What relative probability do you see for each of these in your lifetime?

Based on what the state of the world is when you die. Will scarcity have ended, will you die with everybody else in an extinction event, or will neither occur and instead we get AI-boosted growth? (Feel like there should be an economic collapse scenario so you can add that if you want)

Oracle may slash up to 30k jobs to fund AI data-centers as US banks retreat

Andrew Karpathy’s “autoresearch”: An autonomous loop where AI edits PyTorch, runs 5-min training experiments, and continuously lowers its own val_bpb. "Who knew early singularity could be this fun? :)"

The goal is to engineer your agents to make the fastest research progress indefinitely and without any of your own involvement. In the image, every dot is a complete LLM training run that lasts exactly 5 minutes. The agent works in an autonomous loop on a git feature branch and accumulates git commi

Qwen3.5 family comparison on shared benchmarks

Main takeaway: 122B, 35B, and especially 27B retain a lot of the flagship’s performance, while 2B/0.8B fall off much harder on long-context and agent categories.

Eonsys releases video of a simulated fly, running on the connectome (scanned brain) of a real fly

"The Singularity has belonged exclusively to artificial minds, until now. For decades, whole-brain emulation has been the tantalizing counterpart to artificial intelligence: copy a biological brain, neuron by neuron and synapse by synapse, and run it. Today, for the first time, I am releasing a vide

The First Multi-Behavior Brain Upload: a copy of a biological brain, wired neuron-to-neuron from electron microscopy data, running in simulation, making a body move!

Since when did this sub become so pessimistic?

I’m surprised that lately many responses and viewpoints that are optimistic about the future get quite a lot of downvotes, when before it used to be the opposite. I don’t think AI will bring us a utopia, but I also don’t think it will be a complete dystopia.

Qwen-3.5-27B-Derestricted

Just saw this posted. Has anyone tried this and compared it to Heretic models? I don't see any GGUFs done yet.

I classified 3.5M US patents with Nemotron 9B on a single RTX 5090 — then built a free search engine on top

Patent lawyer here, started coding Dec 2025. **The pipeline:** * Downloaded 3.5M US patents (2016-2025) from USPTO PatentsView * Loaded everything into a single 74GB SQLite file with FTS5 * Ran Nemotron 9B locally on RTX 5090 to classify records into 100 tech tags (\~48 hours) * BM25 ranking with

AI doesn't replace white collar work

I built an Android audiobook reader that runs Kokoro TTS fully offline on-device

Hi everyone, I’ve been experimenting with running **neural TTS locally on Android**, and I ended up building an app around it called **VoiceShelf**. The idea is simple: take an EPUB and turn it into an audiobook using **on-device inference**, with no cloud processing. The app currently runs the *

Does going from 96GB -> 128GB VRAM open up any interesting model options?

I have an RTX Pro 6000 that I've been using as my daily driver with gpt-oss-120b for coding. I recently bought a cheap Thunderbolt 4 dock and was able to add a 5090 to the system (obviously a bit bandwidth limited, but this was the best option without fully redoing my build; I had all the parts need

I gave my Minecraft bot a brain with local Nemotron 9B — it follows orders like "chop that tree" and "guard me from zombies"

Just a fun side project. Hooked up Mineflayer (Node.js Minecraft bot) to Nemotron 9B running on vLLM, with a small Python Flask bridge in between. You chat with the bot in natural language and it figures out what to do. 15 commands supported — follow, attack, hunt, dig, guard mode, navigate, collec

How are fintech companies using AI to speed up loan approvals?

Show HN: Finsight – A Privacy First, AI Credit Card and Bank Statement Analyzer