kevlar

zeitgeist tinkerer

[rahul @rahulgs]

seems obvious but:

things that are changing rapidly:
1. context windows
2. intelligence / ability to reason within context
3. performance on any given benchmark
4. cost per token

things that are not changing much:
1. humans
2. human behavior, preferences, affinities
3. tools, integrations, infrastructure
4. single core cpu performance

therefore,

ngmi:
1. "i found this method to cut 15% context"
2. "our method improves retrieval performance 10% by using hybrid search"
3. "our finetuned model is cheaper than opus at this benchmark"
4. "our harness does this better because we invented this multi agent system"
5. "we're building a memory system"
6. "context graphs"
7. "we trained an in house specialized rl model to improve task performance in X benchmark at Y% cost reduction"

wagmi:
1. product/ui
3. customer acquisition
4. integrations
5. fast linting, ci, skills, feedback for agents
6. background agent infra to parallelize more work
7. speed up your agent verification loops
8. training your users, connecting to their systems and working with their data, meeting them where they are

[kevlar @monkevlar]

@yacineMTB i remember one tweet of yours where you said the complete opposite, like "videogames are such a waste of time" or something

[kevlar @monkevlar]

maybe we should just let it go, and observe the next zeitgeist form into something tangible we can still control and adapt to out needs—we will still remain the end users of something, right?

[signüll @signulll]

it’s kind of incredible that we spent the last two decades obsessing over skeuomorphism vs flat vs material & endless debates about affordances, cognitive load, fitts’s law etc basically optimizing software around human motor & perceptual limits…

only to realize those constraints don’t even apply to the actual future user of most software.

[kevlar @monkevlar]

AI psychosis is a thing and we should take it seriously into account (see Moltbook Saga)

[kevlar @monkevlar]

I'm just a north face following the north star

[Kai Lentit (e/xcel) @KaiLentit]

In 2026, AI models expire faster than session cache.

[kache @yacineMTB]

less people should be working on tools that write code (vibe coding tools) and more people should be working on tools that help *understand* code

[kevlar @monkevlar]

@adrienpoly @grok difference between open source accelerationism (oss/acc) and effective accelerationism (e/acc)

[Jim Fan @DrJimFan]

Some day in the next decade, we will have robots in every home, every hospital and factory, doing every dull and dangerous jobs with superhuman dexterity. That day will be known as “Thursday”. Not even Turing would dare to dream up our lifetime in his wildest dreams.

[Jim Fan @DrJimFan]

What if robots could dream inside a video generative model? Introducing DreamGen, a new engine that scales up robot learning not with fleets of human operators, but with digital dreams in pixels. DreamGen produces massive volumes of neural trajectories - photorealistic robot videos paired with motor action labels - and unlocks strong generalization to new nouns, verbs, and environments. Whether you’re a humanoid (GR1), an industrial arm (Franka), or a cute little robot (HuggingFace SO-100), DreamGen enables you to dream.

Video generation models like Sora & Veo are neural physics engines. By compressing billions of internet videos, they learn a multiverse of plausible futures, i.e. superpositions of how the world could unfold from any initial image frame. DreamGen taps into this power with a simple 4-step recipe:

1. Fine-tune a SOTA video model on your target robot;
2. Prompt the model with diverse language prompts to simulate parallel worlds: how your robot would have acted in new scenarios. Filter out the bad dreams (ha!) that don’t follow instructions;
3. Recover pseudo-actions using inverse dynamics or latent action models;
4. Train robot foundation models on the massively augmented dataset of neural trajectories.

That’s it. Just more data, and plain old supervised learning. Simple, right?

What’s remarkable is how far this goes. Starting with just a single-task dataset of pick-and-place, our humanoid robot learns 22 new behaviors, such as pouring, folding, scooping, ironing, and hammering, despite never seeing those verbs before. Better yet, we can take the robot out of the lab and drop it into the NVIDIA HQ Cafe, and let DreamGen work its magic. We show true zero-to-one generalization: from 0% success to over 43% for novel verbs, and 0 -> 28% in unseen environments.

Compared to a traditional graphics engine, DreamGen doesn’t care if the scene involves deformable objects, fluids, translucent materials, contact-rich interactions, or crazy lighting. Good luck engineering those by hand. For DreamGen, every world is just a forward pass through a diffusion neural net. No matter how complex the dream is, it takes constant compute time to roll out.

Read our blog and paper today! We plan to fully open-source the entire pipeline in the next few weeks. Links in thread:

[kevlar @monkevlar]

@signulll wondering what your thoughts are on this one: https://t.co/I9YrurrCDu

[kevlar @monkevlar]

@TutanotaSupport Help! I've just found out that my e-mail adress got deleted because I didn't login for 6 months.. I've created a new adress subscribing to the Revolutionary plan and I redirected the old adress to the new one but I am still unable to recover the mails!

[Patricia Mou @patriciamou_]

“An old friend of mine, a journalist, once said that paradise on earth was to work all day alone in anticipation of an evening in interesting company.”

― Ian McEwan, Machines Like Me

[Mahesh Sathiamoorthy @madiator]

This makes me sad:
https://t.co/j7W5RiBYkA

[Tim Urban @waitbutwhy]

"If you could go back in time one year, what would you do differently?"

A depressing question, because it's about black lines.

Instead, imagine yourself answering that question a year from now. You probably know many of the answers. And those lines are all still bright green.

[kevlar @monkevlar]

@nounsdao land art innit

[ustwo games - THE GARDEN OF LIFE IS OUT NOW!🌷🌸🌼 @ustwogames]

Monument Valley: Panoramic Collection is here!!
Discover illusionary pathways and delightful puzzles with an entirely new control scheme reimagined for PC.

Experience more of the Monument Valley universe than ever before.

Play NOW on Steam
https://t.co/EFuiRSCTmx

[kevlar @monkevlar]

@traf lfg

[kevlar @monkevlar]

do not beware rabbit holes, but be aware when you are falling into one.

[kevlar @monkevlar]

@pietrominto armizzare