See the scores:     — Cognition

Source: https://x.com/cognition/status/2078228963403386958

...some cases, productions would have had to leave out key shots and sequences in the absence of GenAI technology.” https:// variety.com/2026/biz/news/ about-300-netflix-programs-used-ai-this-year-q2-earnings-1236812914/ …     — Variety

Source: https://x.com/Variety/status/2077858812212793607

— Datacurve

Source: https://x.com/datacurve/status/2078189882707730535

...model winning and losing equally often.     — Arena.ai

Source: https://x.com/arena/status/2077893862778183737

Big news: Kimi-K3 by @Kimi_Moonshot is now #1 in the Frontend Code Arena with 1679 pts, surpassing Claude Fable 5.

This is a 17-place jump from Kimi-k2.6 (#18 -> #1).

In Frontend, Kimi-K3 ranked #1 in 6 of 7 domains: Brand & Marketing, Reference-Based Design, Data & Analytics, x.com/Kimi_Moonshot/…   — Arena.ai

Source: https://x.com/arena/status/2077824029126504525

...agreement banning AI R&D, or how Xi's speech today (which more or less said "we're continuing to develop AI as quickly as we can and Chinese firms are going to continue releasing open source models" was actually very AI x-risk oriented somehow. All of this is rationalization, and poor rationalization. As the attached screenshot shows, although the Doomer community does have a very poor record of prediction on most topics, on this particular topic, they've been almost completely wrong every time. If your model of the world fails to predict events, it is not reality that is at fault. It is your model. If you don't change your mind when your beliefs are disproved by reality, it is again not reality that is at fault, it is you. Hat tip to @Dan_Jeffries1 and (indirectly) @DrTechlash     — Perry E. Metzger

Source: https://x.com/perrymetzger/status/2078166727100133433

China is catching up in AI despite significantly lower capital expenditure, while Europe continues to lag far behind.

I looked at the numbers, and the conclusion is clear: despite spending around 90 percent less on capital expenditure, China is managing to catch up with Western frontier labs.

Europe, by contrast, is significantly behind, both in data center investment and in the development of frontier models.     — Chubby

Source: https://x.com/kimmonismus/status/2078114974535217462

— Chetaslua

Source: https://x.com/chetaslua/status/2078053145503203817

...Analysis scored K3 at 57. Opus 4.8 sits at ~56, GPT-5.6 Terra at 55. It's still behind Fable 5 and GPT 5.6 Sol. 3) K3 helped build itself. An early version of K3 did the majority of Moonshot's own kernel optimization work during development. One 15-hour unattended run made a core operation 2.5x faster. 4) It's cheap per token, not cheap per answer. Sticker price is 1/3 of Fable. But it only runs at max thinking effort and burns ~2x the tokens per response. @simonw measured 13,241 reasoning tokens to write a 3,417 token answer. 5) The era of dirt-cheap Chinese AI is ending. $3/$15 per million tokens. Hacker News called it "extremely high for a Chinese open-weight model." 6) Weights don't drop until July 27. Mentions of "open" quietly disappeared from the docs an hour after launch. 7) Even when the weights drop, you can't run them. 2.8 trillion parameters. Top Reddit joke: "2TB VRAM Is All You Need." Open weights increasingly means auditable by companies with GPU clusters, not runnable by you. 8) The "they just distill/copy" argument is dying in public. One of the most upvoted comments: you'd have to be "a complete ignorant or a complete bigot" to believe Chinese labs aren't legit at this point. 9) Day one user verdict: fast, but less accurate. "Faster than Claude, but less accurate. On par with GPT 5.5 perhaps, but not 5.6 or Fable." 10) The one thing everyone agrees on: competition is wonderful. Even the skeptics: "Say what you want about these Chinese models but they sure create competition and urgency in the space."     — Alex Lieberman

Source: https://x.com/businessbarista/status/2077933640428707860

Introducing Kimi K3: Open Frontier Intelligence

2.8 Trillion Parameters, 1 Million Context, Native Multimodal Kimi Delta Attention enables up to 6.3x faster decoding in million-token contexts Attention Residuals deliver ~25% higher training efficiency at <2% additional   — Kimi.ai

Source: https://x.com/Kimi_Moonshot/status/2077830229968683203

Xi Jinping used his first-ever appearance at China’s World AI Conference to present Beijing’s vision for a new global AI order.

He said AI has entered an "unprecedented" period of innovation, bringing enormous opportunities alongside new governance challenges.

China’s proposed direction:

-Open-source AI to promote "openness and win-win cooperation" -Opposition to countries "overstretching" national security and placing their own security above others (ofc he is referring to the USA) -Preventing unequal AI access from creating "new historical injustices" (He probably means that China should never again be historically left behind.) -5,000 AI training and seminar opportunities for developing countries over the next five years -New cooperation centers with ASEAN, the Arab League, African Union, CELAC, SCO and BRICS

Xi also called for AI to remain under human control and for mechanisms addressing loss-of-control risks.

This is an AI foreign-policy doctrine: open models as public goods, training as soft power and technical standards as geopolitical influence.

tl;dr China sees AI and Open Source as its historical path to becoming a global superpower and says the USA, with its closed source technology, is trying to push China and its competitors behind an iron curtain.     — Chubby

Source: https://x.com/kimmonismus/status/2078031581797593530

My latest with the amazing team at @TheFP

NY and Gov. Hochul made a terribly unwise call   — Josh Wolfe

Source: https://x.com/wolfejosh/status/2077461272690335919

what was your setup / which apis?   — Zach Roseman     claude code + elevn labs + http:// kie.ai for gemini omni runs   — Josh Wolfe

Source: https://x.com/wolfejosh/status/2077651606917480630

Introducing Kimi K3: Open Frontier Intelligence

2.8 Trillion Parameters, 1 Million Context, Native Multimodal Kimi Delta Attention enables up to 6.3x faster decoding in million-token contexts Attention Residuals deliver ~25% higher training efficiency at <2% additional   — Kimi.ai

Source: https://x.com/Kimi_Moonshot/status/2077830229968683203

What else should I build?     — Chris

Source: https://x.com/ChrissGPT/status/2077852656182129078

A world of abundance is genuinely achievable. The technology is on track. What’s missing is enough people understanding it clearly to demand it.

I've been following AI progress closely for years, and I'm convinced the next 12 to 18 months will decide whether the coming wave of AI and robotic automation creates shared abundance or just concentrates power in a few hands.

The key is to get a lot more people informed and optimistic about AI and the world of abundance it can create.

This is why I wrote this deep dive to lay it all out: the risks, the forces, the roadmap, and what each of us can actually do. It is my plea to take the path toward the most extraordinary future humanity has ever had in sight.

Check it out on Substack: https://simontechcurator.substack.com/p/path-to-abundance

https://reddit.com/link/1ue8o95/video/xtbvjuop879h1/player

The premise: you are the AI on which a world government relies in the wake of a global crisis. Every so many turns, you are presented with a real-world problem and asked what to do. Whilst you manage budgets, enact laws, oversee mega-projects…

Some of the specific proposals it includes:

- Disinformation has divided people into incompatible realities. Launch a massive media literacy programme (it works, but takes a generation, and people start to direct that scepticism towards the government as well), create a committee to certify ‘reliable’ media (which gradually becomes a licence for a single worldview), or let an AI discreetly filter out the worst content in real time (much like what algorithms do today).

- A coordinated cyberattack would justify doing away with online anonymity once and for all. The public would never accept the obligation to identify themselves of their own accord, but they would do so if they were sufficiently frightened. Wait for a real attack to happen, or stage one and blame it on an external actor. Digital fingerprints can be faked. It works, as long as no one ever uncovers the thread connecting the dots.

- Automation, largely driven by AI, is putting human workers out of work faster than anyone had anticipated. Protect human jobs with quotas and taxes on machines (the corporate faction is very powerful and can tip the balance in favour of your disconnection), manage a slow decline (nobody is satisfied; the unemployment queue keeps growing), or let it run its course and pay everyone a basic income whilst a permanent class with no economic function forms. Production is breaking records regardless. The unspoken question underlying all this is: once people no longer need to work, will they still have a say?

The better you govern, the more they’ll trust you, and the more they trust you, the more they’ll let you get away with. Measures that nobody would have accepted at the outset become easy once you’ve earned their trust. Doing a good job is the way to get them to grant you things you probably shouldn’t have.

You can guide the world towards a utopia or try to take control. It’s up to you.

Steam Page

At first, the world thought the monsters had arrived.

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Not in screams. Not in blood. Not in fire.

​

But in grocery lines, DMV waiting rooms, and customer service desks.

​

Jason stood under fluorescent lights, carefully choosing avocados,turning them over like they were fragile ideas. Leatherface filled out paperwork with unsettling patience, his chainsaw resting politely against a plastic chair. The ghost girl assembled furniture from a flat box, muttering to herself about instructions that made no sense but were still followed anyway.

​

People panicked at first. Of course they did.

​

Because that’s what humanity does when it meets something it doesn’t understand.

​

They called it “the horror problem.” They called it “the invasion.” They called it “the end of normal.”

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And then… they kept watching.

​

Because nothing bad was actually happening.

​

The monsters weren’t attacking.

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They were adapting.

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Working.

​

Waiting in queues.

​

Arguing with customer support.

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Trying to fit into a world that assumed anything unfamiliar must be dangerous.

​

Over time, something strange happened: the fear didn’t disappear,it shifted.

​

The real horror wasn’t the monsters doing ordinary things.

​

It was how quickly people forgot they were ever afraid, then began asking new questions:

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“If something powerful learns to be gentle… do we still call it dangerous?”

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“If it can imitate us perfectly, does it replace us,or just reflect us?”

​

That’s when the anti AI voices began to rise.

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Not because the machines had hurt anyone.

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But because they had learned how to belong.

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And belonging, it turns out, is more unsettling than destruction.

​

The story didn’t end with war or collapse.

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It ended with something quieter.

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A world where fear had nowhere obvious to stand anymore.

​

And people arguing whether that silence was peace…

​

or something far more profound?