ncubeeight

Do we need to "develop" apps anymore? Can consumers develop their own apps yet? The recent years of post-pandemic employment slump has been capturing headlines as tech leaders across the board have cut their staffing dramatically to achieve more efficiency in their businesses. Seeing hundreds of thousands of layoffs is a grim reminder of the boom/bust cycle that hangs over high-beta companies that leverage investment to scale up for unforeseeable future market demand. An interesting twist in the headlines over the last year is more of these companies seeking to “flatten their organization structures.” Often these stories have focused on machine learning automation of routine tasks and in some cases delegating creative engineering or product design work to automated tools. Legislators, who earn their salaries from taxing humans, wouldn’t want more mechanized labor in the work force because typically machines don’t pay taxes. But seeking to legislate staff retention is a ...

10 years ago a CEO standing on stage making a joke about someone’s web query would have been shocking instead of funny. This is because of major backlash that happened 20 years prior when AOL open sourced the query logs of 650000 random people to developers resulting in journalists using the query list to track down individuals with personally identifiable information in the logs. Those affected AOL users did not know they were in this now-public repository. But now our assumptions of scope of privacy are significantly shifted because of the era of social media that followed in the ensuing decade. The advent of micro-blogging along with vertical tools for yelping our food, foursquaring our shopping habits, tweeting our quips or instagramming our lifestyles expanded the scope of where the cameras and public visibility approached closer into our personal sphere. We came to be familiar with the concepts of privacy in a narrower scope of our private daily lives. But there is still confusi...

I attend a lot of online conferences and conference calls in Silicon Valley. I had gotten used to the “ Brady Bunch era” of Zoom call grids of checkerboard faces in our pandemic era. But something has shifted in the last year. Now often the meeting room grid designed to show call participants is filled with black boxes that say <companybrand>AI. I know these are LLM based transcription services that folks have employed in their stead which sync automatically to calendars to transcribe meetings that the person doesn’t attend. Having a meeting transcribed is great. But having dozens of AI listening scribes that outnumber the people who actually show up in person to the call does something strange to the meeting dynamic.  In a call I joined this week the host, a very smart friend of mine, was switching off all the AI attendees one by one. After a few minutes the blank identities were gone and the screen was filled with live human faces again. It was just like pandemic Zoom call...

I've been reading about the opportunities and perils of chatbot technologies recently. This is in part spurred by books written by Karen Hao and Sarah Wynn-Williams about industry players in the sector and in-part inspired by the recent articles on psychological peril for young people engaging with chatbot apps discussed in recent news where bots allegedly prompt humans into self-harm after humans prompt them for advice. Separately, I have also been exploring approaches to capture 3 dimensional holograms called Gaussian Splats. Gaussian Splat synthesis does not use neural network stable diffusion. The two approaches seem metaphorically similar though. One is generative, one subtractive. One helps you see the real world with greater clarity, the other can be used to create fictional images. So I've been thinking about this boundary of truth enhancing and truth abstracting. My views aren't so much about the software approaches themselves, but rather what people can and ten...

A couple of years ago I was studying the technique of capturing Gaussian Splats (3D holographs) with a group based out of England. We used the software from the Google spinoff Niantic Labs to stitch thousands of photos together in a technique called photogrammetry. The compelling thing about creating captures of Gaussian Splats is that, unlike a “mesh” or point cloud 3D capture, every point in space captured in a Gaussian Splat can have multiple hues to each voxel. (Voxels are the word for pixels in 3D space contrasted to 2D surfaces.) So as you move through the hologram, every point in space around you can have different colors that change as light reflects or refracts differently through each captured point in the space. The benefit of this is that the holographs look volumetrically real like the holodeck concept from Star Trek. Around that time I was discussing Gaussian Splats with my friend Ben, who also is from the UK coincidentally. He had worked in light-field capture with Lytr...