Slingshots // Four is live! Another batch, another fourteen projects shipping open source artifacts that I’m excited about. See below for the full list. A few themes from the batch: 1. Harness time: This quarter harnesses shot up in visibility, with increased appreciation for the parts of an agent that aren’t the model and what they can give you. This batch includes a harness supporting persistent agency (Headlong); a harness supporting self-improvement via context management (ACE); a harness supporting self-improvement of the agentic harness itself (Exo); and a harness supporting multi-agent setups (dotagents). 2. Up and down the stack: There’s innovation to be had at every layer of the stack. We saw projects worth backing at the level of kernels (Thunderkittens); inference (M*); training (Marin); data (Atlantic-CC); evals (Decision Assistants); optimization (SkyDiscover); applications (Wagglehaus), etc. 3. Talk of the town: Slingshots continue to tackle timely problems at the frontier. Concurrent with Jev taking over X, an even faster type 1 decision model (CLM) came out of academia. With RSI on the brain of every big lab researcher, we now have a public literature retrieval benchmark grounded in authors’ firsthand accounts of their research process (ScholarCatalyst). And a new RL training method (Pedagogical RL) addresses head-on the question vexing RL practitioners of how privileged information can be used to discover generalizable behaviors, not just verify. Congrats to all the researchers in this batch and the previous three who continue to ship their research out into the world with open artifacts that can be adopted and built upon. Open science leads to better outcomes for everyone. And the good times will continue to roll – batch five is looking just as good. If you’re a researcher with a project that’s gaining momentum and ready for an adrenaline shot, shoot me a DM or apply at laude.org/slingshots. 👏 @a1zhang, @AlexKrentsel, @ankrgyl, @Azaliamirh, @bariskasikci, @bfspector, @chelseabfinn, @chipro, @Diyi_Yang, @dlwh, @drmapavone, @HazyResearch, @jackyk02, @jonasgeiping, @JonSaadFalcon, @jure, @kothasuhas, @lateinteraction, @martin_casado, @mertcemri, @michaelryan207, @MikeCafarella, @NickAJalbert, @NoahZiems, @nsagan271, @ohmyksh, @percyliang, @qizhengz_alex, @RussoMatthew, @samrmadden, @shagarw21, @ShashwatGoel7, @shulynnliu, @simran_s_arora, @souradipchakr18, @stuart_sul, @tianyu_li_, @tim_kraska, @WilliamBarrHeld, @yoonholeee, @YejinChoinka, @Stanford, @MIT, @LaudeInstitute, @CarnegieMellon, @UW, @UCBerkeley, @MPI_IS, @UWMadison

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions AFAICT the shortest path to AI-based economic revolution

We asked an unreleased research version of Claude to take a stab at the Riemann hypothesis. It didn’t solve it, but it did make strides on a related problem: it increased the lower bound for the fraction of zeros of the Riemann zeta function that satisfy the hypothesis from 41.6% to 67.2%. anthropic.com/research/riema…

Excited to co-found Discovery Loop with my long-time collaborators @JeffDean @Sanjay_Ghemawat @OriolVinyalsML . Our mission is to automate machine learning, engineering and science. Learn more at: discoveryloop.com ♾

We are honored to announce the Test of Time awards for #ICLR2026 🏆 This award recognizes papers published 10 years ago at ICLR 2016 that have had a lasting impact on the field: blog.iclr.cc/2026/04/22/anno…

Small-but-happy win: If you tell ChatGPT not to use em-dashes in your custom instructions, it finally does what it's supposed to do!