Abertura Eu sempre participei de comunidades de tecnologia: grupos de estudo do Google,...

It's more of a baa-ter arrangement.

The saga of Musk's tussle with the SEC over how he disclosed his growing stake in Twitter (now X) has come to an end.

The $300 million round is expected to be led by Menlo Ventures, Sifted reported.

Meta might be the next company to make an always-on AI wearable. The company is working on prototype "super sensing" always-aware smart glasses that could continuously record audio and snap photos "every few seconds," according to the Financial Times. The wearer could then ask Meta AI about the captured audio and images. However, the images […]

It is been while I am learning and build around FastAPI. So there is a project where I was thinking how to add this new feature over exiting one. Like what changes I need to make in database which need to be reflected in my backend and frontend. I already lunched the web locally. Problem started When I when back to the web and reload it it shows this error: ERROR: ConnectTimeout: Unauthorized 401. I was like what? Why? I thougth there is some issue with login endpoint or refresh token function. When i did some debugging and found some new information which is: "Either Supabase's edge/pooler (or OS, or an intermediate proxy/NAT) silently kills those idle connections server-side after some timeout but client-side pool doesn't know that." As I was doing nothing in become idle state so to save the resources server side silently close that particular connection. So I came back and try to connect it give this error. First thought come it my mind after this was there should be a way to automatically check this idle state and if user was in ideal state then create a new connection. Proposed Solutions After a while I come up with these solution: Calculate the Idle time: if it is more then server connection timeout then establish new connection. Retry logic: retry once on the specific connection errors. I thought this will work but This again give me error then this new issue I faced. Cold-start connection problem There is something call dual-stack (IPv4 and IPv6) networks and Happy Eyeballs is a network mechanism which automatically move to IPv4 connection if IPv6 fails. But supabase-py uses httpx and it doesn't support Happy Eyeballs. So in first try after the connection time out it try to establish IPv6 connection which is not routeable in most Pakistani ISPs and ultimately it fails and wait for timeout. There is no way to try it again for IPv4. So we have to do it manually. So this error help me to learn many thing in process. Share your thoughts.

The social platform wants its crowd-sourced corrections to be harder to ignore.

The National Highway Traffic Safety Administration said emergency scenes are not "edge cases."

Introduction My zsh profile is over 1000 lines at this point. A lot of that is functions I asked AI to generate for me, since it's fast, portable, and saves me a ton of typing. Here's the thing though: the shortcuts that save me the most time aren't the clever ones. They're the dumb ones. Things like clone instead of git clone && cd , or dir instead of mkdir -p && cd . Each one only saves a second or two, but I run them so often that it adds up fast. These are in no particular order, just the ones I reach for constantly. Git aliases for common commands A few one-liners I have set up as plain aliases: alias gcp = "git cherry-pick" alias git-append = "git commit --amend --no-edit -a" gcp is self-explanatory. git-append amends the last commit with your currently staged (and unstaged, thanks to -a ) changes without touching the commit message. Great for fixing up a commit you just made before you push. Create a branch or switch to it if it already exists One of my most-used functions. Normally you have to remember whether a branch exists before deciding between git checkout <branch> and git checkout -b <branch> . This just does the right thing either way: gb () { if git rev-parse --verify --quiet " $1 " > /dev/null ; then git checkout " $1 " else git checkout -b " $1 " fi } Nuke all local changes to reset the working tree When an experiment goes sideways or I just want to throw everything away and start clean, I run nah : nah () { git reset --hard git clean -df if [ -d ".git/rebase-apply" ] || [ -d ".git/rebase-merge" ] ; then git rebase --abort fi } This resets tracked changes, removes untracked files and directories. No confirmation prompt, so use it carefully. Print recent commits as ready-to-paste cherry-pick commands Useful when you need to cherry-pick a batch of commits from one branch onto another in order: logs () { if [[ -z " $1 " || " $1 " = ~ [ ^0-9] ]] ; then echo "Usage: logs <number_of_commits>" return 1 fi git log -n " $1 " --reverse --pretty = format: "g

AI cheating leads to "a failed society," professor says.

I run a local LLM agent (Hermes) on my own machine. The problem was never the model — it was the interface . I had a Telegram tab open all day just to talk to it: type a command, wait, read a wall of text back, scroll. It felt like texting a very capable stranger. So I built Ghost Vessel — a monitor-resident, video-call-style avatar that fronts the agent. The name is the whole idea: the ghost is your agent, the vessel is the body it borrows. It's not a waifu toy; it's a real agent client that happens to have a face. Here's what actually turned out to be interesting to build. The reply is a script, not a string The core idea is an output contract . Instead of treating the agent's reply as text to print, I split every reply into three planes: dialogue → spoken via local TTS data → code, logs, files → rendered as chat cards, never read aloud action → emotion beats that drive the avatar Emotion beats are inline tags the model emits in-band with its answer: [working] — the avatar puts on glasses and takes notes while a task runs [confirm] deploy to prod? — pops a human-in-the-loop approve/cancel, and the agent blocks on your keypress [happy] / [concerned] / … — fine-grained facial expressions So "run the build, and if it passes, deploy" becomes a little performance : it looks busy while working, shows you the log as a card, then leans in and asks before the irreversible step. The text you'd have skim-read becomes something you glance at. No runtime GPU for the avatar The obvious way to animate a face is live inference. I didn't want that — the GPU is busy running the actual model. Instead the avatar is ~30 pre-rendered clips , and the emotion beats just select and blend between them (blink-aligned seamless idle loops, a head-pose "settle gate" so an expression only reveals when the head is frontal). The avatar's runtime cost is basically video playback. Your GPU stays 100% on your LLM. The tradeoff: no real-time lip-sync. I decided a believable talking mouth loop + expre