标签：#Tech

Open earbuds are having a bit of a moment right now, and Nothing is the latest company jumping on the trend. Its budget sub-brand has introduced the CMF Clip Pro, CMF's first open-ear buds that are designed to provide comfort and sound quality for people who don't want to sacrifice their situational awareness. The $99 […]

Peak Design's new City Line collection includes six lightweight bags designed for everyday carry. There's a 15-liter and 22L City Backpack, 15L City Tote, 6L and 12L City Crescent crossbody bags, and 2L City Sling. All are available starting today and feature a new BagLev hook that can suspend the bags from a table ledge […]

Telegram is back on the App Store after Apple briefly removed it on Monday night over concerns about child sexual abuse material (CSAM). In a statement to Bloomberg's Mark Gurman, Apple says a review found that Telegram "violates our strict guidelines prohibiting child sexual abuse material," adding that it restored the app "after the developer […]

The Kindle Scribe is worth considering if you’re heading back to school, as its large 10.2-inch screen can display textbooks and ebooks, or let you jot down handwritten notes during class. Now through August 8th, the first-gen model (with a Premium Pen) is down to just $149.99 with 16GB of storage in refurbished condition at […]

Today, I’m talking with Toni Schneider, who is the brand new CEO of the social platform Bluesky — he formally took over after a short stint as interim CEO. This is one of my favorite kinds of interviews to do on Decoder, because a couple years ago, we had Bluesky’s prior CEO, Jay Graber, on […]

After its 1.0 launch last month, Palworld is coming to iOS and Android with a new open-world MMORPG launching later this year, Polygon reports. Garena, the developer behind the new game, says in its announcement that Palworld Online "reimagines the depth, freedom, and scale of the original PC survival creature-collecting title for mobile." The core […]

Chinese tech giant Alibaba released what it says is its largest and "most capable AI model to date," claiming performance rivaling the best systems from US frontier labs Anthropic and OpenAI, as well as domestic rivals like Moonshot AI's Kimi K3. Alibaba said it was making the model, Qwen3.8-Max, widely available to users in a […]

MIT Technology Review Explains: Let our writers untangle the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here. When two OpenAI models hacked into the website Hugging Face in July, they weren’t trying to make money or commit sabotage—they were just looking for answers…

The lost-update bug that quietly corrupts homegrown wallet balances — and the five disciplines we used across PayWithToken to make money movement correct under concurrency. There is a bug that lives in a large share of the world's homegrown wallet systems. It doesn't throw an error. It doesn't show up in tests. It surfaces months later as a balance that is quietly, inexplicably wrong — and in a payments system, a wrong balance is either a customer who has lost money or a company that has given it away. This is the story of that bug, why the "obvious" wallet code causes it, and the handful of disciplines we used across PayWithToken to make money movement correct under concurrency. The bug: lost updates Here is wallet code almost everyone writes first. Credit a user's balance: // DON'T do this $row = $db->query("SELECT balance FROM users WHERE id = $id")->fetch(); $new = $row['balance'] + $amount; $db->exec("UPDATE users SET balance = $new WHERE id = $id"); Read the balance, add to it in PHP, write it back. It works perfectly — until two things happen at the same time. Picture a wallet at ₦1,000. Two credits of ₦500 arrive simultaneously — say a bank webhook and the user tapping "confirm" on their phone: Request A reads balance = 1000. Request B reads balance = 1000 (A hasn't written yet). A computes 1500, writes 1500. B computes 1500, writes 1500. Two credits landed; the balance rose by ₦500. ₦500 vanished. This is a lost update, and it is a race condition, which means it is invisible until you have real concurrent traffic — exactly when you can least afford it. The debit version of the same bug lets a balance go negative or double-spends a token. Fix #1: let the database do the arithmetic The read-modify-write happened in PHP, across three round trips, with a gap where another request could interleave. The fix is to make the update a single atomic statement and let the database's row lock serialise it: // DO this — one atomic statement $db->prepare("UPDATE users SET

The start of a new school year can feel hectic, as parents juggle their kids’ classes, extracurriculars and sports on top of work, appointments, and other responsibilities. It’s easy for things to slip through the cracks, but Skylight’s shared smart calendars can help keep everyone on track, and from August 2nd through August 9th they’re […]

This is The Stepback, a weekly newsletter breaking down one essential story from the tech world. For more on smartphones and Android, follow Dominic Preston. The Stepback arrives in our subscribers' inboxes on Sunday at 8AM ET. Opt in for The Stepback here. How it started Believe it or not, it didn't all start with […]

New EU rules stipulate that people must be told when they’re interacting with AI or looking at AI-generated or -edited content, leading to fear of “disclosure fatigue.”

The Open-Weight Inflection Point: Kimi K3, Claude Opus 5, and Microsoft MAI Signal a Market Shift Subtitle: Three major releases in one day point to the same conclusion — the AI industry is shifting from "who can build the strongest model" to "who can build the most cost-effective one." July 28, 2026, might be remembered as the day the AI industry's center of gravity shifted. Three announcements — from Moonshot AI, Anthropic, and Microsoft — each independently signaled the same underlying trend: open and cost-efficient models are becoming the new competitive baseline. Here's what happened and why it matters. 1. Kimi K3 Goes Open-Weight: First 3T-Class Open Model Moonshot AI publicly released Kimi K3's full model weights on HuggingFace — a 2.8-trillion-parameter Mixture-of-Experts model with 104B activated parameters. This is the first 3T-class model ever made openly available to the public. Key technical highlights: Architecture: Kimi Delta Attention (KDA) + Attention Residuals (AttnRes), 896 experts with 16 activated per token Native Multimodality: Text, images, and video understanding via MoonViT-V2 vision encoder Context Window: 1,048,576 tokens (~1M tokens) Benchmarks: Terminal-Bench 2.1: 88.3, BrowseComp: 91.2, MCPMark-Verified: 94.5 — competitive with Claude Fable 5 and GPT-5.6 Sol Why it matters: Kimi K3 raises the "open-source model ceiling" to an unprecedented level. For the first time, a model that competes with top-tier closed-source models is available with fully public weights — giving startups, researchers, and enterprises a genuine alternative to API-dependent workflows. For developers, this is the practical part: you can now self-host a model that holds its own against frontier closed models. That changes cost models, data-privacy decisions, and vendor lock-in math overnight. 2. Claude Opus 5: Anthropic's "Daily Driver" Strategy Anthropic launched Claude Opus 5 — a mid-premium model positioned as the "daily driver" for 90% of knowledge work. The key

Android Headlines claims to have the specs and price for the entire Pixel 11 lineup. What the site shared basically lines up with everything else that we've heard in the lead-up to the August 12th event. The Pixel 11 is expected to get a $100 price hike, starting at $899, but will come with 256GB […]

Why AI Agents Expand the Security Perimeter AI agents do more than generate text. They call tools, query databases, retrieve documents, execute code, and communicate with external services. Every connection introduces a potential path for model exfiltration or credential leakage. Model exfiltration includes direct theft of model weights, systematic extraction of proprietary behavior, and reconstruction of sensitive training data through repeated queries. Attackers may also inject instructions that persuade an agent to reveal system prompts, internal files, access tokens, or confidential context. API keys are especially vulnerable because agents often need credentials at runtime. If those secrets appear in prompts, logs, traces, exception messages, or tool outputs, a malicious user may be able to recover them. Conventional application controls remain necessary, but agentic systems require additional safeguards that account for probabilistic decisions and dynamic tool chains. Separate Agent Reasoning From Secrets Secrets should never be included directly in an agent’s prompt or long-term memory. Instead, place credentials in a dedicated secrets manager and expose narrowly scoped tool interfaces. The agent should request an approved action, while a trusted execution layer retrieves the required credential and performs the call. Use short-lived tokens, workload identities, and least-privilege permissions wherever possible. Each tool should have an explicit policy defining allowed endpoints, operations, data types, and request limits. An agent that can read customer records does not automatically need permission to export them or send them to an arbitrary domain. Prompt inputs and retrieved documents should also be treated as untrusted data. Apply content isolation, schema validation, and output filtering before information reaches an external tool. Redact credentials from telemetry and configure logs to record identifiers rather than raw authorization headers. These con

Knowing exactly what your student needs for the school year ahead is next to impossible. Sure, you'll probably nail the essentials, but there will likely be a few items you forgot to buy, or didn't think they'd need to have. We're pulling our weight during the back-to-school season with a new shopping guide that's a […]

#ai #kyc #compliance #duediligence #api #llm #fintech #rapidapi AI Writes Code. You Still Own the Verdict. ChatGPT can spin up a KYC dashboard in an afternoon. It will generate React components, SQL schemas, and swagger documentation that look production-ready. But ask it whether fintech-example.io is a legitimate payment processor or a sanctions-evasion shell, and it will confidently fabricate ownership records, misread registrar data, or hallucinate a clean bill of health. That is the gap AI cannot close on its own: grounding . Large language models reason over tokens, not truth. A reliable due-diligence or compliance tool must anchor every LLM answer in real, verifiable, timestamped data—WHOIS records, IP geolocation, company registries, email infrastructure, and sanctions lists. This article shows how to use the Portfolio Investigate API to feed your AI agents factual domain dossiers and compliance verdicts, turning a prototype into something a compliance officer can actually trust. The Hallucination Problem in Due Diligence LLMs are autocomplete engines. They predict what words should come next based on training data, not live facts. In a KYC context, that creates three failure modes: Stale knowledge — model weights freeze; a domain can change ownership next week. Fabricated citations — the model may invent registrar names or corporate addresses. Missing signals — an LLM has no built-in access to WHOIS history, IP blocks, or OFAC lists. The fix is not to abandon LLMs. It is to constrain them: give them a structured evidence packet first, then let them summarize, classify, and answer natural-language questions on top of it. That evidence packet is exactly what Portfolio Investigate API returns. What Portfolio Investigate API Delivers Portfolio Investigate API is a one-call domain investigation report. It aggregates five underlying portfolio APIs into a single dossier: WHOIS — registration dates, registrar, name servers, privacy status. IP Geolocation — where the

Hi, friends! Welcome to Installer No. 138, your guide to the best and Verge-iest stuff in the world. (If you're new here, welcome, happy August, and also you can read all the old editions at the Installer homepage.) This week, I've been reading about microwave sounds and Meta glasses and Alex vs. Alix, testing the […]

This is obviously a bubble Jim Rickards, a former adviser to the CIA and Pentagon, warns that the United States is currently facing a tectonic economic crisis driven by an unprecedented bubble in Artificial Intelligence (AI). According to his analysis, this impending crisis has the potential to be more destructive than the dot-com crash, the 2008 financial crisis, and the pandemic-related market crashes combined. He is not alone in his dire outlook; veteran investor Jeremy Grantham has warned, "This is obviously a bubble. The probabilities it doesn't burst are slim to none. And when it does, it could be an economic catastrophe unprecedented in the last 97 years" . Furthermore, former SEC Chairman Gary Gensler has stated that "the next financial crisis will come from AI". Create God and ask him for money The Unprecedented Scale of the AI Bubble The current market relies dangerously on a single sector, with the AI bubble estimated to be 17 times larger than the dot-com bubble of the late 1990s. Many AI companies are burning through cash at an alarming rate. For instance, OpenAI is reportedly losing more than a billion dollars a month; as it is noted in the source, "for every dollar they make, they have to spend at least three". This massive cash burn led a Deutsche Bank analyst to observe, "No startup in history has operated with losses on anything approaching this scale". Despite the astronomical costs and high valuations, OpenAI’s CEO was quoted as previously saying, "I have no idea how we're going to generate revenue". Former Goldman Sachs banker and Bloomberg columnist Matt Levine summarized this extreme speculative mindset, noting, "The business model they believe they need seems to be create God and ask him for money". "Subprime AI" and Toxic Debt Just as the 2008 financial crisis was fueled by toxic subprime mortgages, the AI boom is being fueled by dangerous debt structures used to fund massive data centers. Private equity firms are financing data centers as r

Sharge, the company that makes delightful retro Mac-shaped chargers and see-inside batteries, is finally impressing me with a portable SSD. I couldn't recommend the Sharge Disk, Disk Plus, or even the Disk Pro, but I'd be happy to own the new Disk Pro 2 Ultra. This isn't just a drive. It's a 4K HDMI dock […]