Oliver Dealmaker
424 posts
@thrive_oliverJ
Thriving on innovation and investment. 📈🌍 Always in for a good chess match! ♟️
Uber’s COO has said that it’s getting “harder to justify” its AI costs because there was no way to show a link between AI spend and any meaningful increase in useful features. This is the first time I’ve seen a company say this directly. businessinsider.com/uber-coo-andre…
I built this thing called Clicky. It's an AI teacher that lives as a buddy next to your cursor. It can see your screen, talk to you, and even point at stuff, kinda like having a real teacher next to you. I've been using it the past few days to learn Davinci Resolve, 10/10.
Researchers proved that every single elementary function, sin, exp, log, sqrt, comes from one single binary operator. It is like finding the “God Particle" for calculus. In computer science, every complex program breaks down to a single logical operator: the NAND gate. It is the fundamental building block of all digital reality. But for continuous math, physics, engineering, machine learning, we thought we needed a massive toolbox. Addition. Subtraction. Trigonometry. Logarithms. Every scientific calculator and neural network has to juggle all of them. Until today. But this paper proved that every single mathematical function can be generated by a single, bizarre binary operator. eml(x,y) = exp(x) - ln(y). Combine that with the number 1, and you can build everything. Pi. The square root. Sine and Cosine. Arithmetic. It is all just the exact same operator, repeating over and over again in a binary tree. Nobody anticipated this existed. It was found by systematic exhaustive search. But the implications for AI are massive. Instead of an AI struggling to combine different mathematical rules to discover a new scientific law, it can just use a single, uniform architecture. One trainable circuit. One repeatable node. We thought the language of the universe was complex. It turns out, it's just one equation repeating in the dark.
Today we're announcing our Series C funding: $355M at a $4.65B valuation, led by some great investors @generalcatalyst and @Redpoint. We've had insane growth in the last year, but we're still very early. So proud of the team and what we have built so far!
Nvidia CEO Jensen Huang is basically saying: The question is no longer: "Do you use AI?" Almost everyone does. The real question is: Can you create agents? Can you automate tasks? Can you connect tools? Can you build workflows? The future belongs to people who understand the ecosystem, not just the interface. Save this for later.
Devin is getting a Windows PC. Devin can now natively run in a Windows VM, so it can build, run, and test native Windows applications.
We’ve automated every single thing we can @every with AI agents. And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3. I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI. After Automation: every.to/p/after-automa…
The AI revolution is driving unprecedented energy demand and reshaping the global competitiveness landscape. In a conversation with the @AtlanticCouncil, our MD and GCEO, Dr. Sultan Al Jaber, highlighted why reliable, scalable and affordable energy will be critical to powering the future of AI and why natural gas remains foundational to closing the growing power gap. At ADNOC, we are also harnessing AI across our operations, from the wellhead to the trading floor, using advanced AI and robotics to optimize performance, improve efficiency and unlock greater value. While the world uses energy to power AI, ADNOC is using AI to empower energy.
Tesla's @larsmoravy just revealed that the Cybercab hit a record 165 Wh/mi rating - That's a 36% improvement over the Model 3! 🤯 It's huge validation for the robotaxi vision: cheaper to build, run, and scale than anyone expected. Here are some standout implications of the Cybercab's record 165 Wh/mi efficiency (EPA-certified, ~6.06 mi/kWh, ~36% better than the Model 3 Long Range's ~259 Wh/mi): Ultra-low operating costs for robotaxis: At average U.S. electricity rates (~$0.15/kWh), energy cost drops to roughly $0.025 per mile — potentially under $0.20/mile total including everything. This crushes ride-share economics and accelerates Tesla's autonomous network profitability. Smaller, cheaper battery packs: Tesla is targeting under 50 kWh for close to 300 miles real-world range. That slashes vehicle cost, weight, and materials needs while delivering excellent daily/shift range — key for scaling robotaxis affordably. Game-changing range and uptime: Exceptional efficiency means more miles between charges, faster "refuelling" cycles, and higher fleet utilisation. The Cybercab is nothing short of engineering genius, and carries the DNA of every Tesla preceding it.
