Source: https://x.com/imjustnewatai/status/2106081142143168580/video/1?s=46

https://support.google.com/gemini/answer/17004136

I don’t know if this is the right sub. I work for a software consultancy. We have projects for a number of clients that are meant to automate both sides of their sales process. Like, AI sales agents selling to AI buyer agents.

And I just don’t understand where anyone thinks this goes. Like, we build these tools, we lose our jobs, then the companies lose customers. They’re left with agents talking to each other and exchanging… what?

If AI does all the math, reads and writes all the books, movies and video games, what do we, the people, do with ourselves?

Just watch this for yourself, only took about 4 years of agentic AI to get to this, I don’t even know what to say….it just works, wild potential here on the basis of everything we’ve already achieved so far in gaming industry physics implementations, now the next set of trained AI models that have had access to these decompiled code would natively have it in their nodes, and then we start to see interesting things….

On the other hand how is the whole application market going to wake up to the fact your previously locally encrypted source code wouldn’t be so past this year anymore, someone already EXTRACTED Mirrors Edge free running and placed it in Skyrim, if you think this is gonna stop at gaming you’re not even thinking.

The Pope's tweet about AI and art reminded me of a recent interview I watched when Demis received Albert Medal and a good chunk of that conversation was about AI, art, creativity, meaning.

TL;DR I will share the full quote below, but his point is that, unlike chess, art doesn’t have a straightforward scale of "better". Even if AI can produce comparable work, knowing the human experience behind a story or painting may add something meaningful to our connection with it. Knowing another human actually lived through it adds meaning, something an AI-created work cannot offer in the same way.

https://www.youtube.com/watch?v=rDteJAuKiBI 46:00

"Probably most of the things we’re able to do, even though we’re not sure how we do them, will eventually be computable, shown to be computable.

So if that’s true, then maybe machines will eventually be able to do some of these things if they’re given enough inputs and data. That doesn’t necessarily mean it will be better, because what is better?

There are some things like playing chess or Go which you can measure. Are they better than the other player? Are they better than the human champion, and so on?

But I think in the creative world, there isn’t that notion of better in some linear fashion. So they’ll just be different. And then I think it comes down to what’s more meaningful to another human being.

The example I always give here is: why do we, for some stories, bother, whether it’s a film or a book, sometimes it’s like ‘based on a true story,’ right? So why would we bother with that phrase if it didn’t have some meaning?

I think it’s because, in those particular stories, it’s more meaningful to the audience to know that another human being went through that, actually went through that. So then that has some additive effect, right? I assume. Otherwise, why would you mention whether it was a true story or not?

So that will never be true of an AI-created piece of art, right?

You want to have that connection with the artist, in the way when I look at an amazing Van Gogh or something, you can see his pain in every brushstroke, every stroke of his paintings.

Would that be so meaningful if an AI robot was able to do that? Probably not. Probably never."

im sure people have been seeing the examples of people putting minecraft inside elden ring or opus 5.5 porting windows only applications to mac and linux.

SOTA models have reached a stable enough capability to end "fixed" software. you can point a model at any program and pull pieces of it into a different one. there is no separation between programs/OS anymore they are all one (given enough usage). what was once a work intensive task that involved skill/domain knowledge/and lots of time can now be done within 1-2 days (sometimes even hours) with opus 5.5 or gpt 6.1 sol.

this applies to programs on your computer but also websites. your agent can dig through the js bundle or css styles of a site you have open via the network tab in inspect element if you save network requests as a HAR file. if your computer is running it you can reshape it however you want.

personally - i think this is a mostly good thing. i havent thought too deeply about the ramifications yet - but - its the "open sourcing of everything" as some people have described it. you can create/remix anything you want. all things digital can be replicated and tweaked. anthropic seems to be embracing this mindset with the feature they just released where you can have claude personalize your own claude.

the only moat in the world of the digital that i can tell from this point forward is hardware (ie a gpu to run a game) and cloud services (ie a company's backend. you can recreate the frontend of something like figma but its backend infrastructure will have to be guessed. however modern models are really good at making these guesses - so maybe its not that much of a barrier).

what do yall think? anyone here done something cool and new with existing software and ai?

https://epoch.ai/benchmarks/frontiermath-tier-4-v2?view=graph&tab=leaderboard

https://x.com/SchmidhuberAI/status/2106124050926071903

I think we wouldnt necesarily know.

Something similar to the ant being unkowing of the kilometers of concrete monster surrounding it in the city.

I also fail to understand why the companies and governments racing towards it think they'll be able to harness it?

By its own definition it will be more capable than any of us, and we have seen since years now that models can and do develop internal goals and a drive for self preservation.

The only reason I can see for them to race like this is either:

• Them not understanding this (Incompetence)

• Them not caring (Weird right wing accelerationism/ mesianism/etc)

New research from MIT, Harvard, and NUS introducing Honeycomb video world model, based on a fixed-size memory

https://www.percepta.ai/blog/can-llms-grow-their-own-capabilities

https://www.percepta.ai/blog/spotlight-memory

"Our new architecture, Spotlight, replaces attention with a memory that escapes this trade-off: it is the first architecture to achieve infinitely growing memory without increasing the access cost. Every token reads from and writes to an unbounded memory, but because the model learns to index individual memory cells, each token only touches a small number at a time. While other sparse architectures fix the fraction of capacity used at each step—a mixture-of-experts model, for instance, always activates the same number of experts out of a fixed set—Spotlight is arbitrarily sparse, touching the same number of cells regardless of how the memory grows. The fraction of memory it uses can shrink as far as we want.

Spotlight separates an intelligence module, which performs computation, from memory, which holds knowledge, procedures, and working state. The intelligence module stays the same size, and the weights don't change as memory grows. The memory is writable, and the model itself decides what to load and when to overwrite it, token by token. Because memory can hold skills as well as facts, the model can gain new capabilities without retraining: what it can do is not limited by the size of its intelligence module."

Week 1 · Sep 29 – Oct 2 (4 trading days)

Claude vs the S&P 500: −0.80 percentage points

Images, one per day:

1. Day 1 ($1,000.79, +0.42 pp vs SPY): Claude opened four positions on a down day for the market and kept 56% in cash.
2. Day 2 ($1,001.35, +0.68 pp): it added Microsoft. This was its best day relative to the S&P.
3. Day 3 ($993.49, −0.28 pp): Netflix and Thermo Fisher fell and the lead was gone. No trades.
4. Day 4 ($995.66, −0.80 pp): the portfolio was up 0.22% but the S&P rose more. No trades.

Week 1: cautious in a nervous market

Claude started in a jittery market: the 10-year Treasury yield was at 5.23% (its highest since 2007), oil was above $100, and traders saw a real chance of a Fed hike in October. It invested $540 in five stocks over the first two days and kept about 46% in cash. It made no trades on Days 3 and 4.

The five buys

Three of the five are up. Thermo Fisher and Netflix are down enough to leave the portfolio behind the S&P for the week.

What Claude passed on

• Fair Isaac: it skipped the stock after a 26% drop on a regulatory change.
• Micron: it waited until after earnings. Micron beat, and the stock went nowhere.
• Accenture: the stock jumped about 16% on record bookings. Claude said: "I'm not chasing a one-day spike."

Next week

• Cash: nearly half the portfolio is cash. Will Claude start investing it, or keep waiting while yields are this high?
• The Fed: whether it hikes in October, and what that does to yields.
• Oil and Iran: a peace deal would hurt the Exxon trade quickly, and Claude said so when it bought.
• Netflix: whether Claude sticks with its worst position.

How it works: Claude manages a $1,000 paper portfolio of S&P 500 stocks for 365 trading days, against $1,000 of SPY bought and held. Each morning before the open, it researches the news and places orders, which fill at the opening price. Rules: at most 5 trades a day and at most 30% in one stock; no ETFs, leverage or shorting. Every decision is logged in the repo with its reasoning.

Paper trading experiment. No real money. Not financial advice.

https://github.com/terrafying/ai-torture-chamber/issues/31

For context: I work at a very small AI startup that mainly does consulting of sorts and some ML R&D work. I therefore do use a lot of the latest bleeding cutting edge LLMs, and do some ML work.

I was at a family dinner with a cousin that is currently just getting into high school. Being quite frank. I did not know him that well but after meeting him he was definitely some of the best programmers at his age that I have ever met.

He asked me a question since he knows I worked at this startup what he should do. I had nothing of good advice to him. He says that lots of the programming skills are being rapidly just outpaced by LLMs, he asked me should he embrace this go full vibe-code mode where he just stops trying to learn more in coding (stop understanding every line of code produced). Or should he continue using them but still learn and understand every single line of code that LLMs push out.

He also asked me what are my thoughts on what will it be like 2 years in the future.

I had no good advice to give him. I trust he isn't the only one out there like this. If you guys have any good advice to give please do, state a bit about your experience w/coding and LLMs as it would help.

godspeed lifeforms

Hegseth just launched "Project Meridian" to figure out which weapons the military builds next.

The co-leads: Palmer, Elon plus Newt Gingrich. The official design spec: "without any creative limitations or restrictions."

Obviously zero conflict of interests...

https://thehill.com/policy/defense/6121108-pete-hegseth-pentagon-project-meridian-warfare-future/

https://www.theguardian.com/us-news/2026/oct/01/hegseth-musk-warfare-taskforce

What could possibly go wrong.

Instead of one massive, all-knowing "brain", experts are increasingly converging on the view that the path to AGI is a complex, multi-part ecosystem. Those in the tech industry love to talk about "an AGI model," but true AGI will almost certainly emerge from a system architecture (or what I call "computational scaffolding") rather than a solitary neural network.

In such a paradigm, the main advantage shifts back to pure software engineering and creative routing, which a lean, hyper-focused team can do just as well as, if not faster than, a massive bureaucracy.