> Their emphasis on bespoke modelling over generalized megaliths will pay off.
Isn't the entire deal with LLMs that they are trained as megaliths? How can bespoke modelling overcome the treasure trove of knowledge that megaliths can generically bring in, even in bespoke scenarios?
ChatGPT is already a small agent that receives your message and decides which agent needs to respond. Within those, agents can have sub agents (like when it does research).
When generating images most services will have a small agent that rewrites your request and hands it off to the generative image model.
So from the treasure trove point of view, optimized agents have their place. From companies building pipelines, they also have their place.
> ChatGPT is already a small agent that receives your message and decides which agent needs to respond.
Right, but this was done to value-optimize the product, i.e. try to always give you the shittiest (cheapest) model you can bear, because otherwise people would always choose the smartest (most expensive) model for any query.
Taking away the model choice from the user introduces a lot of ways to cut down costs, but one thing it does not do is make the product give users better/more reliable answers.
> Isn't the entire deal with LLMs that they are trained as megaliths? How can bespoke modelling overcome the treasure trove of knowledge that megaliths can generically bring in, even in bespoke scenarios?
Think of it as a base model (the megalith) which then has the weights adjusted towards a specific use-case (SAP, for example).
Didnt quite get this - if the only value prop is getting updates straight from the source (trusted/vetted journalists), what use is AI here, except for summaries perhaps?
AI isn't really the draw, it's more of a tool that helps on the backend.
That said, it's both combining various updates into a cohesive timeline of a story, writing the summaries, and assigning it an urgency level which helps in sorting and some other tasks.
Google Translate has been doing this forever and people in countries like Turkiye have been using it for a while. The usecase you're talking about is not exactly an LLM use case tbh.
And yet people are using it for that, even if it's not rational. I use ChatGPT for some things that would be easier and better to do with other tools out of habit.
The article underplays the role stablecoins are going to play in the next 10 years. Compared to 6+ intermediaries in a standard SWIFT payment, a cross-border payment facilitated by USDC/USDT just needs 2 players - an on-ramp provider and an off-ramp provider. The result ⇒ insanely low costs, much lesser than 1-5% typically charged by a SWIFT payment.
This network is sustainable and running on established blockchains which have been running for over a decade now - ETH.
This network somehow needs to penetrate domestically too - something like a UPI. That moment is going to be a watershed moment that should break this duopoly.
PS: Its a separate matter altogether that Visa/Mastercard are trying to gel well into this new age infrastructure
> Compared to 6+ intermediaries in a standard SWIFT payment
Huh? I think the message format in ISO20022 can only 3 intermediaries before having to resort to more complex mechanisms. Most SWIFT payments have 0 or 1 intermediaries.
Nothing any technology does wasn't NOT possible before that tech went mainstream. The point being tech saves time/cost and boosts productivity. For e.g. if you would have been able to find a webpage in an hour before, search made it easier to find that webpage. Similarly, AI synthesizes webpages and information for you.
That is the point of technology. If you could reach from point A to point B, using a bicycle, car, train or an aeroplane, each has its own use case at its own value and price point. Each such tech saves time/cost. To say that is is only a different modality, fails to capture the value add.
Yes without a search engine it’s a very real possibility that I could not find a web. Without a phone I couldn’t reach a person faster than I could physically move in space. Without a space rocket, I couldn’t escape earth’s gravity. Without AI I couldn’t… I don’t know how to finish this sentence without having it be self referential. As in “without AI I couldn’t have used AI to do this”. What can it be?
How will this scale for Product folks? Unlike Engg. and Design, there is very little product guys can do to showcase their work/projects (except for a go-live feature blog). How about Sales guys and other similar functions?
How do you intend to bring liquidity to this? In India, if you buy USDT/USDC, the bid-ask spreads are calamitous - to the tune of 5-6% per side. So going on-ramp and off-ramp is quite costly!
> Did you know that the number of dollars doubles every decade on average? And the effect that has on the value of each dollar (it halves it).
But so do pretty much all developed world currencies isn't it? And relatively speaking dollar has pretty much increased or remained stable against other currencies including EUR, GBP over the last decade or so.
Isn't the entire deal with LLMs that they are trained as megaliths? How can bespoke modelling overcome the treasure trove of knowledge that megaliths can generically bring in, even in bespoke scenarios?