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Microsoft missed the boat on apps, so get ready for agents.

Intel couldn't catch a break. Layoffs. Shakedowns. Crashing CPUs torpedoing its reputation, sending desktop gamers fleeing to AMD. Apple and Qualcomm pushing Intel out of multiple flagship laptops. A gaming graphics card going MIA. But its Panther Lake laptop chip, the first on its all-important 18A process, turned out excellent - and a handheld version […]

Uber's cutback has occurred after the company had reportedly encouraged staff to use AI as much as possible.

International Mathematical Union endorses warning about tech industry influence.

Google's June Android feature drop includes more scam detection, more AirDrop, and yes, more AI.

Available for Android 12 and later, the anti-scam feature is baked into Google Dialer, which sends a silent “confirmation signal” to ensure whoever’s calling you is who they appear to be.

Microsoft’s OpenClaw-style agent appears in Teams, just like a human colleague, and automates your dull office tasks.

The specification lets developer, compliance, and security teams define their own policies for agents to follow in portable policy files.

As people increasingly refuse to answer calls from unknown numbers, scammers are shifting their tactics by spoofing trusted phone numbers and using AI deepfake technology to sound like authority figures, family members, or employers.

Layup Parts co-founder Zack Eakin has drawn on a motorsports background, and his experience working for Palmer Luckey and Elon Musk, to tackle making faster, cheaper, and better composites.

Google is launching a new feature for its Phone app that aims to protect you from AI impersonation scams. Now, when you receive a call from a scammer that appears to be coming from the same number as one of your contacts, Phone by Google will flag the call as suspicious so you can hang […]

At Microsoft Build 2026, GitHub introduced new tools, updates, and surfaces so agents can work the way you already work. The post GitHub Copilot app: The agent-native desktop experience appeared first on The GitHub Blog .

There are sound engineering reasons to use the same approach SpaceX uses with the Falcon 9.

In the social event planner’s first major move toward monetization, Partiful is getting ticketing directly in the app.

Tenho aproveitado meu tempo sem trabalhar pra estudar, enfim a vida de quem trabalha com tecnologia né? E um dos meus maiores focos tem sido IA, seus usos, como ela entra e pode ser aplicada em áreas diferentes, e todas as novidades que saem todos os dias. Hoje vim compartilhar uma coisa bem legal que aprendi no curso AI-Native Engineering Foundations do Addy Osmani , o problema dos 70%. Existe um padrão claro que tenho observado na prática ao acompanhar dezenas de equipes de engenharia: a Inteligência Artificial resolve com impressionante eficiência 70% de quase qualquer tarefa técnica. Falo daquela camada previsível, repetitiva e baseada em padrões exaustivamente documentados na internet. Coisas como código boilerplate, arquivos de configuração, implementações de CRUDs simples, conversão de sintaxe entre linguagens e a escrita de testes unitários básicos. A IA já "viu" milhões de exemplos disso em repositórios públicos e consegue reproduzir o padrão em segundos. Para essa fatia do trabalho, ela é uma aceleradora fantástica. O grande problema, e o motivo pelo qual muitos projetos com IA começam bem mas falham no meio, é que os outros 30% são justamente os que sustentam o software. É nesses 30% que entram as decisões que inteligência nenhuma consegue tomar sozinha: Contexto de Negócio: A IA não sabe por que aquela feature está sendo construída ou como ela impacta o usuário final. Arquitetura e Manutenibilidade: Escrever código que funciona hoje é fácil; escrever código que outra pessoa consegue alterar daqui a seis meses sem quebrar o sistema é outra história. Casos de Borda e Segurança: A IA tende a gerar o "caminho feliz". Tratar falhas de concorrência, vazamento de memória e vulnerabilidades específicas do seu ecossistema exige malícia técnica. Essas questões não se resolvem apenas digitando linhas de código, elas exigem contexto, experiência, histórico de dores passadas e, acima de tudo, julgamento humano. E é exatamente aqui que a IA ainda não entrega. O Parado

Your API is fast. Your code is clean. Your architecture looks solid on paper. Then you hit 500,000 records and everything slows down. Queries that ran in 12ms now take 4 seconds. Your dashboards lag. Users start filing support tickets. Your on-call engineer is staring at a query plan at midnight wondering what went wrong. Nine times out of ten, the answer is indexing. Not missing indexes — wrong indexes. Indexes that exist but don't help. Indexes that actively hurt write performance without meaningfully improving reads. This is a breakdown of the most damaging database indexing mistakes in production SaaS systems — and how to fix them before they become incidents. Mistake 1: Indexing Everything "Just in Case" The most common mistake isn't under-indexing. It's over-indexing out of anxiety. New engineers especially fall into this pattern — add an index on every column that appears in a WHERE clause, just to be safe. Seems responsible. It isn't. Every index you add is a write tax. On every INSERT, UPDATE, and DELETE, PostgreSQL (or MySQL) has to update every index on that table. On a table with 8 indexes, every write touches 8 data structures. At low volume, this is invisible. At 10,000 writes per minute, it becomes your bottleneck. The fix: Audit your indexes regularly. In PostgreSQL: SELECT schemaname , tablename , indexname , idx_scan , idx_tup_read , idx_tup_fetch FROM pg_stat_user_indexes ORDER BY idx_scan ASC ; Any index with idx_scan = 0 or near zero hasn't been used since your last stats reset. That's a candidate for removal — not immediately, but after investigation. Mistake 2: Not Understanding Index Selectivity An index on a boolean column ( is_active , is_deleted ) is almost always useless. Here's why: selectivity measures how many distinct values exist relative to total rows. A boolean column has two values. If 95% of your rows have is_active = true , an index on that column tells the query planner almost nothing useful. It will often skip the index entire

The password manager giant said hackers were able to 'brute-force' its two-factor system, allowing them to access customer accounts and download their password vaults.

Opal, the company famous for making a fancy webcam, has pivoted to making other consumer electronics. Fueled by big investments from OpenAI and Samsung, it’s working on an audio gadget first.

Anthropic is expanding Project Glasswing, its security vulnerability program, and access to Mythos to 150 organizations across 15 countries — targeting critical infrastructure in power, water, healthcare, and communications where a cyberattack could affect 100 million people.

When Lego announced its tech-packed Smart Bricks at CES, we were impressed by the potential - enough to give it our Best in Show award. But when the first Star Wars sets actually launched in March, we were less enamored. All that promise of clever interaction and creative play ultimately boiled down to a few […]