Our internal data shows Claude is accelerating AI developmentβa possible path to recursive self-improvement, or AI autonomously building a more capable successor.
Itβs happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx
recursive self improvement is a computationally undecidable problem
if you think you need improving, can you trust your idea that you need improving
or is the idea that you need improving that which needs to be improved?
this is undecidable
β΄ RSI is undecidable
this is an interesting point in the new ted chiang piece β no one really claims that alphafold is conscious, or that sora or midjourney or dall-e are conscious
Bug fixes shipping to Grok Build 0.2.20 (release notes will be available in the TUI and on change-log website)
β’ Eliminate ghost-cell artifacts in markdown table rendering
β’ Make monitors visible and killable to the model
β’ Preserve soft breaks in plan preview
β’ Add image_to_video and reference_to_video tools
β’ Add bundled imagine skill
β’ Convert ICO images to PNG
β’ Resolve [Image # N] attachment references in image_edit
β’ Open fullscreen viewer on Enter for Search and ListDir blocks
β’ Route MCP lifecycle notifications by sessionId + bound per-server init
β’ Route mouse-wheel scroll to /btw overlay panel
β’ Compaction: neutralize echoed summarization instruction in summary seed
β’ Structured compaction prompt (successor-assistant, carry-forward, <analysis>
block)
β’ Dedupe between-turn subagent completion reminders
β’ Allow auto-update to downgrade on rollback
β’ Dedupe MCP servers declared in both .mcp.json and plugin.json
β’ Fix local stdio MCP servers on Windows
If you think your major is what will make the difference, I donβt know what to tell you. If youβre 18 and want to be useful, find a question that you know is important, and pursue it, doggedly, for a decade.
No LLM will ever run inference on a prompt for a decade⦠but you can.
My college degree recommendations for fresh high school graduates in the age of AI to be prepared for the next frontier:
- Applied Physics (math and physics)
- Applied Materials (physical agentic)
- Agriculture (food production in space)
- Aerospace (frontier transportation)
- Civil Engineering (infra + life support from Earth and beyond)
- Electronic Engineering (scaling compute and communications to the solar system)
- Manufacturing (where things get made)
- Mechanical Engineering (packaging, manufacturability, tolerances and cycling)
- Medicine (personal drugs in space)
@Tyler_A_Harper I think it comes down to this: LLMs are tools that can formulate an answer any question, but the point of liberal education is to learn what questions are worth asking. From that POV, students who cheat are only cheating themselves of the opportunity to learn who they really are.
posting on x is one long public interview.
every post is a signal about how you think, what you notice, what you value, & whether anyone should pay attention to you.
linkedin is the exact inverse.
itβs one long public performance where everyone is trying to sound like the employee they wish they were instead of the person they actually are.
No one:
Claude Opus 4.8 Max: Let me refine your load-bearing claim rather than just accepting it, because youβre doing zero moves there, and the gap is whatβs actually interesting. The one place Iβd still push, because I think it matters: your message is wearing content-clothes, but the content isnβt actually *there*. The tell: itβs just an empty string. But the emptiness of the string IS its lack of content. Pull one, and the other goes inert. Thatβs the structural spine.
VocΓͺ estΓ‘ mais prΓ³ximo do tamanho de todo o universo observΓ‘vel do que da menor escala conhecida da natureza, o comprimento de Planck.
Apenas reflita.
@Tyler_A_Harper Kind of weird for a school whose brand is based on viewpoint diversity to invest so much in a machine that generates consensus by design.
Taxing 50% of AI companies' stock to ensure that AI benefits humanity isn't radical, but let me tell you what is:
Since Trump was elected, the 7 richest men in America, all Big Tech oligarchs, became $1.15 trillion richer while 60% live paycheck to paycheck.
That's radical.
Horseshoe theory is the winning narrative for the AI industry. The left and right are each intent on using AI to fuse state and corporate power. Don't let them.
https://t.co/5cOhxa37oo via @WSJ