trend: non-NVIDIA training DeepSeek V3.1 was trained on Huawei Ascend NPUs this one is a South Korean lab training on AMD

I really needed a Deep Research MCP server to use with Claude Code and other tools — here it is: github.com/pminervini/d...

@togelius.bsky.social has thoughts on Genie 3 and games togelius.blogspot.com/2025/08/geni... Fairly close to my own, though I didn't get the preview the tech. Walking around a generated image-to-image world is not the same as playing a game. There are no game objectives.

quick diagram of Bluesky’s architecture and why it’s nicer here

Anthropic research identifies “inverse scaling in test-time compute,” where longer reasoning degrades AI performance. On certain tasks, models become more distracted by irrelevant data or overfit to spurious correlations. #MLSky

Supermassive congrats to Giwon Hong (@giwonhong.bsky.social) for the amazing feat! 🙂

The amazing folks at EdinburghNLP will be presenting a few papers at ACL 2025 (@aclmeeting.bsky.social); if you're in Vienna, touch base with them!

Hm, hard disagree here. I really fail to see how this is misconduct akin to bribery, it's just a defense mechanism against bad reviewing practices. @neuralnoise.com

🚨 New Paper 🚨 How effectively do reasoning models reevaluate their thought? We find that: - Models excel at identifying unhelpful thoughts but struggle to recover from them - Smaller models can be more robust - Self-reevaluation ability is far from true meta-cognitive awareness 1/N 🧵

Inverse scaling of reasoning models a research collab demonstrated that there are certain types of tasks where all top reasoning models do WORSE the longer they think things like getting distracted by irrelevant info, spurious correlations, etc. www.arxiv.org/abs/2507.14417

Reasoning is about variable binding. It’s not about information retrieval. If a model cannot do variable binding, it is not good at grounded reasoning, and there’s evidence accruing that large scale can make LLMs worse at in-context grounded reasoning. 🧵

Hi @ilsebyl.bsky.social welcome to bsky! 🚀🚀🚀

Sometimes, too much reasoning can hurt model performance! New research by Anthropic (@anthropic.com), by Aryo Pradipta Gema (@aryopg.bsky.social) et al.: huggingface.co/papers/2507....

“LLMs can’t reason” 😅

My "Math, Revealed" series is freely available to anyone -- no paywall! -- in the thread below.

Spotlight poster coming soon at #ICML2025 @icmlconf.bsky.social! 📌East Exhibition Hall A-B E-1806 🗓️Wed 16 Jul 4:30 p.m. PDT — 7 p.m. PDT 📜 arxiv.org/pdf/2410.12537 Let’s chat! I’m always up for conversations about knowledge graphs, reasoning, neuro-symbolic AI, and benchmarking.

This essay by Nisheeth Vishnoi is a thoughtful meditation on the nature of science and a rebuttal to the notion that AI systems are going replace human scientists anytime soon. Worth reading. nisheethvishnoi.substack.com/p/what-count...

"in 2025 we will have flying cars" 😂😂😂

Preprint alert 🎉 Introducing the Agentic eXplanations via Interrogative Simulations (AXIS) algo. AXIS integrates multi-agent simulators with LLMs by having the LLMs interrogate the simulator with counterfactual queries over multiple rounds for explaining agent behaviour. arxiv.org/pdf/2505.17801

'AI Safety for Everyone' is out now in @natmachintell.nature.com! Through an analysis of 383 papers, we find a rich landscape of methods that cover a much larger domain than mainstream notions of AI safety. Our takeaway: Epistemic inclusivity is important, the knowledge is there, we only need use it

Can you train a performant language model using only openly licensed text? We are thrilled to announce the Common Pile v0.1, an 8TB dataset of openly licensed and public domain text. We train 7B models for 1T and 2T tokens and match the performance similar models like LLaMA 1 & 2

COLM (@colmweb.org‬) reviewers, please follow up on author responses if you need to! Most of the papers in my area chair batch didn't receive reviewer follow-ups, and it's dire

Hi @veredshwartz.bsky.social !!! 🙂

claude-code is pretty good at updating personal websites! it has browser use, so it can e.g. scrape your latest papers from arxiv and dblp and use that to update your website's publication list

“You must never be fearful about what you are doing when it is right.” -- Rosa Parks

🗓️ Deadline extended: 💥2nd June 2025!💥 We are looking forward to your works on: 🔌 #circuits and #tensor #networks 🕸️ ⏳ normalizing #flows 💨 ⚖️ scaling #NeSy #AI 🦕 🚅 fast and #reliable inference 🔍 ...& more! please share 🙏

This is a new experience: people using AI to overhype your paper 🫢 @neuralnoise.com

We propose Neurosymbolic Diffusion Models! We find diffusion is especially compelling for neurosymbolic approaches, combining powerful multimodal understanding with symbolic reasoning 🚀 Read more 👇

Just realized that the AI slop also made it into the @inquirer.com. So glad I saved this list of novels that do not exist!!!

Congrats! Looks like time is a big failure case for these models (cc @neuralnoise.com @aryopg.bsky.social @rohit-saxena.bsky.social ) bsky.app/profile/emil...

MMLU-Redux just touched down at #NAACL2025! 🎉 Wish I could be there for our "Are We Done with MMLU?" poster today (9:00-10:30am in Hall 3, Poster Session 7), but visa drama said nope 😅 If anyone's swinging by, give our research some love! Hit me up if you check it out! 👋

We're excited to round out the OLMo 2 family with its smallest member, OLMo 2 1B, surpassing peer models like Gemma 3 1B or Llama 3.2 1B. The 1B model should enable rapid iteration for researchers, more local development, and a more complete picture of how our recipe scales.

New work! 💪🏻💥🤯 When Can Proxies Improve the Sample Complexity of Preference Learning? Our paper is accepted at @icmlconf.bsky.social 2025. Fantastic joint work with @spectral.space, Zhengyan Shi, @meng-yue-yang.bsky.social, @neuralnoise.com, Matt Kusner, @alexdamour.bsky.social. 1/n

Extremely proud of the squad 💕

Happy to share that our work won the best paper award at ESANN 2025! 🚀 Huge thanks to my amazing co-authors✨ Read our work here: doi.org/10.14428/esa...

Massive congrats @manueldileo.bsky.social!!! 🚀🚀🚀🚀🚀🚀🚀

My amazing collaborators will present several works at ICLR and NAACL later this month -- please catch up with them if you're attending! I tried to summarise our recent work in a blog post: neuralnoise.com/2025/march-r...

@transducens.bsky.social hey guys! 🙂

the #TPM ⚡Tractable Probabilistic Modeling ⚡Workshop is back at @auai.org #UAI2025! Submit your works on: - fast and #reliable inference - #circuits and #tensor #networks - normalizing #flows - scaling #NeSy #AI ...& more! 🕓 deadline: 23/05/25 👉 tractable-probabilistic-modeling.github.io/tpm2025/

The AERG has some clear goals for the near future of the association: •Continue to grow: we are ~250 AERG members now but there are ~14k ERC grantees! •strengthen our collaboration with @erc.europa.eu •continue to defend the value of bottom-up, curiosity-driven fundamentals research in Europe

Here are the Top 5 Dogs of the week!

us & some of the topics we're working on! neuralnoise.com/publications/

"Bonobos combine their calls in a complex way that forms distinct phrases, a sign that this type of syntax is more evolutionarily ancient than previously thought." www.newscientist.com/article/2474...

Our hub is funding a post doc researcher to work on projects involving the evaluation and improvement of multi-modal foundation models. Apply by 9th April. Great chance to work with @neuralnoise.com and @edinburgh-uni.bsky.social colleagues! elxw.fa.em3.oraclecloud.com/hcmUI/Candid...

I defended my PhD at the University of Copenhagen ☺️ What a journey! I want to give massive thanks to my amazing supervisors, @iaugenstein.bsky.social and @neuralnoise.com who were there with me throughout the whole process. Thesis on: osoblanco.github.io/thesis/ The Arxiv version is coming soon!

We created Approximate Likelihood Matching, a principled (and very effective) method for *cross-tokenizer distillation*! With ALM, you can create ensembles of models from different families, convert existing subword-level models to byte-level and a bunch more🧵

Still ~8 days to apply for a postdoc position in multimodal foundation models at the University of Edinburgh! (@edinburgh-uni.bsky.social) -- Fully funded position until 2029 by the Generative AI Hub (@genaihub.bsky.social) to work with outstanding research teams! neuralnoise.com/2025/multimo...

We are recruiting a post doc to analyse and improve multimodal foundation models who will be based at the University of Edinburgh. Apply through the university's website by 8 April.

is this AGI?