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The project’s first mission could arrive as soon as this year, with a little help from Blue Origin.

Simulate real store with LLM-powered synthetic consumer Discussion | Link

I am trying to build a guess-the-x sort of game/quiz, a full stack application, the stack doesn't matter, I was trying to find a way to send an API payload to my front-end securely without users being able to cheat by inspecting the payload using the requests devtools tab. the idea of this quiz is users are given a pixelated image, and many game details like title, summary, devs, pubs, platforms etc... depending on the difficulty I reveal to the users a percentage of the hints early, e.g. easy they can 30% of [devs, pubs, summary, etc...] 15% at medium, and 0% at hard. the image cannot be unpixelated manually however, at each wrong guess it unpixelated automatically, but for other indicators users can "unredact" them using hint points, (3 in total) obviously if not designed properly this is very each to cheat if a user is even slighly tech savvy since the backend sends the entire payload as-is to the client, what i did was my payload response looks something like this: { summary: { { text: "xxxxxxxxxxxxxxxxxxxxxx", revealded: false, text: "something something", revealed : true } } } and i store game state in redis that way i dont have to hit my database for every post request the client makes to fetch the game data; the redis state looks something like this { answer : game.title, hints_left: 3, guesses_made: 0, full_game_data : game, } then the other issue is the game cover, the data isnt mine, prior to this i had built an ETL pipeline to ingest data from IGDB's api, i only save their cover id to my database, something like 1234abc. so on the initial GET request, i hit their CDN endpoint, get the cover, process it in the backend, (pixelization), base64 encode it, which im aware that encoding binaries to base64 is a 1.37x increase over the original data, but i found no way of transmitting images securely to the front end except this one; so im asking for recommendations. right now this is a little slow, even on local host it could reach 2s for image load, mainly beca

Deep Research Agentic Systems are AI Agents designed to conduct multi-step research for complex tasks using dynamic reasoning, multi-hop information retrieval, and generate structured analytical reports. Sarang Kulkarni from Thoughtworks spoke at Arc of AI Conference 2026 on how to deploy multi-agent research systems for deep reasoning, and the lessons learned from developing Deep Research Agents. By Srini Penchikala

User onboarding now with an AI copilot Discussion | Link

See how OpenAI, Thrive, and Crete built a self-improving tax agent with Codex, automating filings, improving accuracy, and accelerating workflows.

submitted by /u/esporx [link] [留言]

Pullfrog is an open-source AI-powered GitHub bot by Colin McDonnell, designed for automation in GitHub Actions. It supports a model-agnostic approach, allowing integration with various LLM providers. Key features include orchestration for pull request reviews, issue triage, and CI remediation, all managed within GitHub's environment. The tool operates with a bring-your-own-key model for access. By Daniel Curtis

https://preview.redd.it/ww14mzr2fm3h1.png?width=1890&format=png&auto=webp&s=79873d47ae79c7815ca3e7e91fd43141632174f5 https://www.youtube.com/watch?v=rr_uS4bf0B4&feature=youtu.be trained a 7MB open-source L4 self-driving AI that learns navigation, lane following, and drift recovery directly from visual and sensor input. designed for real-time autonomous driving on lightweight edge hardware like phones and embedded devices, without massive server-scale infrastructure. submitted by /u/moorish-prince [link] [留言]

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 personal

Hi everyone, I'm finishing up my proposal for my undergraduate thesis for computer science on sign language recognition, specifically Filipino Sign Language and i want to ask what architecture to use for my methodology that is best, rn im considering Mediapipe Holistic + Transformers or Media Pipe Holistic + Mamba SSM. The only caveat is prev researches already done the first one and im not very familiar with the latter. Which do you think is the best method? Thank you submitted by /u/Unable_Let_6998 [link] [留言]

We're writing a research paper on explainable fraud detection GNN model and in the first step we're creating a basic Graph Neural Network for that. We're using the most famous dataset available on this topic i.e IEEE CIS Fraud Detection Dataset and implemented all necessary feature engineering on that data (although majority of feature engineering is already performed in the dataset). Then we constructed a heterogeneous graph on that dataset. Various transaction features like device, transaction id, amount are embedded as nodes and connected with transaction nodes. But the issue is after training the model isn't performing well. It is producing average AUC of 0.87, PR-AUC of 0.52, recall@5% around 0.57 and precision@5% around 0.37 (We tried GCN, GraphSAGE and GAT, all performs almost same for rest data) Whereas the SOTA models in this topic produce much better metrics. Can anyone tell where potentially we're doing things wrong? submitted by /u/LiveAccident5312 [link] [留言]

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This is a submission for the Hermes Agent Challenge: Build With Hermes Agent What I...

Introducing Posthorn, a self hosted email gateway. One docker container (or Go binary) between every self hosted app on your VPS and your transactional email provider. Set up Posthorn once, point your apps to it, done. I was trying to deploy Ghost on a DigitalOcean droplet and found that DO and many different VPS services have started to block the default SMTP ports to try to combat the various types of abuse they get. To actually configure my app, I had to hack together a Postfix relay. In anot

I randomly came across this conference/workshop: IEEE Workshop on Machine Learning for Signal Processing. Is this a reputable conference and is it worthwhile to submit here vs. a workshop at an A* like ICML, NeurIPS, etc.?(I know these deadlines have passed, I have a paper currently under review.) I know IEEE varies considerably in quality. I'm an undergrad at a smaller liberal arts school so I unfortunately have limited advising on good quality places to submit, and I don't think this current research project is quite top conference-level. submitted by /u/B3anman [link] [留言]