C9's Profile

For me the above article raises two interesting points — one around how humans are still needed in conjunction with machine learning, and the other around rental abuses.

Specifically with fashion I think there needs to be an intersection between a designer and machine learning. I don’t think machine learning alone can determine the best outfit to send to a consumer. There is something more intuitive and less concrete with fashion (especially a fancy one-time dress) which requires at least a small human touch.

Lastly, I found the point relating to rental abuses illuminating. While I do see a possible scenario where RTR incorrectly identifies someone who is a valuable customer – I think using data to help mitigate risk is something they absolutely need to do.

Before reading this article I was hesitant if FinTech companies could truly be successful in open innovation. But the above vignette on Neighborly has changed my mind! I agree with your idea about the company possibly using community feedback from individual investors to see what projects they want to invest in. But I wonder if asking investors themselves would even be necessary? What is especially powerful with a company like this too, is that that without even asking they should be able to see what investors are interested in — through analyzing trends in which projects get funded vs. not. Is there an opportunity for Neighborly to use both open innovation and machine learning to further scale?

I find the idea of open innovation with product development fascinating. In the above article the idea of limiting risk was raised. I wonder though if this is always the case? I assume Lego is sourcing from across customer bases and validating the ideas that were crowd sourced. But I could see a world where the company looks externally for ideas, sees some emerge and runs with it – to find that the specific toy idea only made sense in a niche market for those few people who submitted the idea. I am also grappling with the idea of trend spotting and data which we have discussed in marketing. Do consumers really know what type of toy they might want? Or are they looking at companies like Lego to tell them and create new and exciting toys?

What drew me to this article was my own fascination with how the mining industry is using machine learning. You hear about large tech companies leveraging data and become efficient with machine learning – but you rarely hear about industries like mining which have the perception of being stuck in the past. While the above article raises some interesting aspects of how BHP uses automation, I wonder though if their actions are truly machine learning?

Within self-driving trucks and automated drilling are they using data to make better informed decisions? Are the drills learning how better to drill over time? I do see some opportunities for a company like BHP to use machine learning in the future. Though I am not an expert in this field, I see an opportunity to use algorithms to make decisions on where / how much to drill – then having these algorithms learn from the return to make better informed decisions. Could use technology like this be the future of mining?

This article raises the idea of users suggesting metadata. As a user of Spotify, I wonder if there are any additional data points I could supply which would be helpful? Spotify currently offers a “I don’t like this song” or “I don’t like this artist” button for users. Would asking for additional information be too much of a burden on consumers?

Found the above article interesting, and left me puzzling the last question as well. Is there a broad enough market for luxury and3D printed watches? Will be luxury brands be able to change perception that 3D printing is still high enough quality and not just a shortcut? Bringing conversations we have had in marketing – can a watch company praise the qualities of hand-made craft AND offer a 3D printed watch? Are these two messages in stark contract?

Found the above article very interesting. I have always viewed additive manufacturing as the future, especially in fields such as aviation, but had not thought about the limitation in order numbers and reliance on past history. I do wonder though – is there an opportunity to use additive manufacturing in rapid prototyping? So instead of using 3D printing for the actual products that will go into space (which as mentioned above would need to have the highest quality), could you use this technology to try different approaches quickly, thus reducing overall R&D?