. Aiden’s creators want to solve these problems. As their co-founder, Pierre-Jean Camillieri says: “As a marketer, you spend tons of time in fragmented dashboards. People spend almost 10 hours a week just searching for data. Another point we found out is that 60 percent of ad spend is actually wasted. Two of the big challenges for marketers today are a) what is important with my data and b) what do I do next.”
Crunching the data from many dashboards, Aiden generates eye-friendly charts. It saves time, helps marketers to manage vast databases and picks up changing trends faster than ever before. You can communicate with it (him?) through email, text messages, and Slack. Thanks to natural language processing, interacting with Aiden seems like chatting with your human coworker.
The second AI assistant presented during the last Startup Battlefield is Iris. The multinational team behind it first met at the Singularity University in 2015 with one goal in mind: to put scientific research into practice. However, digging through the vastness of scientific papers is extremely time-consuming. Finding exactly what you’re looking for without knowing the right keywords could take most of your resources before you even start the actual project. Iris can help fix these problems. How? It browses millions of abstracts of scientific papers and TED talks, mapping their content and learning what they are about. Later on, it can share this knowledge with people to find papers on topics they’re interested in.
Operating on a neural network, a digital representation of a brain, Iris learns partially on its own and partially under the guidance of human instructors. You can become one too – the team is looking for volunteers that could help Iris make sense of what it (she?) is reading. What’s most interesting, though, is the long-term goal for Iris. Apart from being a research assistant analyzing and mapping scientific data, Iris’s creators want it to become an AI scientists on its own rights, capable of formulating and testing hypotheses based on the data it gathered. Pretty neat, right?
The biggest AI personal assistants, like Cortana, Siri, Alexa or Google Assistant, are rather general in nature. They can check the weather for you, manage your calendar, stream music and the like. Although useful and fun to play with, there’s a long road ahead for them to achieve their desirable functionality. Could specialized, task-specific AI make faster progress? The work of startups like Aiden & Iris sure hints that could be the future of AI research. They’re not the only one specialized AI assistants out there – back in October, we featured Julie Desk, a personal assistant who manages your meeting schedule. I wonder what will be next!
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