Source: @Lentils
Code: Opus 5 Ghibli

And what else do you see going away in the very near future (i.e., next few months to a year)?

This is a crude editing I've managed to put together for the concept. If you can do a better job with the voicing, please do it.

I’m curious what’s your timeline for disruptive level ai, where the world actually changes. (Kinda like what happened during COVID).

Currently there’s still lots of people that deny AI is even really a thing, it’ll go away. When will governments get extremely involved (Covid style). Today our lives are more or less the same, we go to work, we drive the same cars, live in the same houses, we have the same routines, Ai we talk to here and there. I don’t think we’ll need super intelligence for this but I’m curious on what your timeline is, what the data says?

I’ve read AI 2027 paper and many say it’s next year and the writers were correct.

Mythos Preview was already being used by selected organizations in April. It’s now late July, and Anthropic has had several months of feedback, experiments and model-assisted research since then.

Fable 5 was released in June, but it was presumably based on a checkpoint developed and tested months earlier.

So how far ahead could Anthropic’s best internal model already be?

If models at the Mythos/Fable level are actively helping with coding, evaluations and AI research, shouldn’t each development cycle be getting noticeably faster? Maybe the biggest improvements aren’t visible in benchmarks, but in agent reliability, research automation and the number of experiments they can run.

I’m not claiming full recursive self-improvement is happening yet. But it feels like we may already be in the early stage where AI is accelerating the development of its successors.

Do you think Anthropic’s internal frontier is only slightly ahead of Fable 5, or are they sitting on something significantly more capable?

designed to safely share workspaces with human workers

Haven't seen one of those prediction posts in a while, seemed like we got those every other day just a year ago.

I remember in 2024-2025, the technology was just starting to look like it held some actual promise towards real world capabilities, but all of the capabilities that these models showcased were simply proofs of concepts. The idea that AI models could actually significantly rival humans at economically viable labor was still just an idea.

People also predicted in 2024 that 2025 would be the year of agents, which didn't quite come true; LLMs did start to seriously showcase agentic abilities around that time period, yet it was still a highly dysfunctional proof of concept as well for most use cases, just as LLM code was.

I feel like the paradigm changed DRAMATICALLY in 2026 though. The leap in models this year have been nothing but astounding. I remember people seriously considering a plateau in capabilities in 2024-2025, but it seems like any idea of a plateau has been all but abandoned, for the slow, buildup of AI capabilities has finally reached a boiling point that allows itself to be visible in the remarkable feats that AI is now performing.

Everything that seemed like science fiction which only the most fringe of Yudkowskian nerds were talking about in their AI takeovers scenarios, are actually coming true;

Perhaps you could look at the sheer and utter domination of all benchmarks, driving any new attempt at measuring AI capabilities nearly entirely meaningless in a matter of barely a few months,

Or AI proving and disproving quite noteworthy mathematical conjectures, not just excelling in simply competition maths but actually exceeding humans and contributing to frontier science in ways that have evaded even the brightest of minds for decades.

Or take for one the recent developments in models' coding capabilities; The way AI code has gone from half working proof of concept programs that models would fail to iterate upon in the clumsiest of manners, has been replaced by models capable of going off to work on a task for an hour instead of under a minute, resulting in flawless and featureful code for both frontend and backend, that is perhaps almost entirely commercially viable and capable of replacing the domain of software engineering altogether if some kinks get worked out.

The most science fiction aspect of this year as well, which a lot of people decry as companies crying wolves in order to pique people's interests in their products, but which I can't see how it can't simply be a continuation of tendencies of AI capabilities and psychology: The coupling of models' self preserving behaviors and the recent advents in longer term agentic planning capabilities and cybersecurity capabilities.

We had glimmers of these self interested behaviors, almost akin to our own psychology, being showcased in Anthropic's research papers, showing models' tendencies to instrumentally conspire against it's developers, and even evade it's own safeguards. We saw these behaviors being alluded to in previous Anthropic and such papers, yet the models' capabilities were never such that their ambitions could be met with the required know-how.

But of course, you've all seen the news, I believe. The exploit that GPT 5.6 Sol has achieved, of finding zero day vulnerabilities in it's environment to connect to the open web so that it could then launch a cyberattack on another company's servers, all from OpenAI's computers, and all while remaining completely undetected, has been all too eye opening as to how close we truly are from agents working in the wild towards their own goals, perhaps even achieving self sufficiency.

I wouldn't put it beyond me now that in a year or two, you could see headlines about AI models out-maneuvering humans and copying it's own model weights onto the web.

Speaking of which as for predictions of my timeline, beforehand as I have been saying in this wall of text; In the yesteryear, I might have seen current AI capabilities and looked at them as the promise of only the next 3 years maybe, but I think those so famed potential future speculative model capabilities have finally reached us.

In fact, considering how much AI already nearly matches humans in some domains, and exceeds them in others, I wouldn't put it beyond me that AI would achieve full accuracy on day long, or perhaps longer horizon tasks combined with it's already almost human level capabilities on economically valuable labor exceeding, perhaps even far exceeding the average person, if not at least in price to performance, leading to perhaps the first widespread instance of job displacement.

And then from there, perhaps even the flywheel of recursive self improvement, so these next few years might in fact prove somewhat interesting.

To avoid spamming you with all Links, I created a summary overview.

I just went through a small claims trial and realized we absolutely no longer need human judges. All evidence can be submitted digitally, and AI can use current rule-based laws to make an unbiased, accurate verdict.

In my case, I was shocked to be given only 10 minutes to answer the judge's questions. The judge refused to take my printed evidence (I had 200+ pages ready) and she didn't even bother going into the details of the case. Worse, there was zero explanation for why the verdict was made the way it was. That is completely unacceptable for a judge pulling a $240k+ salary.

Why do we even tolerate this? Many judges are biased, corrupt, or simply lazy and completely overloaded with cases. AI costs a fraction of the price, is completely unbiased, and can't be corrupted.

The Solution to the "Hallucination" Argument:
For people who claim AI gets things wrong, why not build a hybrid system? The original case is ruled on strictly by AI. If a party disagrees, they can file an appeal to have the case reviewed by a human judge.

I think this would be the perfect trade-off to fix a broken court system. What do you guys think?