All the same they choose to highlight basic prose (and internal knowledge, for that matter) in their marketing material.
They’ve achieved a lot to make recent models more reliable as a building block & more capable of things like math, but for LLMs, saturating prose is to a degree equivalent to saturating usefulness.
On the whole GPT-4 to GPT-5 is clearly the smallest increase in lucidity/intelligence. They had pre-training figured out much better than post-training at that point though (“as an AI model” was a problem of their own making).
I imagine the GPT-4 base model might hold up pretty well on output quality if you’d post-train it with today’s data & techniques (without the architectural changes of 4o/5). Context size & price/performance maybe another story though
This is no different from a web app though, there’s no obvious need to reinvent the wheel. We know how to do this very very well: the underlying TCP connection remains active, we multiplex requests, and cookies bridge the gap for multi-request context. Every language has great client & server support for that.
Instead we ended up with a protocol that fights with load balancers and can in most cases not just be chucked into say an existing Express/FastAPI app.
That makes everything harder (& cynically, it creates room for providers like Cloudflare to create black box tooling & advertise it as _the_ way to deploy a remote MCP server)
I think some of the advanced features around sampling from the calling LLM could theoretically benefit from a bidirectional stream.
In practice, nobody uses those parts of the protocol (it was overdesigned and hardly any clients support it). The key thing MCP brings right now is a standardized way to discover & invoke tools. This would’ve worked equally well as a plain HTTP-based protocol (certainly for a v1) and it’d have made it 10x easier to implement.
MCP should just have been stateless HTTP to begin with. There is no good reason for almost any of the servers I have seen to be stateful at the request/session level —- either the server carries the state globally or it works fine with a session identifier of some sort.
Their patchy JSON schema support for tool calls & structured generation is also very annoying… things like unions that you’d think are table stakes (and in fact work fine with both OpenAI and Anthropic) get rejected & you have to go reengineer your entire setup to accommodate it.
Funnily enough I recently noticed that the X app on iOS started doing this for me… on ads. If I place my finger on an ad while scrolling down, without fault it opens the ad overlay sheet. I guess that’s one way to increase CPC revenue
To be fair, in my experience ticket checking in Luxembourg was (at least in the city buses) so incredibly lax already that not a lot of revenue will be lost by this. All the same it's a nice policy though.
I think that this is at least partially attributable to the average understanding of English in those countries. When you are watching a movie with subtitles, but have absolutely no idea what is being said in the movie because the spoken language is unknown to you, it can be very distracting, because you are missing a certain amount of context. I believe an above-average amount of Dutch people is at least capable of comprehending basic English speech, which puts the movie's subtitles into context. In countries where English isn't as wide-spread, this is more problematic, which is why dubbing is more effective there. Similarly, even in the Netherlands movies which target family audiences are often shown dubbed by default in movie theatres, because the subtitles are just not as effective even if the children that are watching the movie can read them.
While that may be true, it most certainly hasn't happened in the last 3 years. Maybe over time people will stop valuing Jobs' work higher than that of Ritchie and McCarthy, but I think it is likely to stay like this for the forseeable future, just as it has been for quite a while.
And every single time I see an article about Jobs accompanied by a set of comments from a tech-savvy audience I see this same comment about Ritchie (and sometimes McCarthy) resurfacing. You can continue feeling sour about it, but not everyone deserving attention receives as much as they should, and not everyone receiving attention deserves it as much as they get.
Ritchie's and McCarthy's personalities and accomplishments just aren't as interesting to the general public as Jobs', which has little to do with our definition of success but more with the fact that, to be able to obsess over someone, we need them and their work to speak to our imagination, which is a lot harder when their accomplishments are less trivial to understand without any knowledge on their field of study.
It could also mean they are going the Cloud 9 route (unlimited free public editing, limited free private projects) for the web version, which would essentialy be the same as their current subscription model, while still open-sourcing the editor itself.
This seems like a legitimate use case for an FPGA in every PC. Implement a set of expensive algorithms in Verilog, put it up on Github and set up some slick distribution mechanism that updates the logic when needed without bothering non-technical users with it. This would prevent the crypto from using up too much general purpose processing resources, cause it to be acceptably fast and provide a mechanism for updating the algorithms when flaws are found or new algorithms are introduced.
Downside is that it would probably take up to a decade to actually be adopted by the majority of PC users, but then again, the majority of PC users will probably not care too much.
While Go doesn't directly generate any revenue, it's probably not without reason that Google is rewriting some important pieces (dl.google.com for example) in Go. I can imagine their engineers being much more expressive in Go than in C++, causing them to spend less time on writing the code as well as resulting in simpler code (easier to comprehend and maintain, so less time/money spent on maintenance). This doesn't generate revenue but it does optimize development processes, which could indirectly save them some money.
They’ve achieved a lot to make recent models more reliable as a building block & more capable of things like math, but for LLMs, saturating prose is to a degree equivalent to saturating usefulness.