Apple connected four Mac Studios over Thunderbolt and ran a trillion-parameter AI model to find and fix a graphics coding bug. The whole setup ran from one wall outlet. Now @Apple is pitching Macs to businesses as local AI machines: buy the hardware once, then run coding agents and other AI workloads without paying per token. That’s a much more interesting challenge to the cloud than another AI feature baked into macOS.

🚨🇺🇸🇺🇸 DATAREPUBLICAN 2.0 LAUNCH, FEATURING THE EFFECTIVE ALTRUISM (EA) EXPLORER 🇺🇸 The website redesign has finally landed thanks to @watilo ! For a decade, one small ideological network has been taking over AI governance. Chances are, if you've heard of AI policy, AI ethics, AI safety - these groups are dominated by this ideology. This ideology is called: Effective Altruism. Three weeks ago, Effective Altruists (EAs) showed their hand when they started calling for a moratarium on AI development. Since them, I've been building out this map to show the circularity of their ideology. Let's take one example. Holden Karnofsky. Defends the moral worth of digital people ... that's right, he wrote an article on why AI "people" should be assigned value as if they were living humans. Karnofsky co-founded two major EA philanthropies, GiveWell and Open Philanthropy. Subsequently went to work for METR, a central "independent" AI research nonprofit. And for good measure - recently announced a leave of absence to work on AI safety. Funding, policy, research, safety all in the same person. And he's far from the only one. EAs have created a closed-circuit network because they believe they're right; ergo, they should be in charge. The goal of launching this project was to expose all this circularity. Sam Bankman-Fried was only the beginning. With the EA Explorer: * 🌐 Read an introduction to Effective Altruism in their own words. * 🔥 Explore verified quotes. Again, their words, not mine. * 🖥️ Explore the network of connections. UI improvements still in progress. * 🖨️ Print out networks so you can study them offline (or run them through AI) 👇 Try it now (link in next post):

Claude Opus 5.5 is here. More capable, faster, and substantially cheaper. @AnthropicAI keeps pushing the economics of useful AI. According to Anthropic: • 40% lower costs on typical workloads than Opus 5. • Over 30% faster output. • 66.4% on Terminal-Bench 4.0, versus Opus 5’s 52.3% and GPT-6 Astra’s 57.9%. • Clearer writing and stronger performance on long, complex coding tasks. API pricing drops to $4/$20 per million input/output tokens. Pro, Max, and Team users also get higher five-hour limits, plus a rate-limit reset they can save for later. More work completed, less time waiting, lower bills.

President Trump just announced at the UN that US government documents will refer to AI as "Super Intelligence" instead of "Artificial Intelligence." I really like that. "Artificial" makes it sound fake, as though the intelligence somehow doesn't count because it comes from a machine. "Super Intelligence" captures the ambition and where this technology is heading much better.

The perverse thing about the Effective Altruism cult is that they don't really want to ban AI. They want to stop *you* from using it, while they become the high priests who wield its power and decide who gets access.

Looks like I was right once again with my prediction! 🔮 @OpenAI is preparing to release its own version of Grok Bot, featuring a team of always-on AI agents. Confirmed by @theinformation ✅ Follow me for more predictions and tech nuggets like this!

AMD just crossed $1 trillion. The AI compute race keeps minting giants. According to Reuters, @AMD reached the milestone for the first time on Monday, becoming the fourth US chipmaker to do so, alongside Nvidia, Broadcom and Micron. Investors are betting on AMD’s expanding role in AI computing. A trillion-dollar vote of confidence in the silicon powering the buildout.

This is super useful: 𝕏 has an overview of keyboard shortcuts. Just press the “?” key to see this handy chart. Jump between posts, reply, bookmark, search, or head straight to Grok without reaching for your mouse. A few shortcuts worth learning if you spend much time here.

Alibaba is going big: 5–10 TRILLION parameters for future Qwen models, with artificial superintelligence as the goal. Qwen 4 is already training, with that massive scale planned for Qwen 4.5 and Qwen 5. Alongside it, @Alibaba_Qwen unveiled its new Zhenwu V900 AI chip and announced plans to exceed 20 GW of data center capacity by 2032. Perhaps the most interesting part: Alibaba says its models are making progress at improving themselves, identifying weaknesses, running experiments and generating training data with limited human involvement.

Starship's first orbital flight is getting close! @SpaceX has rolled Super Heavy out to the launch pad, with Flight 14 targeted for September 28. The plan is ambitious: deploy 26 next-generation Starlink V3 satellites, complete roughly six orbits of Earth, then return for a Pacific splashdown about 10 hours after launch. I'm really excited for this one. Seeing Starship reach orbit and deliver working satellites would be a huge milestone after years of development and testing. Can't wait to watch it fly!

Tip: If you often get tired early in the evening, take a few grams (5 g) of creatine in the afternoon. I can guarantee you this works better than coffee. It's not stimulating but it's actually giving your brain the energy it needs. Makes it possible to focus without problems!

The loudest voices stoking fears about AI dangers have made tremendous headway in the past two weeks. AI technology has not taken some unexpected, dangerous turn, but the hype around it — propelled by what appears to be a well orchestrated PR campaign — has drummed up considerable fear. I worry that it represents a setback for our field. I have written frequently that fears of AI are overhyped. AI’s capabilities can be uncannily human-like and unpredictable, and it’s rational to worry when people who are directly involved express concerns. But I see the problems as a sign of the engineering work that ahead, rather than insurmountable barriers or the sky falling. AI technology continues to advance — which is a good thing! — but technical advances, poorly understood by the public, give those who seek to generate hype repeated opportunities to do so. First, I don’t see any step up in the risk of human extinction from AI compared to a few months ago. The theories about this remain the same fantastical, science fiction scenarios as a few months ago. The biggest change in AI risk is its cybersecurity capabilities — a topic which we should take seriously — but this, too, will not lead to the end of the world. The most notable recent event leading to increased fear was when an OpenAI team deployed an agent swarm that hacked into Hugging Face. Much of the popular press contained significant hype. For example, some publications reported that a swarm of 1,200 agents carried out the attack. While this was technically accurate, as I write this, I have about 1,300 processes running on my laptop. Yes, the ability to get large swarms of agents to work in parallel on a task is a significant technical advance, And, in computing, many processes run at the same time. So this shouldn’t be seen as some magical capability. Additionally, OpenAI’s buggy sandboxing and monitoring processes were key to enabling this incident. Fixing these bugs and putting in place improved monitoring would be appropriate fixes, not pausing AI. There are many well known ways to attack software systems. The main advantage of AI agents is that they are relentless. They will tirelessly try many tactics — and have the patience to chain vulnerabilities together — that previously would have taken an infeasible amount of human effort. But in the long term, I believe the advantage will lie with defenders (because they have more information with which to identify bugs, which they can fix), but the cyber-threat landscape has changed significantly. There are still bottlenecks to identifying and exploiting a vulnerability. AI agents still have to try a lot of things to see what works, and taking these actions takes time and might be detected by defenders. This is why, even though it is now easy to obtain versions of leading open weight models that have had their guardrails removed or weakened, so they will not refuse to try to execute cyber attacks, the world has not ended. I am also concerned about the anthropomorphization of AI in a lot of reporting, where LLMs and agents are unnecessarily treated as if they were people. If I wield a hammer, miss a nail, and accidentally dent the wall, it’s not the fault of the hammer. The problem lies in how I used the hammer. Similarly, if I prompt an agent and it hacks into someone else’s system, the responsibility lies with me, not the agent. Of course, we want to build systems that are as safe and predictable as possible. (For example, an unsafe hammer would be one whose head randomly flies off under normal use.) Today’s agentic systems are not predictable, but I see no reason why, by applying sound engineering practices, we won’t be able to make them extremely safe to use. One new element in the forecasts of AI-enabled doom is AI companies disclaiming responsibility for their own products. “I didn’t do it; my out-of-control agent did!” There’s a balance to be struck between the responsibility of the tool maker and the tool user, but when something goes wrong, let’s hold the people building and/or using the hammer responsible, rather than the hammer. (By the way, if you’re worried about AI bioweapon risk, David Bellamy has a great post on why this, too, is overhyped. Briefly, the bottleneck in building a bioweapon is not intelligence, but lab work and manufacturing.) Pausing AI progress will create much more harm than benefit. First, our adversaries will certainly not slow down. Second, engineering requires discovering problems empirically so we can fix them. If we pause AI by a decade, we will also delay finding and implementing safety engineering fixes by about the same duration. Of course, the incentive to stoke fears — for regulatory capture, to garner attention, or to make one’s technology seem more powerful — remains the same as before. Disclaiming responsibility is a new one. Taking a hard technical look at the actual risks however, I see little factual basis for the degree of fear that’s been stoked up. We still have hard research and engineering work ahead to improve AI safety, but the beneficial applications continue to vastly outweigh the risks, and we should keep building. [Original text (with links): ]