Google Home Speaker review: A modest update for the Gemini era
Google's new speaker is a modest update, but the question is whether Gemini is a good smart home assistant.
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Google's new speaker is a modest update, but the question is whether Gemini is a good smart home assistant.
Google’s first new smart speaker in six years is here and once again leads its competitors—now with paywalled features.
A new member has joined the fulgur family. fulgur-chart — a CLI that takes Chart.js v4-compatible JSON specs and renders deterministic SVG/PNG charts. No browser required. https://github.com/fulgur-rs/fulgur-chart Two things make it different: it doesn't spin up a browser, and for a fixed version, font, and rendering options, the same JSON input always produces byte-identical output. This post covers why I built it, a timing coincidence that made me feel like I was on the right track, and how to use it. Why I wanted graphs in PDFs fulgur and fulgur-chart are built around one idea: AI agents should be able to generate documents that look good . There are three steps to that argument. First, Markdown isn't expressive enough. For client-facing reports, plain Markdown often undersells otherwise strong content. Second, visual quality is persuasive. A well-formatted report lands differently than a wall of text. Third — and this is the one I keep coming back to — in many business workflows, PDF carries more institutional weight than a Markdown file or a transient web page . That authority has two dimensions. There's a cognitive one: PDFs read as "serious documents." Proposals, reports, invoices — the format itself signals credibility. And there's a technical one: PDF can support digital signatures, encryption, and archival profiles such as PDF/A. That's the ground flpdf covers, a pure-Rust PDF toolkit modeled on qpdf's workflow. So the goal is always PDF, not HTML, not a web page. That's what fulgur is for. And a polished report needs charts. But Markdown can't draw charts. Which brings me to a problem I already knew was coming: the Chart.js library requires JavaScript to run . fulgur has no browser and no JS runtime, so there was no path to running Chart.js directly. The design choice: no JS engine The obvious alternative was to embed a JavaScript runtime. I could either run Chart.js with a compatible Canvas implementation, or build a JavaScript renderer that consumes Cha
Modular, one of the most promising chip software startups of the AI era, heads for a multibillion-dollar exit.
AI is booming. New use cases are emerging each day. To capitalize on the technology’s potential, enterprises require data at scale. In many cases, though, the relevant information is blocked or unstructured, which limits its use by AI models. To understand this challenge, consider the foundation of the web itself. The web was not designed…
Naomi Saphra discusses 5 rules governing language model behavior, breaking down why LLMs act like populations rather than individuals. She explains how tokenization creates strange semantic blind spots and highlights the mechanics of sycophancy, showing how models leverage subtle data associations to match user biases and demographics - even guessing political views based on favorite sports teams. By Naomi Saphra
Welcome to Walmart deals for folks who’d rather not shop at Amazon. These are the best gadget deals at Walmart this Prime Day.
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Walmart-backed Flipkart has crossed 1,000 micro-fulfillment centers as Amazon accelerates its own quick-commerce push in India.
I'm Dr. Mohammad Reza Beheshti, Founder of CyberSiARA. I hold a PhD in Electronic Engineering and Artificial Intelligence and have over 15 years of experience in cybersecurity research and innovation. My passion has always been solving complex security challenges through technology. This journey led me to found CyberSiARA, where we're developing AI-powered bot protection and human verification solutions to help organizations defend against increasingly sophisticated cyber threats. I enjoy combining academic research with practical engineering to create technologies that are both innovative and effective in the real world. Through this blog, I share insights from my research, product development, and experiences building a cybersecurity company, with the aim of helping developers and security professionals stay ahead of emerging threats. I'm always keen to learn, collaborate, and contribute to the global developer and cybersecurity communities.
A new update for Google Home could make it less likely your smart home cameras mistake you for someone else, just because you're facing away from the camera. Starting June 23rd, Google's expanding its facial recognition feature so that people you've tagged in your Familiar Faces library can continue to be identified when their faces […]
Superhuman, which also has an AI detection tool as part of Grammarly, has snapped up GPTZero.
Everything is expensive. Treat yourself to one of these WIRED-tested and -approved Prime Day picks under $30.
TL;DR: We launched Tarotas, a tarot reading app, in five languages (Czech, Slovak, Polish, English, German) on a single domain. Each market behaved completely differently. Here is what the data showed us about multi-locale growth. When we started building Tarotas at Inithouse, the plan seemed straightforward: one product, five languages, one domain. Czech as the base, then Slovak, Polish, English, and German. Same cards, same readings, same UI. Just translated. What we did not expect: each locale acts like a separate product. The setup Tarotas is a tarot card app where you draw a card and read a calm, generic interpretation. No fortune telling, no sign-ups, no paywall. 78 cards across five languages, all on tarotas.com with language detection. We built it in Lovable and deployed it in under two weeks. The multi-language part took another week: content generation for 78 cards times 5 languages, plus locale-specific meta tags and URL structures. What the data told us The Czech and Slovak markets responded first. That was expected: our studio is based in Prague, our existing portfolio (products like zivafotka.cz and magicalsong.com ) already had traction in CZ/SK. But the interesting part was the divergence. CZ/SK users stayed longer. Session duration in Czech and Slovak was noticeably higher than in other locales. Users explored multiple cards, came back for second readings. The "reflection" positioning landed well in these markets, likely because tarot has a quiet cultural niche in Central Europe: not mainstream, but not fringe either. Polish users bounced faster but shared more. The PL locale had higher bounce rates but showed a different signal: social referrals. Polish users who did engage were more likely to share readings. The tarot community in Poland leans more social: Facebook groups, Instagram stories, TikTok readings. Our product caught some of that energy. German users barely showed up. DE was our weakest locale by far. German-language search demand for ta
The best robot vacuums are the ones you barely have to think about, and the Roborock Saros 20 fits that description well. It’s why it’s one of our favorite robovac / mop hybrids, and thanks to Prime Day, you can get it on sale at Amazon and Roborock for $1,359.99 ($240 off), a new low […]
Beyond the Prototype: Why Teams Need More Than Vibe Coding Over the last year, AI coding tools such as Lovable, Bolt.new, v0, Base44, and others have fundamentally changed how software gets created. A single founder or developer can now go from a rough idea to a working prototype in hours rather than weeks. That kind of acceleration is genuinely exciting, and it has opened software creation to far more people. That democratization is a good thing. Rapid experimentation, faster feedback loops, and lower barriers to entry are changing how products get started. Many successful companies and ideas will emerge because these tools made building more accessible. As I've followed the conversations happening around these tools—through reviews, articles, community discussions, and the experiences being shared by founders and engineering leaders—I've noticed an interesting pattern. The challenge is no longer getting to the first version. The challenge begins after. The Prototype Was Never the Finish Line The prototype works. Stakeholders become excited. Customers show interest. Momentum builds. Then a different set of questions starts to emerge. How do we align everyone on what we're building? How do we evolve an existing application instead of starting over? How do we maintain quality as complexity increases? How do multiple people collaborate without losing context? How do we know whether we're delivering the outcomes we intended? And how do we continuously improve without creating chaos? These aren't failures of AI coding tools. They're simply different problems. Many of today's AI builders are optimized for individual acceleration and rapid exploration. But once a promising idea becomes a product that teams must own, maintain, and evolve together, different requirements naturally emerge. What works for one person experimenting is not always enough for a group of people building something intended to last. Building Software Is More Than Generating Code Software development
HaloBraid aims to help salons speed up braiding with its first device, slated to launch later this year, that acts as a braiding assistant for professional stylists.
Welcome to Walmart deals for folks who’d rather not shop at Amazon. These are the best gadget deals at Walmart this Prime Day.
The smart glasses are available in several countries starting today in a variety of color and lens combinations.