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Creating LLM apps from components

I have a colleague who is trying to study her mother's native language (she is second generation non-resident Taiwanese) and wants to have a tool for transliterating her parents' dialog into English with learning highlights for study as flash cards. This is beyond what Duolingo, Apple Translate and Google Translate were designed to do. It seemed this could be built using several existing tools. We could ask Duolingo, Apple or Google to build it for us. But our use case here might be too niche to make sense to the general population of language learners who use those other tools.  Right now she uses a recorder, then ends one step in the process. Then she would look up different words in a dictionary phonetically to find the Chinese character she was hoping to learn. Then she saves those words in a list and practices those terms in her own context. I’ve done this too. I also study Chinese characters for fun. (Han characters, called 漢字 (Kanji) in Japanese, are foundational concept...
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Google is moulting

I have worked with multiple search engine companies through the last three decades. It was what my generation’s task was after the personal computer boom that was defined by the work of my father’s generation. (He was a systems engineer for IBM through the transition from “Big Iron” mainframe computers to desktop computers.) So over the years I’ve seen some fascinating technology advancements in how we author the web as web content creators, how we index it and serve it via search engines, and how we scale accessibility for original creative content bringing new audiences to it through web portals, apps and content aggregation tools.  Recently, I’ve been seeing a transition portended over a decade ago in a panel discussion about new advancements in spam filtering and search engine optimization. The panel featured the legendary Matt Cutts from Google who was their “head of web spam”. In that decade, anchor-text ranking that had defined the early “Page Rank” sorting on the sear...

Vibe coding to a more frictionless future

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 ...

The Shifting Scope of Assumed Privacy with LLMs

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...

People Like Us

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...

“Novel view synthesis” fine in photos or grief bots perhaps, but not for science bots

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...