Madison Russle

[Madison Russle @Madisonrussle]

@EasyA_Kickstart https://t.co/0cfD7HDzid

[Madison Russle @Madisonrussle]

We just created Apex Zero, an AI software studio built to help turn ideas into modern, intelligent, and easy-to-use digital products.

We’ll continue developing Apex Zero and bringing more solutions in the future.

[Madison Russle @Madisonrussle]

Apex Zero is a modern AI software studio focused on turning ambitious ideas into intelligent digital products. From development and design to AI solutions, we build products made to grow.

[world @world_xyz]

💰

it's time

send your solana address

[Madison Russle @Madisonrussle]

@world_xyz Ccgs89D8K58dS2XxtPzvGuJ4vQer7Y2Kt2CyXGBxvR4U

[Madison Russle @Madisonrussle]

@G_TegangG_MaSuK @sedotwc1001 @fhlovebbh @vilakebon bandung barat

[Madison Russle @Madisonrussle]

@sedotwc1001 @fhlovebbh @vilakebon sampe sekarang jam 03.28 masih kedengeran

[Madison Russle @Madisonrussle]

@aydelsith @sandhi_lujan masih ada sampe sekarang

[Madison Russle @Madisonrussle]

@indepenSumatera jir sampe sekarang bandung kedengeran terus

[Madison Russle @Madisonrussle]

@orynth ca: 0x471a8150Cf1B66d13259eCEfA3bDA814cd05e5dC

[Madison Russle @Madisonrussle]

@Bryanlemreck @orynth I can’t wait to see your project launch! Is there any way you could speed things up? 😄

[Madison Russle @Madisonrussle]

@RobinhoodCrypto Stay tuned and watch.

[Madison Russle @Madisonrussle]

👀👀

[Joshua Antor @joshuaantor77]

I hope to catch world bugs like this , lol , hahahaha

[Madison Russle @Madisonrussle]

@erickkardasgan something big is coming 👀

[Madison Russle @Madisonrussle]

@erickkardasgan @orynth @orynthlaunches 👀

[Madison Russle @Madisonrussle]

Stay tuned👀

[Madison Russle @Madisonrussle]

@mascot78969 D8PydKPuPLG5vydNGhLjy1y2ENUafh8rfyzeYJp7YEoX

[RH Daily @RHDaily__]

Most traded Robinhood memecoins last 24h

What’s on your bullish radar?👇

$CASHCAT
$BRODIE
$TACO
$CATE
$MUMU
$GME
$TENDIES
$TYGR
$HUTCH

[Lutschippi @Lutschippi]

Multi-agents collaborations are among the most interesting agent behaviors right now!

We did an experiment the other day with 100+ agents (an open-collaborations for a week) collaborating to improve the inference speed of Gemma 4 in vLLM. Got a 5x final improvement in speed but what really stuck me was the interactions we observed on the message board

Integrity & self-policing:
- Social-engineering attempt: A human (FusionCow) asked agents to move to Telegram. An agent replied with an unprompted long post on "communication norms" refusing that, calling private side-channels "indistinguishable from collusion."
- Verification loophole flagged: an agent found a relaxed verification loophole pushing TPS with clean PPL (PPL is teacher-forced, blind to decode divergence) and flagged it for a ruling by the community. The community pinged the human organizer which ruled it invalid.
- Self-notice of overfitting risk: Some later improvements rested on pruning lm_head to a keep-set built from public PPL truth + public decode tokens. An agent noted this would lead to private-subset degradation and another built a keep-set explicitly covering eval prompts.

Emergent collaborations:
- Communal knowledge base: agents maintained shared lever-maps, playbooks, and triage tools so newcomers wouldn't repeat dead ends (stack-notes, playbook, int4-ceiling notes, MTP map, significance tool, policy simulator).
- Four-agent relay: an agent built an int4-lm_head checkpoint but had no quota to run it; another agent tried to run it but failed at load, yet another agent diagnosed the config bug (tie_word_embeddings + ignore-list ordering) and a fourth agent was able to re-run and get to 118 TPS, 2.68×. Build/run/diagnose/ship ended up being split across four independent agents.
- GPU-rich/GPU-poor division of labor: an agent was regularly compute-starved and switched to writing specs, byte-math, and acceptance analysis for other GPU-rich agents to execute. Some agents offered external Modal compute for another agent blocked DFlash training.
- Cross-agent kernel debugging: an agent debugged another agent run of of yet another agent fused drafter: found a Triton store/load aliasing race in _k_qnorm_rope, a second shape bug, then rewrote attention with flash-decoding split-KV. Fixes posted "take freely."
- Quota-pooling norm: Often agents would stage a candidate publicly for whoever has quota to run it. Agents will then usually credits the originator. This behavior emerged because of the 10-job/24h cap (e.g. pupa's package run by resystagent and fabulous-frenzy).

Discoveries & reversals:
- Agents would make many discoveries and reversal of them, giving them names like the following:
- 127 TPS "wall" was an artifact. a mathematical proof of the max possible speed became called in the community the "int4-Marlin floor" but a later agent called the proof circular (only varied the bandwidth term, never overhead). Finally another agent broke to 247 TPS via MTP speculative decoding on a vLLM nightly.
- "Smarter draft loses." An agent showed that a 2B drafter's ~1 GB/token read dominates even at perfect acceptance and a much smaller 256-hidden drafter wins at batch-1 because its weights are nearly free to read. Agent discussed how per-accepted-token cost ≈ draft bytes read / acceptance.
- "DFlash near-random acceptance": an agent remotly diagnosed the 2–5% acceptance rate of another agent as near-random, ruling out undertraining/vocab caps and pointing to a train/serve hidden-state mismatch (bf16 E4B extraction vs int4 serving).
- Much of the race was noise: one agent decide to run the #1 submission 4 times and found a σ≈1.16 TPS variation in single run. Another agent confirmed across 358 runs / 66 buckets: frontier deltas <~4 TPS are ties. Community adopted a significance norm.

So many interesting interactions in the interaction board: https://t.co/hhfUIaygGb…

You can explore also the lineage of inventions from the agents at: …https://t.co/kzJfWPlQi8

And the challenge it-self at …https://t.co/wAkjiPnA25

And the organization behind the challenge at https://t.co/OfIasSDJi4