Attributed mentions
2061
Across all collected Hacker News results
Discussion intelligence
A source-linked Hacker News monitor for the tracked company graph. These are attributable public discussions—not sentiment, endorsements, or unverified company facts.
Attributed mentions
2061
Across all collected Hacker News results
Companies represented
12
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Showing 1401–1420 of 2061 matching discussions
> A 0.001% optimization on a packing problem just isn't interesting for the amount of investment. I think you have completely misunderstood what OpenAI have accomplished here. Almost certainly no one cares about the specific concrete results achieved; they only care about (a) how difficult it would be for an intelligent human to achieve the same feat (ETA: the feat is the proof), which can be estimated by the amount of time the problem has remained open/a public conjecture, and (b) how general this artificial "intelligence" appears to be, which can be estimated by the diversity of topics where it was able to prove a difficult result. It's as if I showed you a dog that I had taught to speak German fluently, and you remarked: "What point is a dog that can speak a language that less …
Thanks for the pointer to lesswrong. The relevant article on this topic appears to be here: https://www.lesswrong.com/posts/pQYEPitFqztcRvBsS/openai-s-u... Just glanced at it and it looks pretty good!
not very interesting, its the second chance pool. its not a conspiracy of ycombinator vs. openai. https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...
Location: Boston, MA Remote: Open to Willing to relocate: Yes Technologies: * AI/ML- AWS Strands, Langchain, Langgraph, Vercel AI SDK. Agent steering, structured output, autonomous workflows, and multi-agent orchestration. * Web - Rect / Next.js / vercel * Embedded - C/C++. Broad experience working on bare metal * Robotics - Warehouse automation at scale * Infra - Extremely fluent in AWS / terraform / CDK * Other - Java, Swift, JS / Node, Python See resume for additional details Résumé/CV: gasek.net/resume Email: hnhiredaug26@gasek.net Highly autonomous, motivated engineer and founder. Experienced in taking products from 0-1 and shipping MVPs to real customers. Seeking Series-A or late seed stage companies with opportunity for broad impact, own…
Location: Porto Alegre, Brazil (GMT-3) Remote: Yes Willing to relocate: Yes Technologies: Python, Ruby on Rails, OpenAI Agents SDK, agentic/multi-agent systems, RAG/Agentic RAG, evals (LLM-as-judge + code-based), Anthropic/OpenAI/Etc APIs, LiteLLM, PostgreSQL + pgvector, Redis, Sidekiq, React/Next.js, TypeScript, Node.js, AWS, Docker Résumé/CV: https://gerson.is Email: gersonazgo@gmail.com AI Engineer and two-time founder, ~20 years in software. My whole career has been about being a sole engineer or leading small teams (4-5 people), gathering requirements from non-technical people, and turning those into production applications. Currently I'm a sole AI engineer working directly with clinicians at a startup building a clinical "between sessions" AI …
Location: Raleigh, NC Remote: Onsite, remote or hybrid all fine. Willing to relocation: Negotiable Technologies: JavaScript, TypeScript, React, Node.js, Express, Ruby, Python, PostgreSQL, MongoDB,FastAPI, Supabase, Pinecone, REST API's. Resume/CV: Available upon request Website: https://ianlewis.online Email: ianlewisuk1@gmail.com Hey, Ian here. I'm a software engineer with 3+ Years of experience developing full stack web applications. My experience lies most recently in observability, co-creating Trickl as part of a distributed team across two continents. I have embraced AI fully into my workflows, while retaining the solid SWE fundamentals that were instilled into my over the past 5 years. I value empathy and communication, and am looking for a team of like-minded individ…
Location: Mission, TX Remote: Yes Willing to relocate: No Technologies: Python, JavaScript/TypeScript, Node.js, React, Rust, postgresql, three.js, WebGPU, docker, linux, websockets, SIP/VOIP, vllm, Llamaindex, RAG, agent harnesses, tool use, multi-agent systems, browser automation, multimodal models Resume: https://raw.githubusercontent.com/runvnc/resume26/main/Jason... Email: jason@mindroot.io Senior software engineer. Extensive front end and back end experience. I've spent most of the past four years building AI agents and related system. I built an open-source, plugin-based agent framework. It supports tools, delegated jobs, knowledge bases, browser and computer control, database access, custom UIs, and image/video workflows. Lately I've bee…
1. This is not “unrelated to AI safety”. The things they seek in the name of AI safety always seem to be aligned with the path that will eliminate competition and give them maximum economic power. Thus, to disentangle what is sincere and what is ulterior, we have to look at the leadership’s character holistically. A ruthlessly unethical and cutthroat corporation that is also seeking unprecedented power doesn’t deserve the benefit of the doubt when it claims to be doing this for altruistic reasons. 2. You misstated what I wrote. My gripe is not that they have an enterprise sales process. It’s that in negotiations, they say “we’ll drop the safeguards if you agree to spend more”. I haven’t heard of any groundbreaking AI safety research concluding that spending more with Anthropic makes the m…
The big example predates LLMs as a unified tech and it's protein folding, from Google DeepMind. OpenAI and Anthropic are too greedy for cash to do anything of the sort. I don't expect this current economic cycle to bring anything else that will directly greatly improve the life of the average person on the planet, more than it hurts it.
Another interesting question is why the frontier labs are piling on pure maths, which has little direct economic value compared to something like law or improving the efficiency of their own models? How much OpenAI and Anthropic are paying to serve these models for ordinary users is the elephant in the room. A cynical take is that the frontier labs are trying their best to pump up their pre-IPO valuation through flashy headlines.
Location: Santiago, Chile Remote: Yes (remote-only) — US-timezone aligned (UTC-4) Willing to relocate: No Technologies: Python, LangChain/LangGraph, RAG, LLM agents & eval, Ruby on Rails, Django, FastAPI, PostgreSQL/pgvector, microservices Résumé/CV: linkedin.com/in/pablojacobi Email: pablo.jacobi@pyro.cl Senior/Staff engineer, 12 yrs. AI/LLM product engineering + backend. Open to fixed-scope contract / freelance engagements (available now through end of October). Recent: Plenix (production LangGraph NL-analytics, deterministic core + eval-gated), Colliers (RAG on pgvector), ex-CTO HelloWine. Open-source agent: github.com/pablojacobi
Here's the actual quote from the podcast you're presumably referring to. I guess everybody can make up their own mind about what they're saying and whether they are "fundamentally wrong." You gotta watch something, because harnesses have changed how you can look at the cost structure of these things. If you look at cost per million tokens, it might look lower, but if the model consumes four times as many tokens in order to deliver a meaningful result, it's not cheaper. And so, Tom Claburn, one of our senior software reporters, had an excellent piece looking at how Anthropic's latest models use a tremendous number of tokens in order to deliver the result. So, sure, OpenAI's latest models might look less expensive from an API standpoint, which is great for marketing, but if it's using twice…
Not sure I agree with this. The math guy at anthropic's prompts are essentially: "suppose you’ve gotta resolve the $CONJECTURE, like absolutely have to, everything depends on it. think really hard, and try to come up with a bunch of ideas to try. but remember to trust yourself and not necessarily in conventional wisdom!!" https://claude.ai/share/25740bd5-aa97-4bd7-bf58-c4df3793fda7 https://xcancel.com/__alpoge__/status/2083855298239078748 Tao's chat was for him to gain intuition, not to solve the problem from the outset. What's funny is that every other person gets a different conclusion about who these models reward/empower. I've seen people say that the generalist stands to gain the most and others say that it's the experts. Like all of …
Location: Los Angeles, CA Remote: Yes Willing to relocate: No Technologies: Django, FastAPI, Python, React, AI (OpenAI, Anthropic, ChatGPT), Roku BrightScript, Linux, AWS, Google Cloud, DigitalOcean, Ant Media Server (HLS/RTMP streaming, 24/7 channels), video pipelines, automation Résumé/CV: https://www.ryanvinson.com Email: info@ryanvinson.com Who I am: Fractional CTO with 25+ years of experience building and scaling products across multiple generations of the web. I’m often brought in to turn ideas into working systems quickly, or to stabilize and evolve existing platforms. I’ve led teams, hired engineers, defined architecture, and stayed hands-on in the code. My work spans AI-driven platforms, streaming media systems, and full-stack web applications. I’m comfor…
I think Anthropic/OpenAI do have a moat in the (western) enterprise market. Chinese hosted models are a no-go, and my experience with enterprise IT departments is that they will not self-host. So far signing up with a known product (e.g. Claude) seems to be the way they will go and this is the moat that the AI companies have. Alternatively there is Copilot, but that for now seems to mostly be backed by Anthropic/OpenAI models[1]. Will this continue? The field is moving too fast to tell. Kimi, Qwen, Deepseek also produce very capable models but that doesn't automatically translate into trillion dollar valuations. However, trillion dollar valuations on Anthropic and OpenAI, such new companies, never publicly traded and such huge valuations decided just by investors. This is just a…
SEEKING WORK | Remote OK | Willing to Relocate Location: South America (US Citizen) Remote: Yes Willing to relocate: Yes Technologies: TypeScript, JavaScript, Python, PHP, React, React Native, Svelte, Express, Bun, Angular, GraphQL, D3.js, visx, Backbone, jQuery, LangChain, Mastra, FastAPI, pandas, scikit-learn, Optuna, Chrome Extension API, Playwright, Electron, Stagehand, browser-use, Web Audio API, WebRTC, WebSockets, PostgreSQL, TimescaleDB, MySQL, MongoDB, Redis, AWS, EC2, S3, Lambda, Docker, Git, LLM agent design, agent evaluation, reinforcement learning, browser automation, MCP Résumé/CV: Ask via email Email: [HN username]@gmail.com GitHub: https://github.com/adam-s Website: https://adamsohn.com Currently in South America and planning my move back to t…
Why is it that downloading a movie from Netflix and putting it for free on ThePirateBay is illegal but scraping someone’s work to train the AI models and then selling them for a fee is legal? What’s the difference?
Methodology: HN Search returns recent public items matching a monitored company name. AIIStack stores a short normalized excerpt and the original link, deduplicates by company/provider/item ID, and creates an activity signal only after a threshold of newly observed records. Review the original discussion before making a decision.