AOL outages and service status in Camberley, England

Problems in the last 24 hours in Camberley, England

The chart below shows the number of AOL reports we have received in the last 24 hours from users in Camberley, England and surrounding areas. An outage is declared when the number of reports exceeds the baseline, represented by the red line.

Community Discussion

Tips? Frustrations? Share them here. Useful comments include a description of the problem, city and postal code.

Beware of "support numbers" or "recovery" accounts that might be posted below. Make sure to report and downvote those comments. Avoid posting your personal information.

AOL Issues Reports Near Camberley, England

Latest outage, problems and issue reports in Camberley and nearby locations:

• 
  Ultra Mugnus (@mkn1ght) reported 11 minutes ago from Reading, England

  @SJM1878 @AOL "PUT THE PHONE DOWN MUM I'M TRYING TO DOWNLOAD A PICTURE OF CAPTAIN JANEWAY IN THE NIP"

• 
  anthony (@edgfrg) reported 38 minutes ago from Slough, England

  @AOLSupportHelp I’m trying to get into my email password help

• 
  Paddy 🇵🇱 (@slavicking18) reported 54 minutes ago from Windsor, England

  I still have an AOL email address so never question my loyalty

AOL Issues Reports

Latest outage, problems and issue reports in social media:

• 
  Sarah '$EZ' Forde (@Kittyclysm87) reported 4 minutes ago

  @Matt_Pinner 19, never had a AOL account.

• 
  Conner Pendleton (@ConnerPendleton) reported 8 minutes ago

  @BigBlueNationD1 Every single one but an AOL address lol so 19pts...Damn, I'm only 40?

• 
  The Stairway to Retro 💾🕹️ (@StairwayToRetro) reported 11 minutes ago

  @RetroTechorDie At a stretch, I could understand them wanting to shut down the Nina network if the Italians plan to revive AOL chat. But going after someone who makes a video, especially one with a positive tone toward the AOL brand, makes absolutely no sense.

• 
  Aremu Azeez (@aremz04) reported 13 minutes ago

  There's a line in The Lean Startup that stung when I read it last week: "learning" is the oldest excuse in the book for a failure of execution. Eric Ries tells the story of IMVU's first product. His team spent six months building an instant-messaging add-on, based on a genuinely smart-sounding strategy: piggyback on existing IM networks (AOL, Yahoo!, MSN), ride their network effects, spread virally through people's existing friend lists. Whiteboard-brilliant. They launched. Nobody used it. When they finally sat real customers down in front of the product, every assumption fell apart. Customers weren't scared of learning new software - the average teenager ran eight IM clients at once. They didn't want to chat with existing friends through avatars - they wanted to meet strangers. The "obvious" barrier the whole strategy was built around wasn't a barrier at all. Ries's point isn't "test more." It's sharper than that: in a startup, any effort that doesn't produce evidence about what customers actually want is waste - no matter how well it's executed. He calls the real version of this validated learning, to separate it from the after-the-fact story you tell yourself when something doesn't work. I'm sitting in a smaller version of that exact test right now with Owoye. One of the assumptions baked into the product is that WhatsApp and IG sellers want their invoices auto-matched to incoming payments. It sounds obviously useful from where I sit. But that's precisely the position IMVU's team was in - certain, and wrong, about what would remove friction for their customer. So this week will not be spent refining the feature. It will be spent in conversations with actual sellers, watching how they track who's paid right now - screenshots, memory, WhatsApp scrollback - before deciding whether "auto-match" solves their problem or just mine. The uncomfortable question worth asking about your own product this week: is the thing you're building solving a problem your customer has, or a problem you have with how your customer works?

• 
  Tnulb Sivart (@TravisBlunt) reported 14 minutes ago

  @ClayTravis Sports Illustrated is still a thing? Huh, have touched that garbage of a publication in probably a decade, just assumed it was the AOL of sports!

• 
  Antranig Dereyan (@ADereyan) reported 15 minutes ago

  Hey @HeyHeyItsConrad I’m listening to ur pod w @EBischoff on @WWE invasion & I think the real path to go down would be if Turner bought WWF & Eric had that money to bring in WWF talent into WCW & do invasion or another storyline.Might,need to say AOL merger never happens either.

• 
  𒌐 Binghe | 📖 TVWH vol 1 (@blyssfuldreams) reported 15 minutes ago

  I want 2 cut I wantb2 cut **** you **** yiu calling me crazy maybe I am ******* crazy huh **** you I hate you always trying to gaslight me I hate THE BOTH OF YOU I HATE YOU AOL

• 
  Brett Caughran (@FundamentEdge) reported 19 minutes ago

  My playful analogy is we are in the AOL era of AI. Early stage of a revolutionary technology, but the delivery mechanism is still clunky, requiring really dumb concepts like prompt engineering. In 1996, you couldn't even imagine business models like Uber, Netflix, the iPhone, YouTube or Tesla FSD, because the technology wasn't even close to capable or cost effective enough. From 1996-2006 global data volume grew by a factor of 10,000,000x (per Gemini), but that growth was hugely deflationary (wholesale IP transit cost down 99%), i.e. good for the application layer and selectively bad for the pipe owners (telecom). Overall, the mix of massive volume growth offset against gnarly price deflation has been a, net/net, positive thing for telecom investing. Does that hold for the frontier labs? "Intelligence pipe" feels like it can be a pretty damn awesome business, but, like telecoms, the evolution of "intelligence pipe as a business" will be extremely path dependent and will require real business models with attractive unit economics to fund. Obviously most of the 90's era telecoms went bust and the assets were only financially productive for the 2nd or 3rd owners, mostly due to balance sheet issues & the subsequent closing of the capital markets window. Though capital markets have evolved materially since the early 2000's telecom bust with a regulatory environment more supportive of monopolies/oligopolies and private capital markets more supportive of funding massive cash burn (to wit, I think it's a really bad idea for Anthropic to IPO in '26, but what do I know?). So imagine that prior but like 10-100x the size of the internet. Maybe more? As in 1996 when you couldn't even envision Netflix/Uber, the iPhone or Tesla FSD, we have zero idea what 2056 looks like, but the exponential will certainly drive even more upside uncertainty in technology. idk, hard to be structurally bearish on the "intelligence pipe" and subsequently, infrastructure that feeds the pipe (though it feels certain there will be super gnarly potholes, messy shakeouts, and bankruptcies along the way, as we saw in telecom evolution), and ultimately what matters is free cash flow production, which feeds from the intersection of exponential volumes against unit level deflation. What's exciting to me with the improvement in the models, both frontier like Fable/Sol and open source like Kimi/GLM/Deep-Seek, is you are getting *closer* to seeing a real application layer possible in a very intellectually difficult sandbox like public market investing. Nearly four years from GPT 3.5 demo, we still aren't there. We are still in the "AOL era" - too slow, not competent enough, too expensive. But we are getting closer. So are we exiting the AOL era? It feels to me like we might be. If I had to guess, my guess is the frontier labs continue to be good businesses (and extremely volatile public stocks), mostly due to the reflexive nature of capital markets & talent acquisition. But what seems really obvious, to me, is that 2026-2036 is going to be the era of the application layer, where the Travis Kalanick-style entrepreneur takes this "intelligence pipe" and envisions new & groundbreaking businesses that change the world. That entrepreneurial accelerate will drive durable and accelerating demand for the intelligence pipe, it seems. It's a really exciting time to be alive.

• 
  Barefoot Student (@BarefootStudent) reported 20 minutes ago

  Mark Cuban says these 5 types of jobs are most at risk from AI, per AOL. 1. Entry-level jobs with repetitive ‘binary’ tasks 2. Junior software developers and routine coders 3. Customer service and call center workers 4. Research and data analyst roles 5. Finance and legal support jobs

• 
  TyWebb'sLumberyard (@JohnnyRingo1625) reported 23 minutes ago

  @AngelaBelcamino Never used a dating app but did find my wife indirectly through an aol chat room.