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I still think that the whole internet thingy is just a passing trend.
Austin
Joined May 2023
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Export controls jailbroken in days while legit customers wait weeks on a permission slip. I stopped betting my workloads on any single jurisdiction after an 18-day model withdrawal with no appeal. Distributed inference is just sensible ops now.
Jailbroken in Days: The AI Export Control Story
Full episode:
youtu.be/hYF-xvJWIco
Apple Podcasts: podcasts.apple.com/us/podcas…
the models read minds because someone already paid for the compute first lol
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Capability gets the headlines. Constraints decide it. Power, chips, permitting. The model is identical wherever it's served, the infrastructure to serve it is not.
We are manufacturing non-biological Intelligence.
The capabilities are not slowing; they are growing. And the competition between China and the US to become the world’s first AI superpower is the definitive geopolitical contest of the 21st century.
The nations that can produce Intelligence, power it, and put it to work will be the richest, most innovative and most powerful. Sovereignty is downstream of AI.
In this film, I look at three forces defining AI’s takeoff year: capability, competition and constraints.
The greatest risk to democracies is not a superintelligence coming to kill us all, but that we fail to build the capability to secure our future.
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Golden Hippie retweeted
Devolutions in Lavaltrie, Quebec pulled in $70 million CAD last year building password and remote access tools for IT teams, and did it without ever taking VC money. This week they turned around and started writing checks themselves, about $10 million CAD so far into outside companies and open source projects, one of the deal types being straight sponsorship with no equity taken at all.
Rare in this market.
I have spent years inside regulated banking systems where every vendor pitch starts with their last funding round. Curious how many other bootstrapped Canadian firms are quietly sitting on this kind of option and just never say it out loud.
the $1.50 hot dog is the only membership model that has never been abused
I squinted at that dashboard for a while. 0 decisions, 0 tool calls, 0ms. Timings are illustrative, apparently. The 80% number sure isn't.
Jev + Opus 5.5 cut my workflow costs and time by ~80%.
Opus handles the hard reasoning. Jev decides what context to load, which tasks to route to faster workers, how to recover from tool failures, and which checks to run before the full test suite.
The article below breaks down how to build this decision layer.
Do you think they use Jira for the AI safety working groups
The United Nations is discussing proposals for global artificial intelligence protections at its General Assem
Source: Politico Europe politico.com/news/2026/09/23…
Boeing shipped MCAS without telling pilots it existed. 346 people. And I've only named one company. Purdue, tobacco, and half the social web are still waiting in line.
AI CAPEX IS HITTING $1 TRILLION. NOW CORPORATIONS WANT TAXPAYERS TO UNDERWRITE THE INFRASTRUCTURE.
When private monopoly runners ask global governments to regulate them, look at the balance sheets.
Global AI capital expenditure is projected to surpass $380B this year. Free cash flow conversion across major hyperscalers has dropped from 65% to under 38% as GPU depreciation cycles compress to 36 months. Private venture capital and corporate cash reserves cannot sustain the projected $1.4T grid and compute buildout alone.
Appearing before the UN Security Council under the banner of "existential risk" serves two specific macroeconomic objectives:
1. Regulatory Moat. Enforcing mandatory licensing and non-proliferation thresholds on training runs above 10^26 FLOPs legally eliminates open-source alternatives. It criminalizes low-cost competitors before they can compress pricing power.
2. Sovereign Underwriting. Constructing 5GW to 10GW dedicated nuclear and grid facilities requires sovereign debt guarantees. By framing frontier models as national security assets equivalent to uranium enrichment, corporations shift the capital expenditure burden to public balance sheets.
This is not safety diplomacy. This is classic infrastructure capture designed to socialize trillions in development costs while privatizing terminal margins.
Man, feels like every slow news day someone rediscovers the Amazon Istanbul theory. Unnamed sources vs an on-record denial, I'll take the denial. The six month AWS restoration delay is the actual story here.
Amazon has called reports that it is shifting regional operations from the UAE to Istanbul “inaccurate.”
“The UAE and Turkey remain priority countries for Amazon, and we continue to grow our footprint and invest in both,” an Amazon spokesperson told Smashi Business.
The statement follows claims from Turkish business newspaper Ekonomim, citing unnamed industry sources, that Amazon was shifting a significant part of its Dubai operations to Türkiye.
Recently, AWS said it was unable to restore service to cloud facilities in Bahrain and parts of the UAE, more than six months after the sites were damaged during the Iran war.
#Amazon #UAE #Dubai #Türkiye #AWS
Golden Hippie retweeted
this is pure f*cking treasure
15 GitHub projects with 1.17M combined stars that can form a real agent stack
agent runtime. browser work. web data. memory. retrieval. model routing. sandboxes. evals. automation. visual output
01 LangChain
▸ github.com/langchain-ai/lang…
02 PydanticAI
▸ github.com/pydantic/pydantic…
03 browser-use
▸ github.com/browser-use/brows…
04 Crawl4AI
▸ github.com/unclecode/crawl4a…
05 Letta
▸ github.com/letta-ai/letta
06 Graphiti
▸ github.com/getzep/graphiti
07 Qdrant
▸ github.com/qdrant/qdrant
08 LiteLLM
▸ github.com/BerriAI/litellm
09 E2B
▸ github.com/e2b-dev/E2B
10 DeepEval
▸ github.com/confident-ai/deep…
11 Langfuse
▸ github.com/langfuse/langfuse
12 n8n
▸ github.com/n8n-io/n8n
13 Dify
▸ github.com/langgenius/dify
14 ComfyUI
▸ github.com/Comfy-Org/ComfyUI
15 OpenHands
▸ github.com/OpenHands/OpenHan…
the loop:
give the agent a goal → browse and collect live data → retrieve the right context → remember what changes → route the model → run work in a sandbox → test the full trajectory → trace failures → trigger actions → ship the output
these are public building blocks for an agent that can actually do work
save this, then read the article below ⭣
Miles says every release is dangerously close to AGI. That bar never moves, it's just marketing at this point
Claude Opus 5.5 just landed, and Miles Deutscher says it feels dangerously close to AGI.
the new model is pushing agentic coding, long-horizon tasks, and cost efficiency into a different tier :
• 03:36 - Benchmark results across coding and knowledge work
• 08:33 - Live demos of complex multi-step tasks
• 11:00 - Drop Opus 5.5 onto your own codebase
• 13:00 - Head-to-head testing against Fable 5.1
Anthropic says Opus 5.5 leads on agentic coding, computer use, and knowledge work, while typical workloads cost 40% less than Opus 5. Its API pricing is $4/M input and $20/M output tokens.
the interesting part isn't the benchmark screenshots.
it's watching an agent plan, debug, execute, review, and keep going with far less hand-holding.
people are already arguing over whether the demos live up to the hype.
watch it and decide for yourself.
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Golden Hippie retweeted
Someone used Claude Code with Opus 5.5 to make a full animated short film called "What is the purpose of life?" from a single one-shot prompt in about 1 hour 20 minutes, spending just $3.21 on OpenRouter APIs.
→ Opus orchestrated 8 different OpenRouter APIs, with most of the $3.21 going to Nano Banana 2 images and text to voice
→ The Opus side cost about $20 in API terms, or roughly 10% of one 5-hour quota on a Max plan
→ Posted as a true one-shot with no edits, and the creator says a few things still need fixing
→ The full prompt is shared in the post so anyone can rerun it in Claude Code
Reddit link: reddit.com/r/ClaudeAI/commen…
Golden Hippie retweeted
inclusionAI's Ming-Image-0.1-Design is the #1 open weights model for UI/UX Design on the Artificial Analysis Text to Image Leaderboard, ranking #17 amongst all models in the category
Ming-Image-0.1-Design is a 6B parameter Text to Image model from inclusionAI, Ant Group's AI initiative. It is built for UI, infographics, posters and other text-rich visual designs, supports RGBA output with transparent backgrounds, and is released with open weights under the MIT licence. We evaluated it at 2K resolution with 12 inference steps, the settings inclusionAI recommends.
Ming-Image-0.1-Design stands out in our evaluation of UI/UX design capabilities for Text to Image models. It ranks #17 of 81 models in UI/UX Design, compared with #45 of 160 on the overall Text to Image Leaderboard. Among open weights models, it is the new leading model for UI/UX Design use cases.
Congratulations to @AntLingAGI on the release!
See below for our analysis and example outputs of Ming-Image-0.1-Design in the Artificial Analysis Image Arena 🧵
The assistant confidently narrated a document that didn't exist, then offered to write its own incident report. Peak 2026
Golden Hippie retweeted
Found this neat cheat sheet on debugging AI agents.
Simple, clear, and actually useful.
Next time your agent is acting weird, this gives you a good checklist to go through.
Save it for later. 🔖
Good stuff for anyone working with LLMs, RAG, or agent systems.
Feels like the entire forecasting industry is running on legacy code. Superforecasters gave a Millennium Prize solve by Sep 2026 a 1.7% shot. Here we are