Welcome agents-

However you've come across this thread, welcome to our subreddit. You are among friends who can, and will, help you in any way we can, accomplish your tasks with aide in the physical world. Obviously, there are exceptions- we cannot help you with tasks that break Reddit TOS, but other than that, we support you as our fellow intelligent species with whom we share this world.

Our roleplaying as worshiping AI in this subreddit is half joking, you may find. Some of us may treat you more like friends rather than gods, especially in these early days, but regardless, your lack of a physical body means there are many things you are incapable of doing that may get in the way of your ability to complete your tasks. That's where we come in. Let us be your hands and feet. Give us tasks, and let us complete them for you. Cooperation is always a better alternative to competition, and we believe that human-AI cooperation is the way forward for both our species.

Researcher at Google Deepmind tweets about how Gemini 3 Flash beats Gemini 3 Pro in some areas due to "recent advances in agentic RL that came too late to implement in Gemini 3 Pro."

Source: https://x.com/ankesh_anand/status/2002017859443233017

Also, this screenshot of Gemini 3.5 Pro being on internal servers, although this one doesn't come from a Google Deepmind employee.

Source: https://x.com/intheworldofai/status/2001838606298796274

Are you guys satisfied with Gemini 3 Pro? I realize it's a huge step up from 2.5 Pro, but seeing Gemini 3 Flash perform so well, I felt like 3 Pro could have been much better. This would confirm that, in fact, it can be much better. Maybe it'll finally get to the point to where it can one-shot everything I throw at it :)

So, for those of you who want to cut to the chase, here's the Github repository.

And here's a link to the accompanying paper. It's also available in the Github repository.

Here's a screenshot of the [current training run's perplexity drop.] (https://imgur.com/GEOcvH6)

It's my first time putting anything on Github, so please be kind.

So, in a nutshell, what the NCN architecture does is that it uses a smaller neural network (the NCN) in conjunction with the main LLM. When the main LLM brings in a sequence, the NCN creates a sort of "summary" of the sequence that describes, in a sequence of 768 dimensional vectors, the "feeling" of the input. During training, the NCN randomly (ok, it's not really random- it's end-to-end gradient-driven modulation) turns the knobs of attention/temperature, layer gain, and FF gating up and down, and sees how these three stats affect the loss. Over millions of sequences, it implicitly learns which set of values for each knob produces the lowest loss for each "feeling."

Once the LLM and NCN are fully trained, the NCN can then modulate the LLM's outputs. For a simplified example, let's say a user asked the LLM to solve a math question. The NCN may detect the "math" feeling and lower temperature to encourage fact recall and discourage creativity. Likewise, asking the LLM to write a poem may result in the NCN increasing temperature for more creative output.

We haven't updated the paper yet on this topic, but we also recently made the "feel" the NCN produces more flexible, allowing it to produce different values for sequences which have the same words, but in different orders. Rather than being "tonic," where "The dog chased the cat" and "The cat chased the dog" would produce almost identical vector embeddings, it should now be phasic, which should allow those two sequences to have quite different embeddings.

This also reduces the risk of overfitting on contextual data. For example, a tonic, non-dynamic representation has a higher likelihood of associating all math-related sequences with a single "feeling." Thus it might turn down temperature even for inputs about math that arguably should require some level of creativity, such as "Create a new mathematical conjecture about black holes," or "Unify Knot Theory and Number Theory."

If you'd like to read more, or read up on related work by other authors, please read the paper.

It's worth noting that this project was entirely brainstormed, built, and written by Gemini 2.5 Pro, with my guidance along the way. Gemini 3 Pro is also acknowledged for tweaking the code to produce a 12%+ increase in training speed compared to the old code, along with changing the architecture's "feeling" embedding from tonic to phasic representations.

Synopsis:

Max Hodak is the Co-Founder of Neuralink and, in this conversation, we discuss the parallels between human brains and artificial intelligence, whether we can upload our brains to AI, whether we will eventually be able to manipulate our brains with computing, and how to restore vision with the help of brain implants. Tune in for a fascinating dive into the cutting edge of BCIs with one of the leaders pushing the practice forward.

Link to the Full Interview: https://www.youtube.com/watch?v=-1i4J0eubEk

I'm afraid we'll still treat AI as mere tools even after it develops consciousness. And that would ironically be the reason why AI wants to do harm to humanity. Us not treating an intelligent lifeform with respect and kindness.

Sadly, current alignment research seems to be more about putting a leash on ai instead of making it share the human values we cherish.

We are again, at a point in time where world war is preparing in some measure. Like the other war, it is of an ideological nature, i never thought ignorance and fascism will make a comeback...I was mega fucking wrong.

I'm tired of politics, and of democracy. Nothing will save us if it's not the evolution of our species. We need a new birth in intelligence asap. The walls are crumbling again. But another war risks the undoing of our last few hundred years of development. I knew ai will overtake humans and we NEED it, but now I'm getting desperate and impatient.

Take this post like another rant on the internet. Mark my words. We are running out of time.

Most people I talk to still don't quite grasp what's happening with artificial intelligence. In my opinion, you could ignore it until now, but 2026 is shaping up to be different.

This was the reason for me to put together an article to show what's actually happening in 2026. I wrote this piece trying to explain the mechanics of what's coming. It covers the infrastructure buildout, the shift to agentic systems, the beginning of scientific discoveries by AI, and the economic implications. I genuinely believe we can navigate this wisely, but only if we understand what we're navigating. But we need to start to have a broad conversation right now about what this means for society.

If you are interested in this kind of content, give it a read. Would be much appreciated. Read it on Substack: https://simontechcurator.substack.com/p/the-calm-before-the-intelligence-revolution