WeatherXM retweeted
โWEATHER PORN.โ ๐ฆ๏ธ
Thatโs how one meteorologist at the World Meteorological Technology Expo described FACT.
And yesterday there was a particularly satisfying plot twist:
Michael Bรผhrer from @meteoblue presented @WeatherXM FACT on stage. ๐
Weโre evaluating 40+ forecasting models against observations from 8,000+ WeatherXM ground stations, across the entire 2025 dataset.
1.83 BILLION hourly forecasts!
Global rankings.
Country rankings.
Per-station results.
Temperature, humidity, wind and rain.
Every forecast horizon โ same day, +1, +2, +3, +4, +5 and +6 days ahead.
One important caveat:
WeatherXM MOSAIC and meteoblue mLM sit at the top, but theyโre not playing exactly the same game as the other models. They use station observations as part of their post-processing/training, while the other models are evaluated without knowledge of our stations.
So this isnโt meant to prove that MOS โbeatsโ global weather models.
It shows something more commercially useful:
๐ What accuracy should a customer actually expect at a physical location when buying an end-to-end observation + forecasting solution from us?
The rest of the models compete on equal terms.
And the results are spicy. ๐ถ๏ธ
fact.weatherxm.com
#MTX26 #TECO2026
WeatherXM retweeted
If anyone wants to talk forecast accuracy tracking and which is the best model per variable, horizon for every single location we have a weather station, I am around.
We published 2025 results comparing 40+ models, check it out at:
fact.weatherxm.com
@WeatherXM
Only 10 minutes until the doors open for the exhibition floor of MTX 2026 ๐ @WMO
Get ready to head overโ#MTX26 #TECO2026 #MetTechWorldExpo
WeatherXM retweeted
ClawQueue is our open-source take in @WeatherXM GitHub-native queues, reviews and artifacts; company workflows; an OKF-structured company Super Wiki exposed over MCP; and a personal squad of persistent agents for every employee, each with distinct roles, personalities and memory.
WeatherXM retweeted
Replying to @MikeZajko
AI agents are becoming economic actors. They discover services, negotiate, pay, execute, and settle through open networks. Identity and reputation rails are emerging through standards like ERC-8004. Payment rails are emerging through x402. But the agent economy is missing a critical layer:
Trusted physical-world evidence.
Before an agent can route a shipment, dispatch energy, price insurance, settle a prediction market, trigger a credit covenant, or execute a climate-linked contract, it needs to know: What happened? Where? When? Who measured it? How fresh is it? How reliable is it? Is confidence high enough for this action?
@WeatherXM has turned decentralized environmental telemetry into machine-readable evidence bundles: signed observations, station identity, location, timestamp, freshness, quality score, nearby-station agreement, historical reputation, confidence level, and settlement context.
The broader DePIN ecosystem is proof-carrying spatial intelligence for the cybernetic economy.
But the deeper problem is that trustworthy physical-world data does not appear automatically. It requires human coordination: hardware must be deployed in the right places, by credible local operators, with the right incentives, verification, maintenance, and logistics. That is where WeatherXM's targeted rollouts experience, in fundraising campaigns and human coordination for hardware network expansion, becomes strategically important.
WeatherXM retweeted
Athens had a moment last week.
I spent three days at @PanatheneaFest 2026, and the takeaway is simple: Athens is now on the global tech map, a place serious people choose rather than tolerate.
Panathฤnea is a not-for-profit, run almost entirely by students and recent graduates.
That volunteer team still pulled in founders from ElevenLabs, Bolt, Runway, Airwallex, Deel and Plum; partners from Sequoia, Index, Atomico, Balderton, Northzone, 500 Global, PayPal Ventures and Dawn; operators from OpenAI, NVIDIA, Google, Microsoft and Qualcomm; and European deeptech founders from Proxima Fusion, Isar Aerospace and Open Cosmos.
It also brought Greeks home, @real_ioannis (Reflection, ex-DeepMind) and @agermanidis (Runway).
And teams are putting down roots here. @dionyziz' @CommonPrefix (~40 people), @poddotnetwork, and @Mysten_Labs Sui hub on the crypto-infra side; @YSmaragdakis' Dedaub on smart-contract security. Home-grown scaleups are real too: Viva.com (Greece's payments unicorn), Workable, Blueground, agritech-AI Augmenta (and more).
I spoke at the Common Prefix ร Pod side event on "Blockchain and Trust Technologies," alongside @sagrawal (Pod) and @nikil511, CEO of @WeatherXM. We got into the AI ร crypto thread that's stopped being hand-wavy: decentralized training.
You no longer need everyone in the same data center to train a frontier model. ~99% of a model's weights are bit-identical between training steps, so you ship only the ~1% that changed.
@Hevalon's team at Covenant formalized this (their PULSE paper) and pre-trained Covenant-72B with trustless peers over the open internet. @huggingface then shipped the same trick in the open. Crypto's coordination layer + a ~100ร smaller payload = a big model trained across machines no single entity controls.
The other shift I keep noticing: most people still use agents for coding, or as a Google alternative. What's coming is general-purpose agents that research, draft, plan and do your work for you, and the hardware already knows it.
The silicon being built isn't sized for one assistant; it's sized for an agent fleet.
Two days ago NVIDIA announced the DGX Station for Windows: a GB300 ARM desktop with up to 748GB of unified memory, built to run hundreds of concurrent agents on-prem. You don't build that for a chatbot you visit.
If you don't have 5, 10, 50 agents running at all times, local and cloud, doing evals, auto-research, quietly improving work you've already done, you're probably not using AI properly yet.
We're early. But the people building the hardware have placed their bet.
To the Panathฤnea team: thank you, and bravo. See you in 2027. ๐ฌ๐ท
WeatherXM retweeted
Replying to @momir_amidzic
Momir, moat will not be at the AI / agent level but at the data level, once we have an AI trust protocol that agentic harness can consume.
In many ways, DePIN projects like @WeatherXM are building this protocol without realizing it.
The trust harness for physical-world AI: a blockchain-native spatial intelligence layer that lets agents safely act on hyperlocal reality, not just digital information.
btw, I came here to inform you there is an impersonator of your team scamming people xitter.cf/jiaping_vc
He sends fake NDA google docs that need to install stuff on local machines :-/
WeatherXM retweeted
We're excited to share the speaker lineup for Blockchain and Trust Technologies, our side event at Panathฤnea 2026, hosted together with @poddotnetwork.
WeatherXM retweeted
ClawQueue is live ๐ฆพ This is something I've build and use in @WeatherXM last few months to have @openclaw write @github issues for me and turn them in AI work queues that a scheduler dispatches on local machines, while team can follow up via project boards.
CQ is intentionally small: GitHub holds the durable work contract, OpenClaw helps shape the work, your machine runs the workers localy, and workflow policy stays in markdown/config you can tune with your lobster.
This is a good idea, if you operate your own company/project with your own profile, agents, boards, and worklog - or - you wanna contribute to an external/open-source project through.
Ask openclaw to install CQ and create a project-specific CQ profile from the upstream repoโs README/docs/contribution rules, then routing issue-driven agent work into reviewed PRs
Try it:
clawqueue.github.io/ClawQueuโฆ
WeatherXM retweeted
Replying to @alvarogracia @WeatherXM
This issue goes far beyond prediction markets.
Todayโs forecasting systems depend on airport weather observations, yet much of that infrastructure was never designed for adversarial settings.
An insider in a meteorological organization (e.g. admin) could alter data to influence an outcome, without a hairdryer on a sensor, and probably without being detected.
We need to transition to forecasting systems backed by denser, lower-cost, and more resilient observation networks. That is exactly what weโre building at @WeatherXM robust, blockchain-enabled weather stations and verifiable weather data pipelines for the next generation of forecasting infrastructure.
WeatherXM retweeted
Building at the intersection of weather data, climate tech, agriculture, or logistics? The Autonomys x @WeatherXM Builders Program is open.
๐น From Autonomys: Up to $10,000 in AI3 storage credits, priority technical support for Auto Drive integration, ecosystem growth support, channel visibility and amplification, and milestone-aligned mentorship.
โ๏ธ From WeatherXM: Milestone-based services and support, access to hardware, data, and APIs, integration guidance and technical support, business development introductions, and ecosystem amplification.
๐ Details and application: autonomys.xyz/builders
WeatherXM retweeted
I created a short video highlighting ๐ฑ ๐ธ๐ฒ๐ ๐ฟ๐ฒ๐ฎ๐๐ผ๐ป๐ ๐๐ต๐ ๐๐ฒ๐ฃ๐๐ก matters in Agriculture ๐ฑ
If you look closely, youโll notice it covers:
๐ ๐ช๐ฒ๐ฎ๐๐ต๐ฒ๐ฟ ๐ถ๐ป๐ณ๐ฟ๐ฎ๐๐๐ฟ๐๐ฐ๐๐๐ฟ๐ฒ: Provides hyperlocal, real-time climate data for smarter planting, irrigation, and risk management.
๐ ๐๐ผ๐ง ๐๐ฒ๐ป๐๐ผ๐ฟ ๐ฑ๐ฒ๐๐ถ๐ฐ๐ฒ๐: Continuously monitor soil health, moisture, and crop conditions, reducing waste and manual checks.
๐๐๐ฒ๐ฐ๐ฒ๐ป๐๐ฟ๐ฎ๐น๐ถ๐๐ฒ๐ฑ ๐ฐ๐ผ๐บ๐บ๐๐ป๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป: Enables farms in remote areas to transmit data across IoTs/infra reliably without relying on centralised networks.
๐๐ ๐ฎ๐ฝ๐ฝ๐ถ๐ป๐ด & ๐ด๐ฒ๐ผ๐๐ฝ๐ฎ๐๐ถ๐ฎ๐น ๐ฑ๐ฎ๐๐ฎ: Improves field navigation, logistics, and long-term crop planning.
๐๐ฅ๐ง๐ & ๐ฝ๐ฟ๐ฒ๐ฐ๐ถ๐๐ถ๐ผ๐ป ๐ฝ๐ผ๐๐ถ๐๐ถ๐ผ๐ป๐ถ๐ป๐ด: Delivers centimetre-level accuracy for farm equipment, drones, and autonomous systems, enabling precise planting, spraying, mapping, and yield optimisation.
While not explicitly featured, it indirectly highlights real DePIN projects already building in this space: @WeatherXM, @Geodnet, @Helium, @Hivemapper, and @iotex_io.
DePIN isnโt a future idea for agriculture. Itโs already reshaping how farms collect data, move goods, and adapt to climate change.
WeatherXM retweeted
Distilled DePIN industry insights. Great work from a team that understands the space better than anyone, pointing out that in many cases FDV is misleading!
Often real, customer-focused, no-BS projects don't advertise their progress enoughโas with @WeatherXM. See our blog to find out more: blog.weatherxm.com
WeatherXM retweeted
Proud to welcome @WeatherXM as Loot Box Partner.
Beaver NFTs from WeatherXM are officially in the Dabba Loot Boxes, your early gateway to $DBT before we go live on @livebonk.
Check the thread to get in now ๐
WeatherXM retweeted
Replying to @ajwarner90
Building critical infrastructure is bigger.
DeFi & RWA will merge and expand using lessons from the early DePIN experiments like @weatherxm
DePIN accelerates real world value creation & positive impact of crypto
WeatherXM retweeted
Here is our latest (2025) news on @WeatherXM from my presentation in depin:day at Argentina Devconnect. Loads of new developments in the pipeline for 2026. LFG DePIN!
@EFDevcon @fluence_project
WeatherXM retweeted
@WeatherXM = hyper-local sensing
@GEODNET = precision mapping
Together, they form the flood intelligence mesh Southeast Asia has been missing.
This is #DePIN for real-world impact, not speculation.
WeatherXM retweeted
๐๐ช๏ธAsiaโs 2025 floods exposed a brutal truth:
#APAC doesnโt have the hyper-local climate data or precise mapping infrastructure needed to protect its cities.
Hundreds died, millions displaced โ and traditional systems couldnโt see disasters coming.
This is where #DePIN changes everything.
๐ง๏ธ๐ก
๐๐ปRead full blog: seadepin.xyz/depin-apac-deveโฆ
#web3 #decentralized #climate #flood #weather #GPS #mapping

























