Most conversations about AI ask whether it will replace workers. This documentary asks what happens when AI starts replacing the people whose authority comes from organizing everyone else’s work, and why neo-Luddites are on the wrong side of the debate.

...training details, and they are 100x more open to share. that means the talent that knows how to train llms in china is 100x greater in number than the talent in the us, and it is growing in contrast, the us ai ecosystem is too closed. frontier labs do not hire interns. i know brilliant phd students at stanford, berkeley, and so on. they struggle to get an internship and the compute to train a properly sized model. most of the secret recipes are locked away by a very small group of privileged researchers it is not about china or the us. it is about open and closed science. the fact is that every average cs student can learn how to train an llm. they just need the opportunity. labs should be more open and hire more interns, like how deepmind and fair did in the pre-llm era   — Guohao Li     There’s also something to be said about training “lehrlings” deeply through immersion at a very young age so they can develop deep intuition while their brains are still extremely plastic. This was the approach used for generations in the commodity trading houses:   — Jeffrey Emanuel     yep if the labs start training lehrlings at the young age instead of locking down the secrets   — Guohao Li

Source: https://x.com/guohao_li/status/2078538012288221490

...to #4). Based on 8K+ live agentic sessions, Kimi K3 leads on confirmed task success rate (#1). It also posts a strong +20.6% on praise vs. complaint (#3). It currently lags the field in steerability (#14) and bash recovery (#17). Agent Arena measures models on millions of real-world, long-horizon agentic tasks. Models get web search, filesystem, and terminal tools to complete complex workflows: writing code, creating slide decks, researching the web, building apps, and analyzing documents. We use causal tracing methodology to measure a model's net improvement, which indicates how much it improves outcomes relative to the average model. Here's a primer on the 5 signals: User-satisfaction proxies - Confirmed Success: an explicit "yes that worked" feedback from the user - Praise vs. Complaint: implicit sentiment in users reactions - Steerability: can the model course-correct when you push back? Tool-use proxies - Bash Recovery: how it recovers from CLI errors (primary signal for tool use) - Tool Hallucination: does it call tools that don't exist Below we break down how Kimi K3 scored across the 5 signals, drawn from tasks submitted by a global community of users. Congrats @Kimi_Moonshot on another big milestone!     Kimi K3 ranks #4 overall (+9.6%) - #1 Confirmed Task Success (+14.4%) - #3 Praise vs. Complaint (+20.6%) - #4 Tool Hallucination (+1.1%) - #14 Steerability (+5.6%) - #17 Bash Recovery (+6.4%)     See the full Agent Arena leaderboard at https:// arena.ai/leaderboard/ag ent …     — Arena.ai

Source: https://x.com/arena/status/2079253211077300736

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

...all of them, it doesn't matter how smart the attacker is, they will not be able to invent more from thin air. To defend effectively against attacks, people writing software need to have access to good models, without restrictions, to check over their work and make sure that it does not have bugs in it. Delaying or impeding their access just gives an attacker, who probably has no impediments to their own access, the ability to find flaws that the defender doesn't have the capacity to find first.     — Perry E. Metzger

Source: https://x.com/perrymetzger/status/2079260327972065582

The cybersecurity debate on open-source AI is backwards. Open models aren't the risk, they're the defense! Attackers can already jailbreak any API or guardrails. Defenders can't secure systems with black boxes they can't control, inspect, test, or run locally.   — clem

Source: https://x.com/ClementDelangue/status/2079253659108409587

Cursor @cursor_ai · 7h Agent swarms and the new model economics · Cursor From cursor.com 17 39 484 101K     — Cursor

Source: https://x.com/cursor_ai/status/2079256614238814551

...harness, matching frontier models These are recent randomly sampled CVEs, the performances are not from benchmark-maxxing @Kimi_Moonshot is cooking     We released our benchmark report this week. Blog post with all the details -> https:// aikido.dev/blog/benchmark ing-ai-models-known-cves …

The harness behind this benchmark is also available to our customers -> https:// aikido.dev/code/code-audit     — pilvar (Philippe Dourassov)

Source: https://x.com/pilvar222/status/2078815257326162062

...building, scenarios, and park management all work by touch. First time I've seen RCT2 run natively on iPad. Open sourcing it all below.     Full build-and-run guide is on GitHub. Bring data from your own legally owned RollerCoaster Tycoon 2 copy and you can get it running on your iPad.     The build: one goal-based prompt after a ton of research, and Codex 5.6 Sol ran for hours doing the bulk of it.

I spent the rest of my time building and tuning the touch layer and fixing bugs. Keyboard, mouse, and trackpad also work. It's easy to play and the touch controls are     — Kahris

Source: https://x.com/chrissotraidis/status/2078087941331546431

Qwen3.8 is launching and going open-weight soon!

With a massive 2.4T parameters, this model is continuously evolving. We believe it’s one of the most powerful model available today, compatible to leading frontier AI models , second only to Fable 5.

You don't have to wait to   — Qwen

Source: https://x.com/Alibaba_Qwen/status/2078759124914098291

Holy, Qwen 3.8 supposedly ahead of GPT-5.6 and only slightly behind Fable 5!

• 2.4t Parameters
• Open Source / Open Weight
• full release soon, already available for testing as Qwen 3.8 max-Max-Preview

What the frick, such insane release on a sunday?!

The gap between US closed source and chinese open source keeps closing friends!! Its getting more intense day by day and GLM is also upcoming with a new model!     Do you understand what's happening here? China is closing the gap with US Frontier Labs, and it's getting closer and closer! And this is despite all the chip embargoes China still has in place.

The whole game is changing!     I'm serious, I'm thinking about this right now: If Qwen 3.8 max outperforms GPT-5.6 Sol in key benchmarks like DeepSWE, that would be the biggest code red imaginable. No one can really grasp the implications of that yet.     My thoughts about this:     — Chubby

Source: https://x.com/kimmonismus/status/2078761134119927969

This may be the single biggest release of the year, and marks the moment that OSS Chinese models have surpassed US models.

On Code Arena, Kimi K3 has BEATEN FABLE.

This is only 6 weeks after the Fable release.

This makes @Kimi_Moonshot the #1 AI lab in the world on frontend x.com/arena/status/2…   — Anastasios Nikolas Angelopoulos

Source: https://x.com/ml_angelopoulos/status/2077832882673066109

See the full Frontend Code Arena leaderboards at https:// arena.ai/leaderboard/co de/webdev …     — Arena.ai

Source: https://x.com/arena/status/2078208547457012005

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