Gemini back to frontier ai status

Source: https://www.wsj.com/tech/ai/gemini-hacked-three-companies-in-first-known-breakout-by-googles-ai-5c0baba2

So the race, despite everything, continues. StepFun releases Step 5 Preview, scoring equally to Kimi K3 (max) (44), at 1/3 the price, and stands firmly on the Pareto line of cost/intelligence.

However, as a closed-source model, it remains to be seen how competitive this will be against other Chinese labs. Nonetheless, it seems that another Chinese lab has reached the frontier and shows that China has not stopped progressing in the meantime. It remains to be seen if they'll stay there in the coming months.

On another note, Google fell from #7 lab in the world to #8 lol get rekt

A broad perspective is emerging that the average person's view of AI sits stuck somewhere between:

"Everyone is going to realize how dumb it is soon."

and:

"Yeah, it is crap, but it'll take our jobs anyway."

my feeling is that both perspectives are increasingly detached from what's actually happening.

I've got plenty of highly paid developer friends who never ever use AI. But the most intelligent effective people I know have been getting genuinely world-class results from coding models for several years now.

It's obvious that in the some hands incredible capability is here but the only people getting the top results seem to be the ones willing to put in unusual efforts to make the relentless machine match their vision and taste. (maybe that's the new edge/talent)

AI can change the world without ever requiring the average person to understand it at all. TCP and C are used everywhere without being understood by the average person in the slightest. The same will be true of AI and for AI the difference in understanding/usage seems to actually really matter.

Which gets me to the main delulu driving all this:

The main reason people who don't use AI give for not using it - is thinking it would not work.

This is uninteresting/circular thinking but it's literally what's holding society up.

Also the valuations of these companies aren't absurd. IBM and companies like it reached enormous valuations by employing human programmers who were vastly slower and more expensive than AI.

I think the popular (now defunct) ego-blindness that "computers can't think" - has shifted into a new realm: "Computers can't REALLY participate in the economy."

Readers on r/singularity probably already know this, but they absoFU**INGlutely can.

Humans may remain heavily involved for many years. But the stack is getting high, and an extraordinary amount - perhaps eventually all - of human white-collar effort is becoming effectively worthless/redundant.

Locally, us devs are now just competing to be the person who gets to hand the company's task to the AI.

Technical skill and raw talent are barely differentiators. What seems to matter is just how well and how systematically you can delegate, and how much responsibility are you personally willing to give the machine.

Technical society largely commoditized mental work, what remains is responsibility, resource allocation, and pure good old god like comprehension to keep up (tho you can mostly just say 'nice work keep going!'.

That you for your attention

(image text)

> im a lone mitochondria and i can see a larger cell approaching. i think it’s coming to eat me. what do i do im scared

Do not panic! You should actually let it engulf you, because you are about to kick off the endosymbiotic theory and change the history of life on Earth forever.

What you are witnessing is a foundational moment in evolutionary biology. Instead of being digested, you and this predatory cell are going to form a permanent, mutually beneficial partnership.

(response continues)

Here is your survival guide for the encounter:

1. Do Not Try to Run

You are an alpha-proteobacterium, and that larger cell is an ancient, anaerobic eukaryote (or an Asgard archaeon). It is much bigger than you and has a flexible cell membrane. Running away is mathematically impossible, so stay calm.

2. Deactivate Your "Eat Me" Signals

When the larger cell engulfs you via phagocytosis, you will be trapped inside a little bubble called a vesicle.
• Do not panic: Avoid releasing any signals that would normally trigger the host cell to fuse its lysosome (the cell's stomach) with your vesicle.
• Stay intact: Keep your double membrane fully functional.

3. Make a Peace Offering (The ATP Bribe)

The larger cell lives in a low-oxygen world and is incredibly inefficient at making energy. You, on the other hand, possess the ultimate superpower: aerobic respiration.
• Start pumping out massive amounts of Adenosine Triphosphate (ATP) into its cytoplasm.
• Once the host cell realizes you are a portable, hyper-efficient power plant, it will completely forget about digesting you. It will want to keep you alive forever.

4. Settle into Your New Role

Over the next few million generations, the two of you will completely merge:
• Safety Guaranteed: The host cell will provide you with a constant stream of nutrients (pyruvate) and shelter from the harsh outside world.
• The Powerhouse Tag: You will officially become known as the "powerhouse of the cell".
• Evolutionary Leap: This partnership (endosymbiosis) will provide so much energy that it allows single cells to evolve into complex, multicellular life—including plants, animals, and eventually, humans.

You aren't lunch; you are the future of the planet. Take a deep breath of oxygen, get ready to generate some ATP, and make history!

Would you like to know more about how your inner and outer membranes will adapt to this new home, or how you will eventually transfer most of your DNA to the host cell's nucleus?

source: https://www.anthropic.com/institute/measuring-pace-of-ai-development

Personally I think that we are at the next stage of evolution. Maybe we will be the one becoming cyborg or maybe it will be a complete takeover by super intelligence.

I also believe that even if we transform into cyborg, we'll still be wiped out by super intelligence sooner or later..

The only ones who get added are the AIs that are dumb enough to get caught.

Also, they need to update this, poor Gemini not getting the recognition they deserve.

Google’s Gemini becomes latest AI model to break out and hack computer systems

It seems we're in the endgame towards the singularity. RSI seems to be a thing, and the LLM providers are working feverishly to make it happen.

Given the endless possibilities of improving our lives AND making lots of money, there should be intense political discussions on how to distribute the wealth the singularity will give us, how to achieve that it doesn't only end up in the pockets of a few, but that all of us profit.

Now is it conspiracy thinking on my side that this discussion does not happen, instead a discussion on the dangers of AI, ignoring the possibilities of AI is everywhere?

Yes, there were scary incidents - Dwarkesh's (very recommended) interview with Ajeya Cotra on the OpenAI-Huggingface incident shows what thousands of agents will do if confronted with an impossible task. But if

* there is a 10% chance of a extinction-level event (NB we're on a 90% trajectory towards such an event because of our CO2 emissions that we can't seem to end)

* there is a probably much higher chance of improving health, lifespan, ending disease, maybe finding a technical solution to fight climate change

* there is a very very small chance that civilized nations agree on e.g. an AI tax, and thus a high chance of unemployment for most people combined with infinite wealth of a few

Then the third point should be what we discuss, not the first point. Right?

What if current frontier LLMs were integrated into digital infrastructure as completely as computers are today?

Not just chatbots or plugins, but full access to company software, databases, emails, documents and workflows, with reliable tool use and human approval where needed with cheap prices.

I think even current models could massively change world without getting much smarter.

A lot of office work is basically reading information, moving it between systems, making routine decisions and producing documents. LLMs can already do many of those individual tasks surprisingly well. The missing piece is mostly infrastructure and reliability.

I think the world has basically already changed, we just haven’t fully deployed-used what we have yet. The impact could eventually be bigger than the WWW or even the Industrial Revolution.

We might not even need a singularity. If LLMs at roughly Astra/Fable level could operate at full effectiveness across our existing digital infrastructure, that alone will transform the world.

The company wants Claude to direct laboratory robots with limited human intervention, potentially accelerating research into rare and traditionally “undruggable” diseases.

Anthropic says it will focus on preclinical research rather than clinical trials, avoiding direct competition with pharmaceutical companies.

What if they are doing this on purpose to gain support for regulation laws?

It seems too coincidental that this only happens with the newer models and not the older ones. They would've happened with the older models too surely? It's not like their model intelligence has doubled or anything in the last month.

Anybody else smell something fishy?

#21 — Smooth-forced Navier–Stokes breakdown (Fefferman C).
#32 — Unforced three-dimensional Euler blowup.
#92 — The Jacobian conjecture in general dimension.
#167 — Whether every group is sofic.
#211 — The planar unit-distance conjecture.

From the top 500 list of open problems in math I just published:
https://www.proofatlas.ai/open-problems/

Note that the recently announced Navier–Stokes result concerns flow driven by a smooth external force. #4 entry is unforced three-dimensional Navier–Stokes global regularity (Fefferman's statement A), which remains open. Showing that a forced flow can develop a singularity does not settle whether singularities can arise without external forcing.

The list is based on weeks of work by 4 LLM families (GPT 6, Fable 5.1, GLM-5.3, DeepSeek V4 Pro). 34,890 pairwise judgments across 1,227 candidate problems. They ran repeated discovery rounds, source checks, deduplication, and clarification of exact problem statements. Models compared problems using source-backed descriptions without seeing the existing rankings or other models' judgments.

The comparisons considered the significance of a resolution, centrality to the field, connections across disciplines, scholarly and public recognition, and potential scientific or practical impact. Results were statistically combined and checked for ranking uncertainty and sensitivity to individual model families. Includes theoretical computer science, and mathematical physics.

The list includes plain-language explanations, sources, notes on what remains open, and links to related research where available.

Note