Part one hit 69K views, 250 upvotes here. The comments were better than the post. A lot of you asked about SEO, accessibility, performance, and whether GSAP is even necessary. Several pointed out the demo was missing something. You were right. Part one had a cursor clicking through scenes on a flat stage. No depth, no focus. This post adds a camera: zoom into the action on right-click, pan to follow the cursor through a save dialog, zoom into the result on the destination board, pull back and loop. Still under 40 KB. Still no video files. What part two covers: Zoom wrapper architecture — why gsap.to(frame, { scale: 1.4 }) breaks responsive scaling Pan math — the formula to center any target in the viewport at a given zoom level "Stay zoomed, pan to follow" — zoom in once, pan through the interaction, zoom out once. Not PowerPoint. Easing philosophy — why camera pans need sine.inOut , not power2.inOut , and the full easing table by motion type Cursor alive during camera moves — a frozen cursor during a zoom makes the whole thing feel mechanical. 30% drift fixes it. Graceful loop lifecycle — outro pattern instead of snap-reset SEO — every button label and heading in the demo is indexable DOM text, not a black box video Accessibility — prefers-reduced-motion support, autoAlpha for screen readers Performance — live FPS stress test you can run in your browser (8 → 24 → 48 elements with zoom + pan + stagger), not much performance drop The agent split — I wrote ~60% (the directing), an AI agent wrote ~40% (the tedious timeline code). Still a lot of manual editing, but way better than recording a video and the maintenance The full post has 4 interactive demos you can pause and inspect, including side-by-side comparisons of easing curves and cursor behavior during zooms. Full writeup with live demos: https://spanthi.com/blog/gsap-choreography-part-2 Production examples: https://costumary.com and https://costumary.com/web-clipper Skill for AI agents if anyone wants to save ti

🚨 URGENT: Highly Critical Drupal Core SQL Injection (CVE-2026-9082) Affecting PostgreSQL — Patch Immediately! The Drupal Security Team has released a "Highly Critical" security advisory ( SA-CORE-2026-004 / CVE-2026-9082 ) fixing a severe unauthenticated SQL injection vulnerability in Drupal Core. If you are running a Drupal site backed by a PostgreSQL database, you are at extreme risk. 📌 Vulnerability Overview CVE ID: CVE-2026-9082 Drupal Risk Score: 23/25 (Highly Critical) Attack Vector: Remote, Unauthenticated (Anonymous) HTTP requests Exploitation Status: ACTIVE IN-THE-WILD ATTACKS reported globally. CISA has officially added this flaw to its Known Exploited Vulnerabilities (KEV) catalog. Over 15,000 attack probes across thousands of sites have already been detected. Root Cause: A flaw in Drupal Core's database abstraction API—specifically within the PostgreSQL EntityQuery condition handler. Attacker-controlled PHP array keys reach SQL placeholder construction without proper sanitization, allowing arbitrary SQL execution. 💥 High Impact & Risks While Drupal estimates that less than 5% of installations use PostgreSQL, this configuration is heavily concentrated in enterprise, government, and higher-education environments. Successful exploitation grants: Full Database Access: Exfiltration of session tokens, sensitive data, and password hashes. Privilege Escalation: Promotion of standard or anonymous sessions to Administrator. Remote Code Execution (RCE): In PostgreSQL environments where database permissions are misconfigured (e.g., allowing COPY FROM PROGRAM ), attackers can pivot from SQL injection to executing arbitrary shell commands on the host server. 🔍 Affected Versions The flaw impacts all supported Drupal Core branches configured with PostgreSQL, including some legacy branches: Drupal Core 8.9.0 through 10.4.9 Drupal Core 10.5.x before 10.5.10 Drupal Core 10.6.x before 10.6.9 Drupal Core 11.1.x before 11.1.10 Drupal Core 11.2.x before 11.2.12 Drupal Core 11.

I got passion and no money submitted by /u/Free-Ant-463 [link] [留言]

I recently wanted to see whether an AI agent could self-improve a harness to solve terminal bench tasks. It’s possible for an AI agent to propose a meaningful one-time change to the harness, but after experimenting with this for a couple of weeks, I think the continuous self-improvement is mostly an experiment-systems problem. The system needs a way to decide what kind of improvements can safely compound. Turns out there's a lot of parallels to coding-agent customization (e.g. SKILLS.md etc..) too. I wrote my experience of building such system here, including the successful and failure attempts during the process, and how I approached the self-improvement loop. It's not intended as a benchmark claim but more of a systems/research writeup. https://www.henrypan.com/blog/2026-05-25-self-improvement-harness/ submitted by /u/Megadragon9 [link] [留言]

Article URL: https://www.ycombinator.com/companies/reflex/jobs Comments URL: https://news.ycombinator.com/item?id=48297116 Points: 0 # Comments: 0

PR exec says Govee "did not meet the standard required."

Graduating from college is exciting, but it can also feel slightly terrifying. Along with celebrating a huge accomplishment, many grads jump right into looking for a job. Some might be getting their first apartment, too, which brings on a whole new set of responsibilities. That's why getting the right graduation gift is so important: They […]

Cybercriminals used the Glassworm botnet to infect open source software projects with malware, and in turn hack the developers and companies that use that software.

AI social media copilot for teams and agents Discussion | Link

xTool has announced a new multi-purpose crafting machine that could potentially be one of the most affordable ways to start an Etsy shop. Its modular design facilitates a CMYK print head that works on multiple materials including paper, wood, and felt. It can later be swapped with laser-based cutting and engraving tools. You can use […]

Motorola says that recently discovered behavior, which saw some of its phones sending users to an affiliate tracking website before opening the Amazon app, was "unintended" and has been "promptly corrected." The company didn't explain how the error was introduced in the first place. "Recently, Motorola acted quickly to resolve an issue that was identified, […]

Last month NVIDIA released SOL-ExecBench , a new benchmark of 235 production CUDA kernels lifted from DeepSeek, Qwen, Gemma, and Kimi. We took several top-ranked AI-generated submissions and tried using them in production workloads. Many of them broke, sometimes in surprising ways. One of those kernels is the fused embedding-gradient + RMSNorm backward pass, which runs at the end of every transformer training step. We took the fastest submission on the benchmark for it, and dropped it into the training loop of a small transformer. The kernel had passed the benchmark's verifier with room to spare. But in our training run, the loss diverged and never recovered. We started debugging. Replace the dataset distribution with uniformly sampled tokens, the divergence vanishes. Swap SGD for AdamW, also vanishes. This is the worst kind of bug for research. Symptoms and masks both look exactly like "the idea didn't work". It's the type of bug that can make researchers spend a long time debugging without knowing what's at fault: the dataset? the research idea? the architecture? or the implementation itself? Turns out, the actual bug is that the embedding-gradient half of the kernel accumulates in bf16 instead of fp32. Embedding backward sums many small gradient contributions into each token's row of the embedding matrix. With uniform random tokens the contributions spread evenly and bf16 precision is enough. In real text, a handful of token IDs end up with thousands of contributions: the small ones round to zero against the growing accumulator, and the high-frequency rows drift. AdamW's per-parameter normalization absorbs the resulting multiplicative bias, so under AdamW the same drift is invisible in the loss. The other broken submissions had different bug shapes (all interesting). More examples in our blogpost . submitted by /u/laginimaineb [link] [留言]

I am wondering how are businesses integrating AI while protecting their data? submitted by /u/pappugulal [link] [留言]

These WIRED-tested computer speakers, from stereo speakers to surround sound, will suit any budget.