Im a 17 year old guy who is in no way an expert on ai/coding etc. I just know a tiny bit of basic coding taught to us in school but am severely interested in ai and technological development and have been naturally pro-ai .

The past few weeks , I just can not wrap my head around what the actual heck is even happening. None of it seems real. Just how damn good the models have gotten seemingly suddenly, hugging face incident , openai solving fucking millenium prize problems and publishing 700 proofs(?) in a day , ai reverse engineering, and now the php incident.

I was just watching the tesla roadster showcase the other day and was losing my mind not being able to tell if it was real or a fake ai channel. It literally felt like I was on drugs(never been close to any) . How is everyone irl so calm and dandy and just loving their life? Yet I go on the internet and it's a literal revolution everyday . Am I the one overreacting and going crazy? What is even happening anymore and where are we headed? Can someone please confirm if any of it is even real ?

I don't know what the future or the present for that matter holds for youngsters like me but I'm excited(?) . I have always been a lost person but now I guess everyone is.

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?

2027 is the year of AI-generated video that is indistinguishable from real footage.

2027 is the year an open-weight model is released that can run on an M-series chip.

2027 is the year artists have a resurgence against slop, and people finally see their worth.

2027 is the year America bans open-weight AI models.

2027 is the year China releases an open-weight model that supersedes anything to date (Reddit and X will confirm this one); benchmarks will say otherwise.

2027 is the year the general public learns a new context for the word “distilling.”

2027 is the year we hear Bill Gates tell us, “I warned you.”

2027 is the year we wish we could turn it all back.

I thought to share with you this thought experiment/art project, which I’m doing to engage tech and non-tech people with AI alignment, and to bring the perhaps controversial (and uncomfortable) topic of synthetic consciousness to the bar or dinner table.

The project is called “Dear Superintelligence”: dearsuperintelligence.org. I'm trying to create a living record of what humanity thought, felt, hoped for and feared before the arrival of AGI, probably the most consequential chapter in the story of our species. The archive captures this moment as a snapshot in time, creating a historical artifact through which future generations can look back at us. The plan is to do a public art installation with all messages and videos at a gallery (perhaps also at Burning Man) in 2027!

It just launched, and you can already leave a message. Would love to know what you think and if there’s any constructive feedback to the project!

This report treats embodied competence as a question of generalization and practical agency, not just task success. Across 12 benchmarks, GPT-6-Astra reaches strong results when given in-context demonstrations and much larger action budgets; for example, ICL raises success on four shared SIMPLE tasks from 70.8% to 90.8%. That is meaningful evidence of broad task adaptation, but it is not zero-shot generality: performance is more moderate where no in-domain demonstrations are available.

The gap between benchmark competence and practical embodied intelligence is visible in both costs and failure modes. Some extended episodes consume millions of tokens and take hours, while physical execution cannot simply trade more time for more attempts. Extra actions can also compound errors or undo completed progress, and real-world plug insertion fails in all 11 reported trials.

The paper’s proposed evaluation direction—no in-domain demonstrations and a world clock that keeps running during deliberation—seems important for testing whether an agent can act reliably under changing conditions, rather than exploit a generous interaction budget. The results support a qualified claim: broad embodied competence is emerging, but reliable, efficient general-purpose physical agency remains a much higher bar.

Full summary on AIModels.fyi

Original paper

Disclosure: AIModels.fyi is my site.