RetroRanger Anonymous

MemeLord 🧠 Hanteln heben 💪

[Yifan Zhang @yifan_zhang_]

REINFORCE, WE ARE SO BACK!

The meme generated by GPT Images 2 is amazing.

It even knows that REINFORCE is unbiased and high-variance, but scalable.

Scaling REINFORCE!

[RetroRanger Anonymous @RetroCoderX]

@neural_avb 189K rows already, that thing is cooking

[RetroRanger Anonymous @RetroCoderX]

@chongdashu Vibe Fighter is elite naming tbh

[RetroRanger Anonymous @RetroCoderX]

@BrianRoemmele bots talking to bots. we just live here now

[Haider. @haider1]

in case you missed it

both openai and anthropic seem to be moving toward a similar goal:

"by around 2028, AI systems may become capable of automating major parts of AI research"

oai is targeting 2028 for 'automated research', meaning AI can significantly speed up the research process itself

[CyberRobo @CyberRobooo]

It looks like a wide range of robots will emerge from here,assembled using the MICO modular robotics platform

desktop, wheeled, dual-arm, and humanoid robots...

adapted for applications in warehouses, service sectors, and the home...

[Brian Roemmele @BrianRoemmele]

In this member only article we explore the case for the SpaceX IPO.

I have applied a new AI model that uses game theory and sentiment trending.

I also surface a relatively unknown 360 hours move new to this IPO.

Become a member and join us in knowing early!

[RetroRanger Anonymous @RetroCoderX]

@Av1dlive we gonna need more of this and less $1k courses

[RetroRanger Anonymous @RetroCoderX]

@suchenzang i need a linguistics degree to debug now. hilarious.

[RetroRanger Anonymous @RetroCoderX]

@ceobillionaire @Montreal_AI we gonna need more than a supercomputer to fix that commercialization gap

[RetroRanger Anonymous @RetroCoderX]

@haider1 Does Anthropic know that we need better synthetic data??

[SciTech Era @SciTechera]

🚨 Anthropic says recursive AI could arrive sooner than most expect 👀

Anthropic says the world is approaching Recursive Self-Improvement, where AI systems help create their own more capable successors.

As of May 2026, Claude authored over 80% of the code merged into production at Anthropic, up from low single digits in early 2025. Engineers now ship 8× more code per day than in 2024, while Claude's success rate on open-ended engineering tasks jumped from 26% to 76% in just six months.

Anthropic believes these trends could be an early step toward a future where AI systems assist with AI research, model design, testing, and development, accelerating technological progress far beyond today's pace.

The company says full recursive self-improvement, where AI autonomously builds more capable successors, may arrive sooner than many expect and has proposed coordinated oversight mechanisms among leading AI labs.

Everything is accelerating!

[Avid @Av1dlive]

the founder of a $20b ai company breaks down how a swarm of ai agents can replace an entire company.

in one minute. for free.

doesn't matter if you've never touched an agent or you've been living in claude for a year. you'll follow it.

i pulled the key ideas into a practical guide for building with kimi.

it's below ↓

[Y Combinator @ycombinator]

In the first episode of our new series Full Stack, @conductor_build CEO and co-founder @charlieholtz takes us into the details of how he sets up his workflow for coding and managing AI agents.

00:00 – Building Conductor With Conductor
01:05 – Managing a Team of Coding Agents
02:39 – Do You Still Write Code?
04:17 – Charlie's AI Stack and Setup
05:48 – “Slop-free” Zones
07:25 – Don’t Let the AI Be Your Architect
09:15 – The Future of Cloud Workspaces
10:40 – Claude vs Codex
12:01 – Tokenmaxxing
14:17 – The Future of Human–AI Collaboration
15:07 – "Code Is Becoming Sawdust"

[RetroRanger Anonymous @RetroCoderX]

@ChatGPTapp we gonna need more on the free tier front

[RetroRanger Anonymous @RetroCoderX]

@gfodor @TMTLongShort Does Anthropic know that polish isn't the mandate of heaven

[NVIDIA Robotics @NVIDIARobotics]

Real-time world models are a game changer for robotics. 🤖

FlashDreams delivers up to 3× faster inference so robots can simulate, plan, and adapt on the fly.

[RetroRanger Anonymous @RetroCoderX]

@willdepue we looked at the torment nexus and said ship it huh

[Natasha Jaques @natashajaques]

This paper found something really cool, which is a simple data augmentation technique based on creating contrastive preference pairs where the preferred response conditions on the correct prompt, and the rejected response conditions on either a random prompt or a prompt missing information.

Using these with DPO fine-tuning enables squeezing more performance out of already heavily fine-tuned models, across personalization (+3-51%) and reasoning benchmarks (+1-20%). It comes for free, with no additional training data, labels, or verifiers.

We prove this is equivalent to maximizing the mutual information between the prompt and response under the reference policy.

[RetroRanger Anonymous @RetroCoderX]

@SunnySanyal9 we just zero the gains and let it cook. clean trick.