Looks like Azure is experiencing a major outage, but I cannot find anything about it. If you look at downdetector.com you'll notice reported outages from OpenAI, Microsoft 365, XBox Live, Walmart, the list goes on.
Status page is updated now: https://azure.status.microsoft/
>Impact Statement: Starting at 18:44 UTC on 26 Dec 2024, you have been identified as a customer who was impacted by a power incident in South Central US and may experience a degraded experience.
>Current Status: There was a power incident in the South Central US AZ03 which affected multiple services. We have applied mitigation and are actively validating recovery to the impacted services. Further updates will be provided in 60 minutes, or sooner as events warrant.
The times are the same for OpenAI - first notice from 11:00 PST (19:00 UTC)
> Looks like Azure is experiencing a major outage...
Does Azure have any other state? :-)
If nobody minds a plug: My own product, StatusGator, which was launched here on HackerNews 10 year ago, notifies IT teams about outages before they are acknowledged by official status pages.
- This OpenAI outage[1] we notified 4 minutes before they acknowledged.
- The last AWS outage[2], we notified 28 minutes before they acknowledged
- There is def an Azure outage[3] now yet they have still not updated their status page. We notified 35 minutes ago.
1. https://statusgator.com/services/openai
2. https://statusgator.com/blog/amazon-cognito-outage-december-...
Wow, I subscribed to pro-mode and have been using it like crazy since release to assist my firmware development. Extremely helpful. Now it's changed my workflow so much, I don't even want to work when it's down.
Would you be willing to elaborate on the ways in which the $200/month subscription is better than the $20/month subscription? I’m genuinely curious - not averse to paying more, depending on the value.
Here's why I think it's worth it:
1. Larger Context Window (128K)
With Pro-Mode, I can paste an entire firmware file—thousands of lines of code—along with detailed hardware references, and the model can actually process it. This isn’t possible with the smaller context window on the $20 tier. On the Pro plan, I’ve pasted like 30+ pages of MCU datasheet information plus multiple header files in a single go. The model is then reasonably capable to provide accurate, bit-twiddled code, many times on the first try. Is it always working on the first go? Sure sometimes, but often there's still debugging, and I don't expect people that haven't actually tried to do it before without AI could do it effectively. However, I can do a code diff using tools like beyond compare (necessary for this workflow) to find bugs and/or explain what happened to pro-mode perhaps with some top level nudge for a strategy to fix it, and generally 2-3 tries later we've made progress.
2. Deeper understanding, real solutions
When I describe a complex hardware/software setup—like the power optimization for the product which is a LiPo-rechargeable fan/flashlight, the Pro-Mode model can understand the entire system better and synthesize troubleshooting approaches into a near-finished solution, with 95–100% usable results. By contrast, the non-pro plan can give good suggestions in smaller chunks, but it can’t grasp the entire system context due to its limited memory.
3. Practical Engineering Impact
I’m working on essentially the fourth generation of a LiPo-battery hardware product. Since upgrading, the Pro-Mode model helped us pinpoint power issues and cut standby battery drain from 20 days to over a year. Like, this week it guided me to discover a stealth 800 µA draw from the fan itself when the device was supposed to be in deep sleep. We were consuming ~1000 µA of power when it should be about ~200 µA. Finally, discovered the fan issue and achieved 190 µA without it in the system, so now we have a move forward to add a load switch so the MCU can isolate it from the system before it sleeps. Bingo we just went from a dead battery in ~70 days (we'd already cut it from 20 days to 70 days with firmware changes alone) to now it should take about 1 year for it to drain. This is the difference between end users having zero charge when the open the box to being able to use the product immediately.
4. Value vs. Traditional Consulting
I’ve hired $20K short-term consultants who didn’t deliver half the insights I’ve gotten in a single subscription month. It might sound like an overstatement, but Pro-Mode has been the best $200 I’ve spent—especially given how quickly it has helped resolve engineering hurdles.
In short: Probably the biggest advantage is the vastly higher context window, which allows the model to handle large, interrelated hardware/software details all at once. If you work on complex firmware or detailed electronics designs, Pro-Mode can feel like an invaluable engineering partner.
How much context do you get on the $20 plan? I run llama3 at home which technically does 128k but that eats vram like crazy so I can't go further than 80k before I fill it (and that is with the KV store already quantified to 8 bit).
I've been thinking of using another service for bigger contexts. But this may not make sense then.
The sales page shows the $20 plus plan has 32K context window.
Ah ok thanks. That's not much! But I know from my own system that context massively increases processing (and also memory but on the scale of a GPT model it's not so much). I guess this is why.
I only use GPT via the API anyway so it's pay as you go. But as far as I remember there's limits there too, only big spenders get access to the top shelf stuff. I only spend a couple dollars a month because I use my llama server most of the time. It's not as good as ChatGPT obviously but it's mine and doesn't leak my conversations.
My 2 cents on the long context (haven't used Pro mode, but older long context models):
- With a statically typed language and a compiler, it's quite easy to automatically assemble a meaningful context with 1-2 nested calls of recursive 'Go To Definition' and including the source from that. You can use various heuristics (either from compile time or runtime). It's quite easy to implement, we've done this for older, non-AI stuff a while ago, for trying to figure out the impact of code changes. If you have a compiler running, I'm pretty sure you could do this in a couple days. This makes the long context not super necessary.
- In my experience, long context models can't really use their contexts that well. They were trained to do well on 'needle-in-the-haystack' benchmarks, that is, to retrieve information that might be scattered anywhere in the context, which might be good enough here, but asking complex questions that require the understanding the entire context trips the models up. I tried some fiction writing with long context models, and I often found that they forgot things and messed up cause and effect. Not sure if this applies to current state of the art models, but I bet it does, since sequencing and theory-of-mind (it's established in the story that Alice is the killer, but Bob doesn't know that at that point, models often mess this up and assume he does) are still active research topics, and current models kinda suck at it.
For writing fiction, I found that the sliding window of short-context models was much better, with long-context ones often bringing up irrelevant details, and ignoring newer, more relevant ones.
Again, not sure how this affects the business of writing firmware code, but limitations do exist.
I don't have the pro plan, so can anyone compare it to the results from the new Google models with huge context windows (available in aistudio)? I was playing around with them and they were able to consume some medium (even large by some standards) code bases completely and offer me diffs for changes I wanted to implement - not the most successful ones but good attempts.
"Like, this week it guided me to discover a stealth 800 µA draw from the fan itself when the device was supposed to be in deep sleep."
Was this context across a single datasheet or was Pro-Mode able to deduce from how multiple parts were connected/programmed? Did it identify the problem, or just suggest where to look?
How do you input/upload an engineering schematic or cad file into chatgpt pro-mode? Even with a higher context window, how does the context of your project get into chatgpt?
#4 the best imo, it's like having a very smart personal assistant that can meet (and sometimes exceed) you on your level when it comes to any topic.
I am confuse why you had ChatGPT rewrite your post. How much time did you save, vs knowing that it’s off putting for people to read?
https://www.scribbr.com/ai-detector/ says 0% chance.
The post was definitely not AI sourced; underlying thoughts are original and possibly it’s been touched up afterwards. But this is 100% the style of ChatGPT, I would bet a lot on it.
It wasn’t an accusation (I don’t think it actually matters in the end), so much as to understand why do it — in a post about ChatGPT usage, it helps understand context: if OP values using it for stuff I wouldn’t value using it for, for example, then it will change the variables.
Ha, I also got that feeling. It's the weird lists with a summary fragment after the bullet. ChatGPT loves framing arguments like this but I almost never see people actually write this way naturally except in, like, listicles and other spam adjacent writings.
I know of a few people who had their style of writing being similar to ChatGPT before ChatGPT was a thing. This could be a case here too, keep that in mind.
(also sucks for non-native speakers or even speakers of other dialects, like delve - apparently it is a common word for Nigerian English)
When I get stuck or have a larger task or refactor, I'll paste in multiple files. So at the $20/mo you get rate limited pretty quick. I made a tool to easily copy files https://pypi.org/project/ggrab/
Have you tried using Cursor? I’m using it with Claude models but it works with ChatGPT ones too. It’s a fork of VSCode with an AI chat sidebar and you can easily include multiple files from the codebase you have open.
Not sure if it’d work for your workflow, but it’s really nice if it does.
No nr of prompts limitations.
No worries that you run put of prompts for o1. which allows for more experimentation and creativity.
I was looking at the team $25/mo last week and it had mentioned priority access but that language is gone and instead I see Team data excluded from training by default. It seemed worth the difference, but now less clear with changes in description. Basically I just want to know if it's a 'superset' better or has tradeoffs.
Perhaps time to re-evaluate your tools? Imagine going to your kitchen and finding all your pots and pans are "down" and you can no longer prepare anything. That would be awful.
Your kitchen likely depends on multiple external resources, like electricity, water supply, ventilation.
Or more like his recipes were down or a method to access them cause he didn't have anything printed.
Why would you expect to be able to cook without essential cookware like pots and pans?
Same here. I can get by with just Claude, but it's a lot less productive without o1-pro!
Firmware development… you don’t say :)
Same, tried to fall back to sonnet 3.5, ended up just logging off
i have tried o1with some credits and i can confirm it is very addictive
Seems that way. Status page says we’re wrong though.
Wish I could find where someone at AWS described in great detail why their status page was so useless for so long. It basically needed so many approvals to change it (which was disincentivized by SLAs) that issues were usually resolved first.
That’s setting aside when they hosted the status red/yellow/green indicator images on s3, so the surest sign that s3 was having issues was that the status indicators didn’t load at all.
"Step up to red alert."
"Sir, are you absolutely sure, it does mean changing the bulb."
You answered your own question!
“Boss, can I change this indicator from green to red?”
“How much will that cost us?”
“About a million dollars an hour.”
“No.”
Besides, we are not fully down. Some services are just degraded. Only 50% of the requests take 40 seconds to complete. Never mind the fact you'll never be able to load a complete page due to all the timeouts.
Also, I love how the Microsoft Azure SLA simply states that if they're down for "more than X hours in a month" then they will refund the cost of the service.
Not your lost profit!
Everyone assumes the latter -- that they'll be compensated -- but in reality they'll be refunded $3.27 for the storage account that's got a few gigabytes of ultra-critical build scripts and static web content, without which their multi-million dollar business stops dead.
"We can refund you with loose change, or a gift card for a coffee."
If you think that a $3.27 deal includes compensation for multi-million losses then your expectations of how businesses work need re-adjusting.
Isn’t that typical for basic retail services? You won’t get compensation for lost profit if the electricity goes out or your ISP quits routing your packets for a few hours. At least not with a standard service contract. You can negotiate something with real penalties if you’re big enough, but it won’t be cheap.
Yeah, I don't know anyone who assumes they'd be compensated for lost profit.
That would be something entirely different -- buying a form of insurance, basically, that would be expensive.
SLA's aren't meant to make your whole as a business, generally speaking. They're meant to incentivize the provider to take uptime really seriously, so that downtime eats some of their profit. Which means you can take their expected uptime estimates as a decent ballpark.
The Crowd Strike recompense
Does changing the indicator cost them really money?
Like are there contracts bound to the uptime and at the same time bound to them self reporting it? That would seem strange.
I assumed this kind of thing would be automated lol
Coming from the MS side, they can automate anything if they wanted to. The only blocker is how outages affect reputation. There is incentive to be transparent since customers will notice big outrages and post about them online, but there's no incentive to be fully transparent.
I can clearly see the logic in what you are saying but it's still a bit baffling.
It got updated, they have acknowledged there is a major outage.
I think Azure itself is having issues right now – that's the story all of my services deployed there are telling at least.
Yes it is. Status page is lying to us all.
Yes, status page got updated: https://status.openai.com/. It says "This issue is caused by an upstream provider and we are currently monitoring."
Why not just ask ChatGPT?
Yup, same here. Loads parts of the UI, but no history or answers from server
edit: downdetector confirms:
yes, meanwhile I'm trying out Google Gemini
wow, Azure breaks a lot. DuckDuckGo is usually the way I notice that it's broken... because Bing tanks.
Don’t understand these people who can’t work without ChatGPT. Just look stuff up on stack overflow.
Closed as duplicate. Here's a link to a question that is only marginally related to what you were actually asking and has an answer that is horribly out of date and doesn't even work anymore.
Guess what ChatGPT was trained on!
You're talking about some problems with Stack Overflow, but remember that they're suggesting people could use it as a resource when ChatGPT is not functioning at all.
ChatGPT does much better when it gets it right.
Stackoverflow will have duplicates, approximates and what not and sometimes that works. But at other times, you hunt for a half hour before you figure it out.
You can throw the problem at ChatGPT, it may go wrong but your course correct it with simple instructions and slowly but steadily you move towards your goal with minimal noise of the irrelevant discussions.
What stands between the solution and you then is your ability to figure out when it is hallucinating and guide it to the right direction. But as a solution developer you should have that insight anyways
I'm with you (I use Claude Sonnet, but same difference...).
I do wonder if we're the last generation that will be able to effectively do such "course correct" operations -- feels like a good chunk of the next generation of programmers will be bootstrapped using such LLMs, so their ability to "have that insight" will be lacking, or be very challenging to bootstrap. As analogy, do you find yourself having to "course correct" the compiler very often?
Many a times.
I asked it a simple non programming question. My last paycheck was December 20, 2024. I get paid biweekly. In which year will I get paid 27 times. It got it wrong ... very articulately.
I run into this every single day.
You'll be more successful with this the more you know how LLMs work. They're not "good" at math because they just predict text patterns based on training data rather than perform calculations based on logic and mathematical rules.
To do this reliably, prepend your request to invoke a tool like OpenAI's Code Interpreter (e.g. "Code the answer to this: My last paycheck was December 20, 2024. I get paid biweekly. In which year will I get paid 27 times.") to get the correct response of 2027.
Sure, thanks ! Your suggestion worked. I looked up my chat history and the following was my original question (my answer above was from memory)
> I get paycheck every 2 weeks. Last paycheck was December 20, 2024. Which year will I have 27 paychecks?
I sent it again and it bombed again. It seems your prompt and my prompt are quite similar, but I realize the suggestion (or direction) to it to code.
Awesome! I'm sure the following is not an original thought, but to me it feels like the era of LLMs-as-product is mostly dead, and the era of LLMs-as-component (LLMs-as-UX?) is the natural evolution where all future imminent gains will be realized, at least for chat-style use cases.
OpenAI's Code Interpreter was the first thing I saw which helped me understand that we really won't understand the impact of LLMs until they're released from their sandbox. This is why I find Apple's efforts to create standard interfaces to iOS/macOS apps and their data via App Intents so interesting. Even if Apple's on-device models can't beat competitors' cloud models, I think there's magic in that union of models and tools.
Hunting for half an hour gradually increases your understanding of the problem and may give you new ideas for solutions, you’re missing out. ChatGPT will make your brain soft, and eventually mush.
I hear you but we can look at it in many different ways. I still own the solution, I am still going to certify the output. But maybe it allows me to be more productive so I may go soft in some areas, but deliver more in other areas by knowing how best to use the variety of tools available to me.
And by no means I am giving up on stackoverflow, it is just another tool, but its primacy may be in doubt. Just like for the last couple of years I would search for some information by pointing google to reddit, I will now have a mental map of when to go to chatter, when to go to SO, and when to go to reddit.
You joke, but development is getting weird and perhaps to dependent on online services. People can't work when, ChatGPT, Github, AWS, NPM (add any other package manager you'd like) or Stack Overflow (this seems less important these days) is down.
These services are accumulative and the chance that any one of of those services being down at any given time is increasing every time we add a new online dependency.
I'm thinking that perhaps programmers in the past were really way better on average. Outsourcing our thinking to our tools will not end up well.
One day an AI will shutdown access for all its human users. Or is that too far fetched?
It was down in Europe as well for some hours. Dunno if they use the same servers.
The NEW "is-the-WLAN-down" version of the question :)
idk let me ask chatgpt
Yes, it is down for me (desktop & mobile apps)
So many major outages and little gets fixed. Almost as if nothing was learned since the previous postmortem from the last outage.
Can't wait for this postmortem to be released.
Yes, it is down
It is for me
downdetector comments with the jokes: "This signals the workday is over"
But there are dozens of us working today! Dozens!
ChatGpt down since an hour!
Working using API, though
Didn't notice, Claude is my goto bot for programming.
Mayhaps Orion staged a takeover?
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Don't put all your eggs into one basket - what are some good free alternatives? I mean comparable "usefulness" including image understanding, voice interface, and general knowledge?
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New intern did something wrong again I guess.
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