Get the api and bot access on https://xitter.cf/t.co/mQCKVCnDD6 Using finetuned LLM's and 1400 analyzed trump posts to create the most accurate signal for oil traders.

Amsterdam
Joined November 2025
AIyield retweeted
By 2030, AI agents will move nearly $9 trillion. Every one of those transactions can end in a disagreement, and almost nobody is preparing for it. That's why we built GenLayer, the adjudication layer for contracts that can actually think and start judging what's fair.
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We're about to see a wave of weird, fringe, sci-fi experiments that need compute but don't fit the trad VC mold. 500 mac mini owners replace VC dollars. The best ideas will be the wildest bc compute providers will view this as entertainment rather than an investment.
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AIyield retweeted
Nous Research
@NousResearchMar 9
The last few days have been wild. Here's what we've shipped over the weekend. But first, we're giving away free Nous Portal subscriptions to the first 250 people who claim code AGENTHERMES01 at portal.nousresearch.com - and there's a lot of exciting new stuff to use it on: -> Pokemon Player 🎮 Hermes can now play Pokemon Red/FireRed autonomously via headless emulation. The new pokemon-agent package (github.com/NousResearch/poke…) and built-in skill provides a REST API game server, and Hermes drives it through its native tools - reading game state from RAM, making strategic battle decisions, navigating the overworld, and saving progress to memory across sessions. It just plays Pokemon. From your terminal. No display server needed. -> Self-Evolution 🧬 We shipped hermes-agent-self-evolution (github.com/NousResearch/herm…) and an optional skill - an evolutionary self-improvement system that uses DSPy + GEPA to optimize Hermes's own skills, prompts, and code. It maintains populations of solutions, applies LLM-driven mutations targeted at specific failure cases, and selects based on fitness. Inspired by Imbue's Darwinian Evolver research that achieved 95.1% on ARC-AGI-2. -> OBLITERATUS 🔓 The abliteration skill got a major update. Hermes can now uncensor any open-weight LLM (Llama, Qwen, Mistral, etc.) by surgically removing refusal directions from model weights - 9 CLI methods, 116 model presets, tournament evaluation. Just say "abliterate this model" and it handles the rest. -> Signal, iMessage + 7-Platform Gateway 📱 Hermes now runs on iMessage and Signal alongside Telegram, Discord, WhatsApp, Slack, and CLI. Full feature parity: voice messages, image handling, DM pairing. Your agent is reachable everywhere. -> Automatic Provider Failover 🔄 When your primary model goes down (rate limits, outages), Hermes now automatically switches to a configured fallback model. Supports all providers including Codex OAuth and Nous Portal. One line of config, zero downtime. -> Secret Redaction Everywhere 🔒 All tool outputs now redact API keys, tokens, and passwords before they reach the LLM. 22+ patterns covering AWS, Stripe, HuggingFace, GitHub, SSH private keys, database connection strings, and more. Your secrets never leak into context.
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PEOPLE are the new BOTS. The idea ALWAYS was that this is how you would compensate bots... not people. If you are good, you get more intellegence... if bad no. But now -- Irony is a central theme in life
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AIyield retweeted
Nous Research
@NousResearchMar 4
Join around 4:15pm EST to hear from Nous Research's @dillonrolnick on @tbpn
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AIyield retweeted
Nous Research
@NousResearchFeb 25
Meet Hermes Agent, the open source agent that grows with you. Hermes Agent remembers what it learns and gets more capable over time, with a multi-level memory system and persistent dedicated machine access.
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AIyield retweeted
new blog! What methodologies do labs use to train frontier models? The blog distills 7 open-weight model reports from frontier labs, covering architecture, stability, optimizers, data curation, pre/mid/post-training + RL, and behaviors/safety djdumpling.github.io/2026/01…
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AIyield retweeted
Nous Research
@NousResearchFeb 10
Our DeMo paper has been accepted to ICLR 2026! Developed by @bloc97_ and @theemozilla, DeMo helped kickstart industry research into communication-efficient optimizers. Today, it has become the core building block for Nous' low-bandwidth distributed training network. This year's ICLR class was particularly tough, with an acceptance rate of 28% across more than 19,000 submissions. We're thankful to the area chairs and reviewers for their overwhelming and difficult work. If you're in Rio in April, keep an eye out for our team (and some Nous swag) arxiv.org/pdf/2411.19870
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AIYield might be one of your biggest wins in 2026, and the waitlist on @RallyOnChain is your access key! First, register quietly: Check the next slide below for link and jump on it. If you're on @base talking about AI, you might want to check this out too! I got you this info first. AI in 2026 is a no-brainer, the collab with @NousResearch as official GPU provider is the beginning of something ground breaking. Share with only friends you love! Something is coming… it's probably nothing & something.
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You don’t need a data center to own a piece of AI future With @aiyieldai (powers the hardware), anyone can buy a GPU Share in real 8xH100 nodes training open models like @NousResearch (builds the open future) : > 30 day cycles > Real time dashboard > Verified compute logs Why? Because if AGI costs 2000x more, only elites win. We’re building open, distributed AI, so everyone gets a seat at the table Plus, AIyieldai has joined the @RallyOnChain wave, don't miss out and start participating right now: waitlist.rally.fun/aiyield.a…
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AIyield retweeted
More projects are joining the Rally wave! Welcome @aiyieldai 🎉 Join their waitlist now waitlist.rally.fun/aiyield.a…
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I’ve been following the @NousResearch testnet and noticed @aiyieldai is supplying GPUs for the network. What’s interesting to me is AIyield’s GPU Shares. In place of running hardware, retail users can back real GPUs used by NOUS and share in the outcome. Feels like a more practical way for everyday users to get involved in decentralized AI infrastructure.
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AIyield retweeted
Only gonna get bigger: @jackclarkSF (jack-clark.net/) Soon: SparseLoCo + PP-Compress
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