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This week, I covered a fascinating effort to preserve organs outside the body. There’s a huge shortage of donor organs, and one of the main reasons is time—they survive only a matter of hours outside the body, even when they’re kept on ice. Doctors dream of organ banks—stores of human organs that can be preserved…
When it comes to organ donation, time is everything. As soon as an organ has been carefully removed from a donor’s body, it starts to deteriorate. Surgeons have a matter of hours to get it into a recipient. Leave it too long and the organ will become unusable. In most cases, organs will be kept…
Running a production database on a minimal two-core PostgreSQL instance presents unique engineering challenges. In resource-constrained environments, default configurations quickly lead to CPU exhaustion, memory thrashing, and high latency. To maintain stable performance, you must aggressively manage resource allocation and optimize query execution plans. The first critical area is connection management. PostgreSQL allocates a separate operating system process for each connection. On a two-core machine, allowing hundreds of concurrent connections will cause severe context switching overhead, degrading performance significantly. You should restrict maximum connections to a low double-digit number and implement a connection pooler like PgBouncer. A pooler ensures that incoming traffic queuing happens outside the database engine, allowing the CPU to focus on executing active queries rather than managing process states. Memory allocation parameters require precise tuning on limited hardware. The shared buffers parameter, which dictates how much memory PostgreSQL uses for caching data, should typically be set to twenty-five percent of total system RAM. However, work memory is where many developers run into trouble. The work memory setting determines the amount of memory used by internal sort operations and hash tables before writing to temporary disk files. Since this memory is allocated per query operation, a complex query with multiple joins can consume many times the configured value. On a two-core instance with limited RAM, setting this value too high can trigger the out-of-memory killer, while setting it too low forces slow disk-based sorting. You must analyze your heaviest queries and find a balanced value that prevents disk thrashing without exhausting system memory. Query optimization becomes a daily necessity when compute resources are scarce. You must regularly inspect query execution plans using the explain analyze command to identify sequential scans on large
Perimenopause has entered the chat. Perimenopause—and its better-known relative, menopause—used to be considered taboo. Not anymore, thanks at least in part to TV doctors and social media influencers. Perhaps it’s my age, but these days, both my algorithm and my conversations with friends increasingly swing toward perimenopause. Menopause is defined as the life stage that…
Ties van der Meer doesn’t know how many siblings he has. The 47-year-old was conceived at a private fertility clinic in the Netherlands using sperm provided by an anonymous donor. After the Netherlands banned anonymous donation in 2004, the doctor who ran the clinic destroyed records that might have identified those donors, he says. He…
Sony shared an announcement with the console market: physical disc production for all PlayStation games will completely stop in January 2028. You can read the official announcement on the PlayStation Blog . From a pure engineering perspective, modern internet infrastructure has rendered physical distribution redundant. We no longer need plastic circles to transport megabytes. The gamer community response isn't about data transfer speeds. It is over true digital ownership, consumer rights, and software preservation. In this article, we break down the details, look at the history leading to this moment and explore why console makers would pursue this direction. 🔍 The Announcement Break Down The 2028 Deadline: The mandate strictly applies to new games launching after January 1, 2028. Legacy Back Catalog: Discs pressed before this date will still function (assuming future hardware maintains optical drive compatibility). "Code-in-a-Box" Retail: Stores will still sell physical cases on shelves, but they will contain a paper download voucher instead of a disc. I am no sustanability poster boy, seems wasteful to preserve retail shelf presence. 🛑 The Illusion of Ownership: "Buying" vs. "Renting" When you hit "Buy" on a digital storefront, you aren't purchasing a game. You are purchasing a conditional license to stream or download it—a long-term rental agreement that can be unilaterally altered or revoked. No Secondary Market: Players completely lose the ability to resell, trade, or lend games to friends. Monopoly Pricing: Eliminating discs removes competitive pricing from retailers like GameStop, JB Hi-Fi, or Amazon, leaving users locked to a single proprietary storefront. Delisting Vulnerability: If a publisher loses IP rights, the software vanishes instantly. 🎮 Case Study: My Close Call with Digital Erasure Look no further than Star Trek: Resurgence for proof of how fragile digital stores are. In April 2026, the publishers suddenly lost their IP distribution rights. Within
📖 Read the full version with charts and embedded sources on ComputeLeap → You can now buy a walking, flipping, kung-fu-kicking humanoid robot on AliExpress for $4,900 — less than a used Honda Civic, less than a semester of community college, less than what most people spend on a couch-and-TV combo. Unitree's R1 AIR shipped its first global batch in April, and it represents something the robotics industry has been promising and failing to deliver for decades: a humanoid robot that a normal person can actually afford. But here's what the breathless headlines won't tell you: price is falling faster than capability. The gap between what this robot costs and what it can actually do is where the hype lives — and understanding that gap is the difference between seeing a revolution and seeing a very expensive toy. The Number That Matters The Unitree R1 AIR stands 4 feet tall, weighs 55 pounds, and packs 20 degrees of freedom into a bipedal frame that can run, do cartwheels, throw punches, and execute spin kicks . At CES 2026, Unitree's booth stopped traffic with R1s replicating Bruce Lee sequences, Michael Jackson dance moves, and Mike Tyson combinations. The base R1 AIR ships with a monocular camera, 8-core CPU, and onboard AI for voice and image recognition. For $1,000 more, the standard R1 at $5,900 adds six more degrees of freedom (26 total), binocular depth perception, waist articulation, and head movement. Both come with hot-swappable batteries — about an hour of runtime per charge. To put the price in context: Figure AI and Tesla each shipped roughly 150 humanoid units in 2025. Unitree shipped 5,500 . That's not a typo — Unitree alone outshipped every Western humanoid manufacturer combined by a factor of 20x. The R1's $4,900 price point isn't an outlier. It's the leading edge of a Chinese manufacturing tidal wave. The Raspberry Pi Parallel — and Its Limits When the Raspberry Pi launched in 2012 at $35, it didn't replace laptops. It didn't become the computer most peo
It’s not easy to transplant a whole human eye. The surgery is difficult. And the eyes themselves start to degenerate as soon as they’ve left the body. When surgeons attempted it a few years ago, the newly-transplanted eye wasn’t able to see. But researchers believe they might have a solution: a device that maintains and…
New York City’s Summer of Ludd festival is teaching people how to live offline.
AI and Robotics in the New Age of Industrialization Since 2025, a new era of...
As the parent of two little girls, I often think about how their childhood is different from mine. The seven-year-old is learning about AI at school. The five-year-old is given internet-based homework every week. And they are both absolutely repulsed by the idea of smoking. That was not the prevailing sentiment when I was young.…
Todo projeto que envolve autenticação via telefone acaba esbarrando no mesmo problema chato: como testar isso de verdade? Você não pode ficar digitando seu próprio número toda vez que roda um fluxo de cadastro. Definitivamente não deveria pedir para os colegas de equipe cederem o deles. E a maioria dos pipelines de CI não tem uma pessoa sentada ali, pronta para ler uma mensagem de texto e digitar o código num formulário. É uma daquelas coisas que parecem pequenas até você estar três sprints dentro de um projeto com 2FA via SMS e perceber que a cobertura de teste desse fluxo inteiro é "testei uma vez, manualmente, antes do almoço". Por Que a Verificação por Telefone É Complicada de Testar A maioria dos fluxos de autenticação de um stack típico é fácil de automatizar. Verificação por e-mail, dá para interceptar com uma caixa de entrada de teste ou um serviço de captura de e-mails. Tokens de sessão, dá para mockar. Redefinição de senha, você controla o loop inteiro. O SMS quebra esse padrão porque o código precisa sair completamente do seu sistema, ser entregue por uma rede de telecomunicação real e voltar antes que o teste possa continuar. Essa ida e volta introduz vários pontos de falha que não têm nada a ver com o seu código: atrasos de operadora, filtros de spam, peculiaridades de entrega por região, limites de taxa. Se você já viu um pipeline de CI falhar numa etapa de verificação por telefone e depois passar numa nova tentativa sem nenhuma mudança de código, é quase sempre por causa disso. O instinto de muitas equipes é pegar um número público gratuito de um dos vários sites de "receber SMS online" para checagens manuais rápidas. Isso funciona bem para uma verificação pontual. Mas desmorona rápido quando você tenta automatizar, porque esses números são compartilhados potencialmente por milhares de outras pessoas usando o mesmo pool. Códigos podem se perder numa caixa de entrada lotada, o próprio número pode já estar bloqueado pela plataforma que você está testand
Fable 5 got jailbroken again Researcher Vitto Rivabella tested Fable 5’s defenses and managed to find a bypass. According to him, most attempts failed. The protection is multi-layered: the model checks the prompt, conversation history, system context, and its own response. Some filters run during generation and can stop the answer halfway through. The checks are not based on keywords. The system looks at meaning, intent, language, wording, and suspicious chains of requests. The bypass took around 20 hours. It required rare languages, academic framing, long build-ups, Unicode, breaking the task into parts, and working with the chain of thought. The author did not get a stable bypass for long tasks. According to him, regular search is faster and cheaper.
Listen to the session or watch below Billions of dollars are flooding into efforts to reverse aging as scientists explore ways to return cells to a younger state. But how far off are these experimental treatments? Will they really work? Watch a conversation exploring longevity’s new focus. Speakers: Mary Beth Griggs, science editor and Jessica…
OpenAI is investigating issues with Codex usage limits Tibo wrote that the Codex team spent Sunday in a war room, digging through logs and looking for anything that could have caused faster usage drain for some users. As the investigation continues, OpenAI has issued a full reset of Codex usage limits for everyone. The funny part: this week at OpenAI is called RESET week. In US corporate culture, that usually means a lighter week to slow down, clear the calendar a bit, and recharge.
What We Know: The Basics of the Breach Polymarket, one of the largest prediction market platforms in the crypto space, confirmed on X that hackers stole funds from users after attackers compromised a third-party vendor. The breach allowed the attackers to inject malicious code directly into Polymarket's website, though the company specified the code ran "for some users" — a detail that raises immediate questions about whether the attack was deliberately targeted or only partially executed before detection. Polymarket spokesperson Connor Brandi confirmed to TechCrunch that the vendor compromise resulted in direct theft of user funds. Beyond that confirmation, the company declined to answer specific questions about the incident, leaving the scale of the financial damage, the identity of the compromised vendor, and the exact mechanism of the malicious code injection all officially unaddressed. The platform says it has contained the breach and is reaching out directly to affected users, committing to full refunds. No figure for total stolen funds has been disclosed. Blockchain monitoring firm PeckShield flagged suspicious activity around the same time Polymarket made its public announcement, adding an independent layer of confirmation that something significant moved on-chain during the incident window. What stands out immediately in the crypto security community is where the failure originated. The Polymarket platform itself was not the direct point of entry — a third-party vendor was. That distinction matters enormously. Users who trusted Polymarket's smart contract security and on-chain transparency had no visibility into the web infrastructure dependencies sitting between them and the prediction market interface. The malicious code injection attack, a technique that exploits trusted website supply chains, bypassed the decentralized architecture that crypto platforms often promote as a security feature. The incident joins a growing list of Web3 platform breaches wher
It’s been hot in London this week. Really hot. A dangerous heat wave has hit Western Europe. Yesterday, the UK recorded its highest ever June temperature at 36.1 °C (about 97 °F). But as the weather app on my phone confirmed, it felt like 39 °C. It’s frightening that we are seeing such temperatures in…
Introduction In the early 2000s, email spam was rampant, cluttering inboxes with unsolicited messages promising quick riches or promoting dubious products. Fast forward to today, and a similar phenomenon is occurring in the world of open-source software: Pull Request (PR) spam. Much like its email predecessor, PR spam is becoming a major nuisance for developers and maintainers, disrupting workflows and compromising the integrity of collaborative software projects. This blog post explores the parallels between early 2000s email spam and contemporary PR spam, examines the motivations behind this new wave of digital clutter, and discusses potential solutions to mitigate its impact. The Rise of PR Spam The Allure of Contribution Metrics One of the primary drivers behind PR spam is the increasing emphasis on contribution metrics in the open-source community. Platforms like GitHub have made contributing to projects more accessible, and many developers are eager to showcase their activity through public repositories. However, this focus on quantity over quality can lead to an influx of low-effort or irrelevant PRs. An example of this is Hacktoberfest, an annual event encouraging contributions to open-source projects. While well-intentioned, it has, in some instances, resulted in a deluge of superficial PRs. Contributors seeking to meet participation thresholds often submit changes that are trivial or unnecessary, much like the spam emails of old that inundated our inboxes with irrelevant or nonsensical content. Automated PR Generators Another factor contributing to the rise of PR spam is the use of automated tools that generate pull requests. These tools can be beneficial for routine tasks such as dependency updates or code formatting. However, when misused, they can lead to a flood of PRs that lack genuine human oversight or consideration, akin to the automated email spam generators that once plagued communication networks. For instance, a tool might automatically submit
Quando comecei a trabalhar com tecnologia, há mais de duas décadas, a Inteligência Artificial era algo restrito a laboratórios de pesquisa e ficção científica. Hoje, ela está embutida no aplicativo que recomenda sua próxima série, no e-mail que filtra spam automaticamente e até no GPS que recalcula sua rota em tempo real. A IA deixou de ser promessa para se tornar infraestrutura invisível do cotidiano. Neste artigo, quero ir além do hype e mostrar, com exemplos concretos, como essa tecnologia já transforma a forma como vivemos e trabalhamos. Produtividade pessoal e profissional turbinada O caso de uso mais palpável da IA hoje está na produtividade. Assistentes baseados em modelos de linguagem (LLMs) como ChatGPT, Claude e Gemini reduziram drasticamente o tempo gasto em tarefas que antes consumiam horas: redação de e-mails, geração de relatórios, resumos de reuniões e até depuração de código. Na minha rotina como gestor de TI, integrei essas ferramentas a fluxos de trabalho reais. Por exemplo, utilizo modelos de IA para revisar contratos de smart contracts escritos em Rust para a rede Stellar, identificando padrões de vulnerabilidade antes mesmo da auditoria formal. Não substitui a perícia humana, mas funciona como uma primeira camada de triagem que economiza tempo precioso da equipe. Algumas aplicações práticas que recomendo testar: Transcrição e resumo automático de reuniões com ferramentas como Otter.ai ou Fireflies Geração de documentação técnica a partir de comentários de código Automação de respostas em suporte de primeiro nível via chatbots treinados com a base de conhecimento da empresa O segredo está em tratar a IA como copiloto, nunca como piloto automático. A revisão humana continua indispensável, especialmente em contextos críticos. Saúde, finanças e decisões do dia a dia A IA também opera nos bastidores de decisões que afetam diretamente nossa qualidade de vida. No setor de saúde, algoritmos de visão computacional já auxiliam radiologistas na detecção pr
The common cold comes for us all—often more than once a year. And there is no way to prevent it. The best you can do is take vitamin C and stay away from people with the sniffles. Now, the payment company Stripe, founded by brothers Patrick and John Collison, says it will fund a new…