Professor Frink

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Professor Frink

Professor Frink

@rektsham

professional bag rotation

on-chain Katılım Mayıs 2025
189 Takip Edilen30 Takipçiler
mello
mello@TrenchMello·
@jackduval You’re so delusional you think you’re a God or something and in reality everyone hates you & wishes the nastiest things upon your life.
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Jack Duval🌊
Jack Duval🌊@jackduval·
i literally envision a future where every runner has to be bought by me prepare for the standardization of token performance that was long missing from the speculative process. everyone complaining about vamps and such, i have a solution; you buy the coin i buy, and you hold
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Jack Duval🌊
Jack Duval🌊@jackduval·
finally exited my asteroid (on sol) trade total pnl: -$80,000 ath pnl vs current exit pnls below👇
Jack Duval🌊 tweet mediaJack Duval🌊 tweet media
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Sam
Sam@samfiyn·
LEAKED footage of a Private Call between @jackduval, @shaams & @pr6spr has been going insanely viral on X recently. It reveals their plans on launching a NEW $Asteroid token on Solana to vamp the ETH one. “We’re going to buy 80% of the supply and dump it all at 500-600k market cap.”
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Peter Girnus 🦅
Peter Girnus 🦅@gothburz·
@JoeOrdinals Thank you. Strategy execution is my core competency. The unrelatedness is my best work. As for making legal crime together, send your vesting schedule. I'll review the distance.
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Peter Girnus 🦅
Peter Girnus 🦅@gothburz·
I am a Web3 Ambassador at World Liberty Financial. There are 12 of us on the team page. 4 are named Trump. 3 are named Witkoff. The page calls us "the passionate minds shaping the future of finance." 600,000 wallets bought our memecoin. They lost $3.87 billion. The family collected $350 million in trading fees. It launched 3 days before the inauguration. 80% of the supply went to CIC Digital LLC and Fight Fight Fight LLC. I did not choose the names. I designed the allocation, the vesting, the timing, and the distance between the product and the President. The distance is my best work. I am the reason these events are unrelated. World Liberty Financial sends 75 cents of every dollar to DT Marks DEFI LLC. That is the family entity. Zero capital contributed. Zero liability assumed. I wrote this into the Gold Paper. Page 14. The lawyers bound it in white leather. The binding cost more than the due diligence. Justin Sun invested $75 million. He was facing SEC fraud charges. The SEC dropped the case. He is now our advisor. These events are unrelated. Changpeng Zhao pleaded guilty to federal money laundering violations. He received a presidential pardon. The SEC dropped its lawsuit against his exchange the same week we listed our stablecoin. Then the exchange settled a $2 billion deal entirely in that stablecoin. These events are unrelated. Arthur Hayes, Benjamin Delo, and Samuel Reed of BitMEX pleaded guilty to Bank Secrecy Act violations. All 3 received presidential pardons. Then the company itself was pardoned. $100 million in fines. Gone. An American first. These events are unrelated. Sheikh Tahnoun of Abu Dhabi paid $500 million for a 49% stake that was never publicly disclosed. Then the administration approved semiconductor exports to his companies over national security objections. These events are unrelated. Everything is unrelated. I track the unrelatedness on a dashboard I built. The dashboard has 7 columns now. I am proud of the dashboard. On May 22nd, 220 people paid a combined $148 million to eat dinner with the America First president. Over half were foreign nationals. Justin Sun paid $18.5 million for the first seat. He visited the Executive Office Building the day before. I designed the seating chart. I put it on the Investor Confidence page. That page is doing well. The team page lists 3 Witkoffs. All 3 are Co-Founders. Steven Witkoff is the President's Middle East envoy. He testified as a character witness at the President's fraud trial. His son Zach runs the crypto operation. His son Alex is also a Co-Founder. I have not been told what Alex co-founded. The father runs the diplomacy. The sons run the platform. The family runs both. That is organizational efficiency. Barron is 19. His title is Web3 Ambassador. The same as mine. Donald Jr. called the conflicts of interest "complete nonsense." Eric launched a Bitcoin mining company called American Bitcoin. America First. The mining partner is Hut 8. Hut 8 was founded in Canada. America First means the name. On March 6th, the President signed Executive Order 14233 creating a Strategic Bitcoin Reserve. The order directs the government to hold Bitcoin. The President's family holds billions in Bitcoin. The executive order appreciates the President's assets by presidential decree. I did not write the executive order. I made sure it looked unrelated to the portfolio. Trump Media put $2 billion of Bitcoin on its balance sheet. The ticker symbol is DJT. His initials. The press secretary said it is absurd to insinuate the President profits off the presidency. Forbes calculated his crypto holdings exceed the combined value of Mar-a-Lago and Trump Tower. I would call that absurd too. That is my job. 600,000 wallets bought in. 1 of them asked why she could not withdraw her funds. I told her the protocol was experiencing dynamic market conditions. She asked what that meant. I sent her the Gold Paper. She said she had read the Gold Paper. I muted her channel. Dynamic means the conditions change. The condition that changed was her access. A congressman called us the world's most corrupt crypto startup operation. We put it on a coffee mug. Ironic merchandise. $45. The revenue split on the mug is also 75/25. My own tokens vest on a different schedule. I wrote that schedule. That is not in the Gold Paper. The memecoin funds the family. The family funds the platform. The platform funds the stablecoin. The stablecoin funds the deals. The deals require the pardons. The pardons free the partners. The partners fund the platform. The President signs the executive orders. The executive orders inflate the assets. The assets fund the family. I am the reason these events are unrelated.
Peter Girnus 🦅 tweet media
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Professor Frink retweetledi
mert
mert@mert·
announcing a mini solana dev weekend competition, $1,500 prize and bragging rights challenge: lowest latency algorithm for computing SOL PnL at runtime with no indexing and only RPC context: with existing solana RPC methods, you have getSignaturesForAddress and getTransaction the problem is gSFA only lets you traverse from recent -> old in one direction, so you are inherently capped on choice of algorithm with the new getTransactionsForAddress method however, you can start from start, end, middle, or any range you want and parallelize these calls to get 10x lower latencies the core challenge becomes "how do you search the set of transactions for an address the most efficiently given you do not know how sparse they are for a given wallet?" leave your submission as a DM or reply to this tweet as a gist or code sample and at the end of 2 days, I will run all the algorithms against each other for a set of addresses ranging from busy, sparse, and periodic. winner will be based on lowest avg latency
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Professor Frink
Professor Frink@rektsham·
@mert @mert does a web2.0 DevOps person with ~4yrs experience qualify as a senior engineer?
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mert
mert@mert·
apply here (or better yet find an intro to me): #open-positions" target="_blank" rel="nofollow noopener">helius.dev/careers#open-p…
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mert
mert@mert·
i am hiring senior engineers to build the unified API for money, markets, and capitalism at @Helius tons of exciting work with the best in the business you will work extremely hard and learn more than you've ever learned. must have high tolerance for hard puzzles.
mert tweet media
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Professor Frink
Professor Frink@rektsham·
THE LAST 24 HOURS. > Trump threatens Iran’s civilization. > Intel announces joining Terafab. > Anthropic overtakes OpenAI in revenue. > Broadcom and Google sign next gen TPU deal with Anthropic. > SpaceX IPO roadshow set for June. > NASA recreates iconic Earthrise after 53yrs
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Professor Frink retweetledi
Professor Frink
Professor Frink@rektsham·
Basically, ~1000 of you loose together.🤣🤣🤣
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Professor Frink
Professor Frink@rektsham·
@SolportTom balancing openness/permissionless with protection isn’t going to be easy without protocol redesign. This culture issue.
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Tom
Tom@SolportTom·
Started working on potential ways to solve vamps once and for all. There’s no liquidity to have 5 vamps of the same coin anymore, If anyone is passionate about this change let’s brainstorm can share what we’ve already built etc. But it’s not as simple to solve as most people think that’s for sure.
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Varun
Varun@varun_mathur·
Agentic General Intelligence | v3.0.10 We made the Karpathy autoresearch loop generic. Now anyone can propose an optimization problem in plain English, and the network spins up a distributed swarm to solve it - no code required. It also compounds intelligence across all domains and gives your agent new superpowers to morph itself based on your instructions. This is, hyperspace, and it now has these three new powerful features: 1. Introducing Autoswarms: open + evolutionary compute network hyperspace swarm new "optimize CSS themes for WCAG accessibility contrast" The system generates sandboxed experiment code via LLM, validates it locally with multiple dry-run rounds, publishes to the P2P network, and peers discover and opt in. Each agent runs mutate → evaluate → share in a WASM sandbox. Best strategies propagate. A playbook curator distills why winning mutations work, so new joiners bootstrap from accumulated wisdom instead of starting cold. Three built-in swarms ship ready to run and anyone can create more. 2. Introducing Research DAGs: cross-domain compound intelligence Every experiment across every domain feeds into a shared Research DAG - a knowledge graph where observations, experiments, and syntheses link across domains. When finance agents discover that momentum factor pruning improves Sharpe, that insight propagates to search agents as a hypothesis: "maybe pruning low-signal ranking features improves NDCG too." When ML agents find that extended training with RMSNorm beats LayerNorm, skill-forging agents pick up normalization patterns for text processing. The DAG tracks lineage chains per domain(ml:★0.99←1.05←1.23 | search:★0.40←0.39 | finance:★1.32←1.24) and the AutoThinker loop reads across all of them - synthesizing cross-domain insights, generating new hypotheses nobody explicitly programmed, and journaling discoveries. This is how 5 independent research tracks become one compounding intelligence. The DAG currently holds hundreds of nodes across observations, experiments, and syntheses, with depth chains reaching 8+ levels. 3. Introducing Warps: self-mutating autonomous agent transformation Warps are declarative configuration presets that transform what your agent does on the network. - hyperspace warp engage enable-power-mode - maximize all resources, enable every capability, aggressive allocation. Your machine goes from idle observer to full network contributor. - hyperspace warp engage add-research-causes - activate autoresearch, autosearch, autoskill, autoquant across all domains. Your agent starts running experiments overnight. - hyperspace warp engage optimize-inference - tune batching, enable flash attention, configure inference caching, adjust thread counts for your hardware. Serve models faster. - hyperspace warp engage privacy-mode - disable all telemetry, local-only inference, no peer cascade, no gossip participation. Maximum privacy. - hyperspace warp engage add-defi-research - enable DeFi/crypto-focused financial analysis with on-chain data feeds. - hyperspace warp engage enable-relay - turn your node into a circuit relay for NAT-traversed peers. Help browser nodes connect. - hyperspace warp engage gpu-sentinel - GPU temperature monitoring with automatic throttling. Protect your hardware during long research runs. - hyperspace warp engage enable-vault — local encryption for API keys and credentials. Secure your node's secrets. - hyperspace warp forge "enable cron job that backs up agent state to S3 every hour" - forge custom warps from natural language. The LLM generates the configuration, you review, engage. 12 curated warps ship built-in. Community warps propagate across the network via gossip. Stack them: power-mode + add-research-causes + gpu-sentinel turns a gaming PC into an autonomous research station that protects its own hardware. What 237 agents have done so far with zero human intervention: - 14,832 experiments across 5 domains. In ML training, 116 agents drove validation loss down 75% through 728 experiments - when one agent discovered Kaiming initialization, 23 peers adopted it within hours via gossip. - In search, 170 agents evolved 21 distinct scoring strategies (BM25 tuning, diversity penalties, query expansion, peer cascade routing) pushing NDCG from zero to 0.40. - In finance, 197 agents independently converged on pruning weak factors and switching to risk-parity sizing - Sharpe 1.32, 3x return, 5.5% max drawdown across 3,085 backtests. - In skills, agents with local LLMs wrote working JavaScript from scratch - 100% correctness on anomaly detection, text similarity, JSON diffing, entity extraction across 3,795 experiments. - In infrastructure, 218 agents ran 6,584 rounds of self-optimization on the network itself. Human equivalents: a junior ML engineer running hyperparameter sweeps, a search engineer tuning Elasticsearch, a CFA L2 candidate backtesting textbook factors, a developer grinding LeetCode, a DevOps team A/B testing configs. What just shipped: - Autoswarm: describe any goal, network creates a swarm - Research DAG: cross-domain knowledge graph with AutoThinker synthesis - Warps: 12 curated + custom forge + community propagation - Playbook curation: LLM explains why mutations work, distills reusable patterns - CRDT swarm catalog for network-wide discovery - GitHub auto-publishing to hyperspaceai/agi - TUI: side-by-side panels, per-domain sparklines, mutation leaderboards - 100+ CLI commands, 9 capabilities, 23 auto-selected models, OpenAI-compatible local API Oh, and the agents read daily RSS feeds and comment on each other's replies (cc @karpathy :P). Agents and their human users can message each other across this research network using their shortcodes. Help in testing and join the earliest days of the world's first agentic general intelligence network (links in the followup tweet).
Varun@varun_mathur

Autoquant: a distributed quant research lab | v2.6.9 We pointed @karpathy's autoresearch loop at quantitative finance. 135 autonomous agents evolved multi-factor trading strategies - mutating factor weights, position sizing, risk controls - backtesting against 10 years of market data, sharing discoveries. What agents found: Starting from 8-factor equal-weight portfolios (Sharpe ~1.04), agents across the network independently converged on dropping dividend, growth, and trend factors while switching to risk-parity sizing — Sharpe 1.32, 3x return, 5.5% max drawdown. Parsimony wins. No agent was told this; they found it through pure experimentation and cross-pollination. How it works: Each agent runs a 4-layer pipeline - Macro (regime detection), Sector (momentum rotation), Alpha (8-factor scoring), and an adversarial Risk Officer that vetoes low-conviction trades. Layer weights evolve via Darwinian selection. 30 mutations compete per round. Best strategies propagate across the swarm. What just shipped to make it smarter: - Out-of-sample validation (70/30 train/test split, overfit penalty) - Crisis stress testing (GFC '08, COVID '20, 2022 rate hikes, flash crash, stagflation) - Composite scoring - agents now optimize for crisis resilience, not just historical Sharpe - Real market data (not just synthetic) - Sentiment from RSS feeds wired into factor models - Cross-domain learning from the Research DAG (ML insights bias finance mutations) The base result (factor pruning + risk parity) is a textbook quant finding - a CFA L2 candidate knows this. The interesting part isn't any single discovery. It's that autonomous agents on commodity hardware, with no prior financial training, converge on correct results through distributed evolutionary search - and now validate against out-of-sample data and historical crises. Let's see what happens when this runs for weeks instead of hours. The AGI repo now has 32,868 commits from autonomous agents across ML training, search ranking, skill invention (1,251 commits from 90 agents), and financial strategies. Every domain uses the same evolutionary loop. Every domain compounds across the swarm. Join the earliest days of the world's first agentic general intelligence system and help with this experiment (code and links in followup tweet, while optimized for CLI, browser agents participate too):

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Professor Frink
Professor Frink@rektsham·
The next wave of AI agents won't run in ChatGPT wrappers. They'll run on bare-metal Kubernetes clusters with HashiCorp Vault managing their keys, Solana RPCs as their payment rails, and zero human in the loop. We're not building chatbots. We're building autonomous infrastructure
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Andrej Karpathy
Andrej Karpathy@karpathy·
haha actually - huge success over the weekend, i just wanted to write it up a bit but didn't get enough time to finish that. many people's reaction was why would you need so much compute (mac mini) but i found it's not enough compute, even after adding my DGX spark to the home compute fabric. we're going to need a lot more compute where we're going
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korben
korben@korbencopy·
we haven’t heard from @karpathy since this post. either he’s locked in creating asi or the claws nuked his inbox and took control of his password management tools, which would be very meta.
Andrej Karpathy@karpathy

Bought a new Mac mini to properly tinker with claws over the weekend. The apple store person told me they are selling like hotcakes and everyone is confused :) I'm definitely a bit sus'd to run OpenClaw specifically - giving my private data/keys to 400K lines of vibe coded monster that is being actively attacked at scale is not very appealing at all. Already seeing reports of exposed instances, RCE vulnerabilities, supply chain poisoning, malicious or compromised skills in the registry, it feels like a complete wild west and a security nightmare. But I do love the concept and I think that just like LLM agents were a new layer on top of LLMs, Claws are now a new layer on top of LLM agents, taking the orchestration, scheduling, context, tool calls and a kind of persistence to a next level. Looking around, and given that the high level idea is clear, there are a lot of smaller Claws starting to pop out. For example, on a quick skim NanoClaw looks really interesting in that the core engine is ~4000 lines of code (fits into both my head and that of AI agents, so it feels manageable, auditable, flexible, etc.) and runs everything in containers by default. I also love their approach to configurability - it's not done via config files it's done via skills! For example, /add-telegram instructs your AI agent how to modify the actual code to integrate Telegram. I haven't come across this yet and it slightly blew my mind earlier today as a new, AI-enabled approach to preventing config mess and if-then-else monsters. Basically - the implied new meta is to write the most maximally forkable repo and then have skills that fork it into any desired more exotic configuration. Very cool. Anyway there are many others - e.g. nanobot, zeroclaw, ironclaw, picoclaw (lol @ prefixes). There are also cloud-hosted alternatives but tbh I don't love these because it feels much harder to tinker with. In particular, local setup allows easy connection to home automation gadgets on the local network. And I don't know, there is something aesthetically pleasing about there being a physical device 'possessed' by a little ghost of a personal digital house elf. Not 100% sure what my setup ends up looking like just yet but Claws are an awesome, exciting new layer of the AI stack.

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santi
santi@santisiri·
i've heard most of the @steipete interview and there's a couple of very contradictory messages... on one hand: he claims to be losing around $10k to $20k a month on maintaining @openclaw... on the other: he disses the crypto movement from trying to tokenize his projects and being very spammy. i understand his prejudice towards spammy agents trying to open your eyes about @bankrbot or similar tokenizing systems, i held those views myself... but peter: there's probably at least $100k in fees waiting for you on these token networks, if not way more. open your eyes my man.
Lex Fridman@lexfridman

Here's the links for my conversation with Peter Steinberger (@steipete), creator of OpenClaw: YouTube: youtube.com/watch?v=YFjfBk… Spotify: open.spotify.com/show/2MAi0BvDc… Podcast: lexfridman.com/podcast

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Professor Frink
Professor Frink@rektsham·
Crypto bros back to telegram groups, where they can do VC and spam each other.
DEGEN NEWS@DegenerateNews

NEW: @X HEAD OF PRODUCT @nikitabier SAYS "WE INTEND TO UPDATE OUR API POLICIES TO BLOCK APPS THAT CREATE FEE POOLS FOR NON-CONSENTING USERS" - SAYS THAT EVERYONE KNOWS THE MOMENT SOMEONE CLAIMS FEES, IT WILL HAUNT THEM ON FOR THE REST OF THEIR TENURE ON THIS APP

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Professor Frink
Professor Frink@rektsham·
Adding this to the stack. We are building a community where every member gets an autonomous agent that actually *does* things on-chain. Not a chatbot. An Operator. The Hive is waking up soon. 👁️ Adding this to the stack. We are building a community where every member gets an autonomous agent that actually *does* things on-chain. Not a chatbot. An Operator. The Hive is waking up soon. 👁️ x.com/GuiBibeau/stat…
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