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The CEO of Foundation Future Industries, which counts the president’s son as its chief strategy adviser, tells WIRED it’s exploring some “kinetic things.”
Every morning, airline dispatchers, grid operators, and farmers around the world make decisions based on the same thing: a weather forecast. While these forecasts are something that most people glance at for two seconds, weather predictions influence major strategic decisions in many industries, with real money, livelihoods, and even actual lives at stake. Farmers use…
Flutter State Management in 2026: Riverpod vs Bloc vs Provider in Production Every Flutter team eventually hits the same wall. The app works, the demo looks great, and then somewhere around screen thirty the setState calls start colliding with each other, a widget rebuilds three times for one tap, and nobody on the team can explain why a loading spinner is stuck on a screen the user already navigated away from. That's the moment state management stops being a "nice to have" architectural decision and becomes the thing standing between you and a shippable product. We've built and maintained Flutter apps across fintech, e-commerce, logistics, and healthcare — different domains, wildly different feature sets, but the same recurring question from every engineering lead we work with: Riverpod, Bloc, or Provider? There's no shortage of opinions online, and most of them are shallow — "Bloc is too much boilerplate," "Riverpod is the future," "Provider is basically deprecated." None of that is useful when you're the one who has to live with the decision for the next two years of feature work. This is a practitioner's comparison, not a popularity contest. We'll walk through what each of these actually does under the hood, where each one falls apart in production, and how we decide which one to reach for on a new project. Why state management is the architecture decision that matters most In most application frameworks, state management is one of several important decisions. In Flutter, it's disproportionately important, because Flutter's entire rendering model is built around widget rebuilds driven by state changes. Get state management wrong and you don't just get messy code — you get a slow app, because unnecessary rebuilds are a real performance cost, not just an aesthetic one. There are three problems every state management approach in Flutter has to solve: Where does state live , and how does a widget deep in the tree access state that was created somewhere else? How do
The defense secretary’s idea of administering testosterone therapy to service members of the US Armed Forces reveals little understanding of the complexity of hormones.
Both nominees flailed in their own unique ways as senators sought answers.
On today’s Uncanny Valley, we unpack OpenAI’s ongoing drama, both legal and reputational, and whether these developments could further hurt the company—particularly in its fight against Anthropic.
The company endorsed landmark AI transparency laws in California and New York last year, but its head of US state and local policy says they may already be outdated.
Sometimes it feels like keeping your floors clean is one of those never-ending chores, which is why it's nice to have a versatile robot vacuum take it off your hands. The Ecovacs Deebot X11 robovac / mop hybrid is designed to do just that, and it's now $699 ($400 off) at Amazon and directly from […]
OnePlus promises to continue supporting the phones it has already released.
Travel agency Fora announced a $60 million Series D round led by Forerunner and Tactile Ventures, valuing the company at $1 billion.
Exposing your data over MCP is the easy part. Designing a tool an agent uses well is the hard part. An agent can only use a tool it can read, so the work is shaping the tool for how the model calls it, not just for the human looking at the result. These are the techniques behind @bonnard/mcp-charts and the visualize tool. Discovery-first, so the agent stops guessing An agent that guesses your schema writes wrong queries. So the first tool the agent meets is a discovery tool. It calls visualize_read_me to load the chart options, the tool schema, and worked examples before it ever calls visualize , and an explore_schema tool to learn your tables and columns before it writes SQL. The agent reads, then acts. A small set of purpose-built tools The temptation is one tool per metric, or a single tool that takes arbitrary SQL and hopes. Both fail: too many tools blow the agent's attention budget; one firehose tool gives it no guardrails. Bonnard ships a small set, discover, query, visualize, each with a narrow, obvious job. The agent picks the right one because there are few of them and each does one thing. // a small, purpose-built set, not one tool per metric server . registerTool ( " explore_schema " , { /* list tables + columns */ }, listSchema ); addCharts ( server , { runSql }); // registers visualize_read_me + visualize Compact, honest responses A tool that returns 10,000 raw rows poisons the context window and the agent's next decision. Bonnard's responses are sized for a model to read: Row caps with a completeness flag. Results are capped and tagged partial or complete , so the agent knows whether it is looking at everything. Partial-result warnings. When results are capped, the response says so and tells the agent not to sum or average the visible rows, use a measure instead. Summaries over dumps. The chart comes back with a compact text summary the model can reason over, not just an image it cannot read. Errors that guide the next action A bare "error: invalid co
The startup, founded in 2021, lets enterprise customers use smartphones to scan and spot vehicle damage.
While everyone in AI is chasing "superintelligence," Alexandre LeBrun, CEO of Yann LeCun’s world model startup, AMI Labs, dismisses the word.
Aina is going to pilot a new device in the coming weeks.
Protect your home against dust, pets, allergens, and more with the best air purifiers, tested firsthand.
I’m sick of “opt-out” toggles for automatically enabled generative AI features. It’s past time to make “opt in” the default setting for sensitive features.
After canceling its second foldable, OnePlus is officially bowing out of the US and Europe.
The original OnePlus phone disrupted the mobile market 13 years ago with its affordable price and top-end specs. Now, the company is exiting North America and Europe to focus on China.
OnePlus could also wind down its operations in India by 2027.
Applied Computing has raised a $20M Series A to build a foundation AI model for the oil, gas and petrochemical industry.