u/Asleep-Pilot-4142

Recent recursive-agent papers contain a useful definition problem: identifying exactly what is doing the improving.

The AQuA architecture keeps the underlying language model and evaluator fixed. Evaluated evidence accumulates in a local research state and changes which proposals come next. Its two research systems are separate as well, with no shared agents, memories, candidate spaces, outputs, or research state.

This is a systems-level feedback mechanism, not a claim that the model updates its own weights. Calling both mechanisms “self-improvement” may be reasonable, but they imply very different evaluation standards.

Is retained evidence enough to call a fixed-model process self-improving, or should that term require a change to the model or evaluator?

Walked past today and one of the staff handed me this sticker sheet. We chatted for a bit and they told me they’re opening on the 21st.

Pretty happy about this because I won’t have to go so far just to get my mango coconut anymore lol.

Partway through the day, an intraday feature divided volume so far by the day’s total volume. The denominator already included trades from later that day. The paper says an author agent described the feature as backward-looking and a reviewer agent approved it. The signal failed a clean re-split, and a manual audit exposed the problem.

AQuA’s response was to restrict the agent to a fixed registry of causal operators, which meant that full-day denominator could no longer be expressed.

The failure is ordinary enough to be useful. The description sounded causal even though the allowed operation was not. A second model could inspect the same explanation and still miss what the tool was actually permitted to compute. Taking that operation away means the reviewer no longer has to catch this specific path. There are plenty of other paths left to inspect.

The exact feature code and deployed expressions are not public, so an independent reader cannot audit this example end to end.

For agent systems, which failure classes should reviewers catch, and which are important enough to remove from the tool interface entirely?

Curious what people who run things locally make of this one, because the caveat is doing most of the work.

One prompt to an open model on a single desktop machine, and back comes a finished front end with gauges, a temperature bar and sparkline charts. The prompt is legible on screen and it asks for placeholder data, so none of those readings are real. It's a UI, not a monitor. The clip is about forty seconds.

The other half is who did the work. The builds people actually download, and the patch that gets a local runner to load the thing at all, came from strangers rather than from the lab. Ling 3.0 Flash went out under MIT, and every one of those community pieces carries the same tag.

The design is finished and the numbers behind it are invented. So is that the ordering now, presentation layer first and the reasoning a long way behind? Or is that just what short demos select for?

Most of these releases ship a bespoke community licence with a revenue cap or a usage carve-out, and everyone still calls the result open source. Ling-3.0-flash went up on Aug 4 under plain MIT. OSI listed, no cap, no field-of-use clause.

The weights are 124B total with 5.1B active, and there's a free tier on OpenRouter this week, so the access story is real rather than theoretical.

I'd take a mediocre model under MIT over a good one under a licence written by a lawyer who wanted an escape hatch. Curious whether anyone here disagrees.

Repos for anyone checking: inclusionAI/Ling-3.0-flash and inclusionAI/Ling-3.0-flash-fp8 on Hugging Face, both mirrored on ModelScope. inclusionAI is Ant Group's lab, the Alipay company.

Cheapest executor-shaped model we've had open weighted, if their numbers hold up. Ant Group's inclusionAI put it out Aug 4 under MIT, repos are inclusionAI/Ling-3.0-flash and inclusionAI/Ling-3.0-flash-fp8. 124B total, 5.1B active, 256K context. Their reported figures, not mine: SWE-bench Pro 56.6, AIME 2026 93.2. SGLang and vLLM forks only, no GGUF.

Anyone swapped their executor node to a 5B-active model and kept tool calls stable over a long session?

Ling-3.0-flash showed up on OpenRouter late last month, from inclusionAI, which is Ant Group's model lab.

124B total parameters, 5.1B active per token. That's roughly 24:1 sparsity, which is aggressive even next to the other MoE releases this year.

The free window closes today, August 3, per their launch announcement, so most of the reaction is going to stop at the price tag and then at the line about an open-source release coming.

The ratio is what I keep going back to. 5.1B active is small enough that time-to-first-token comes in under 100ms, and it still carries a 256K context. Routing that sparse usually costs you something, and from what the lab says about its own model, rare world knowledge is exactly where it thins out.

Curious where people think the ceiling on that ratio actually is before quality falls off a cliff.

I picked up a matte black LEVEL8 check-in case a couple of weeks ago for a trip next month—just wanted something plain with no massive logos.

Then I was watching that post-tournament clip of Michael Olise at the airport with his colorful LV bag, and I looked down at the suitcase underneath it. Held my phone up to the case in my room and realized it’s literally the exact same one.

I didn't buy it because of him, but I’m not gonna lie, seeing a top player rolling the same quiet black box makes me feel 10x better about my purchase.

Has anyone else ever accidentally matched gear with a pro athlete, or am I overhyping a black plastic box?

Pata hai aaj kya hua ,I just checked latest video from beebom and felt seriously disappointed in this. Like marriage was already becoming plaything lately with hearing these many news and now this?! seriously like they are making a way of "safely" cheat in your marriage? Even if its about choices of women and other things if anyone wanna argue or state a point. But this is feeling disgusting and disappointing to me rn. I know earning is important too...but making paths for such things is nowhere near a good thing...this will only gonna hurt people's life and my hope for a good marriage is getting dimmer with each news and each dramas.

For some info: Gleeden is an app about extramartial affairs made by women in 2009 in france, have free acc for women but charges men with like 1800-2k money if they makes acc. It always saves any payment under the name of google instead of gleeden, has secured privacy too.

It did had this argument but they tried to silence ppl with actual reasons about infedality, maritial issues and some needs related. Yet communities are still in argument if this app is ass or grass

Summary : a controversial app ensuring extramarital affair in "safe" way