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A 37-year-old man with a rare blood disease was being sent to hospice. An AI model searched thousands of existing drugs and ranked a combination no one had tried for his condition. He responded within a week. He is in remission. The drugs were already on the shelf. The AI model found the match.

you don't hate math. you just never saw it like this.

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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): deeplearning.ai/the-batch/is… ]

This is cool 😎

you are going to fail, so fail while daring greatly

Grok 4.7 places @SpaceXAI as third, after Anthropic & OpenAI, for agentic coding. When factoring in that Grok is significantly faster & lower cost, it’s a great choice for your everyday workhorse.

Incentivizes and disincentives drive most all behavior.

Excited to bring 4.7 to you all! Numerics aside, it's incredibly capable in Grok Build/Cursor. We spent a lot of hours on the harness, iterating with some of the greatest engineers in the world. Also, the fast mode has INSANE tps. Happy Grok Building :) Lmk what you think!

Hive Intelligence (HI) is most accurate.

Elon made some of the key technical decisions and still does to this day. We meet with him weekly (often more frequently). He goes deep with the team and contributes significantly. I don’t know how he does this, but he just makes it happen. Consistently for the past 10 years, and I don’t see this changing.

🎯🤣 That @tszzl character must of asked Astra for their commentary too... If only they actually understood the domain. Sadly, it is VERY obvious they don't.

It’s been an honor to partner with Ziv, Tom, and the entire Glass Imaging team. When I first invested in 2023 and joined the board as an observer, it quickly became clear that Ziv and Tom are one-of-a-kind founders. They were pushing the boundaries of computational photography to a level I simply hadn’t seen before, combining deep technical insight with enormous ambition. It’s been incredibly rewarding to watch them build with conviction and turn that work into something remarkable. wsj.com/tech/openai-buys-sta…

Thrilled to be named @NJIT's 2026 Excellence in Research Prize and Medal recipient. Huge thanks to the students, postdocs, and collaborators who made this work possible. #HPC #GraphAnalytics #DataScience @NJITYingWu bit.ly/4xxzAIx

As predicted.

Build in public FTW

This seems really cool!

😎