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Instagram is coming for streaming services like Netflix and Amazon Prime Video as it sets its ambitions for living room viewing.

"I don’t know of a bigger question we can answer as humans."

Today, I’m talking with Jack Conte, the CEO of Patreon. Jack last joined me on the show almost exactly five years ago, in the summer of 2021, and a lot has changed on the internet and in the creator landscape since then, so I was very excited to talk to him again, especially since his […]

Walmart has the Apple AirPods Max 2 in every color discounted to $399.99 (normally $549) during Walmart Deals, the lowest price we’ve seen yet by a long shot. Amazon currently has the starlight color selling at this price. In our review, we praised Apple’s latest over-ear headset for its excellent sound quality, impressive noise cancellation, […]

The company warned about dangers of advanced AI far more than rival OpenAI.

The company is also eliminating a production shift at its Arizona factory to align "production plans with anticipated demand."

After 18 years of focusing on Europe, early-stage investor Seedcamp said that it has raised $320 million for its latest fund which will see it expanding its presence in the United States.

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This week's Java roundup for June 15th, 2026, features news highlighting: point releases of Spring Tools, Helidon, JobRunr and Gradle; the June 2026 edition of Open Liberty; the first milestone release of Apache TomEE 11.0; the first beta release of Hibernate ORM 8.0; Quarkus emergency maintenance releases to address CVE-2026-50559; and four open-source projects join the Commonhaus Foundation. By Michael Redlich

I wrote about interesting amd64-specific quirk. If a large array is 4-byte misaligned, making it 8-byte aligned can make the array clearing ~49% faster (at least on my Intel machine). In the post I also touch on Intel's REP STOSQ implementation, ERMS and also on other optimizations related to array clearing. submitted by /u/watman12 [link] [留言]

submitted by /u/andersmurphy [link] [留言]

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My Testing Setup I used Midjourney V7 (midjourney.com, Standard plan at $30/mo for this project — volume was too high for Basic) over five weeks across six product photo projects: lifestyle context images, background replacement concepts, packaging mockups, and mood-board style reference images for briefing photographers. Some outputs went live in ads. Others were used internally. A few were scrapped entirely. Two specific examples: I generated 12 lifestyle context images showing a skincare product in a bathroom setting — no actual product in the image, just the environment and mood — and used them as ad backgrounds with the real product composited in afterward. Results were strong. I also tried to generate images of the actual product itself from reference photos. That failed in ways I will explain. Pricing: Standard plan at $30/mo. For product photo work at volume, Basic at $10/mo runs out fast. Budget for Standard if this is a regular workflow. 1. Lifestyle Context and Environment Images This is where Midjourney V7 earns its place in a product photo workflow. Generating the environment — a kitchen countertop, a gym bag, a coffee shop table — without needing to stage or shoot it is genuinely useful. I needed eight lifestyle backgrounds for a supplement brand's ad campaign. Real location shoots for eight setups would have cost $3,000 and taken two weeks. I generated the environments in Midjourney, exported them, and composited the real product in using Photoshop. Total cost: $30 for the month's Midjourney subscription and four hours of compositing work. The images ran in paid Meta ads for six weeks. CTR was in line with our studio-shot creative. Nobody asked if the backgrounds were AI-generated. The key: generate the environment only. Do not try to put your specific product into the Midjourney image. Composite it in post. That division of labor is where the workflow holds up. 2. Packaging Mockups for Concepts That Do Not Exist Yet Before you manufacture a product o

What is a Link? Definition A link is an interactive element that redirects the user to a new location which can be another section inside the current page, modifying the URL with a # parameter, or a new page. It can be used to download a file. Once activated, it takes the user to the URL set in its href. The browser records that navigation in its history, so the user can return to the previous page using the back button. Semantic The elements needs the attribute href with a valid URL or an IDREF pointing to a section inside the current page to have the semantic value of a link, otherwise it will be considered as generic . <a href= "/URL" > Go to main page </a> Keyboard Interaction It can only be activated by pressing the key Enter . If the key Space is pressed while the focus is on the link, the page will scroll down. Screen Reader Interaction Screen Readers, generally, announce the links in the following way: Link, [accessible name of the link] . It is extremely important to provide a descriptive and correct accessible name to the element. Bad Practice It is completely unnaceptable, a bad practice and goes against the native behavior of the element, forcing it to behave as a button by doing the following: <a href= "javascript:void(0)" onclick= "openModal()" > Open Menu </a> <a href= "#" role= "button" onclick= "button()" > Link with role button </a> If you need to do this, it means that you need a link. What is a button? Definition A button is an interactive element that dispatches an action inside the page where it is located. It does not redirect the user to another place or location nor modifies the url. The actions that are being dispatched can be: open a modal, play a video, post a comment, etc. Semantic The button needs the attribute type with a value according to its action: - type="button" : it is used when the button does not have a default behavior. - type="submit" : it is used when the button sends information to a server. - type="reset" : it is used to

Everyone is asking whether AI can write code. That question is already answered. The more important question is: Can AI understand the system it is changing? The biggest limitation of AI coding tools isn't code generation. It's system understanding. That is no longer the interesting question. AI can already generate APIs, tests, database migrations, infrastructure files, and entire services. The better question is: Does your AI understand the system it is changing? For most engineering teams, the answer is no. And that is where many AI-assisted workflows quietly fail. The illusion of understanding Ask an AI assistant to: create a new endpoint add a background worker generate a service layer write a migration Most models will produce something that looks correct. The code compiles. The tests may even pass. But production systems are not collections of files. They are collections of relationships. The real questions are: Which service owns this capability? Which projects depend on it? Which runtime executes it? Which release gates are affected? Which verification steps must pass? What breaks if this change is wrong? These questions are rarely visible in source code. They exist in architecture, operational knowledge, deployment rules, contracts, and team conventions. That is why an AI agent can generate valid code and still make the wrong change. Bigger context windows won't solve this The common response is: Give the model more context. But more context is not the same as better context. A million tokens of source code still do not explicitly answer: What projects exist? Which commands are safe? What evidence is trusted? What is currently blocked? What is ready for release? The issue is not missing tokens. The issue is missing structure. The missing layer Most AI tools understand: files functions repositories Production systems require understanding: ownership architecture dependencies operational boundaries verification requirements change impact This is the gap betw

Sometimes designers have silly ideas that eventually grow on you. That happened to me with this concept where I had to build columns of items moving in opposite directions when a user scrolls the page. CodePen Embed Fallback Note: This … Using Scroll-Driven Animations for Opposing Scroll Directions originally handwritten and published with love on CSS-Tricks . You should really get the newsletter as well.

¿Qué es un enlace? Definición Un link/enlace/elemento ancla es un elemento interactivo que redirecciona al usuario a una nueva ubicación la cual puede ser una página diferente, una ubicación distinta en la misma página (se modifica el URL en ese caso con un parametro # ) o también se puede utilizar para descagar un archivo, entre otras cosas. Al activarse, lleva al usuario a la URL definida en su href. El navegador guarda esa navegación en su historial, de modo que el usuario puede volver a la página anterior. Semántica Para que el elemento tenga carga semántica de elemento interactivo, tiene que si o si tener un atributo href con una URL válida o un IDREF que apunte a un elemento en la misma página, de lo contrario va a ser tratado como un elemento genérico . <a href= "/URL" > Ir a la página principal </a> Interacción con el teclado Solo se puede activar con la tecla Enter . Si se presiona la tecla Space mientras el foco esta en el enlace, la página va a scrollear hacia abajo. Interacción con lectores de pantalla Los lectores de pantalla, generalmente, anuncian el elemento de la siguiente manera: "Enlace, [Nombre accessible del enlace]" por lo cual es importante que el enlace tenga un nombre accesible pertinente y descriptivo. Malas prácticas Es totalmente inaceptable, una mala práctica y va en contra del funcionamiento nativo del elemento, forzar a un enlace a comportarse como un botón de la siguiente manera: <a href= "javascript:void(0)" onclick= "openModal()" > Abrir menu </a> <a href= "#" role= "button" onclick= "boton()" > Enlace con rol botón </a> Si necesitas hacerlo, quiere decir que necesitas un botón ¿Qué es un botón? Definición Un botón es un elemento interactivo que al ser cliqueado ejecuta una acción dentro de la página donde se encuentra. NO redirige al usuario a otro lugar, ni modifica la URL. Las acciones ejecutadas pueden ser abrir un modal, reproducir un vídeo, publicar un comentario, etc. Semántica El botón necesita el atributo type según la acci

Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is...

Let's be fair. The title of this post is confusing at first, but once you read it in full, I hope you...

GitOps policy drift is what happens when a control plane keeps a policy perfectly reconciled long after the reason for that policy has stopped being true. Every commit is applied. Every pull request is merged cleanly. Every dashboard reads green. And the rule being enforced no longer reflects anything anyone would choose to enforce today — it just hasn't been told to stop. That gap is the subject of this post. Not configuration drift — the thing GitOps was built to kill — but a second, quieter failure mode that lives one layer above it: the policy is right by every technical measure and wrong by every practical one, and nothing in the reconciliation loop is capable of telling the difference. The Promise GitOps Actually Kept GitOps earned its place in the infrastructure as code architecture stack by solving a real and expensive problem: state drift. Before declarative reconciliation, infrastructure diverged from its source of truth constantly — a console change here, an emergency hotfix there, a manual override nobody logged. The git repository said one thing. Production said another. Reconciling the two was a forensic exercise. GitOps closed that gap with a simple, durable mechanism: a controller that continuously compares declared state to actual state and corrects the difference without waiting for a human to notice. That's not a small win. It's the reason platform teams can run infrastructure at a scale that would have been operationally unmanageable a decade ago, and it's why GitOps controllers sit at the center of nearly every modern infrastructure as code architecture built since. This post isn't an argument against that mechanism. It's an argument that the mechanism's success created a blind spot nobody designed for. What GitOps Never Promised to Solve Here's the boundary GitOps was never built to cross: reconciliation proves that declared state and actual state match. It says nothing about whether the declared state should still exist in its current form. A