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Google DeepMind AI

Google DeepMind AI

Google DeepMind AI

Google DeepMind AI

Google DeepMind AI

Google DeepMind AI

Google DeepMind AI

Google DeepMind AI

Google DeepMind AI

Google DeepMind AI

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 experience? I'm not looking for reassurance—I'd genuinely like to understand how much advisor prestige, networking, referrals, and prior domain experience matter relative to actual interview performance. Any candid insider perspectives would be appreciated. Reddit is perhaps the only place I could find the answer ;) submitted by /u/South-Conference-395 [link] [comments]

How I build my own zero cost Agent

I’ve spent the last few weeks obsessing over one goal: having a personal, self maintaining AI assistant that costs $0and can be controlled from my phone. It wasn't easy. I started with an AWS Ec2 with 50GB storage and t3.micro memory- minimal setup (using the free credits) and made Oracle Cloud instance ($300 free credits but just for a month so I used it for experimenting with local models) I was using Termius to SSH into everything from my phone At first I used OpenClaw. It was cool, but I spent more time fixing it than actually using it. I almost gave up until I saw a video about Hermes Agent. And i actually found Hermes while looking for how to fix an OpenClaw error on YouTube (thanks NetworkChuck 🙌🏽) He mentioned the exact same frustrations I was having, and that Hermes had been stable for a month. I didn't even finish the video before I pulled the repo. The best part? It had a "migrate from OpenClaw" feature. I was up and running in minutes. The hardest part is the rate limits. If you use cloud models especially for code, you hit a wall fast. My solution? The Fallback Chain. Initially I was using openrouter/owl-alpha (stealth models are usually flagships in testing, like big-pickle is deepseek v4) which has 1M context window and was on multiple rankings. Over time after I transitioned to Hermes, I wanted a bit more customization, while owl alpha was good at tasks, It’s nothing to talk about on roleplay, it just scrapes the surface of the character I set in SOUL md file. On my oracle instance I had been experimenting with local models (keep in mind, if you go local, you’ll be sacrificing speed but privacy. Ofc since the vms don’t have a gpu it would be slower, about 3-5 minutes for a simple response) The one I was most impressed with is Google’s Gemma-4-31b-it It played the role perfectly Buuut if you know Google, you’re familiar with their aggressive rate limiting. So I set up my agent to rotate through providers. I start with Gemma 4 for that perfect personality and roleplay via openrouter (add an ai studio api key in BYOK for longer usage). If that hits a limit, I’ve also set the same model via ollama cloud and using Google OAuth directly (basically Gemma 4 3 times lol) And if those all hit limits, it jumps to Qwen3-coder-next (Alibaba, 1M free tokens per model. There’s like 80), then Nova (AWS bedrock), DeepSeek v4 (Azure and Opencode Zen), and Claude Haiku (GitHub). If everything fails, I have Owl Alpha; which is an absolute beast, took almost 70M tokens before I got rate limited once, that too for a few hours. It lives in my Telegram and Discord. It manages my Spotify, handles my emails, and when I need real research done, I have it spawn three separate agents to work in parallel. It’s been 8 days and it hasn't broken once. If you're looking to get AI without spending a fortune, I highly recommend looking into this 🫪 submitted by /u/king0mar22 [link] [comments]

OpenAI and ElevenLabs are adopting Google's SynthID watermarking

submitted by /u/Adi4x4 [link] [comments]

AI has just solved not one, but nine novel math problems, and proved 44 new conjectures. Some of these problems had been unsolved for 50 years.

submitted by /u/EchoOfOppenheimer [link] [comments]

Why We Build

One silver-lining to the dead internet we're living in, today, is that it's very quickly teaching us that we can't rely on our senses as much as we believe we can. It's not healthy to always live in skepticism, but it is necessary in a World where you don't know what's up or down anymore. That's why we need great minds to focus their attention on solving the problems associated with credible information sharing without it becoming some centralized playground designed to look like the free-flowing exchange of ideas. If we don't solve for that, then I guess we're heading into a future that a small handful of people want because elections or public opinion will no longer matter. One of the biggest focuses in AI should be in figuring out how to get it to provide deep credible knowledge in specific domains that can be best applied to the problems we're trying to solve. Sure, it can do this with enough fenagling, but what I really mean is having something easy for everyone to use like Perplexity or Gemini, only it doesn't simply find consensus information from the internet using all these black box methods that are owned by major corporations. Instead, it should use direct knowledge from domain experts who structure and cite their material and as users, we should be able to backtrack all of it, including the original author. And all of this should be achievable by simply engaging with a chatbot agent that can reliably go out and help me discover all of these things. Also, we shouldn't have to simply trust that the application works. We should be able to go in and see exactly how it's working. This way, the public can audit the systems we're relying on for grounding our worldviews. That, to me, is where we should be if we really want to break from the chains of propaganda and reclaim our genuine thoughts about how we ought to live. The alternative independent media space was co-opted long ago and now all of the feeds keep us in a state of perpetual dislocation from our friends, family, communities, new solutions, and better approximations to the truth. We exist in a walled-off digital pasture. But if regular people who are smart and capable enough decide to leverage this new technology, then we can break through the fencing and finally live in a world where discovery-based researching and learning can be easier than Google, which could eventually individuate society again, like how it was before, instead of keeping us clustered into specific groups based on our viewing preferences. That's why my brother and I got into this business. Yeah, sure, we also wanna make a buck so we can retire with dignity. That's true. But the drive has always stemmed from wanting to figure out a better way for people to share hidden insights and create things that are bigger than they thought they could handle. We have a long way to go, but we're making the first small steps, even if it isn't obvious, just yet. Bottom line, though? Humanity must figure out a way to help us master the means and methods of discovery-based knowledge acquisition, execution, and immediate distribution of information based on relevancy and needs from those who search instead of those who passively soak information in from the curated feeds. And all of this needs to be easy enough for a 12 year-old to do. If anyone else is working on this problem, we'd love to hear your thoughts, even if it's through a DM. We're living in the most exciting times, but with adventure, comes danger. So maybe, idk. Let's make it more fun and less hazardous, so that we can, at least, live long enough to re-tell this great story that we're all a part of. submitted by /u/CyborgWriter [link] [comments]

Race to create ASI

submitted by /u/KeanuRave100 [link] [comments]

AIWire, AI news in one feed, so you don't need 5 tabs open anymore, trusted sources only, updates every 30 min

Hey everyone 👋 OpenAI alone drops updates fast enough to keep you busy. Add Anthropic, Google DeepMind, Meta AI, and the media covering all of it, and keeping up turns into a part-time job. I built AIWire to fix that. One clean feed. 20+ trusted sources. Updates every 30 minutes. Completely free. All in one place Just the stories from sources worth reading. Open it and you're caught up. Sources include: OpenAI, Anthropic, Google DeepMind, Meta AI, Microsoft AI MIT Technology Review, The Verge, TechCrunch, Ars Technica YouTube: Andrej Karpathy, AI Explained, Two Minute Papers Newsletters: The Batch, ImportAI, TLDR AI, Ben's Bites Features: Auto-refreshes every 30 minutes, always current Top Stories from the last 24h pinned at the top Filter by source, date, and category Bookmarks to save articles for later For people who want to stay current on ChatGPT and everything around it, without spending an hour a day on it. 🔗 aiwire.app Full source list at aiwire.app/sources Feedback is very welcome: what sources are missing, and what would make this more useful for you? submitted by /u/Endlessxyz [link] [comments]

I got tired of having 7+ different tabs open every morning just to follow AI news, so I built AIWire

Every morning: check Twitter for what dropped overnight, open The Verge, check Anthropic's blog, OpenAI's blog, go through a couple of newsletters, maybe catch a YouTube video from Andrej Karpathy or AI Explained if I had time. None of it was in one place. I was spending 45 minutes just catching up before I could think about anything else. So I built AIWire. It is a free, real time AI news aggregator. One feed, 20+ handpicked sources, updates every 30 minutes. free, no algorithm deciding what you see, no ads. Just the latest from sources I actually trust. __________________________________________________________________________________________________ What I was trying to solve The problem wasn't that good AI coverage and news doesn't exist. It's everywhere. The problem is that it's scattered. You have to know which sources are worth checking, remember to check them, and then piece together the picture yourself. That's a lot of cognitive load before you've even read anything. AIWire doesn't summarize or edit articles. It just puts everything in one place and lets you decide what matters. __________________________________________________________________________________________________ Sources it pulls from: Labs: OpenAI, Anthropic, Google DeepMind, Meta AI, Microsoft AI Media: MIT Technology Review, The Verge, TechCrunch, VentureBeat, Ars Technica YouTube: Andrej Karpathy, AI Explained, Two Minute Papers Newsletters: The Batch, ImportAI, TLDR AI, Ben's Bites Full list at aiwire.app/sources __________________________________________________________________________________________________ Where it is now Over the last few weeks, I added more sources, which include The Innermost Loop and AI explained. Last week, I launched a weekly newsletter: 5 stories that mattered this week, with a short breakdown of why each one matters. Not just headlines, but with context. Takes about 5 minutes to read, and you're caught up. __________________________________________________________________________________________________ Honest question What sources do you think are missing? And for those of you who already have a routine for following AI news, what would actually make something like this worth adding to it? Genuinely curious. Building in public means the product gets better when people are honest about what's wrong with it. 🔗 aiwire.app submitted by /u/Endlessxyz [link] [comments]

AIWire, AI news in one feed, so you don't need 5 tabs open anymore, trusted sources only, updates every 30 min

Hey everyone 👋 OpenAI alone drops updates fast enough to keep you busy. Add Anthropic, Google DeepMind, Meta AI, and the media covering all of it, and keeping up turns into a part-time job. I built AIWire to fix that. One clean feed. 20+ trusted sources. Updates every 30 minutes. Completely free, no account needed. Just the stories from sources worth reading. Open it and you're caught up. Sources include: OpenAI, Anthropic, Google DeepMind, Meta AI, Microsoft AI MIT Technology Review, The Verge, TechCrunch, Ars Technica YouTube: Andrej Karpathy, AI Explained, Two Minute Papers Newsletters: The Batch, ImportAI, TLDR AI, Ben's Bites Features: Auto-refreshes every 30 minutes, always current Top Stories from the last 24h pinned at the top Filter by source, date, and category Bookmarks to save articles for later For people who want to stay current on ChatGPT and everything around it, without spending an hour a day on it. 🔗 aiwire.app Full source list at aiwire.app/sources Feedback is very welcome: what sources are missing, and what would make this more useful for you? submitted by /u/Endlessxyz [link] [comments]

Built a free AI news feed so I don't need 5 tabs open anymore, trusted sources only, updates every 30 min

Hey everyone 👋 AI moves fast. Keeping up means checking Twitter, YouTube, newsletters, and a dozen tech sites every day. None of it in one place. I built AIWire to fix that. One clean feed. 20+ trusted sources. Updates every 30 minutes. Completely free, no account needed. Just the stories that came from sources worth reading, open it and you're caught up. **Sources include:** * OpenAI, Anthropic, Google DeepMind, Meta AI, Microsoft AI * MIT Technology Review, The Verge, TechCrunch, VentureBeat, Ars Technica * YouTube: Andrej Karpathy, AI Explained, Two Minute Papers * Newsletters: The Batch, ImportAI, TLDR AI, Ben's Bites **Features:** * Auto-refreshes every 30 minutes, always current * Top Stories from the last 24h pinned at the top * Filter by source, date, and category * Bookmarks to save articles for later Built for people who want to stay current, not just scroll. 🔗 aiwire.app Full source list at aiwire.app/sources Feedback is very welcome; what sources are missing, and what would make this more useful for you? submitted by /u/Endlessxyz [link] [comments]

Pre-Deployment AI Evaluations

The US government signed agreements with Google DeepMind, Microsoft, and xAI to evaluate frontier AI models before public release. China's 2023 Generative AI rules already require pre-release security assessments and model registration with the Cyberspace Administration of China. China's approach is tied directly to content control and state supervision, while the U.S. approach is framed around national security and cybersecurity. Most importantly, in China, there is a mandatory registration requirement and, in the US, at least for now, this is a voluntary effort. Will the pre-release review mechanism stay narrow and technical or grow into something closer to a licensing regime? Will it remain voluntary? Link here. submitted by /u/BubblyOption7980 [link] [comments]

AIWire, one feed for all AI news, OpenAI front and center, trusted sources only, completely free, no sign up

Hello everyone 👋 Keeping up with AI means having Twitter, Reddit, YouTube, newsletters, and half a dozen tech sites open at once. And even then, you still miss things. Built AIWire to cut through that. One clean feed. Trusted sources only. Auto refreshes every 30 minutes, so you're always current, no chasing, no tab switching, no missing things. OpenAI's blog is pulled directly, alongside 20+ other trusted sources covering everything in AI worth knowing about. Features: * Auto-refreshes every 30 minutes * Top Stories, last 24h pinned at the top so you never miss what matters * Bookmarks, save articles to read later * Filter by source, date, and category * Search across all articles * Dark and light mode * Completely free, no account needed Sources include: * OpenAI, Anthropic, Google DeepMind, Meta AI, Microsoft AI * MIT Technology Review, The Verge, TechCrunch, VentureBeat, Ars Technica * YouTube: Andrej Karpathy, AI Explained, Two Minute Papers * Newsletters: The Batch, ImportAI, TLDR AI, Ben's Bite 🔗 aiwire.app Full source list at aiwire.app/sources Would love feedback from this community specifically, what OpenAI content or general features would make this more useful for you? submitted by /u/Endlessxyz [link] [comments]

Google DeepMind Researchers Map Out Ways Hackers Hijack AI Agents

submitted by /u/Sumsub_Insights [link] [comments]

List of people at big-tech / professors / researchers who've jumped shit to launch their own AI labs for something Frontier/Foundational/AGI/Superintelligence/WorldModel

Note: gemini deep research -> rearranged/filtered ; valuation numbers likely not accurate but big point is quite mind blowing the number of researchers now with their own >100million/billion dolar values labs in quite a short time with a vague pitch and a maybe demo. Skipped perplexity/cursor/huggingface since they are with utility. Left some just for completion like black forest labs, synthesia, mistral since they have tanginble products. Skipped labs from china since they've been meaningfully killing it with their open source releases ───────────────────────────────────────────────────────── Safe Superintelligence Inc. (SSI) Founders:Ilya Sutskever (former OpenAI Chief Scientist), Daniel Gross, Daniel Levy Location & Founded:Palo Alto, USA & Tel Aviv, Israel | Founded: 2024 Funding / Valuation:$3B raised | Series A Description:Singularly focused on safely developing superintelligent AI that surpasses human capabilities. Deliberately avoids near-term commercial products to concentrate entirely on the technical challenge of safe superintelligence. ───────────────────────────────────────────────────────── Thinking Machine Labs Founders:Mira Murati (former OpenAI CTO), Barrett Zoph et al. Location & Founded:San Francisco, USA | Founded: 2025 Funding / Valuation:$2B seed | $12B valuation Description:Advance AI research and products that are customizable, capable, and safe for broad human-AI collaboration. Focused on frontier multimodal models with a strong safety and interpretability research agenda. ───────────────────────────────────────────────────────── Mistral AI Founders:Arthur Mensch, Guillaume Lample, Timothée Lacroix (former DeepMind & Meta FAIR) Location & Founded:Paris, France | Founded: 2023 Funding / Valuation:~€11.7B valuation | Series C Description:Develops open-weight and proprietary frontier language and multimodal foundation models. Champions openness and efficiency in AI development, with models like Mistral 7B and Mixtral widely adopted in enterprise and research settings. ───────────────────────────────────────────────────────── Advanced Machine Intelligence (AMI) Founders:Yann LeCun (Meta Chief AI Scientist), Alexandre LeBrun, Laurent Solly Location & Founded:Paris, France | Founded: 2026 Funding / Valuation:$3.5B pre-money valuation | Seed Description:Aims to build world-model AI systems capable of reasoning, planning, and operating safely in real-world environments — directly inspired by LeCun's 'world model' thesis as an alternative path to AGI beyond current LLM paradigms. ───────────────────────────────────────────────────────── World Labs Founders:Fei-Fei Li (Stanford AI Lab), Justin Johnson et al. Location & Founded:San Francisco, USA | Founded: 2023 Funding / Valuation:$230M raised | Series D Description:Build AI models that can perceive, generate, reason, and interact with 3D spatial worlds. Focused on large world models (LWMs) that go beyond language and flat images to understand physical space and context. ───────────────────────────────────────────────────────── Eureka Labs Founders:Andrej Karpathy (former Tesla AI Director & OpenAI co-founder) Location & Founded:Tel Aviv, Israel & Kraków, Poland | Founded: 2024 Funding / Valuation:$6.7M seed Description:Creating an AI-native educational platform integrating AI Teaching Assistants to radically scale personalised learning. Envisions a future where an AI teacher can guide anyone through any subject, starting with deep technical topics like neural networks. ───────────────────────────────────────────────────────── H Company Founders:Former DeepMind researchers Location & Founded:Paris, France | Founded: 2023 Funding / Valuation:€175.5M raised Description:Develops AI models to boost worker productivity through advanced agentic capabilities, with a long-term vision of achieving AGI. Focuses on models that can take sequences of actions and interact with digital environments. ───────────────────────────────────────────────────────── Poolside Founders:Jason Warner, Eiso Kant Location & Founded:Paris, France | Founded: 2023 Funding / Valuation:$500M | Series B Description:Building AI agents that autonomously generate production-grade code, framed as a stepping stone toward AGI. Believes that software engineering is a key domain for training and demonstrating general reasoning capabilities. ───────────────────────────────────────────────────────── CuspAI Founders:Max Welling (University of Amsterdam / Microsoft Research), Chad Edwards Location & Founded:Cambridge, UK | Founded: 2024 Funding / Valuation:$130M raised | Series A Description:Accelerating materials discovery using AI foundation models, aiming to power human progress through AI-driven science. Applies large generative models to the design and prediction of novel materials for energy, medicine, and manufacturing. ───────────────────────────────────────────────────────── Inception Founders:Stefano Ermon (Stanford) Locat

Jeff Bezos's "Project Prometheus" is raising $10B at a $38B valuation to build "Physical AI".

Jeff Bezos’s five-month-old startup, Project Prometheus, is nearing a historic $10B funding round backed by Wall Street giants like JPMorgan and BlackRock. The Tech: They are building "Physical AI" that natively understands the laws of physics to revolutionize physical products like aerospace, automotive, and robotics. It is Bezos's first operational role since leaving Amazon in 2021 with co-CEO Vik Bajaj, a physicist and former Google X scientist who co-founded the Alphabet health startup Verily. They’ve aggressively assembled a 100+ person powerhouse team by poaching top-tier researchers from OpenAI, Meta, Google DeepMind, and xAI. They even acquired the agentic AI startup General Agents shortly after launch specifically to bring former DeepMind researcher Sherjil Ozair and his engineering team into the fold. I am all for money going into companies that accelerate discoveries in physical AI, materials, manufacturing. Another great effort is periodic labs, they raised $300 m. But, is this valuation justified, or are we really in a massive bubble? Are they expecting that they are going to solve all of the physical AI ? submitted by /u/Greedy-Ant6911 [link] [comments]