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TechCrunch

What happens when companies become too AI-pilled?

The people deciding that AI can replace your job are also the ones least likely to understand what your job truly involves, according to Box founder Aaron Levie, who pointed to this as an example of “AI psychosis.” Indeed, ClickUp recently cut 22% of its workforce for AI agents, tech layoffs in 2026 are already nearly matching all of 2025, […]

Theresa Loconsolo 2026-05-30 01:57 👁 14 查看原文 →
Reddit r/artificial

Is there a point in majoring in anything computer or coding related anymore?

I graduated Highschool with an Associate of science degree in data science and currently debating on pursuing a bachelors or if I should go straight blue collar and bust my balls everyday working for my dad’s construction company. As you know there’s millions of people getting laid off because of AI and my parents are grilling me about that. Please share your opinion. submitted by /u/Im_Humaaaaaaan [link] [留言]

/u/Im_Humaaaaaaan 2026-05-30 01:49 👁 5 查看原文 →
Reddit r/MachineLearning

How long does it realistically take for you to produce an ICML/NeurIPS/ICLR-level paper? [D]

Hey everyone, Since there are many researchers here who regularly publish at top-tier ML conferences like ICML, NeurIPS, and ICLR, I wanted to ask about realistic paper timelines. In your lab or research setting, how long does it usually take to develop a paper from the initial idea to a complete submission, and then eventually to final acceptance? submitted by /u/Hope999991 [link] [留言]

/u/Hope999991 2026-05-30 01:38 👁 5 查看原文 →
The Verge AI

Tech companies desperately want to film you doing chores

This week, an AI training startup called Shift said it would clean New Yorkers' homes for free. It has plans to expand into other cities as well, including London, and looking around my flat, I get the appeal. But there's a catch. There's always a catch. In exchange for the cleaning, Shift wants footage of […]

Robert Hart 2026-05-30 01:37 👁 7 查看原文 →
Reddit r/MachineLearning

Does anyone have a copy of the ICDAR2013 Chinese Handwriting Competition Dataset? [R]

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]

/u/Aathishs04 2026-05-30 01:35 👁 5 查看原文 →
Reddit r/webdev

How do I make the dev experience of Wordpress suck less?

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]

/u/dont_trust_lizards 2026-05-30 01:25 👁 4 查看原文 →
Reddit r/webdev

where to land a contractor job as a mid level full stack dev (remote overseas)?

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]

/u/In-Hell123 2026-05-30 01:23 👁 4 查看原文 →
Reddit r/artificial

Hidden Latent-State Shifts in LLMs: Why Current Alignment Is Blind to Real Internal Dangers — Especially With Agents

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

/u/PresentSituation8736 2026-05-30 01:15 👁 4 查看原文 →
Reddit r/MachineLearning

How Much of a Shortcut Are Connections in Top AI Lab Hiring for PhD grads? [D]

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

/u/South-Conference-395 2026-05-30 00:52 👁 5 查看原文 →
The Verge AI

Microsoft delays Fable (again) to avoid GTA VI

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 […]

Jay Peters 2026-05-30 00:51 👁 10 查看原文 →