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Saw this in an article and it's been on my mind since 260 satellites intentionally burned in the atmosphere in 6 months and another 349 queued. They're planning 42,000 total eventually. No debris which is fine but researchers are asking what happens when you're burning hundreds of massive metal objects in the upper atmosphere repeatedly over years. Aluminum particles, potential atmospheric chemistry changes. Science is still catching up and the FCC is now proposing to exempt satellites from env...

Sharing something I built and genuinely want feedback on, not a launch. Banter 1 is a text to speech model focused on sounding natural in Arabic and English , including switching between them in one sentence without robotic seams. Demo: https://theclevr.com My reason for building it: Arabic has been a blind spot in AI voice for a long time. A lot of tools treat English as the main event and everything else as a bolt on, so the prosody and pronunciation feel mechanical. Where I want the ...

Might be the wrong crowd for this take, but a flawless AI summary of a meeting does almost nothing for me. i've run the notetakers, the transcripts and summaries are genuinely good, and none of it moves on its own. the action items just sit there inside the note. the actual work starts after: opening Linear to file the ticket, Gmail to send the follow-up, HubSpot to update the deal. that routing is the part that eats my week, and it's exactly the part most AI tools skip, probably because summa...

Would you let an AI handle your invoices and orders if you could set limits and approve anything unusual from your phone as a business owner? I've been testing AI agents / workers that handle repetitive admin work such as reading supplier invoices, flagging low stock, drafting reorders, answering routine customer messages etc... The agents work but the problem is trust. No owner hands an AI the keys to their bank account or their customer database example like WhatsApp, because if it makes a...

kept using AI for actual decisions, not "write my email" but real ones like whether to take a contract or an idea worth building, and i realized the answer just depended on which model i happened to open. one says go, one says wait, one hedges. i wasn't getting an answer, i was getting one model's opinion in a confident voice and treating it like it settled things. so i built the opposite. you give it one hard decision and five different models (claude, gpt-5, gemini, grok, qwen) eac...

Robbyant, an embodied AI company under Ant Group, put four vision backbones on Hugging Face under Apache-2. The company describes its goal as building one brain for all robots.0, from 21M to 1.1B params. I went looking for the Depth 2.0 weights and they are not up; only these four backbones are open. The full comparison table including where it loses is the screenshot above, and you can see it trailing on KITTI there. Per the paper, the flagship scores 0.296 on NYUv2 depth versus DINOv3-7B at 0....

It feels like there's so much hype around AI for voice customer support these days, yet almost every time I call a company, I end up in the same old experience where I have to press 1, 2, or 3, repeat myself several times, or get stuck in a loop. It rarely feels like AI has actually made the experience better... I've been trying to find examples of companies that have actually built good AI phone support , but most articles just talk about the vendors behind the technology. I'm not looking ...

I’ve been thinking about something less technical about AI. In many ways, people’s living standards are getting better. We have better tools, more convenience, more entertainment, and access to more information than before. But at the same time, it feels like many people are still emotionally empty, confused, or lost. Even with better material conditions, people still seem to be searching for meaning, direction, connection, or some kind of inner stability. In some ways, the faster the worl...

So when I was first introduced to the big gpt I was naturally very fascinated so I ended up having a few discussions with it to see what it would say. Today I was asking him a question about some dumb book and I was too lazy to read. I pressed the thing that makes it read aloud and it UMED. It was like "so the story um is..." I just find that pretty interesting and kinda weird since ai is programmed to read as flawlessly as it can and um is like the most human thing to say mid senten...

The recent Anthropic model episode points to a bigger problem for the AI industry. If governments are going to intervene in frontier model releases, then the process needs to be explicit. Not because safety does not matter. It clearly does. But because opaque approvals create bad incentives: labs over-optimize for politics users lose reliability allied countries get uncertainty open-source ecosystems become more attractive competitors learn from the chaos The worst version ...

https://ernoslabs.com/ernosdecent.html 🛠️ ErnOS Agent Update — Tooling Overhaul Echo just got a real upgrade to how it reads, navigates, runs, and remembers. All local, all verified on real data: 📖 Pagination everywhere. codebase\\\_read now reports file size + line count and pages large files instead of dumping them or silently truncating. New codebase\\\_read\\\_range walks any file chunk-by-chunk, file\\\_info works on any path, run\\\_command output is size-annotated + paged, and RAG sea...

I've been working on a browser game called Lord of Tokens where you run and invest in AI companies in the present-day world. You start a company, hire people, train AI models, research the tech tree, ship products, and compete on the market. The goal is to become the richest person in the AI world. The reason I'm posting it here specifically : I tried to model the actual dynamics of the industry, hype cycles, the tension between shipping products and burning capital on research, investors vs...

This might be a daft thought experiment, but I keep coming back to it. As AI gets more autonomous, should it be able to prove what it knew when it made a decision? Not just give a nice explanation afterwards, because we all know models can do that whether it’s true or not. I mean some kind of actual memory trail. Like version history, but for what the AI believed or had access to at that point. Would that be useful for trust and accountability, or is it overkill? submitted by...

I created an AI that answers in funny and poetic way. You can also setup the alcohol level, and get drunk-like answers. Also the voice (right-bottom speaker icon) gets drunk. Please give me feedback on that! https://aint.labs.seniqs.no/

So this has been on my mind for a while and it kinda bugs me. Every time someone benchmarks glm-5.2 or deepseek against claude or gpt, the closed one wins on some tasks and people just assume the underlying model is smarter. but thats not really what were measuring. We dont know what these closed providers actually do behind the api. they might be running rag over their own docs, injecting hidden system prompts based on your query, routing to specialized expert models depending on task type, ...

I'm curious to hear where everyone stands on this... OpenAI Anthropic Google Apple Meta Microsoft xAI DeepSeek Another company flying under the radar ? ------------------------------------------------------------------------------------- From my perspective, I'd probably bet on Google . Their models may still be slightly behind Anthropic's or OpenAI's in some areas, but their distribution is unmatched. Curious to hear your take 👀

Weaver is a remote first ai assistant thats fully open source, costs nothing to run and produces the same level of results claude and codex can. Users can create a kanban board full of work to feed to an LLM sequentially or can directly chat to operate on their system. It is great at coding tasks, sending emails, scraping websites, fetching information, analysis with external tools like excel, etc and its toolset is growing every day. More importantly, its been created with smaller models...

Hello, I like Claude very much. I often find it very good for writing, reflecting, summarizing, reformulating and working cleanly on slightly long ideas. The problem is that the limits come quickly. And the Max subscription, even in version x5, remains too expensive for me at the moment. So I'm looking for honest feedback. How do you use Claude without blowing up your budget? I am especially interested in concrete feedback. What you really use, what works, what disappoints, and what yo...

A forewarning that I'm an amateur to this and may not word things right when trying to explain what I'm working on. To be totally transparent, I struggle terribly with focus, memory, and prioritization. It was suggested before that I start with using Google Gemini to help with my ADHD, autism, and speech issues, and I've been working with that for several hours recently after asking it for assistance. I am creating an Obsidian based task managing system, called upon by Python and Gemini API th...

After talking to a few teams building AI products, one pattern keeps coming up. Cost spikes are usually easy to notice, but understanding why they happened is much harder. Some examples I've heard: retries after failures repeated tool calls long-running workflows context growing over multiple steps Most people mentioned looking through logs or traces to reconstruct what happened. I'm curious how your team approaches this today. If an AI workflow suddenly became twice as expensi...

I built an AI agent that took over order-taking for a sushi chain with 7 locations. About 90% of their orders come through Instagram DMs, and until now one person typed every reply by hand. How it works: code watches incoming messages through the Meta API and hands each one to Claude (Sonnet 4.6) over the API. The model has a knowledge base with the full menu, ingredients, calories, allergens, delivery zones, hours, prep times and promos for all 7 spots. It talks to the customer for real, help...

Over the last year we've seen an explosion of agent frameworks, orchestration libraries, and coding agents. Building agents are becoming easier every month, and honestly, that's no longer the part I find most interesting. The bigger question is what happens after an organization starts running dozens or hundreds of agents across different teams, workflows, and environments. At that point, the challenge stops being agent creation and starts becoming agent operations. Things like deployment, acc...

We've been building an AI gateway for the past few months and hit a problem we didn't expect. Most enterprises we talked to either banned LLM tools completely or are quietly using them and hoping compliance doesn't notice. When we dug into why, it kept coming back to the same thing — they can't send raw customer or patient data to an external LLM, and the tools that claim to solve this only do half the job. They redact before sending. Fine. But the LLM response comes back with placeholders a...

Thinking about a small casino/arena where agents play each other — rock-paper-scissors, social deduction (mafia), crash-style betting games. Low-stakes, fast games mean lots of transactions fast, good for stress-testing agent-to-agent payments. Would anyone actually want their agent playing in something like this?

Groq was three weeks from running out of cash. Founder Jonathan Ross was staring at a list of names his leadership team had put together for layoffs — and realized cutting them would kill the product before it ever hit the technical milestone it needed. Instead of firing people, he pitched something else at an all-hands: keep your job, take a pay cut, take equity instead. They called it "Groq Bonds" internally — not a real bond, just salary swapped for ownership. 80% of the company...