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Top robotics researchers and founders explain how robot autonomy is evolving.

Top robotics researchers and founders explain how robot autonomy is evolving.

Not sure this will have any effect, but I support the effort: According to Google’s legal filing, Outsider Enterprise operates through Telegram. The group offers phishing-as-a-service to individuals who may not be technically savvy enough to set up fraudulent websites and text campaigns on their own. In its Telegram channels, Outsider Enterprise reportedly provided instructions on how to use Google’s Gemini AI to create websites that imitate those of Google, YouTube, and government agencies such as New York’s E-ZPass. The group offered nearly 300 scam templates...

Grow a backyard’s worth of greens and vegetables in your house with a vertical hydroponic garden. Here are a few that might be worth the investment.

Nothing's Ear (3a) are ANC-equipped earbuds that cost less than $100.

Anthony Agueda, a third-generation California dairy farmer, pulls a rake through a bed of dark, wet wood chips on his family’s land in Hickman, a tiny town in the state’s agricultural heartland. He reaches down with both hands and pulls up a clump of muck, turning it over to reveal a half-dozen squirming red earthworms.…

“You can make a living, you can have a life, and leave 55,000 emails unread with a big fuck off.”

Norwegian striker Erling Haaland isn’t just a footballer anymore. He’s become an internet character perpetuated by fans and AI.

In a world regulated by devices, humanity has become disconnected from the physical world—from stick-shift cars to postcards.

Like most developers, I have a handful of small utilities I reach for every day — formatting JSON, decoding a JWT, generating a UUID, testing a regex. For years I just googled "json formatter" and pasted my data into whatever site came up first. Then one day I caught myself pasting a production JWT into a random online parser that POSTs everything to its server. That felt bad. So I built my own toolbox that never sends data anywhere. It's called WeTool — free, no login, and every tool runs 100% in your browser . You can open DevTools → Network and confirm there are zero requests while you use it. Here are the 15 I use most: Everyday JSON formatter / validator URL encode / decode Base64 encode / decode Timestamp ↔ date converter Security & encoding Hash calculator (MD5 / SHA) JWT parser UUID generator QR code generator Text & format Regex tester Text diff Markdown preview SQL formatter Debugging Cron expression parser Color converter User-agent parser Two things that matter to me and might to you: Nothing is uploaded. No backend, no login, no tracking of what you type. Local-only. 15 languages. Most tool boxes are English-only; this one isn't. It's free and I'm actively adding tools — if something you use daily is missing, tell me in the comments and I'll add it. 👉 wetool.site

We build an internal helpdesk, and I want to talk through a problem we only partly solved — because I suspect a lot of you have hit it too, and I'd genuinely like to hear how you handled it. The most requested thing from our users was never "better ticket forms." It was "please make the duplicates stop." Here's the shape of it. A deploy goes slightly wrong at a 40-person company. Within ten minutes you have: a handful of chat messages : "login is broken", "can't get into dashboard???", "deploy looks weird" several error-tracker events (whatever you run — Sentry, Rollbar, an APM): TokenExpiredError ×2, a 401 spike on /api/auth , a 5xx spike on auth-svc a couple of emails to IT : "access token expired", "need login reset" Nine items across three channels. One root cause: token rotation broke in that deploy. Whoever's on rotation spends the morning proving that, instead of fixing anything. We wanted to automate the recognition step — "these are the same thing" — not the fixing step. This is the honest version: what we tried, the small thing we actually shipped, and the parts we haven't cracked. If you've built something similar, I'd love to be told what we got wrong. Attempt 1: rules and keywords (broke immediately) The obvious first cut: normalize ticket text, match on keywords and categories, merge on high overlap. It fails on the example above, and it fails structurally: "login is broken" and TokenExpiredError share zero tokens. The human on rotation isn't string-matching — they know a deploy just happened, they know what auth-svc does, they've seen this failure shape before. Rules encode none of that. Rule systems also rot. Every incident teaches you a new synonym for "it's down," and six months in you own a regex museum nobody wants to touch. Maybe you've kept one of these healthy long-term — if so I'd honestly like to know how. Attempt 2: embed everything, cluster by similarity (the one we didn't ship) The tempting next move: embed ticket text, cluster on cosine

The data layer for AI agents Discussion | Link

The lab will beam back data to train AI models to predict how proteins behind age-related diseases like Alzheimer’s and certain cancers behave.

The first question I ask when reviewing a frontend architecture is: where does the state live relative to where it is used? In most codebases I have reviewed, the answer is "in a global store, regardless of scope." This is the wrong default. The rule State should live as close to its consumers as possible. If only one component needs it, it is component state. If a subtree needs it, it is a context or service scoped to that subtree. Global state is for truly global concerns: authentication, locale, theme.

Most async code in frontend apps has a hidden bug: it doesn't stop when it should. A user navigates away mid-request. A component unmounts. A newer search query supersedes the previous one. The old network call keeps running, eventually resolves, and tries to update state that no longer exists. In React, that's the infamous warning: "Can't perform a React state update on an unmounted component." In vanilla JS, it silently delivers stale data. AbortController is the browser's built-in solution. It's been in every major browser since 2018 — old enough that there's no excuse not to use it. But most tutorials skip it, most codebases use it inconsistently, and most devs reach for it only after they've debugged a flicker one too many times. Here's the pattern, end to end. The race condition you already have function SearchResults ({ query }: { query : string }) { const [ results , setResults ] = useState < Result [] > ([]); useEffect (() => { fetch ( `/api/search?q= ${ query } ` ) . then ( r => r . json ()) . then ( data => setResults ( data )); // runs even if query changed }, [ query ]); return < ul > { results . map ( r => < li key = { r . id } > { r . name } </ li >) } </ ul >; } When the user types "re" and then "rea" before the first request finishes, two fetches are in flight simultaneously. The request for "re" might complete after the request for "rea" — and when it does, setResults silently overwrites the correct result with the stale one. The component shows the wrong data. No error, no warning, no clue. This is a race condition, not a hypothetical. It happens on slow networks, during fast typing, on underpowered devices, and in staging environments right before a demo. AbortController: the three-line fix An AbortController is a pair: a controller object and a signal. You pass the signal into any abort-aware API; you call abort() to cancel it. useEffect (() => { const controller = new AbortController (); fetch ( `/api/search?q= ${ query } ` , { signal : control

In 2008, Richard Thaler and Cass Sunstein needed an example simple enough to explain the whole of economic theory from a single application. They used a cafeteria menu. By moving the fruit to eye level and sending the fries to the periphery, they demonstrated that a slightly adjusted environment could convince thousands of students to make healthier choices. No one is stopped from choosing fries and the fries-loving student still chooses fries. But the undecided student chooses the apple, simply because it is now right in front of him. In 2017, Thaler was awarded the Nobel Prize in Economics for his body of work, including the development of “The Nudge Theory” with Sunstein. In the years that followed, product teams building mobile applications have taken to referring to any call-to-action on-screen as a nudge. The design of an effective nudge There are two requirements for a nudge to work reliably. The user should have an apparent desire for the thing they are being nudged toward, and the nudge should appear at the moment when this desire is at its peak. The first requirement ensures the user has a mental model of the target action, meaning they understand roughly what they are supposed to do. The second requirement serves to remove any extraneous context, ensuring the nudge does not fail due to poor timing. A checkout confirmation modal shown straight after launching the application will fail miserably as a nudge. The desire to checkout is non-existent at the launch moment, and the context of the action has little to do with the action itself. A tooltip shown after a specific number of unsuccessful attempts to checkout after viewing the cart, however, is a nudge. It has the desired behavior and the right timing. Why the difference shows up in the numbers In the example with Duolingo, the product team has effectively used the framing of an existing streak as a reference point for the next level of engagement. The players who saw streak-based progress notifications

Parts 1 and 2 of this series ( Microsoft Entra extensibility is a gift. It is also Control Plane. and Securing the code that decides who Entra trusts ) made two static decisions. Where the code lives: a dedicated Control Plane subscription, directly under the root management group or under a dedicated Control Plane management group, never in the platform identity subscription or an application landing zone. What credential it uses to call out: a managed identity by default, federated identity credentials when the call must leave Azure, certificates as a tolerated middle step, and static symmetric keys never. Both decisions are one-time. You make them, you walk away, you do not touch them for months. The third decision is not like that. It is continuous, and it is the one most teams quietly skip: how do you know the deployed code on that Function App is still the code your reviewers approved? How do you know the Logic App workflow definition has not been rewritten since last Tuesday? How do you know nobody added a federated identity credential to the managed identity at 3 a.m. on a Saturday? The answer is monitoring. Not "we have Log Analytics turned on." Monitoring with a specific operating contract attached. The posture inversion For most Azure workloads, the default operating posture is reasonable trust. Engineers deploy. Pipelines run. Configuration drifts a little. The team reviews changes weekly. Anomalies are caught eventually. For a Microsoft Entra extension, that posture is wrong. The default has to be inverted. Once an Entra extension lands in production, every change to it is suspicious by default. Not "needs review." Not "let's check first." Suspicious. The default state of an alert firing on a Function App that hosts a custom claims provider is "the SOC is investigating, prove this was approved." If you cannot prove the change was approved within the team's response SLA, the change is treated as an incident and rolled back. That posture is harsh on purpo