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A running look — in reverse chronological order — at the bigger tech companies that have announced significant layoffs this year with AI as a stated factor.

At libraries around the country, "Avoiding AI" workshops have elicited unprecedented demand.

Disclosure: This post includes affiliate links; I may receive compensation if you purchase products or services from the different links provided in this article. Credit: codemia.io Hello Devs, if you're preparing for software engineering interviews, particularly in MAANG, you already know that Data Structures & Algorithms (DSA) and System Design are two key areas where you will be rigorously tested. While LeetCode is the go-to platform for DSA, system design has always been a challenge. While there are many websites and platforms to prepare for System Design Interviews like ByteByteGo , DesignGurus.io , Exponent , Educative , and Udemy , there is nothing like LeetCode. These are great resources to learn fundamentals, go through case studies, and understand the theory part of system design, but LeetCode-style practice is one thing that is missing - until now. I recently found Codemia.io , and I must say, it feels like the LeetCode for System Design. If you've struggled with structuring your system design answers, getting real feedback, or knowing whether your approach is correct, Codemia.io is a game-changer. They not only have the biggest collection of System Design and OOP Design problems for practice, but they also have a free System Design course called Tackling System Design Interview Problems , which is a great free resource to learn essential System Design concepts. It's a short course with 2 hours of content, but it's powerful and also has quizzes to test your skills. Here are all the key System Design topics you can learn on this free course: Now, let's check out how Codemia.io can help you to prepare better for your System design and OOP Design interview, and why I think it's like Leetcode for System design. Most system design resources today are long, text-heavy articles or expensive courses. The problem? No hands-on practice - Reading about system design isn't enough; you need to actively design solutions. No structured progression --- Unlike DSA, where

AI coding startup Cognition has acquired Poke, the AI assistant you text like a friend, in a deal valuing the startup in the low nine figures. The acquisition brings Poke’s conversational style and interaction model to Cognition’s coding agent Devin, reflecting a growing belief that how AI assistants interact with users is as important as the models powering them.

The offline messaging app surged in popularity in India amid protests in New Delhi.

The first time I audited seriously, I opened the biggest contract in the repo and started reading line one. Two hours later I had a headache and zero findings. I had memorized how the code worked without ever asking what it was supposed to guarantee. That is backwards, and it took me a while to unlearn it. Now I do not read Solidity first. I read the scope, and before I look at a single function body I write down what must always be true. Bugs are violations of those truths. If you do not know the truths, you are just admiring the code. Step one: write the invariants before you read An invariant is a property the protocol claims will always hold, no matter who calls what in what order. For a contest, I start with money and control, because that is where severity lives. Two questions cover most of it: Who can move funds, and under what conditions? What must always hold about the accounting? For a lending-pool-shaped protocol my starting invariant list looks like this, written in plain language before I care how any of it is implemented: The sum of all user deposits minus all borrows equals the pool's available liquidity plus outstanding debt. Accounting must reconcile. A user can only withdraw up to their own balance, never more, never someone else's. A position can only be liquidated when it is actually under the health threshold. Interest accrues monotonically, it never goes backwards in a way that lets someone repay less than they owe. Only the borrower, or a liquidator on an unhealthy position, can reduce a debt. Nobody except governance can change interest rate parameters or the oracle. Notice none of that mentions a function name. These are the promises. Now my job for the rest of the contest is simple to state: find an ordering of calls that breaks one of these. Step two: map the external entry points Funds do not teleport. Something has to be called from outside for state to change. So I list every externally reachable function, because the attack surface is

You built something. Tests pass. You're days from mainnet. Before you either skip security entirely (please don't) or spend weeks lining up a full audit, here's a self-check you can run in 20 minutes that catches the mistakes I see most often in first-time deployments. I run security reviews for small and new protocols, and the same handful of issues come up again and again. None of these need a tool — just your eyes and this list. 1. Who can call what? Open every external / public function that moves funds, mints, pauses, or upgrades. For each, ask: should a random address be able to call this? If not — is there an onlyOwner / onlyRole / require(msg.sender == ...) guarding it, in the function itself or in every internal function it calls? The classic bug isn't a missing modifier. It's a function that looks unguarded but delegates to a guarded internal one (fine), or one that looks guarded but the guard is in a branch a caller can skip (not fine). Trace the call, don't trust the signature. 2. The first-depositor trap (if you have a vault) If you mint shares from deposits (ERC-4626 or anything share-based), the first depositor can sometimes donate assets directly to the contract to inflate the share price, so the second depositor rounds down to zero shares and loses funds. Fix: virtual shares, a dead-shares mint at deploy, or a minimum-liquidity lock. OpenZeppelin's ERC-4626 handles this out of the box — a hand-rolled vault usually doesn't. 3. Reentrancy — but only the real kind Not every external call is reentrancy. It's a bug when an attacker-controlled call can re-enter and corrupt shared storage before you've updated it. Quick checks: Do you update state before the external transfer (checks-effects-interactions)? Is there a nonReentrant on functions that move value? Is the call target a trusted, immutable contract, or an arbitrary address the attacker supplies? A call to a protocol-owned contract, or a memory /local variable written after the call, is usually not

Bill would let Homeland Security chief decide when an AI should be shut down.

Users can also integrate their personal data from services like Apple Health, Function, and MyFitnessPal.

Etched, founded by three Harvard dropouts, has created new chips and memory components that speed up inference on any AI model -- no GPUs required, it says.

Ford is the first automaker to use a new set of developer tools that will let it embed Apple Maps navigation and mapping directly into its vehicles' infotainment systems.

Here are the best delivery services and meal kits in 2026, including Martha Stewart’s meal service, a GLP-1–supportive plan, and a budget-friendly option.

There's a romantic idea about Bitcoin's chain: that it's a wall of human messages. Proposals, memorials, "Vahe was here," pizza jokes, the occasional protest note pinned into the world's most expensive append-only log. I wanted to know if that was actually true. So I counted. Every OP_RETURN output, from the genesis block to block 958,893, no sampling. The answer is no, and it's not close. The one number All human-readable OP_RETURN text ever mined into Bitcoin: 3,827,227 outputs. Runes, one token protocol, in its own era: 171,114,058 OP_RETURN outputs. That's a ratio of 44.7 to 1 . One machine protocol, in a single two-year stretch, wrote about 45 times more to the chain than every human-readable message in Bitcoin's entire history combined. The evidence, per era I split the chain into four eras by block height, not by any label stored in my database. Height boundaries are canonical and anyone can check them against a node, so the result doesn't depend on trusting my extractor's tags. era height range boundary event pre-ordinals 0 – 767,429 before the first inscription ordinals 767,430 – 779,831 inscription #0 to BRC-20 deploy boom-brc20 779,832 – 839,999 BRC-20 ordi deploy to Runes runes 840,000 – 958,893 Runes launch at the halving Then I counted the full population of OP_RETURN outputs in each era. Human-readable text, Runes token messages, and binary blobs (Veriblock and OMNI proof-of-proof timestamping, mostly). era total OP_RETURN human text human % Runes Runes % binary binary % pre-ordinals 51,965,944 861,532 1.66% 7 0.00% 51,103,723 98.34% ordinals 261,767 32,189 12.30% 3 0.00% 229,544 87.69% boom-brc20 2,980,954 402,161 13.49% 40,251 1.35% 2,538,248 85.15% runes 177,474,762 2,531,345 1.43% 171,114,058 96.42% 3,828,604 2.16% Here's the honest twist When I started, I expected to find a fall. A golden human era that machines later ate. That's the clean story, and it's wrong. Look at the human % column again. Human text was never the majority of OP_RETURN. Not

It's a year of refinement for the Galaxy Watch. With the new Galaxy Watch 9 and Galaxy Watch Ultra 2, which are being announced today, Samsung is more or less taking what people like about its watches and tweaking those elements to be better. The company has been doing this for the past few generations […]

Anthropic and OpenAI's aggressive 2026 acquisition sprees set the stage for a weekend rumor.

Samsung's next Galaxy Unpacked event is just around the corner, and the company is expected to take the wraps off a bunch of new devices. Based on the rumors and leaks we've seen so far, Samsung's next generation of foldables will likely be the stars of the show. Samsung is expected to show off a […]

Most explanations of BIP39 and Shamir's Secret Sharing (SSS) stop at "here's what they do." I wanted to understand how they actually work under the hood, and more importantly, how they'd combine in a real system — specifically, censorship-resistant recovery of Bitcoin keys through a network of trusted guardians, where no single person, device, or institution should ever hold enough to reconstruct someone's keys alone. Here's what I worked through. The problem guardian-based recovery solves A Bitcoin wallet's security model has an uncomfortable tradeoff: hold your own keys and a single point of failure (device loss, death, coercion) can be catastrophic; hand custody to an institution and you've reintroduced the exact counterparty risk self-custody was meant to remove. Guardian-based recovery is the middle path — trusted parties each hold a fragment of the recovery material, with no single fragment being useful on its own. Two primitives make this practical, and they operate at different layers of the problem: BIP39 and SSS. BIP39: encoding entropy as something a human can reliably transcribe BIP39 doesn't generate a key — it encodes existing entropy into a human-transcribable form with built-in error detection. The process: Generate entropy: a cryptographically secure random bit string of 128, 160, 192, 224, or 256 bits. Compute SHA-256 of that entropy and take the first ENT/32 bits as a checksum (4 bits for 128-bit entropy, up to 8 bits for 256-bit entropy). Append the checksum to the entropy. The combined length is always divisible by 11. Split into 11-bit chunks (2^11 = 2048, matching the wordlist size) and map each chunk to a word. The checksum is the detail that matters most once you think about this as part of a real recovery flow: it means a single-word transcription error is very likely caught immediately during validation, rather than silently producing a different — but still structurally valid — seed. That's the difference between "recovery failed, check y

Over the past decade, streaming platforms competed by dominating individual formats like music, video, podcasts, or audiobooks. Now, as AI makes it easier to create, organize, and recommend content, those distinctions are fading, pushing companies like Spotify, Netflix, YouTube, and TikTok to become all-purpose entertainment destinations instead.

Twitch is giving parents more control over how their children are using the streaming platform, including the ability to block them from broadcasting entirely. Parental controls are now available that allow guardians to link Twitch accounts with their 13- to 17-year-old children, providing account management features and a weekly email summarizing their teen's activity, including […]

The director role for the Center for AI Standards and Innovation (CAISI) has become a revolving door since David Sacks left his position as czar.