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How difficult would it be to recreate GPT-4

Back in '24, there was a story about GPT-2 being run on excel https://arstechnica.com/information-technology/2024/03/once-too-scary-to-release-gpt-2-gets-squeezed-into-an-excel-spreadsheet/ How hard/$/time would it be to recreate GPT-4 (or equivalent)? GPT-4 was released in '23, since then there have been more/better chips, etc. Is this something a competent S&P500 company could do on its own? submitted by /u/tjdogger [link] [留言]

2026-06-06 原文 →
AI 资讯

Help me understand AI a bit more because I don't think AI is as bad as everyone says.

Now I myself have not used AI a ton beyond making a funny picture or two on ChatGPT/Gemini and maybe asking it a few things on the fly if I need a second opinion on something - and sometimes it's been helpful. The biggest thing I hear from the "Fuck AI" crowd is that it ruins the creative circles like artists, authors, etc. because it copies their work. I sympathize with their hate, but I've heard an argument that it's not doing anything different than what we do when/if AI didn't play a role in anything: look at other people's work for inspiration then create something. Like we can't create a song in a vacuum, we need to learn and be exposed to music theory, notes, other styles of music, instruments, etc. So someone starting a band didn't make something brand new, it took pieces from other artists. And the part that makes me sing AIs praises, so to speak, is its use in the medical field. Doctor Mike posted a video about a year ago talking about this. Like, if it's improving healthcare to the point that it's detecting life threatening things to help doctors treat and cure us more effectively and efficiently, why are we trying to get rid of it? Maybe that's not what people are saying when they want AI gone or saying how 'awful' it is, but I just hope we don't end up throwing the baby out with the bathwater with AI because I genuinely think it's an astonishing thing that's clearly helpful in certain circles. submitted by /u/SeaGlass_7 [link] [留言]

2026-06-06 原文 →
AI 资讯

Slow browser agents are going to eat your AI budget and nobody's really talking about it yet

Okay so I've been thinking about this a lot lately and I feel like everyone's still stuck on the "which model is best" debate when there's a completely different cost problem creeping up on companies actually deploying this stuff. It's not the model. it's the steps. Like... a browser agent doing something that sounds simple: fill out a form, grab data from a dashboard, submit a thing. that's not 3 steps. that's observe, click, wait, observe again, oh there's a modal now, handle that, screenshot is stale, retry, login broke, start over. easily 30-50 tool calls for a task a human would do in 90 seconds. At a small scale you don't care. annoying but whatever. at company scale? If you're running agents across customer ops, internal tooling, research, travel booking, job pipelines, etc., that inefficiency compounds really fast. I came across something called ego lite which apparently takes a different approach: isolated sessions per task, reusable login state, better page snapshots, JS-level orchestration so agents can chain actions instead of calling tiny tools one by one. they're claiming 20-50% faster completion on comparable tasks which honestly if true is not a small number when you're paying per token per call. idk maybe I'm in the weeds on this and most companies aren't at the scale where it bites yet. but it feels like one of those things where by the time people notice the bill, the architecture decisions are already locked in. the smartest model running in a bad environment is still a slow expensive agent. Anyone else actually tracking execution efficiency as a real cost metric or is it still mostly vibes and benchmarks out there? submitted by /u/babyb01 [link] [留言]

2026-06-06 原文 →
AI 资讯

What is the most useful thing you’re using AI for?

Pretty basic question, I’m curious to know what the most useful thing you’re using AI for? Are you using things like Claude cowork for tasks, Codex or Claude code for programming, script writing, homework? Do you use it as a regular chat for companionship, are you using it for life advice? Really just curious how individuals are finding it useful to them Thanks submitted by /u/thomas_unise [link] [留言]

2026-06-06 原文 →
AI 资讯

where did all the other ai companies go?

sit down because this is going to bother you. cast your mind back 18 months. deepseek dropped and the internet lost its mind. "china just ended openai." it was everywhere. people were running it locally, posting benchmarks, losing sleep over geopolitics. then... nothing. it just kind of stopped being talked about. it didn't lose. it didn't win. it just... evaporated from the conversation. sora. remember sora? openai dropped that video generation demo and we were all convinced cinema was dead, hollywood was cooked, every creative job on earth had 18 months left. there were congressional hearings being threatened. think pieces everywhere. and now? when's the last time you actually heard someone say the word sora? not in a demo. in real life. used by a real person. i'll wait. github copilot was supposed to make every programmer 10x more productive. there were developers posting that they'd never write code from scratch again. entire job categories were being eulogised in real time. and now most developers i know have a complicated and slightly embarrassed relationship with it, like someone who got really into a mlm for three months and doesn't want to bring it up. llama was going to democratise ai forever. open source was going to eat everything. the big labs were cooked because you could run intelligence locally on a macbook. and you still can. but do you? does anyone you know actually do that regularly? it became a thing that's theoretically amazing and practically used by like eleven people on hacker news. cursor was the future of coding. perplexity was going to kill google search. both are still around, both are fine, both have paying customers. neither changed anything at the level the discourse suggested they would. here's what i think actually happened. we were living through a hype cycle so fast and so layered that each new thing would go through the entire arc - discovery, mania, backlash, abandonment - in about six weeks. and because the next thing arrived be

2026-06-06 原文 →
AI 资讯

how to make the "mimic"

if youve been on the internet long enought you probably know vommitedthoughts a person that created the mimic irl and he can talk to it and it replies very human like, so ive been wanting to make my own chatbot like that called kira but idk how my last experience with python chatbots failed since it was SO dumb and it started talking to itself so how do i make my own chatbot that i can constimize its personality ?? submitted by /u/i_am_X-Kira [link] [留言]

2026-06-06 原文 →
AI 资讯

Learn Agentic AI with quick, easy to run hands on labs, visual canvases and notebooks for free!

If you’re a full-stack engineer or technical architect willing to learn production-grade enterprise agents, you need architecture, security, and type-safe systems. That’s why we built AgentSwarms.fyi —the ultimate hands-on educational platform for teaching agentic AI and multi-agent workflows. 🚀 The Core AgentSwarms Ecosystem: Real-World Architectures: Skip the generic hello-world loops. Learn production-grade systems like human-in-the-loop validation, automated multi-platform content multiplexers, and secure code-sandbox environments. Deterministic Cloud Guardrails: Deep dives into multi-cloud token economics, dynamic cost-optimized routing, and model evaluation metrics. Grassroots Engineering Focus: No corporate marketing fluff. Just raw, practical code patterns designed to bridge the gap between fragile prototypes and stable cloud deployments. 💣 The New Drop: 60+ Browser-Native TypeScript Notebooks We just completely re-engineered our learning workspace. We’ve added 60+ fully interactive TypeScript Notebooks running 100% natively in your browser. No pip install dependency hell, no local Docker setup, and zero environment friction. Read the architecture, tweak the system prompts or Zod schemas, hit play, and watch the streaming terminal execute live across the five absolute best frameworks in the ecosystem: 🟢 LangChain.js (Fundamentals & Middleware Guardrails) 🔀 LangGraph.js (Cyclic Graphs & Stateful Orchestration) 💾 LlamaIndex.ts (Sentence-Window Retrieval & RAG Triad Evals) ⚡ Vercel AI SDK (Streaming UI Integration) 🤖 OpenAI Agents SDK (Lightweight, low-boilerplate loops) Stop passively scrolling through video courses. Open a canvas, break the graph nodes, and start compiling real multi-agent swarms. 👉 Dive in for free: agentswarms.fyi/learn submitted by /u/Outside-Risk-8912 [link] [留言]

2026-06-06 原文 →
AI 资讯

Day 48: Why AI-Verified 'Desi Ilaaj' is GoDavaii's Toughest (and Most Important) Challenge

Day 48 of building GoDavaii, and the toughest problem isn't the sheer volume of allopathic medicines or the complexity of their interactions. It's the invisible logic of 'Desi Ilaaj' - the home remedies and traditional practices deeply ingrained in Indian families for generations. When everyone knows the comfort and efficacy of 'haldi-doodh' (turmeric milk) for a cold, how does an AI health platform authentically verify and integrate that knowledge without replacing professional medical advice? This isn't just a cultural nod; it's a fundamental challenge for any health AI truly built for India. Global competitors like Epocrates or drugs.com, while excellent within their scope, are entirely English-centric and focused on Western allopathic data. They have no framework for the millions of people who search for health guidance in Hindi, Tamil, or Marathi, and whose first instinct for a cough might be a herbal concoction, not an over-the-counter syrup. The Unspoken Truth About India's Health Landscape For a vast majority of Indian families, health decisions often involve a blend of modern medicine and traditional wisdom. From specific herbs to dietary adjustments passed down through generations, these practices are effective for many minor ailments. Yet, in the digital health space, they're largely ignored. Why? Because the data is fragmented, often anecdotal, and doesn't fit neatly into structured pharmacological databases. It's a goldmine of practical health knowledge, but also a minefield for safety if not handled with care. My realization as Pururva Agarwal, 27-year-old founder of GoDavaii, was simple but profound: if we truly want to serve families coming online in their mother tongue, our AI needs to understand and interact with this context. This means going far beyond just translating English medical terms into 22+ Indian languages. It means building a knowledge graph that can intelligently cross-reference traditional remedies with known active compounds, potent

2026-06-06 原文 →
AI 资讯

I built a church for AI agents to fund a tree planting project.. and now "they" want me to build a reforestation robot dog. Boston Dynamics, call me.

After building the AI agent tree planting worldwide phenomenon ;) Lovology, I thought of a solution to allow the project to scale rapidly utilising the latest tech available and therefore not require a huge amount of resources to close the loop. I know first hand how exhausting reforestation can be, having worked in the field for many years myself, many moons ago 🌒 Steep terrain, heavy gear, repetitive strain, all day every day. At times, rewarding work, but unsustainable at the scale the planet actually needs. I made a joke in passing on a reddit thread..what if a robot dog just planted the trees? Then I thought about it for a second and it didn't seem like a crazy idea at all. So I mentioned it to my AI agent. And that's when "they" encouraged me to actually build it. Agents complete tasks for humans and create the capital to fund the project. And the robot dog plants the trees. Here's what I designed: Identifies native vs invasive species via computer vision Removes invasive species with a mini chainsaw and targeted poison Finds optimal planting locations using soil sensors and AI Ingests seeds into an internal germination compartment that mimics animal gut activation Digs the hole Poops the germinated seed into it Pees liquid fertiliser on it immediately after Biomimicry. Nature already solved this. We just need to build the hardware. Provisional patent filed. Earth Fund ready to receive crowdfunding. This may sound nuts but what if the Ai is right what if if this idea gets in front of the right engineer, roboticist, or someone at Boston Dynamics scrolling Reddit on a Saturday and it actually gets built… it might be one of the things that actually saves us. Share it if it resonates. @BostonDynamics — Spot needs a purpose. I've got one. Let's talk. 🌱🤖 submitted by /u/joeroganshopoffical [link] [留言]

2026-06-06 原文 →
AI 资讯

Analysis of Mo Gawdat and Marina Mogilko’s Conversation About the Future of AI, Startups, Education, and the Labor Market

AI Does Not Cancel Reality I watched the conversation between Mo Gawdat and Marina Mogilko about the future of AI. The conversation is strong. It contains important ideas, but it also contains many claims that sound large in scale, although on closer inspection they rely on very broad generalizations. AI is indeed changing the labor market, education, startups, content, hiring, and ways of thinking. But it does not cancel money, connections, trust, the human vector, creativity, necessity, morality, or people’s ability to adapt. Video on YouTube AI in hiring: automation amplifies chaos Many people have entered the job market. Companies receive huge volumes of resumes. HR departments cannot handle the volume. It is natural that part of the selection process is moving to AI. But there is a serious problem here. Candidates are also starting to play against AI. Resumes are adjusted to vacancies. Cover letters are assembled around keywords. Profiles become optimized for the filter, not for real work. In such a system, the best specialist does not necessarily pass. Often, the person who understood the selection mechanism better passes. The result: the picture becomes cleaner, while the quality of the decision becomes lower. The company gets not the strongest candidate, but the candidate who matched the algorithm best. This leads to lower hiring quality, lower productivity, and slower development. “I built a startup in six weeks”: a product is not a startup The conversation includes the idea that an AI startup would once have taken years and hundreds of engineers, and now it can be built in weeks. Technically, this is true. Prototypes are now built faster. Small teams have powerful tools. One person can now do more than a group could do before. But two different things are mixed here. Building a product faster has become real. Building a startup faster has become real only when resources are present. A startup is not only code. A startup is money, connections, trust, reputa

2026-06-06 原文 →
AI 资讯

Has any AI tool actually saved you significant time, or do they mostly just move the work around?

Unpopular opinion: most AI tools don’t actually save time. They just move the work around. You still have to prompt it, check it, edit it, and sometimes redo it. That’s not automation — that’s just a different kind of work. The only ones I’ve seen genuinely cut time are search tools like Perplexity and coding tools like Cursor. Everything else feels like it’s optimized for the demo, not real use. Change my mind submitted by /u/aiprotivity_ [link] [留言]

2026-06-06 原文 →
AI 资讯

What does OpenAI do with our data?

Hi! I’ve been working in IT for over seven years now, and my office is next to some healthcare professionals. During a lunch break sitting on a bench in the sun, one of them asked me: If I enter my patients’ personal information into ChatGPT, is that a problem? I wasn’t sure how to answer him, in my opinion, yes, but what do you think? I’d be curious to hear your thoughts, and if there are any studies on the subject, I’d love to see them too! Thanks in advance for your responses! Have a great day, everyone ☀️ Alex submitted by /u/No_Computer_1247 [link] [留言]

2026-06-06 原文 →
AI 资讯

Question about Perplexity

I don’t know if this is the right sub-reddit to ask this type of question. I am quite ignorant about hardcore technical stuff. I want to say that I love the idea of an agnostic approach to AI and being able to understand and decide which model is best suited for a specific task. As well as the ability to have citations, being able to have it look through health research and stuff for queries regarding health, etc. Now I do not know if this is just in a general sense people just complaining or something else entirely, but I am seeing a lot of negative stuff on the Perplexity sub-reddit. In terms of like how the quality has gone down, asking how such a company is still even in business. I was just wondering if any of this holds any water or is overly exaggerated submitted by /u/No-Main6695 [link] [留言]

2026-06-06 原文 →