Daniel Knight's Profile

Al – you raise a great point. My understanding is that Winsun’s houses (and 3D-printed homes in general) do in fact require “traditional” foundations. Therefore, Winsun would rely on a contractor or developer to 1) lay the foundation, and 2) assemble the individual elements printed by Winsun’s printers. However, as Winsun considers the option of printing homes directly on a construction site, they’ll need to consider whether to lay the foundations themselves. Given the potential regulatory advantages or partnering with a larger construction firm, my best guess is that Winsun should keep its focus specialized on additive manufacturing, rather than diversifying into more traditional methods of construction.

You raise some great points regarding the true potential of 3D printing. Is this something that will really change the shoe landscape, or is this a fad that should be limited to prototyping early concepts? After reading your piece, I’ve been thinking about how 3D printed shoes would change the purchasing process for consumer. Most purchase journeys begin in a store or online — you know what type of shoe you’re looking for, but want to test size, fit, and look. Would a 3D printed shoe purchase require a change in customer behavior? For example, would a consumer need to add a step in the process and visit a retail location to get properly fit for a shoe? Alternatively, if this change in behavior poses too much of an attrition risk, how might ADIDAS recycle shoes that do not fit / are returned by unsatisfied consumers?

Spotify appears to be at the cutting edge of bridging art and science. In your article, you raise an interesting point regarding potential competitive threats. However, given the volume of data that Spotify has collected, is it reasonable to view this data bank as a stand-alone asset? I also wonder whether Spotify is deploying its capital most effectively in its quest to push the applications of machine learning. For example, do they generate more value by 1) assessing the validity of their existing tags (e.g., generated through NLP), or 2) investing in new forms of data collection and processing (e.g., beyond NLP or raw audio processing) to come up with new ways to tag songs? Finally, it feels like Spotify still relies on its people in order to test the validity of its tags and collaborative filtering. Do you see a world in which Spotify’s machine learning algorithms no longer need human validation/testing?

Ian – this article is fascinating. Neighborly’s work and mission and both impressive. It seems like Neighborly could benefit from expanding beyond its roots in municipal bonds in order to 1) increase the breadth of its product offering, and 2) decrease its sensitivity to the macro-trends you’ve highlighted. As Neighborly scales its operating, do you see value in the organization operating as more of an aggregator (or 2-sided marketplace) — collecting and screening investment-worthy projects, and providing a portal for investors to view those projects? It seems that the challenges these small projects face are two-fold: 1) they don’t meet funding requirements for traditional institutional investors, and 2) they lack access to /communication with other investors who are willing to put their capital to good use. Could Neighborly’s “value add” be in its ability to accept/promote viable community projects, rather than structuring the funding for each project?

I am wrestling with the tradeoff you allude to in this piece – namely, how can the US government incentivize accurate, appropriate use of crowd-sourcing anti-terrorism technology while limiting potential abuse? You also raise an interesting point regarding compensation. Rewarding individuals for reporting suspicious activity feels like an activity that rewards the general public by producing a positive externality (safety for all). Is it safe to assume that, with the right messaging (e.g., “if you see something, say something”), concerned citizens would act when they sensed a serious threat?

Christie also raises an interesting point above. It seems like we have two data points: 1) the past performance of government operatives, and 2) the wisdom of the uneducated masses. Is there a third data point we should be trying to measure — namely, how much more (or less) effective are intelligence agents when armed with open-sourced concerns?

It’s interesting to hear the ways in which the Raptors have quickly leveraged IBM Watson’s capabilities to inform their talent acquisition strategy. It seems like IBM’s technology is effective in providing the Raptors scouting team with a more holistic view of 1) their team’s performance and potential gaps, and 2) individual player potential – based on a much wider array of data. One concern I have is that this feels like a static view. If the Raptors are assessing their performance gaps at a point in time, can machine learning effectively help to predict how those gaps may change over time? In other words, can IBM Watson predict player-team compatibility based on potential future scenarios?

This is a fascinating article. It seems like under the right regulatory conditions, this technology has the potential to revolutionize the healthcare landscape. However, it seems like Organovo faces significant challenges. As you mentioned, given the potential in this industry, competition is heating up. How does Organovo plan on differentiating itself from the competition? Are there any new types of biological tissue that they could begin producing? To avoid becoming commoditized (e.g., just a printer), should they invest in more creative talent to design new prototypes of printed organs? Finally, would it make sense for Organovo to partner with a pharmaceutical company over the coming years? Organovo’s goal of affecting change within the FDA seems ambitious. Would fighting the good fight – while leveraging a pharma company’s considerable resources and power – help them to achieve their goal?

You make a great point regarding the potential for 3D-printing in humanitarian efforts. In particular, could Winsun leverage its ability to produce homes quickly and cheaply to aid in areas affected by natural disasters? They’ve demonstrated their ability to print 10+ homes in under a day for a few thousand dollars a piece. Imagine what 100 printers could do! Additionally, given Winsun’s production process uses recycled/waste material, I would suspect that homes initially built in emergency contexts could be repurposed as future “ink.”