Kicking off our anniversary month of weekly Waypoint Chronicles is 'Elegy' by Jeremy Patenaude. A lone Sangheili journeys to Feldokra and uncovers ancestral history that alters his life and loyalties. 📜

It’s kids’ first day at Waypoint Academy, the new outdoors-based Alpha School. They do their AI-powered academics in two hours, then spend the rest of the day exploring and learning outside. I couldn’t be more jealous.

How do you correctly pass a large RL-trained teacher's "change" on to a smaller student? The answer turned out to be hiding in the training process, not just the endpoints. Title: Waypoint-OPD: Transferring RL-Induced Policy Shifts via Gated On-Policy Distillation URL: Researchers at Alibaba Cloud propose Waypoint-OPD, a distillation method that uses an intermediate checkpoint from the teacher's RL training to sharpen what gets transferred to the student. Highlight 1 🧭 Checking direction, not just the endpoint Standard distillation only compares before and after training. Waypoint-OPD adds a mid-training checkpoint and measures, via cosine similarity, whether the first-half and second-half policy shifts point the same direction. Tokens where the directions disagree get automatically down-weighted. Highlight 2 📈 Consistent gains across math and code Across Qwen3-8B/14B/30B-A3B, it beats Direct-OPD on all 7 math benchmarks and all 5 code benchmarks tested, improving by 1.59-2.18 points on math and 1.19-2.66 points on code. Qwen3-14B even surpasses its own teacher model on all 7 math benchmarks. Highlight 3 ⚙️ Lightweight and robust The only extra cost is one additional scoring pass through the frozen teacher, no new trainable parameters or verifier calls needed. Moving the mid-training checkpoint between RL steps 500, 600, and 700 changes the score by only 0.05 points, so the exact choice barely matters. Exploiting the direction of training dynamics, something endpoint-only comparisons simply can't see, improves distillation quality at almost no extra compute cost. #Distillation# #ReinforcementLearning#

“We expect to exceed this year’s ROTCE target of 10-11%, even as we pull forward the investments to support our near-term target of 11-13%. But these are simply the next waypoints in our path to reach 14-15% in a sustainable manner, which we will do.” – Jane Fraser, Chair & CEO

Dominic Guay has a convenient exception. At Ubisoft he helped ship Watch Dogs worlds that trained players to chase a marker until the map went quiet. Now Invoke is selling Warlock: Dungeons & Dragons as the game with no AAA waypoints, because a find should feel earned, not assigned. They already knew the icon kills curiosity. They built the icon. They watched it work. The compass can still hide. The map is just thinner. The lecture is new. The résumé isn’t. Wizards didn’t hire a man who suddenly hates waypoints. They hired a man who already sold them, and now needs a 2027 D&D open world that cannot look like Watch Dogs.

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One of the coolest parts of Gunship Origins is going to be planning out missions. You can just jump in the cockpit and lift off, head straight for the objective. It's not very smart, but you can do that. Or, you can use up to 9 waypoints and a relief map to plan a route through valleys, sneaking up behind objectives, tankbusting while masking behind ridges, and RTBing before they even know you're there.

Hey @Tesla, two things immediately come to mind that would make the Fleet API even more powerful. Expose the active Driver Profile. This would allow applications to accurately log who was in control of the vehicle, improve fleet auditing and compliance, personalize automations, and provide much richer reporting for shared vehicles. Support multiple waypoints in the Route Planner API. Many commercial and enterprise use cases require multi-stop routing, including healthcare transportation, field service, inspections, deliveries, and future autonomous operations. Sending one destination at a time limits what’s possible. Both additions would significantly expand what’s possible for developers building on the Tesla ecosystem.