.@Grok in your Tesla can now do meaningful work for you With Connectors, you can manage your inbox, clean up your calendar, or talk through existing files/chat/tasks – all hands-free

🚨 Cathie Wood’s Starship math gets crazy very quickly! Larry Goldberg @TeslaLarry breaks down ARK’s estimate that a single Starship launch could eventually generate around $1 BILLION in connectivity revenue. Now combine that with Elon’s goal of 10,000 Starship flights per year. The theoretical math? Up to $10 TRILLION in annual revenue. Of course, there are huge assumptions here. Bandwidth demand, launch cadence, pricing, and network capacity all have to scale. But that’s the bigger point. If Starship goes from occasional launches to multiple flights per day, SpaceX starts looking like something very different from a rocket company. And orbital data centers could add another layer on top. The numbers are speculative. The scale of the idea isn’t. $SPCX

Some of the funniest times on this app 😂

Never forget that in New York they eliminated the literacy exam in 2017. And this exam wasn't for students - it was the literacy exam for TEACHERS. Only 61% could pass it!

Over the last few weeks, Grok Build teams have optimized the harness for 4.7: - Better presentation, less slop, and better prose - Better self-validation - Improved thinking efficiency - Improved long-horizon monitoring tasks - Improved VLM and multimodal tasks Many FSD and Cybercab features I personally shipped were done with my overnight agents. Give it a try.

Grok 4.7 turned a simple prompt into this interactive 3D jet engine visualizer in minutes. This is insane. 🔥

I’ve been building with Grok 4.7 extra high in Grok Build today for hours. It’s fantastic and my usage percent (Cursor Ultra) is barely moving. Getting so much done. While Build works on one thing, I discuss the next feature/change with my Grok Bot team and have Engineer Bot explain our conclusion so I can give that to Build. At the start of the day I had 4.7 do a full code review in Cursor, then had Fable 5.1 review the review and it largely agreed with only a slight change in priorities.

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… ]

Grok 4.7 just built a GTA-style open-world game from a single prompt in Grok Build You can walk around, drive cars, enter vehicles and explore an entire city It looks insane, and I had way too much fun playing it 😂