Most “cloud storage 101” pages dodge the only questions people actually care about: where is my data, and who can see it. Our Hivenet explainer on cloud storage answers those directly with locations, keys, and access patterns, instead of hiding everything behind adjectives and

AI has started targeting people who can’t defend themselves: the dead. Cybernews reports deepfakes and “griefbots” built from victims of violent crime and public figures, with almost no federal protection in the US for the image of the deceased unless money changes hands.

The emergency alert on your phone might depend on one company’s patch policy. OnSolve’s CodeRED system, used by local governments across the US, was hit by the Inc Ransom group, leaking names, addresses, emails, and passwords while disrupting alert services that people think of

Your bank can have great security and still leak your data through a vendor buried three layers down the org chart. This week’s SitusAMC breach, hitting a real-estate processor used by many of the top 20 US banks, shows how one vendor can spray customer and legal data across

Everyone wants an A100, fewer people can explain why. We can explain why you shouldn't. We break down memory, bandwidth, and real workloads in plain English so you know when it actually makes sense to rent one, or when you should consider 4090s and 5090s.

Christine @Lagarde warned that Europe is “missing the boat” on AI and can’t just keep buying models and compute from abroad. If your “AI strategy” is basically renting GPUs from the same three US hyperscalers, you’re not sovereign, you’re a high-value customer on someone else’s

BFFs? @AWS and @Google launched a joint “multicloud” fast lane, weeks after an AWS outage is estimated to have cost US companies $500–$650 million in lost business. This is what true Big Tech love looks like.

Funny how we joke about ads “reading our minds” instead of asking why companies track every scroll, pause and half-typed message. You’re not weird if that feels off; Hivenet is a bet that cloud services can work without turning your behaviour into a trading asset.

How can UAE-based organizations harness AI while ensuring compliance and data sovereignty? 🇦🇪 Our latest blog on LLM Inference with Local Hosting explores deploying vLLM servers in the UAE for ultra-low latency, faster token streaming, and adherence to regulations like the

If you look at “sign in with X” and think “this feels like one big surveillance basket,” you’re not being dramatic. Central login, storage and analytics all fail in central ways; Hivenet exists because trusting a single identity and data broker for everything feels broken.

Harvard confirmed a breach after a phone scammer got into its alumni fundraising systems and accessed contact and donation records. The bigger issue is how much background data universities keep forever; Hivenet’s instinct is to keep less and avoid putting it all in one place.

A new “AI factory” in Taiwan will pack 7,000 Nvidia Blackwell GPUs into a $500M data centre drawing around 16MW of power. If our only answer to AI demand is bigger boxes on fragile grids, we’re missing the point of distributed compute, the kind Hivenet exists to explore.

GPU shopping in 2025 feels like filing a tax return. Our Compute blog breaks down vRAM, interconnects and pricing tiers in plain English, and shows where RTX 4090s outperform “data centre” GPUs on throughput per dollar for deep learning: https://t.co/wL09ZT0B2O

2/2 That dataset in the wrong hands means cheap, targeted scams. If your business runs on giant identity graphs, you end up with APIs like this; Hivenet assumes scraping is inevitable and keeps data to a minimum, spread across many encrypted nodes instead of one big target.

1/2 WhatsApp didn’t “get breached.” Researchers used its contact-discovery API to test 63B phone numbers and confirm 3.5B active accounts, scraping profile photos and “about” text along the way. That’s what happens when rate limiting is an afterthought.

Everyone talks about “the cloud” like it’s everywhere. Roughly 38% of the world’s data centers sit in the US alone. If your backups and AI jobs all live in those same hubs, you’ve centralized risk; Hivenet’s whole point is to spread risk across many independent nodes instead.

‘Sovereign cloud’ that still answers to the US CLOUD Act is a neat trick. This piece looks at why server location isn’t sovereignty and why only 28% of people are still willing to trade personal data for “free” services: https://t.co/86NIEy8Yf2

Thinking “maybe half the internet shouldn’t hinge on a single company’s bad day” is not paranoia. Distributed cloud exists so a config bug, power cut, or BGP oops in one place doesn’t take your life, work, and data down with it. That design choice is the whole point of Hivenet.

Well... @Cloudflare’s Nov 18 outage briefly broke access to X, ChatGPT, and thousands of other sites for around 2.6B users. When 20% of the web sits behind one provider, you don’t have redundancy, you have a bottleneck. Hivenet spreads storage and compute across many small

In today's AI-driven world, how can US-based teams optimize LLM inference for speed, compliance, and data privacy? 🇺🇸 Our new blog explores deploying inference servers with local USA hosting—reducing latency for faster token times, ensuring adherence to regulations like HIPAA