HackerNews

Qwen3.8-27B

Article URL: https://twitter.com/alibaba_qwen/status/2088280182356611304 Comments URL: https://news.ycombinator.com/item?id=49299684 Points: 165 # Comments: 61
HackerNews

Unsloth Qwen3.8-27B GGUF files

Article URL: https://huggingface.co/unsloth/Qwen3.8-27B-GGUF Comments URL: https://news.ycombinator.com/item?id=49299688 Points: 21 # Comments: 0
HackerNews

Introducing Toast 1

Article URL: https://www.mixedbread.com/blog/toast-1 Comments URL: https://news.ycombinator.com/item?id=49299746 Points: 33 # Comments: 4
HackerNews

"Solving a largely imaginary user goal"

Article URL: https://unsung.aresluna.org/solving-a-largely-imaginary-user-goal/ Comments URL: https://news.ycombinator.com/item?id=49300411 Points: 3 # Comments: 0
Meet Ember, my custom ChatGPT Pet Dragon
Reddit

Meet Ember, my custom ChatGPT Pet Dragon

So I was poking around with ChatGPT settings, while waiting for a task to finish, and noticed that I can actually make my own agent pet. After some extensive "engineering" here is the final result. The concept is that it is a chibi dragon that roasts its marshmellow with its fiery breath (when agent is working) and it is inspecting the results of the marshmellow-cooking when agent is thinking/reviewing etc. There is even a jumping animation when hovering the cursor. Feedback and ideas ...
Reddit

Ran Unitree founder Wang Xingxing's interview audio through a personality-analysis model I'm building — here's what came out (fun experiment, not a validated psych tool)

Been building a personality-analysis framework (Outframe). I ran my own profile through it first and it felt pretty accurate, so out of curiosity I tried it on a public figure too — Wang Xingxing, the Unitree founder whose robots have been getting a ton of buzz lately (the dancing robot, the backflips). Fed one of his public interview clips in and let it generate a behavioral profile. To be upfront: this isn't a validated psychometric instrument. Take it as a fun read, not a diagnosis. What ...
Reddit

New to AI

Hi! I recently graduated high school and will be starting university this upcoming fall as an engineering major. Although I have used AI tools like Claude, ChatGPT etc but I lack experience (or any kind of knowledge) about how to make my own AI models and AI ethics. I just wanted to ask for some guidance from people who are already experienced in this field if there are classes/courses they recommend I take. I have some free time before university starts so I want to build some projects and ki...
Reddit

Realized there's a name for the thing I kept doing wrong in AI debugging sessions: confusing "symptom resolved" with "cause found"

Kept running into a specific failure pattern across different AI-assisted debugging sessions and didn't have a clean way to describe it until I actually sat down and compared a few of them side by side. The pattern: an error goes away, I file the problem as solved, and sometime later the same underlying issue resurfaces wearing a different symptom. Turns out those are two separate claims that get treated as one by default. "The error is gone" only tells you the symptom stopped being ...
Reddit

When the smartest AI model is actually a terrible business move

I came across this article that flips the script on AI hype: sometimes the most advanced models are the worst for business. High costs, misaligned incentives, and ethical risks can turn a technical win into a strategic loss. Have you seen this play out in your work or industry? (Not affiliated, just thought it was a refreshing take.) [Source: https://www.hitechies.com/ai-smartest-model-worst-business-decision/\ ] [link] [commen...
I've built a fully autonomous meditation system for TouchDesigner
Reddit

I've built a fully autonomous meditation system for TouchDesigner

A new output from this experimental real-time BCI system for TouchDesigner; a Brain-Computer Interface pipeline that reads live EEG signals, classifies your mental state, and autonomously generates responsive AI video: a meditation guide that adapts to your brain activity, second by second. The system is built around OpenBCI (open-source hardware + software), but it's designed to work with most BCI headsets after a few pertinent tweaks to the OSC routing and channel-rename logic; Muse, Neurosi...
🌍 TheVerge

Help build a monument to that ‘sad little bitch’ Elon Musk

Cards Against Humanity is gearing up to build "something that will annoy Elon Musk," and it's crowdfunding the project with its usual flavor of vulgarity. The company behind the card game announced plans to build "a grand monument" to Musk on the parcel of land it owns near Starbase, Texas, with the aim to "make […]
🌍 TheVerge

Apple trained its own AI model for China with help from Alibaba

Apple has reportedly trained a custom AI model for the China market alongside domestic tech giant Alibaba, a rare cross-border partnership that cuts across growing tensions between Beijing and Washington. The China-focused large language model was developed in partnership with Alibaba and trained with the company's support, Reuters reports, citing three unnamed people familiar with […]
🌍 TheVerge

Hoto’s new cordless soldering iron heats up in three seconds

Hoto is introducing its first soldering iron through its modular Snapbloq collection that lets you assemble your own custom toolbox by stacking magnetic cases and tools together. The new I-A06 Cordless Soldering Iron can heat to just over 200 degrees Celsius in about three seconds and offers an adjustable temperature range from 100 to up […]
🌍 Dev.to

All 26 of My MCP Tools Failed the Same Way. My Test to Rule Out the Token Proved It Was the Problem.

Every tool the GitHub MCP server offered was sitting right there in the list — all 26 were recognized correctly. Call any one of them and it failed in under 1 second, every time, with one line on screen: Tool execution failed . No reason attached. Even reading a fully public repository — something that needs no permission at all — failed the exact same way. TL;DR: my AI assistant's first guess — "maybe the token's gone bad" — was right the whole time. I ran an experiment that looked like it...
🌍 Dev.to

I Built an AI Agent to Boss Me Around — and It Made Me Launch an Open Source Project

Nine days ago, I did something a little unhinged: I built an AI agent whose only job is to be my marketing boss. It calls me "kid," scolds me when I disappear for five days, and hands me a daily list of propaganda tasks with exact copy to paste. This is me following its orders. Because it told me to post this. What the boss made me do My AI boss runs a 30-day "cold-start marketing campaign" for two open source projects I've been building: Parthenon — a self-hosted AI a...
🌍 Dev.to

Your Coding Agent Probably Doesn’t Need a Memory SaaS

I kept seeing SaaS products for coding-agent memory. The continuity I actually needed fit in one small, bounded Markdown file inside the repository. I started seeing a whole bunch of vibe-coded SaaS solutions for giving coding agents memory between sessions. Some of them are interesting, but I thought there might be a much simpler way. For this particular problem, a full-blown SaaS is not really needed. At least, not for what I was trying to solve. I did not need another account, SDK, d...
🌍 Dev.to

I Gave XGBoost and LightGBM the Same 30 Seconds — The Speed Winner Didn't Win Anything

The One-Line Summary: On the same data with the same tuning budget, XGBoost and LightGBM finished 0.00020 AUC apart — and when I handed LightGBM its 2.23× speed advantage back as extra search time, it fitted 1.59× as many candidates and gained −0.00013 AUC for the trouble; the real difference between them is not accuracy, it is that LightGBM trains 3.3× faster while XGBoost predicts 2.2× faster. The Question Everyone Asks Wrong "Which is more accurate, XGBoost or LightGBM?"...
🌍 Dev.to

Measure a Free Model Route With a Golden Set, Not a Leaderboard

The first number I track when evaluating a free model route is not the public benchmark delta. It is the semantic failure count in a 100-case golden set. A public benchmark can be flat while your application's specific tool calls, JSON schemas, and failure states move. I start with a golden set: 100–300 request/response pairs captured from the current route. Each case stores the expected tool call and a small list of acceptable result patterns. The set must include ambiguous prompts, permissi...
🌍 Dev.to

React Email Checks Need One Source of Truth

If your signup form still stores email validation as a loose pile of booleans, that field is probably lying to your UI from time to time. I keep seeing the same combo in production React apps: isChecking , isAvailable , error , maybe hasBlurred , and then one slow request arrives late and the screen says something that is no longer true. It looks fine in demos, but under real typing speed it gets messy fast. Lately I have been treating email checks as one workflow with one state shape. Th...
🌍 Dev.to

A No-Cost Harness for Comparing Free Coding-Agent Models and Runtimes

You can waste hours comparing coding agents by reading model cards or watching polished demos. The cheaper signal is a tiny audit that records whether the agent changes only the intended files and leaves the test suite green after one under-specified, realistic task. This guide gives you the harness, the fixture pattern, and the reading rubric. MonkeyCode is a useful platform for this because its free model access lets you repeat the same probe across different model labels without metering e...
🌍 Dev.to

A course generator with a quality gate: five ADK agents on Cloud Run

This post is my submission for DEV Education Track: Build Multi-Agent Systems with ADK . What I Built A course-creation service with a built-in quality gate. You give it a topic, and roughly two minutes later you get a structured course module — researched, reviewed, and only then written. The interesting part is the reviewed . Single-agent generation pipelines happily write authoritative-sounding courses from whatever their first research pass dredged up. This system puts ...
🌍 Dev.to

Your linter has been spreading the bug it was built to catch.

Single source of truth One number described your product. It appeared in five places with five different values. The tool built to prevent exactly this had spent months making it worse. Five values for one fact The number was how many tools our server offers. A simple, countable fact. It is generated from the code itself, so there is no room for opinion. The generated truth said 122. Thirteen public pages said 126. The launch texts for Hacker News said 89. The marketing em...
🌍 Dev.to

A Two-Model Regression Harness for Evaluating a New Low-Cost Model Release

When a new low-cost model appears, launch-day benchmarks tend to dominate the discussion. Developers rarely need a global leaderboard; they need to know whether the model breaks a critical parse function, emits an unsafe shell command, or changes behavior on a repo-specific bug fix. That answer cannot come from a vendor chart. This article presents a small regression harness for comparing a candidate model with a baseline on a handful of private, deterministic tasks. The harness is useful whe...