Years from now, people will look back and say Grok Bot was the moment AI actually became useful for normal people. This week, I just texted it and: 1/ My kids woke up to new math and reading worksheets already printed 2/ It planned and booked trips for my family 3/ It ordered stuff for me from one text 4/ It printed my return label for a shoe I own and set a reminder so I don't miss the deadline 5/ It built a page that breaks down my net worth And look at what other people are getting it to do too: 6/ Book a flight from start to finish 7/ Build a website or an Etsy store 8/ Reconcile crypto taxes that would cost hundreds 9/ Book a Tesla tire rotation during school drop-off 10/ Order itself a 3D-printed body and mail the parts home You just text it like a person. I've been early on Tesla. I've been early on SpaceX. I'm telling you, I'm early on this too. This is the greatest thing that has happened to AI.

BREAKING: Offshore oil rigs could become AI data centers powered by stranded natural gas. Kalypso Offshore Energy and Offshore Data Center have announced plans to explore converting underutilized offshore natural gas into electricity for computing infrastructure, including potentially repurposing existing oil and gas platforms in the Gulf of Mexico.

Just another Sunday afternoon in SF: I paid $60 for 2 humanoid robots to clean for an hour. Here's how it went: (1) What happened: Sergey and Chelsea (the names of the two robots) finished about 80% of one floor in an hour: tidying, wiping down surfaces, vacuuming, mopping, cleaning the toilet. - They came with a staff engineer at the company, who dropped them off and picked them up after an hour. - They were controlled by 1 human operator each, in the Mission where the company office is at. - The engineer gave me a number to text them, I texted a request to wipe the mirror. They did it. (2) Performance and dexterity: Chelsea dropped a toy, struggled with a pillow, and had trouble balancing on the playmat. But overall, for all the tasks they did, grippers were enough. 5 fingers were not needed. - The engineer told me the hardest task for them was making bed. - They were quite loud, stomping around the house. Took a bit of time to get used to. They both wore gripper socks which protected the floors and helped them not slip. - Interaction: I didn't know they can respond via voice. In the end they were conversing with us in voice which was nice. (3) Unexpected observation: Their pants and shirts have holes in them. It's because they were dragged on and off the vans that transported them. (4) Other user feedback: I shared my experience with some friends afterwards. A user told me that unloading dishwasher was an "advanced task". They didn't attempt at mine since it was running at the time they were working. Another user said they scratched their hardwood floor. That's probably why they now wear gripper socks. (5) Did they do as well as human cleaners? In terms of the tasks they did, I think so. In terms of speed, they were ~80% speed of humans when it comes to the more delicate tasks, but I would say they are quite smooth. They didn't finish the whole place, so it wasn't a full service. (6) How does the math work out? Each booking was only for 1 hour, since their batteries need to be swapped after 1 hour. So they didn't finish the place. For a user: In SF, it's ~$200-220 to clean a full home around my neighborhood, with two human cleaners. Usually it takes around 2.5 hours. So around $40/manhour. This is $30/robot hour. Slightly cheaper, but again it's not fully finished with the 1 hour they were available. For the company: It took 2 robots, 2 human operators, 1 staff member to dropoff/pickup, and 1 driver of the van to transport the robot. Definitely labor intensive. But they also retain the data they collect for training purposes. (7) My biggest takeaway as a user: interaction / hospitality mattered. One of the humanoids was more friendly (Sergey), he waved at us when he came in. It'd have been great if they both introduced themselves in the beginning. Beyond that, being able to do 2 hour slots (instead of one) would be great to finish the cleaning. Overall, I appreciated their work and the fact that they got the robots out in people's homes. Deployment is not easy and so much learning from it each time

GPT-6 Astra got +80% on a Physics benchmark. It insisted the expert results were wrong and its calculations were right. A team checked. And yes. GPT-6 Astra was right. New score: 98%

Cyber is going to be one of the biggest spaces for AI agents in the future. Obviously the risks of software exploits and the attack surface area increases 100 fold due to the ability for agents to work through any crack to find what they’re looking for. But this goes the other way as well. The ability to have agent swarms review every line of code, test any number of permutations of exploits, and research any incident faster than humans as they happen, will be a huge boost in how we secure systems in the future. Cyber has always been a category where it’s hard to keep up with (and triage) all the incoming risks, alerts, and changes in the enterprise and across all system. You can never hire enough people or work through the backlog of all known risks. Agents actually give you a chance finally to have far better coverage of this. This is going to be a huge opportunity as well because we’ll see plays at the labs, data providers, the layer of the network and firewall, identity, devices and endpoints, SDLC, and even how we protect our data in the enterprise. Lots of interesting dimensions to cyber at the moment.

BREAKING: California is building its first new steel mill in over half a century. Pacific Steel Group is investing $700 million in a steel production facility in Kern County, designed to melt recycled steel and manufacture rebar for critical infrastructure projects.

bro went from code review to damage control 😭

Google Deepmind (FNV3) CRUSHED the forecast for #Isaias up to 11 days in advance. It picked up some appreciable signal on September 23, locked in on the exact landfall location4 days before it happened, and nailed the peak intensity consistently 3 days before it happened. A new age of forecasting is upon us. First video: Track density using 1000 member ensemble Second Video: Individual tracks and mean using 50 member ensemble

Formula 1 Singapur yarışı canlı yayınında yaşanan kamera geçişi:

Technical moats are mostly over at this point. If you’re building something that is meant to be durable, the only moats now are: • Proprietary data • Network effects • A physical component

Şu görüntüleri filmlerde göremezsiniz. Biri "Fransızlar çıldırdı" diye yorum yapmış, hakikaten öyle. İnanılmaz! 🙄

BREAKING: @RainmakerCorp, the American cloud-seeding technology startup, has signed an agreement with the Jordan Valley Authority to enhance rainfall in northern Jordan, strengthening water security in one of the world's most water-scarce countries.

We are living in the goddamn renaissance.