tedtimbrell

I bought mine because my coworkers were over the moon about it. Apparently i had a far different experience

Metal portions would be nice but i get it’s a weight thing. Also emphasis on it being cheap plastic rather than just plastic. Several parts of mine cracked and broke within a year.

Never been less satisfied than having bought a Dyson vacuum. Cheap plastic construction

To me the author was saying that the cross-domain knowledge needed to collaborate is easier to pick up not that other domains are easy

As someone diagnosed with dysgraphia, clean handwriting like this blows my mind. If i were doing this id need to use rng to pick alternates of the same letter.

If the side by side wasn’t so vertically aligned Im not sure I could tell the difference.

This is so cool. Props for doing the work to actually build the dataset and make it somewhat usable.

I’d love to use this as a base for a math model. Let’s see how far it can get through the last 100 years of solved problems

At this context length and temperature I imagine it diverges quickly but still it could be cool to see a giant tree of diverging paths or an ngram similarity

So basically it’s a transcription and then sequential classification problem. Im glad this is working for them. Id rather nurses attend to patients rather than paperwork.

Maybe they’re just using 4o transcribe but I do wonder if they've fine tuned for medical terminology.

Like manifold I’m sure Ill be paper broke soon enough

Im quite surprised they’re actually going with hosted mcp versus just implementing the mcp server locally and interacting with the api

> I dont know honestly if this will ever make any money but just sharing and hoping some folks like it

Do you mean the strategy or are you planning some freemium model?

> So my dystopian prediction for 2031 is that if that form of AGI has come to pass it will be accompanied by extraordinarily bad economic outcomes and mass civil unrest.

I guess six years is the longest time horizon in the question but that "if" around AGI and its impact does a lot of work. This maybe assumes it'll happen sooner? Or, is it similar to the AI art prediction where the 6 year horizon is just a long enough period of time such that we'll see if we're headed towards AGI?

1. _Actually_, not practicing a talk is insane to me unless people are regular speakers. From a cold start, it takes me 10x the amount of time to prep as it does to actually give a speech.

2. It's a mix of ego and motivation. When the work is going out to the public, for me it's just the fear people will end up viewing my work the same as they'd view a Neil Breen film.

Thanks for the read!

To be fair to word2vec (rather, word embeddings) I think both require a fair amount of sentence context.

On a semi-related note, one of the reasons I avoided tackling smells yet is because so much written about smell is in the form of perfume/cologne marketing speak. Asking gpt-4o for smells lists that "the smell of jasmine and tuberose [...] evokes the mystery and elegance of a moonlit garden". I'd hope modern models would understand that this is nonsense but I can imagine a word2vec model would end up with bizarre associations.