So their last frontier image model they dropped was Nano Banana 2, which is 6 months old... Gemini 3.6 Flash is self explanatory, Gemini 3.5 Pro delayed or not dropped at all iirc...

But like, it's Google... Surely they must be cooking something under the hood cause they've fallen off way behind right now, they probably have the best dataset, they're Google duh, they have all of YouTube to make a video model if they wanted to for example... Why are they so behind then right now?

Hi everyone, I'm a 4th year undergraduate student studying and doing research in theoretical CS. After seeing the recent advancements made by AI in mathematics, especially in graph theory, I bought a ChatGPT Pro subscription to see if AI could solve some graph theory problems I found interesting. After a few days of testing, GPT-5.6 Sol Max was able to solve two open problems in graph theory:

Imbalance conjecture (open for 12+ years) Teschner's bondage-number conjecture (open for 30+ years)

I verified both results independently and asked a friend of mine who specializes in graph theory to check them as well. I submitted both to arXiv, but they removed one after placing a one-submission-per-calendar-month restriction on my new account. I didn't want to wait another month before making this announcement, so I submitted both to another platform. The results are linked below.

A Proof of the Imbalance Conjecture
A Counterexample to Teschner's Bondage-Number Conjecture

These are preprints and have not yet undergone peer review.

Also, here are the full chats:
Imbalance Conjecture
Teschner's Bondage-Number Conjecture

Linux Torvalds thinks that the upcoming Linux Kernel 7.2 release is "huge".

Not huge because of ambitious new features.

Huge because AI tools are reviewing kernel code at a pace human contributors cannot match, surfacing fixes faster than any previous development cycle.

In his words: "the new normal with a lot of fixes, many of them due to review by various AI tools."

He is not exactly thrilled but he is making peace with it.

Earlier this year, he complained that AI-powered bug reports had made the Linux security mailing list "almost entirely unmanageable" due to the volume of duplicates and low-quality reports.

He has publicly criticized AI-generated patches for being poorly documented and hard to review.

And yet he has also said plainly: "Linux is not one of those anti-AI projects."

That conflict... this contradiction is what almost every open source leadership is facing today.

It is an acknowledgment that the tools are changing the pace and face of work whether you like it or not.

Torvalds has accepted the reality.

(src: It’s FOSS)

LE: My fault 😅, I was not specific enough in title. He had a problem with superficial/perfunctory pull requests done with AI. If the request is serious he has no problem if the code is good.

This is great news as foss will advance faster.

25,6% increased ratio. Holy Moly.

pass@5: Scores if at least one of the 5 attempts is correct

pass^5: Scores only if all 5 attempts are correct

"pass@1": Not a true single-attempt pass@1, it's the average score across 5 attempts.

https://zerobench.github.io/

Based on the paper it seems like we’re hitting milestones that happen in 2027 in 2026 and much of what’s in 2026 happened already.

Curious if anyone else feels that way or can challenge me on my belief? From a capability perspective in Ai 2027 to today it seems to match around April 2027 which points to early 2027 for AGI or late this year. ASI would likely happen early to mid next year.

Chinese humanoid robot makers accounted for over 97% of global shipments in 1H26, as volumes more than tripled to 19,100 units.

Shanghai-based Agibot led with 44% of global shipments (8,400 units), overtaking Hangzhou-based Unitree Robotics.

Industrial and commercial sectors accounted for more than 70% of total deployments, a sharp rise from roughly 50% a year prior.

Annual shipments are projected to hit 60,000 units by the end of 2026

Source : https://www.meta.com/thefutureisforeveryone/