127.0.0.1
If the original sin of Web 1.0 was the  pop-up ad , the original sin of web 2.0 was the move to algorithmic feeds. Opaque optimization strategies aimed at maximizing private revenue for the sake of what was otherwise externally billed as public goods became increasingly toxic,
There's no shortage of analogies for explaining what an LLM is capable of - one of the best, though, is from this  New Yorker  article proclaiming it as a "blurry JPEG of the web". This metaphor is particularly useful for capturing many of the technical
Long short-term memory models (LSTMs) are a family of neural networks that are predominantly used to predict the next value given a historical chain of previous values. These can be numerical predictions (i.e. where is the stock price going based on historical stock data) or categorical predictions (i.
Recently, I gave a talk at the PIE/Autodesk space to help contextualize some thoughts that have been percolating with regards to the nascent introduction of API-based, widely available LLMs like ChatGPT. In the hype cycle, I've observed some pretty broad claims about what's happening
Over the summer, I got really interested in the  Helium network . Unlike many other crypto-backed projects, there was something at least of articulable value being provided by the project. In short, the promise of the Helium network is in building a two-sided market. On one side, there
Big news! My good friend  Tim Hwang  and I have started a company,  International Persuasion Machines (IPM) . Our company is based off several foundational principles: The history of cybersecurity is, in essence, chasing threat actors up an escalating software abstraction pyramid (e.g. as we build new
For the past year, I've been increasingly focusing on what I have come to call "sociotechnical security" - whereas "technical security" seeks to identify and remove unintended flaws in the architecture of platforms, "sociotechnical security" is all about identifying and removing the incentives
About 10 days ago, I saw a post for a ridiculously cute car of a make and model that I previously did not know existed: I knew about MGBs and how they had a fairly terrible reputation but this thing looked so slick. I started reading up on them and
@TAP_deals is a bot on Twitter that uses machine learning to extrapolate the estimated value of a plane based on historical trends from listings of all other planes on Trade-a-Plane.com. While the code underpinning the Twitter bot constantly evaluates all planes listed at Trade-a-Plane.
Large-Scale Missing Data in a Widely-Published Reddit Corpus As researchers study complex social behaviors at scale with large datasets, the validity of this computational social science depends on the integrity of the data. That’s why researchers have a duty to check the datasets rather than assume
I bought a Raspberry Pi a while back without much of a plan for what it would ultimately work on. After getting annoyed by a local traffic issue outside my house, I decided to go all in and see if I could write up a set of software that would:
Background On December 5th, the following tweet passed through my timeline: The DudeBro Tournament 2016 pic.twitter.com/z8Ei56dBKX — DudeBroWatch👮🚨 (@DudeBroTourney) December 6, 2016 Embedded JavaScript To which I replied: @NateSilver538  please run some bracketology on  @DudeBroTourney — Devin 'meat' Gaffney (@DGaff) 
When I first heard about  Amazon Lambda , I was skeptical. It was explained to me as basically "code in the cloud" and my immediate take was "why even bother putting code 'in the cloud'? Why would I take my code over to some flimsy
Building a Network of Conversation Points Over the summer, I spent the summer working with a good friend  Gilad Lotan  as a data science intern at  Betaworks . It was a good opportunity to see what people are building these days, and see if there would be any
This last week, I attended a several day seminar about combating online harassment, saw an academic friend get an  award for her book on trolling from the Association of Internet Researchers  (you should  buy it ), and I ended the week by seeing this cover from Time: There&