I wanted a version of Tetris that had a logarithmic board instead of a square grid. I couldn’t get the idea out of my head, so I turned to AI.
Read moreTrust can be found between individuals, within organizations, and between an individual and an institution. When we consider the concept of trust, we might think about people we trust to be vulnerable around when we are going through a difficult time in our lives. We might think about the trust that we have with the institutions in our lives, such as trusting that we will be able to access medical care when it is needed. As of 2023, Generative AI was trusted more than any institution – which includes church, Congress, the military, businesses, and schools.
Read moreI’m no stranger to being a contrarian – so when ChatGPT exploded onto the scene a few years back, I resisted the urge to start using it for everything and instead decided to go as long as possible without. At the one year mark, I wrote about how my non-use of ChatGPT was going. The TL;DR – the ethical concerns related to large-scale, hosted LLMs around copyright, labor in training, climate, and monopolization/market capture led
Read moreOn the list of “things that annoy me about AI”, trying to upsell AI features as part of a service is close to the top. I’ve recently noticed that my LinkedIn feed has been shoving an AI icon and related “coaching prompts” into my feed, and my solution of hiding every post that had the icons on them wasn’t actually filtering the system the way that I wanted. Today I spent a few minutes learning
Read moreAs an autistic and queer individual, the role that technology plays in identifying, surveilling, and categorizing acceptable behavior within society is not lost on me. Despite using machine learning technology since 2014, I have used ChatGPT one time. The challenge that has come from not using OpenAI products and ChatGPT has actually been in the way that it impacts my relationship with people more than anything else.
Read moreOne decision that many organizations may be making right now is how to develop a corporate policy about artificial intelligence. Could, perhaps, an eigenvalue be calculated against a matrix of perspectives within an organization, to represent a new form of communicating the nuance and fluid nature of these complex, multi-cellular entities in which we house business endeavors? To evaluate this idea, I took a small (9 person) survey of team members and asked them to share their perspectives on AI innovation.
Read moreAs I’m writing this, I’m wearing a green t-shirt with a giant eyeball over my rapidly growing stomach. It’s Halloween, and I’ve decided to dress up as Mike Wazowski – it feels like I’m all stomach these days, so it felt appropriate. My partner dressed up as Boo. Halloween is an especially interesting time of year to reflect on identity and persona: it’s a holiday that encourages people to step into a different character and
Read moreI joke sometimes that my entire career to date has been about Learning How to Human – that I was drawn to social VR and metaverse platforms because my neurodivergent self wanted to experience a taste of a world that I could both understand, navigate, and flourish within. As it turns out, there’s a ton of overlap in the product domains of AI and metaverse, because while the core enabling technologies and their interaction modes look quite different from one another, the entire premise of the advancements and opportunities are grounded in emergent behaviors of computers simulating people and reality.
Read moreI can understand the appeal of language models. Language – the act and structure of communicating the cognitive processes I undergo on a day to day basis – is observable, whereas memory is not.Over the past several months, I’ve been working through the development of an architecture that may someday allow me to digitize my memory in a more complete way on the glass whiteboard in my office.
Read moreBecause foundation models are used to build many other models that are trained to new, more specific tasks, it can be hard to evaluate models consistently. The one-model-many-models paradigm attempts to study interpretability of foundation models by looking for similarities and differences across the foundation model and its downstream models to try and understand which behaviors were likely emergent from the foundation model itself, and which come from the derivative models.
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