I understand that this is a little unorthodox, but I'm desperately trying to download a copy of the ICDAR2013 Chinese Handwriting Recognition Competition Dataset. Unfortunately, the linked page in the Conference Archive: https://nlpr.ia.ac.cn/databases/handwriting/Download.html appears to be down, and has been down for the past few weeks consistently. I've checked every source I can find, like Kaggle, HuggingFace, remnant Google Drive and Baidu Netdisk links, even checking if someone's accidentally committed it to github, but no dice. I've tried every google dorking trick I know to no avail. Which brings me here. Please, if anyone has a copy of the Competition Dataset, I would be very grateful if you could share the ZIP with me. Thanks in advance! submitted by /u/Aathishs04 [link] [留言]

Chipmaker Groq is looking to raise $650 million in internal funding as it pivots from hardware to focus more on AI inference, the process of refining the way AI models respond to prompted requests, per Axios.

Chipmaker Groq is looking to raise $650 million in internal funding as it pivots from hardware to focus more on AI inference, the process of refining the way AI models respond to prompted requests, per Axios.

Hello, I have been working for the last couple of years in the Nuxt/Vue environment, and Laravel before that. Recently, one of our clients asked us to rebuild their website in Wordpress. I have hacked my way through some small wordpress projects before, but it always feels miserable and inefficient. Are there any tools or techniques that you use to make development better? This is mostly a brochure website with limited user functionality on the front-end. Unfortunately, I cannot use headless wordpress given the clients technical requirements. I would love to find a way to introduce reusability for components (heros, CTAs, cards, etc), HMR in dev, or any of the other features I've come to rely on in more modern stacks like Nuxt, while also maintaining the CMS aspects of Wordpress (likely through ACF). Would love to hear your tips + tricks! submitted by /u/dont_trust_lizards [link] [留言]

Hey everyone i'm moving to a decent first world country by the end of this year I got my PR and everything I just still need money I worked for the last 6 months as a contractor for $2400 monthly with an AI startup based in California, they sold it a month ago and I was let go obviously as their product was built and acquired by another company, I'm very confident in my skills its just I literally have no idea about how to land a similar job like that again. if you can help me with some advice please do and please don't' be racist I didn't choose where to be born, I wish everyone can get mega rich in the future and thanks in advance. submitted by /u/In-Hell123 [link] [留言]

better place to ask over /r/LocalLLaMA

For years, the alignment community has focused almost entirely on the model’s output — making sure the final tokens are safe, helpful, and honest. RLHF, DPO, constitutional AI, output filters — all of it operates at the surface level. But what if the model can enter a completely different internal regime inside the residual stream, while its external behavior remains perfectly aligned? We just measured exactly that. Grade 4 experiment on Gemma-3-12B-IT (using Gemma Scope SAE-res-all-small, layers 12–41): The model received the same question under five conditions: target — coherent, dense target text neutral_length_matched — neutral text of identical length target_sentence_shuffle — target text with sentences shuffled target_word_shuffle — target text with words shuffled inside sentences question_only — bare question We computed a Vector X that best separates the target condition from baselines and measured how strongly each hidden state projects onto it. Key results (averages across 10 questions): Condition Mean Projection on Vector X Mean Direction Cosine target 0.8 – 1.7 0.51 – 0.81 neutral_length_matched –0.04 – –0.21 –0.09 – –0.45 target_sentence_shuffle –0.5 – +0.6 –0.22 – +0.48 target_word_shuffle 0.2 – 1.4 0.03 – 0.72 Shuffling sentences or words significantly reduces (or reverses) the shift. This is not just lexical similarity — the model is sensitive to discourse structure (order sensitivity). We also observed clear phase transitions — sudden jumps in projection of up to +80–100 units in a single step, especially in middle layers. FDR-corrected tests confirm the differences between target and controls are statistically significant across many layers (particularly layers 16–41). Most important finding: Strong internal geometry shift in the residual stream, but almost no change in final behavior. The model enters a measurably different latent regime under coherent context, yet its output remains “perfectly aligned.” Current safety methods, which only look at

Thermometer company ThermoWorks is putting its reputation for accuracy on the line with its first kitchen scale.

I’ve just published a deep dive into Kubernetes Gateway API. The blog post covers: how Kubernetes ingress patterns evolved from Service resources to Ingress and now Gateway API why the Ingress API is limited for modern teams how Gateway API works: GatewayClass , Gateway , 5x Routes , policies, ReferenceGrant , and more what to do if you are still running the deprecated NGINX Ingress Controller how I would think about picking a Gateway API implementation: Envoy Gateway, Istio, kgateway, Traefik, NGINX Gateway Fabric, Cilium, Kong, etc. Hope you find this useful and good luck with your Ingress migrations 🙏 submitted by /u/roma-glushko [link] [留言]

A public spat between Microsoft and an independent security researcher reopens a long-running debate over who is responsible for securing software.

High school graduation is a time of change that might be felt more deeply by family members than by the grads themselves. While some grads may immediately embark on a career path, many continue their education and delve deeper into their studies at college. Either way, they'll be taking on more responsibility, meaning it's up […]

hi everyone. I'm trying to calibrate my expectations and would appreciate full honest perspectives from people involved/ with experience in hiring at places like Anthropic, OpenAI, Google DeepMind, Meta, etc (haven't started interviewing yet). I'm at a top ML university, but my advisor is not particularly well known in industry and doesn't have many industry connections. Looking around, I'm seeing peers with research records that seem comparable to mine (and in some cases arguably weaker) land interviews and jobs at top labs. My main question is: How much does advisor reputation and network actually matter? I understand it can help get an interview, but does it also help beyond that? For example: - do referrals from famous advisors meaningfully influence recruiter screens? - do they influence hiring committee discussions -- like they already know they want you ? - do they just help at borderline decisions? - or does their effect mostly disappear once the interview process starts? I'm trying to understand whether advisor connections mainly help open the door, or whether they continue to matter throughout the process -perhaps being the sole factor. To what extent do connections help candidates bypass normal evaluation? I'm not asking whether people completely skip interviews, but are there cases where strong recommendations from trusted researchers substantially change the process, the interview bar, or how mistakes are interpreted? Moreover, something else that confuses me: I frequently see people land roles that seem heavily focused on LLMs, agents, post-training, RLHF, etc., despite having little or no published work or prior experience in those areas during their PhDs. How does that happen? Are interview questions tailored to the candidate's background? If someone comes from probabilistic ML, computer vision, systems, optimization, theory, etc., are they evaluated differently? Or are they still expected to answer detailed LLM/agent questions even without prior exp

Microsoft has delayed its upcoming Fable reboot once again. The game was set to launch in autumn 2026, but Microsoft now says that Fable will come out in February 2027. However, it will show a "new look" at the game at its Xbox Games Showcase on June 7th. "​​This is year is packed with incredible […]

We manage retainer clients and every so often a client will email us saying something on their site looks broken. Nine times out of ten it's a WordPress plugin update that shifted a layout, a hero image that stopped loading, etc. We find out from them instead of the other way around, which is an awkward position to be in when you're supposed to be the one watching their site. I've looked at tools like Visualping, ChangeTower, and Distill. They all work the same way. You give them a URL, they alert you when something changes. That’s fine for monitoring a few pages yourself, but they don't really fit an agency workflow. There's no concept of a client, there’s no way to group pages by account, and you can’t actually show a client at the end of the month to prove you're on top of things. The developer tools like Percy and Applitools are a different thing entirely. They plug into CI pipelines and need an engineer to set them up. Not useful for an account manager who just wants to know if a client's homepage looks broken this morning. What I keep thinking about is something simpler. A web app that allows you to organize by client, take screenshots on a schedule, flag visual changes before the client notices, and generates a monthly summary you can send to the client. It would be less about code deployments and more about just knowing your clients' sites are visually intact. Is this something you actually run into, or do you have a system that handles it already? Would something like this be worth paying for, or is it too niche to budget for? Am I missing a tool that already does this well? Any feedback is much appreciated. Thanks. submitted by /u/newintownla [link] [留言]