Author: Liv

Development, Machine Learning, Tech Policy

No, Llama 2 is not actually open source

While LLAMA 2 is certainly interesting, and more openly licensed than some other AI language models, it’s definitely not open source. Open source is a term that is defined by a non-profit called the Open Source Initiative. The OSI explicitly calls out that it is not sufficient for code to be open for something to be called open source. The actual definition of open source includes provisions that must be true for the licensing of the software. LLAMA 2’s “permissive” license doesn’t apply.

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Business & Leadership, Communication, Machine Learning, Philosophy, Random Thoughts

Resistance to Change is Often a Lack of Clarity

I’m on exchange at London Business School this week to study Strategic Innovation. Today, we covered a lot of ground, starting with why it is challenging for established organizations to truly innovate, as well as the individual thought patterns that challenge us in thinking “outside of the box”. And speaking of thinking outside the box, we also touched on communication (and why it’s so freaking hard to do it well). As it turns out, resistance to change is often a lack of clarity, more than it is an actual resistance to trying something new, and the ambiguity that begets creative thinking – and subsequently, innovation – often comes from a number of conflicts between alignment at an organizational and individual level.

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Communication, Machine Learning, Spatial Computing

Multidimensional Computing Accessibility in the Age of XR and AI

Today, I’m sharing the slides that I prepared for my talk at the 2023 XR Access Symposium. In building this presentation, I had a few goals – the first was to establish my own new paradigm for talking about XR and AI. I found that “multidimensional computing” encompassed both of those characteristics nicely, especially when we think through the vast amount of information that is built into each of those types of technology. Is it a bit wordy, as far as terminology goes? Absolutely, and frankly, I love it even more for that.

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Machine Learning, Random Thoughts, Tech Policy

Google Bard: OpenAI’s Exclusivity Deal with Microsoft may Violate Anti-Trust Law in US

I decided to ask both ChatGPT and Google Bard to provide three arguments about why this particular exclusivity deal was in violation with the Sherman Act.

Completely in alignment with my expectations, ChatGPT immediately announced that it was unable to answer such a question, but it happily explained some generics about the Sherman Act. Bard, on the other hand, gave a seemingly quite convincing breakdown of the reasons for and against an anti-competitive ruling.

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Development, Machine Learning

Open Source, not OpenAI

The open source movement gives me hope. It’s how I’m able to run multiple different interfaces to local language models that can be fine-tuned on my computers with my own data, and know that it’s not leaving my own environment. It’s how I can build the Firefox web browser locally, and add custom patches so that I can run experiments with my browsing history safely. It’s how I can picture re-imagined fair value exchange systems working.

The commercial software stack is collapsing, locking users into increasingly tightly controlled environments where customization is locked away, abstracted because of its complexity. This is not the way.

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Development, Machine Learning

TIL: How to Build Firefox from Source

Today, I learned how to build Firefox from source. I’ve been a Mozillian since 2019, but this is the first time that I built the browser on my own machine. My sophomore year of college, I used Visual Studio and en embedded iexplore.exe window to make a simplified browser that had bookmarks permanently placed as UI buttons. I can’t even remember if it had an address bar, but I remember feeling accomplished that my portal to the internet was uniquely mine.

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Development, Machine Learning, Spatial Computing

In the Era of Multi-Dimensional Computing, XR is the Future of Front-End; AI is the Future of Back-End

My work over the past ten+ (wtf?) years has focused on emerging technologies, primarily spatial computing and machine learning – so this moment is pretty spectacular to see. We’re entering a new age where generative AI can create infinite worlds of content as a tool to aid and augment human creativity and understanding, and with today’s announcement, we’re creeping ever-closer to advancements in spatial computing hardware that allows us to experience technology in ways that allow us to use our natural cognition to better facilitate our relationship to information.

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