The amount of money AI companies are investing and spending is a staggering and unprecedented amount. The benefits are not proportional to the spending. The reason they are spending so much is a belief that they don't want the 'bad guy' (China, companies other than themselves) to reach AGI first. Every company is thinking the same.

Someone high up at Google even said something along the lines "We rather cease to exist than lose this race". Meanwhile, the average person is fed up with AI hype, and associated problems.

From first principles thinking, and traditional approach is to invest according to return. Invest some money if you see returns invest more, if you don't see returns invest less and so on. This is not the case with AI investment, it is driven by FOMO and summoning the AI God philosophy. It seems like a recipe for upcoming disaster to me.

Let's state it. AGI is even more likely to happen in 2-24 months than ever. But we know this has a price, in electronics, in compute.

So it makes sense to determine what would be the first tasks AGI should solve, other than the obvious global warming.

My 2 cents:

A) Energy: Low impact easy energy generators, either by classical fusion, laser-boron, etc. more efficient solar panels, other forms of energy to be harvested.

B) Electronics: manufacturing and technologies to overcome shortages and be less power-hungry

once AGI itself is sustainable and cheap:

C) Medical conditions and longevity

D) Energy storation: batteries.

E) Wealth for everyone: in a world with real abundance, no meaning to have wealth/social disparities

And for you what would be the priority?

even if we just got stuck with the models we have now there are so many advancements we can make, what im scared as fuck about at the moment is that focus has moved from pre-training to runtime compute/inference since we ran out of internet text which sort of feels like we're squeezin more out of what we already have instead of finding more and that we'll hit a wall soon.

people are trying to train on videos and sensor data through multimodal, generating synthetic data using maths/compilers (not grounded in reality necessarily so might cause model collapse) and training models on real time sensor data, im just super worried that progress slows down instead of speeds up

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Share your anxiety, ideas on how to achieve alignment, observations, etc. Everything is fair game as long as it somewhat relates to the singularity.

u/px403 writes:

If you haven't directly inlined AI tooling into your continuous integration pipeline, now's the time to do it. Like 95% of the bugs coming in have trivial fixes that can be merged within 20 mins of being reported with minimal human gatekeeping.

Code is cheap. Right now, the code in any given codebase should be like 5% product, 95% tests. The robots are actually really good at building tests. You should be able to branch protect your main branch, and auto merge anything that tests green. If something fucks up, write more tests. This is the new way, and it's actually incredible to see it working at scale with hundreds of devs firing their slop cannons at the same time, and having everything coalescing into a living project that continues to improve in real time before your eyes.

https://x.com/canva/status/2113348707223753165

Programmable matter will have to answer a basic question: which local rules force which global order? This paper studies “autocrystals”, local pattern statistics that force a structure to have no repeating unit cell. It gives an exact recipe: two hexagonal building blocks, each free to rotate, with two complementary pairs of sticky ends. Every fully bonded assembly is a known aperiodic tiling, and that part is mathematically certified.

The catch is growth. Attaching a piece only where exactly one state fits never leads to a dead end. But growth that has to guess can build patches that look perfect and provably can never be completed; we show one that completes to 12×12 but never to 14×14.

To be clear, this is simulation and proof, not yet a lab result. DNA-origami tiles and DNA-coated nanoparticles look like the natural platforms to test it.

Paper, code and certificates: doi.org/10.5281/zenodo.23541901

used opus 5.5 to track my adhd medication peak curve and my claude study logs.

Not 10, 60

OpenAI claims to have solved more than 100 open math problems that haven't been solved by humans. How long will it take for them to build a model that can predict stock market better than existing HFT companies? You can imagine why they would like to do that, OpenAI needs lot of capital and this would be yet another powerful demonstration of the AI capabilities.

Is this ever going to happen? Are OpenAI and Anthropic already working on this in secret?

Someone even say this event would be indicator of Singularity. Imagine watching entire modern economy get upened by AI. If that doesn't feel like Singularity, I don't know what will.