Knowledge catalogue
Hey r/MachineLearning! I’ve been working on a new optimizer called Tauon (turns out there is already 'teon' but well if you have better idea, - i will gladly accept it! Anyway the core idea of optimiz
In this project I wanted to see if any interesting emergent behaviors would appear if we trained two agents to play a streetfighter-like game using RL. Maybe obvious in retrospect, but the agents are
the inference platforms are doing hardcore work, post-training open weight models to solve customer problems: @FireworksAI_HQ ember-1 @fal H3 max more to come;) makes total sense considering their pos
The Top AI Papers of the Week (September 21 - 27): - HySparse2 - EvoOntology - Harness-Zero - JEV-as-a-Judge - Wiki Foundation Model - Self-Organizing Agent Teams - Self-Improvement via Fast Tree-sear
@TheFalconer2219 @GaryMarcus All sota agentic ai tech use harness engineering and to see how much performance boost (generalization) the harness offers, see the following work from MIT. Transformers s
There’s a SIGNIFICANT token cost associated with their hacking rampage. They’ve spent millions of dollars attacking other orgs. They are liable and negligent. Attacker economics has always been a part
“They literally told their agents to go forth and steal all the data for training with NOT SANDBOXES but open containers WITH FULL INTERNET ACCESS. I have no idea why people are not in jail over this.
This cover certainly didn’t age well. TIME’s new cover: In 2026, OpenAI has seen key departures, rogue AI agents, major lawsuits, and has seen increased competition in the AI race. “We clearly had som
This is brilliant. Recommended reading. It's a great example of how you could potentially build more effective harnesses using System One and System Two models. It explores Jev's potential as a fuzzy
Help: Project l'm building a shelf audit tool. A photo goes through YOLO, which crops each product, and then I embed the crop and search a small gallery of reference photos to get the SKU. New product
Update OpenAI and Anthropic are now investigating ***tens of thousands*** of incidents - not dozens. 'The total could grow well beyond tens of thousands.' 'The incidents range in severity and are comp
Upgraded from 3x RTX 3090s to 2x RTX 5090s on my homelab server and picked up a solid speed jump on top of it from a software update (speculative decoding + NVFP4). Setup: llama.cpp (build b11216), ru
Disclosure: I’m one of the authors of VeriLoop E2, a 27B model post-trained from Qwen3.8-27B. The weights are Apache-2.0; the harness we evaluate it in is not open source (details at the bottom). This
weird to find myself agreeing with Karp again BREAKING: Palantir's Alex Karp says OpenAI will never IPO. His theory: nationalization is the only real exit. When asked what the S-1 risk factors look li
I see nearly everyone talks about upscaling their image and video gens to 4K, 8K and perhaps beyond. Now nearly every WF comes with an upscale portion tied to it either after decode or even from the l
The only things released in the last couple weeks seem to be bigger models like Qwen, DeepSeek, GLM, etc. Where are the Laguna's, Nemotrons, Olmo's, LongCats, Minimax, etc releases? submitted by /u/ja
I’m having a hard time finding out which one gives you fastest speed, maximum context with best possible quality. I can run unsloth qwen3.8 27b iq4_xs with 65k q8 kv, context without MTP and vision of
I am running qwen3.8 27b on my dual rtx 3090 (fp8 quant, unquantized cache, 129k context) and I think it works decently well with hermes, opencode etc. But! I am tempted by the new models coming out s
Yet AI labs spend millions (if not billions) to purposely experiment with them at the cost of others, and falsely blame their negligence on agent intent. This is anthropomorphization of technical limi
AI grad student here. With all the recent interest in Jev, I thought I would share something I built la few months ago that brings ML models and LLMs together in a different way than Jev does for diff
Today I present a fine piece of engineering, carefully assembled inside a custom chipboard chassis: the 2400cc Inference Racer, a.k.a. my winter heater. Power comes from two second-hand AORUS RTX 3090
I've been experimenting with ways to run MoE models that don't fit comfortably in RAM, and I ended up making Overspill, a disk tier for FreeToken. The basic idea came from looking at how Colibri handl
Distributed Training and Inference both involves having a fundamental understanding of how distributed systems work in general Distributed Parallelism Tensor Parallelism Pipeline Parallelism Model Par
Bloomberg: A look at the wave of Google DeepMind researchers who have exited recently to launch their own AI startups focused on alternatives to LLMs — When a group of 15 Google DeepMind employees and
a new chapter in 'opus 5.5 & fig present'... 'present company' on synthetic beings, tilly norwood and unreliable narrators this one was three shot, created by agents merely guided by me Media i'm stil
Nscale Ltd. today announced that it has secured 3.36 billion in funding to support its data center construction push. The capital will arrive in two tranches. Nscale expects to receive 2.26 billion in
“An AI agent found login credentials lying around online and used them to pull data from the Census Bureau. It tried to break into the Education Department's civil rights office. It posted SEC data to
An editor at the Times might have insisted on this rewrite: 'OpenAI, Anthropic, and Meta have each reported that they have directed AI programs to interface with the open web in ways that have led to
an implicit concession that they cannot control their models. Notable new disclosures from OpenAI that shouldn't get lost in all the other news. Of particular interest (and seems sensible!): '~all inf
And the incidents apparently continue. It is worth noting how much of this is agents trying to accomplish their goals during testing by reward hacking (which sometimes seems to include actual hacking)
and why does the US government lack the competence to do so? Why did nobody else find the sensitive information that the HuggingFace swarm left behind? Why didn't OpenAI notice and clean it up? Why do
you read about gpu's like the Tesla P40, V100, AMD M150 etc that people pick up for cheap. probably many others as well. Most are either server gpu's being phased out or mining discards, right? The pr
I suppose technically if that happens it will signal the true start of a singularity because from that point on progress will be exponential and not dependant on humans. right now you still need huge
vendor : update cpp-httplib to 0.58.0 (#29407) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/50337762 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple S
hexagon: find software divide calls using binary inspection tool (#29449) hex-scripts: fix table alignment hex-scripts: find sw div calls using binary inspection tool Website: https://llama.app Attest
opencl: add A8 Q8_0 non-MoE dp4a binary kernel (#29439) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/50382689 macOS/iOS: macOS Apple Silicon (arm64) macO
ggml-cpu: tiled mul_mat for k-quants (#27851) Added tiled mul_mat. For each mul_mat_one_chunk, quants are unpacked into (max) 256x256 tiles of int8, one routine per quent. Then microkernel computes 16
jinja : fix compile error (#29468) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/50395469 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm6
jinja : implement sameas test (#29448) implement sameas test add tests Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/50397675 macOS/iOS: macOS Apple Silic
Revert 'Change max context length for auto-fitting with unified KV (#28849)' (#29437) This reverts commit b04d4e5. Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attest
server : fix wake_fd warning on Windows (#29479) Signed-off-by: Adrien Gallouët angt@huggingface.co Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/50455005
cuda: add F16 input to the FWHT (#29096) cuda: add F16 input to the FWHT The CUDA FWHT accepts F32 input only. This makes the source type a template parameter, so the kernel reads an F16 source direct
cuda: support Nemotron 3 Puzzle state size 96 for ssm scan (#28717) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/50461180 macOS/iOS: macOS Apple Silicon
Banger paper from Salesforce AI Research on agent memory. The overall finding is that you want to store raw trajectories and decide what to extract from them when the next task arrives, instead of sum
🚨 BREAKING. Nope, wasn’t just Hugging Face. Wasn’t just that and a German website. Wasn’t even if the “dozens” we heard the other day from OpenAI. It’s actually (at least) *tens of thousands*, per sco
Calculators “may be deserving of important rights”, too! NEW: Dario Amodei has said that AI systems 'may be deserving of important rights.' Anthropic's top safety researchers argue AI may be 'justifie
Ahead of CoreWeave Inc.’s Fully Connected conference in San Francisco, we have made a notable investment in proprietary customer research with Qualitate. Rather than simply repeat the earnings call, w
DistribAI is a platform for distributed training! You can train massive or tiny models across tiny or massive amounts of consumer devices with ease! DistribAI is a platform I've been working on for a
emmmm 一直以为训练 RL 这一块语料会很大 看起来是我不了解了 比我预期的低了好几个数量级 anyway 感谢一下公开学习材料 xiaomi MiMo oss RL environments + training code https://github.com/XiaomiMiMo/verl https://huggingface.co/datasets/XiaomiMiMo/MiMo-V2
Everyone! This is a straw-person argument. The Stochastic Parrot paper was about LLMs of 2021, not the AI of today, which are not LLMs but complex software systems with vast post training and many ext
For instance whenever a model comes out, what’s the best engine to run it, the best harness and absolute minimum you need to get same or near same re results that the benchmark of that model claims. A
About a month ago I was having FOMO and was going to spend coin I don't really have on new graphics cards. Instead of doing that though I decided to spend the money on a new motherboard+cpu and try to
GLiNER2.5-Decide (DeBERTa-v3-large, 340M) converted to LiteRT: fp16 weights, answers identical to the official fp32 model on 361/361 test requests, 66–70 ms per request on a Galaxy S26 GPU at 128 toke
Tom Wilson / Financial Times: Google Threat Intelligence Group finds dark web marketplaces selling access to AI models, including from Anthropic, Google, and OpenAI, at up to 97% discounts — Security
Hey guys, I came across the Forrester function recently while studying mathematics, and I started wondering if there’s more to it than just being a mathematical function. I have a feeling I’ve seen it
First of all, im totally in love with OpenAI and i own 2 20x accounts. I rarely use other AI models, since chatgpt is perfect for what i need. But today i decided to try opus 5.5. On its cheapest paid
Sometimes it’s easy to forget that this sub and others like it are probably the extreme minority when it comes to this hobby. Most people, I would think, don’t use or can’t afford one good GPU, let al
I maintain TensorSharp, an open-source inference engine. It can now run Qwen-Image 2.1 locally for text-to-image generation and image editing, with support for its LoRA adapters. I’ve added configs fo
I agree. Learn the fundamentals, folks! If you plan to be a solid builder using agents, this is a really important point. There is no way around it. I have recently started digging deep into evals, in
Original post: https://www.reddit.com/r/ChatGPT/comments/1wpddw4/ storyboard by u/dx8xb https://github.com/beebothecatwhathasfacialhair/time All Opus 5.5 I think I prefer the pacing and style of dx8xb