> For an LLM, words are the source, and any meaning is just a byproduct that falls out by accident.
Recently, I've been thinking a lot about context and whether an LLM actually creates a true representation of a concept within its vectors. And for our current usage of LLMs, does it even matter? As models become so large, will the difference even be perceivable to us?
If OpenAI and Anthropic eventually become public companies with trillion-dollar valuations, it will be interesting to see if their company ethos remains the same. With that much purchasing power, it's very tempting to gobble up competitors and raise prices.
The Flash era was the most fun I ever had as a developer. Flash was so ahead of its time, and it still feels like we're slowly crawling back after 20 years. Tools like Rive are helping us get closer, but there was something special about the Flash timeline and drawing tools that made it very approachable and fun to work with.
Director was such a fun app for creating CD-ROM content back in the day! I still have fond memories of learning the Lingo scripting language inside Director to make interactive "multimedia" apps, then uploading them to the web and playing them in the browser using the Shockwave Player. It felt like magic at the time.
I recall thinking about this recently when watching a Netflix series. I'm far from a TV/film production connoisseur, but there's something about the aesthetic that makes it stand out. I wouldn't say it's better or worse, just different. With most things related to design, I'm sure the trends will shift over time as a means of differentiation. Perhaps, once AI video generation becomes more standard, we'll see entirely new production styles.
I agree with this point. One can view this is as an extension of the current trend towards platform/infrastructure outsourcing. If AI and ML are deemed essential to future apps, we should be just as comfortable consuming it via a PaaS as we are with leveraging other parts of a cloud infrastructure.
A valid concern, as pointed out, is when the large platform providers begin moving into domain-specific markets, leveraging their scale and closing out start-ups/small business. However, I believe nimbler startups will always be able to carve out a successful niche as long as they are closer to the customers.
Recently, I've been thinking a lot about context and whether an LLM actually creates a true representation of a concept within its vectors. And for our current usage of LLMs, does it even matter? As models become so large, will the difference even be perceivable to us?