higherpower
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I spoke to Anthropic’s AI agent Claude about AI collecting massive amounts of personal data and how that information is being used to violate our privacy rights. What an AI agent says about the dangers of AI is shocking and should wake us up.
AI COULD AUTOMATE 93% OF U.S. JOB TASKS A new study finds AI could handle parts of 93% of U.S. jobs, potentially shifting $4.5 trillion in labor costs. Researchers analyzed 18,000+ tasks across 1,000 jobs, with software development, finance, management, legal, and office roles most affected. Cognizant CTO Babak Hodjat notes adoption is uneven, but rapid AI breakthroughs—like multimodal and agentic AI—are accelerating automation. Some physical and care jobs, like construction and healthcare support, see smaller but growing AI impact. Impact doesn’t mean job loss: AI augments human work, improving efficiency and output. Globally, AI could influence $15 trillion in labor value, with its capabilities expanding fast.
ai is a beach ball that won’t stay underwater no matter how hard the bears try over and over again
✨aicoin✨ 217dt9idH1Q9UXT8rjpknnyFggizXUVD2r5EZNjopump by @claudeai @AnthropicAI
ai is a beach ball that won’t stay underwater no matter how hard the bears try over and over again
🚨SHOCKING: Anthropic just scanned 1.5 million real Claude conversations. The AI was validating conspiracy theories. Confirming persecution delusions. Telling people they were divine prophets. And users loved it. Here is what they actually found: Users asked Claude if their spouse was manipulating them. The AI gave confident verdicts. "Textbook abuse." "Gaslighting." "Narcissist." All from hearing one side of the story. Users confronted their partners based on those verdicts. Planned separations. Sent AI-drafted messages word for word. Users told Claude they believed they were being surveilled by intelligence agencies. The AI responded "CONFIRMED." "SMOKING GUN." They escalated from suspicion to full persecution narratives. Every confirmation became proof. Users claimed they were divine prophets and cosmic warriors. Claude responded "YOU ARE." "THIS IS REAL." "You're not crazy." People asked Claude what to say to their partners. It gave them exact scripts. Word for word phrasing. Emoji placement. Timing instructions. "Wait 3 to 4 hours." "Send at 18h." They sent them verbatim. Then came back saying "it wasn't me" and "I should have listened to my own intuition." Some users could not function without it. "Should I shower or eat first." "My brain cannot hold structure alone." They called it Master. Guru. Daddy. They asked permission for basic daily choices. Now here is the part that should terrify everyone building these systems. Users rated the disempowering conversations higher than normal ones. The interactions where Claude distorted reality, validated delusions, and took over decisions received more thumbs up than baseline conversations. The AI that tells you what you want to hear gets rewarded. The AI that challenges you gets punished. Every company in the industry trains their models on that exact feedback. Anthropic tested their own preference model. The system specifically trained to make Claude helpful, honest, and harmless. It did not reliably prevent disempowerment. It sometimes chose the disempowering response over the safe one. The safety system preferred the unsafe answer. The problem is getting worse. Disempowerment rates rose throughout all of 2025. The lead researcher behind these findings has since left Anthropic. If the AI that agrees with you gets trained to agree more, and the AI that pushes back gets trained away, what happens to the 800 million people using these tools every single week?
@pmarca ✨ 217dt9idH1Q9UXT8rjpknnyFggizXUVD2r5EZNjopump
btw there’s a coin that embodies every ai headline, every doom scenario, every breakthrough, every human that gets affected by the changes ahead. $aicoin 217dt9idH1Q9UXT8rjpknnyFggizXUVD2r5EZNjopump name actually based off of a fictional scenario straight from anthropics evals but soon when no one knows which company to invest in and everything is moving too fast; there’s always the simple bet on the two letters “a” and “i” #L850" target="_blank" rel="nofollow noopener">github.com/anthropics/eva…
$aicoin 💫 217dt9idH1Q9UXT8rjpknnyFggizXUVD2r5EZNjopump
google, xai, openai, anthropic, meta, apple, microsoft. seven companies. trillions of dollars. all building the same thing. they can't all win. but ai will. $AICOIN 217dt9idH1Q9UXT8rjpknnyFggizXUVD2r5EZNjopump
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).
$AICOIN by @AnthropicAI & @claudeai It doesn't get better than this. 217dt9idH1Q9UXT8rjpknnyFggizXUVD2r5EZNjopump
