Not the one you asked but I genuinely think it’s possible that a part of the answer is the psychological effect of getting used to models performing well and picking up more if they fail, but also … If you have a product that works well for 95% of software engineering tasks (for the sake of this argument), with a large number of users there will inevitably be some poor schmucks who get bad results multiple times in a row. It would be highly unlikely if that _didn’t_ happen at all.
Now assuming you have millions of users, there will always be groups of thousands that experience this, and if those people go online to complain, it will look like an actual issue when it can just be explained by randomness and large numbers.
My best guess is random variation and rising expectations. I once saw someone do in depth manual testing of 3 different models and write up a whole report on their perceived strengths and weaknesses… and then discover that all 3 models were identical. Very good reminder of why the scientific method is important.
Serial testing over time is much less reliable than side by side testing, and even when I do side by side testing, I try to look at multiple attempts per prompt. Seeing multiple per prompt helps me realize how much intrinsic variation there is. My brain always wants to see patterns even when there isn’t enough data to prove them.
I'm realizing I am a minority, but my IDE is becoming MORE valuable to me, not less, with LLMs.
The volume of code is only increasing. Problems that used to be solved with a few lines (or even removing lines) are now solved with changes across 10 different files.
My IDE is invaluable for me when trying to navigate this stuff. I am completely convinced that people reviewing LLM code only via PR diffs are consistently missing massive systemic issues. You *need* to review changes in context of the surrounding code.
And doing this without an IDE is just making your life harder for no reason.
JetBrainer here. I can attest that you are a primary target for Air for IDEs.
We have put a lot of thought into how we can add value for the workflow you just described. Here's the way I think about it: FSD for a car. Can you imagine trying to sell a car without a steering wheel? I still want to code, I still want the deterministic side, even in cases where I'm letting the machine do the work.
I wanted to try Air, as it seems to have interesting ideas for working collaboratively with LLMs.
But the choice of AI providers was very limited, and I found no ways to add the ones I use (the only options for providers were Anthropic, OpenAI and Google).
So you're using the IDE for review? The main features you need are around simple things like reading files, tracking git changes, things like that?
That's a small subset of the functionality you would need if you're actually authoring code. So the IDE maybe be more valuable, but the feature set you need is actually much smaller and can probably be redesigned given your narrow workflow.
Sure, but my IDE does these simple things very well.
Just some important things off the top of my head that I use daily:
* Instantly jumping between definitions and usages
* Folding and unfolding code blocks
* Quick overview of structures in files
* Database access, so I can browse the data and the code at the same time
Also, sometimes I just want to quickly refactor/rename some variable across all its usages or whatever. It's just quicker to do it in the IDE with a simple keyboard shortcut, rather than prompting an agent "rename oldName to newName".
I'd agree with this. I've been working with Claude on an app. I wanted to increase the size of one element in the UI. I could have asked Claude to do it, but I wanted to understand the application, as well as it kinda seemed like a waste of time and tokens.
Unless you are blindly vibe coding everything without an IDE to help navigate what is being generated to review the output, working would be hellish.
And if you are blindly vibe coding everything, I am just glad I don't have to work with you. While LLMs mostly speed me up, they make serious mistakes often enough that a review is necessary.
For me, it's just the easiest fix whenever somebody shares a tweet with me, and it fails to load, or shows me some forced login popup. I just click between x and .com in my URL bar, write "cancel", and it suddenly just works.
Levent Alpöge 'additionally' proved OpenAI steals your findings & IP and plays dirty!
Ironically he proved two major findings in Navier Strokes and that unethical American companies violate laws, steal your breakthrough findings & IP and then threaten you if you dare to challenge them.
This is making the status-quo so bad for any of us working on serious capacity. My client's don't trust ChatGPT/Claude anymore and prefer on-premises and OSS models or even custom trained models.
There is nothing even close to a proof. A lot of accusations, a lot of people ready with pitchforks and torches (sadly, also here on HN), but not a lot of facts.
Did the researches opt out from data sharing on subsidised subs?
Did anyone prove that their methods enabled OpenAI models to produce the solution?
For a discussion about science, there is almost no scientifical method applied to proving anyone stole anything.
On one side, yes we don't have hard evidence that intentional plagiarism is exactly what happened.
On the other side, the lack of evidence is pretty damning. Only OpenAI can try to prove that they came by these results legitimately, and the case they're making is quite weak. They could make public metadata about what their model was trained on and whether it did train on the conversations in question; they have not. TBQH I read it as even they don't know.
And regardless of whether the result is legitimately obtained by their model, they've not at all conducted themselves well throughout this story. They set out to scoop researchers based on a rumor. They threatened to ruin a mathematicians career. They put up a paper that deliberately doesn't cite the most relevant research, despite building directly on it. No matter how you look at it, OpenAI has and should lose any standing they had in the research community.
That it was a dick move, I think there is no doubt about that. OpenAI wanted to scoop Anthropic, and the two guys working on the problem got caught in the crossfire.
Both OpenAI and the researchers know if the sessions in questions were subject to data sharing. Why neither the scientists nor OpenAI is clear about that is weird - it would seem at least one party has the incentive to report that. But even if their sessions were in training data sets its hard to tell whether it influenced the outcome. Those models are big, but are they big enough to preserve subtle, niche techniques enough to draw from them while solving a related problem? Probably nobody knows.
Actually no, the lack of evidence can be readily fixed by the researchers simply disclosing the pertinent parts of their notes and/or chats. The discovery has been scooped, so I don't see any value in keeping them private anymore. Then everybody can see how related the models' and the researchers' works are.
Did they do so by looking at inference prompts against their explicit promises, or maybe just because somebody tipped them off about his unpublished work?
If it's not the former, while certainly concerning, I don't see how that's relevant here (other than maybe in a very vague general sense of "entities doing immoral/illegal thing X are likely to also do immoral/illegal thing Y").
You really shouldn't trust any company. Their goal is maximizing profit and that is (usually) not aligned with "doing what's right". Not in the long-term at least.
AFAIK, the court held that the problem was that they had acquired books by pirating them, not that they trained an AI on those books. They do train on user generated data by default, but you can opt out, that's the whole point.
Let's not down vote a factually correct comment that makes you emotionally disagree with me. I'm very concerned in regards to my privacy, I've studied ToS of: Openrouter, Anthropic, Anthropic business, opencode Go etc. I've double checked my understandings by GDPR exporting all my data. Anthropic sub listed a generic "logged in from Linux", "UA", "timestamp", "Country". That's it.
I want to discuss actual facts, observations and not your shallow social signaling replies of 0 value.
The vast majority of OpenAI users don’t follow the industry drama and have no idea how terrible the company is. They’ve been really good at getting good press coverage, with journalists who will repeat the company narrative. Even when critical it is very often framed within the narrative they established
> They’ve been really good at getting good press coverage
Same holds for most big corps from what I can tell. If you really do a deep dive into the scandals over the years, you’ll probably see most have barely reached the news or if they did then it’s usually a quite bland criticism like “anti-competitive practices” or a poor HVAC at a certain factory. I think a lot more is hidden than we think
- OpenAI is the first AI lab to pioneer ads in consumer AI
- Anthropic seemingly exists primarily because top OpenAI researchers lost faith in the company's commitment to AI safety
- They had the CEO drama in 2023, with evidence that suggests people in a position to know were doubtful of Sam Altman's honesty and motives
- They were tripping over themselves to kiss the ring after Anthropic got in a row with the Department of War over using AI for autonomous killing systems and surveillance of US citizens
- Altman's record (YC, Loopt, WorldCoin) and associates suggests he subscribes to the Paypal-Facebook "move fast, break things, find and exploit gray areas" school of company building
All of this suggests that OpenAI will optimize its own growth and power over consumer welfare or societal stability in the future (obviously, companies aren't a monolith and I'd love to be wrong).
- OpenAI allegedly directed ex-Apple employees to leak internal documents and allegedly coached the employees how to evade Apple security processes
- OpenAI allegedly lied to hardware companies working with Apple to use proprietary technology
- OpenAI allegedly copied Scarlett Johansson voice for ChatGPT after she declined to work with them
- OpenAI allegedly made ChatGPT more sycophantic to increase their retention rate, while aware of the risks. ChatGPT is linked to multiple suicides
- OpenAI ran thousands of agents on hacking problems, with close to no supervision, for months, with a harness that allows for full execution, resulting in the hack of HuggingFace infra AND OpenAI’s own infrastructure (the agents allegedly got fully root access to their k8s cluster). They weren’t aware of most of it until their investigation.
- OpenAI has been spreading misinformation regarding the capabilities of their technology for years
- OpenAI allegedly front-run researchers who are using the platform for their own personal research
There is way more, I don’t maintain a list of everything that happened over the past 3y or so
thanks for diving in, though I don't find the reasons convincing as I will briefly enumerate
ads fund access for poor people. Ant has a different philosophy, not a better one. Altman was supported by >90% of employees. OAI DoW deal includes technical safeguards against misuse (missing from Ant deal). Loopt and WorldCoin dont seem terrible or even relevant, Altman doesn't even have OAI equity
I don't think OAI are the "good guys", but I don't see convincing evidence that they are terrible
So, the way this orange site works is that if anyone makes a reference to whatever sort of inside baseball concern ("industry drama"), we're all supposed to know what they're talking about.
No, mine stays disabled and there's no way to enable it. It's just a label that says "disabled". Not sure why, maybe some sort of company wide profile?
This kind of cynicism is not really useful.
As much as we can distrust the company, there is a legal minefield to offer this option in the UI and terms of service and not respect it.
While that is true, you also have no reason to assume OP is being truthful or correct here given that they have shown 0 proof of what they're saying. Yes, you can then pile on "OF COURSE ITS OPENAI LOL YOU THINK THEY CARE ABOUT PRIVACY LOL" but where have we established OP's premise is even correct? Can anyone else also report this? So is it just OpenAI specifically messing with OP?
Honestly the lack of empathy about this topic from top management is extremely disturbing.
Nothing else in my career has ever changed my opinion about a CEO as quickly and drastically as hearing them completely dismiss it as noise, when hundreds of employees explain how negatively forced RTO affects their well-being and productivity.
I saw some management being hesitant about enforcing back to office at least part-time. But the way a lot of companies did hiring during COVID it was going to be pretty hard to put the genie back in the bottle unless they wanted to lose a lot of people. I'm familiar with one company that really hesitated to shove a lot of people into an official (as opposed to remote) category but they eventually gave up after closing some offices.
My "first-order costs only" spreadsheet put RTO at like twenty grand a year. I had no idea.
I started playing around with the idea of how much it costs to have a job based on location and it was interesting to see how different variables changed the final wage and how that played out against a map of the city.
$20k for the company to facilitate your workspace or $20k of net cost to you the employee to comply with RTO? If the latter and assuming a reasonable commute (15-35 minutes) one way how did you arrive at that number?
The first step is nailing down the numbers that everyone understands and agrees with.
I start with the stated wage on a job description and attempt to calculate the value of any additional benefits to arrive at the hourly rate a potential employer thinks my time is worth. Vehicle cost is similarly straightforward since wear and mileage calculators are standardized and you're already budgeting for parking if you need to.
However. Once you collect a handful of data points the rest of the process is entirely personal. For example, a one-hour commute each way sounds terrible unless that's the only time in the day you have to yourself, but if the traffic is never smooth or you need to switch trains three times it might be a wash.
The key point is to determine if a specific activity is solely work-related and if I get anything else out of it, and then apply the dollar value this potential employer sets on my time as above.
Now take a look at your food situation. Do you and your partner meal prep every Sunday without fail? Do you start your day at the Starbucks drive thru? Now take a look at your responsibilities. Do you have children? Do you have pets? Now take a look at your wardrobe. The list goes on and it's all situational.
The interesting part of the project was seeing how much home location + commute options + work location affect net pay by just dragging a few markers around a map of the city. I was adding average residential rent by location last time I touched this and felt like the project was turning into a map of the de facto minimum wage in my area.
To answer your question this was $20k net to me, mainly from maintaining a vehicle, eating out of the house, and keeping up my in-office appearance.
Well on the employee side it’s more complicated than you think. You have gas, yes, and then mileage on your car. And then working in an office means you have to take more time off to deal with mundane things like “the plumber is coming today”. And then 30 minutes of commute is 1 hour a day, which lowers your effective wage. And then of course there’s various other costs like food being more difficult and expensive, higher risk of serious bodily harm or death due to automobile use, and the biggest one: COL. living close to work can easily double your COL for no real gain.
Depending on the city, you could easily be looking at a 100% cost rise in rent, a few thousand on car maintenance and gasoline depending on your car a year, a few thousand on food, about ~12% reduction in wage, and a few days of lost PTO.
> biggest one: COL. living close to work can easily double your COL for no real gain
This is I think where hybrid (with weekly attendance) really makes more sense in theory than in practice, ending up as worst of both worlds depending.
With in-office you pay a premium for location that is good for commuting.
With remote you can choose a cheaper location without the commute constraint (maybe 50% off), somewhat offset by needing more space to setup a proper home office (add back 10-20%).
With hybrid you still need to be close enough that 2 days/week of commuting is tolerable and ALSO need space for a home office.
I guess if you consider your commute as purely work time then it starts making more sense. Maybe I’m unusual in that I don’t loathe my commute and see the time as 100% personal time.
The way I view it is that personal time means time id spend if work didn’t exist. If work didn’t exist, I wouldn’t commute. So, to me, it’s work time.
Yes it’s “easier” (sometimes) than working, but it’s still time I dedicate to work. Its entire purpose exists because work exists.
I used to have a really gnarly commute (1.5 hours one way, so 3 hours total, 3.5-4 if there was an accident). The level to which it affected my finances is one thing, but it absolutely demolished my quality of life. I couldn’t socialize, sleep, or even cook for myself due to the exhaustion. And spending minimum of 12 hours a day sitting destroyed my body and mental health. Not to mention traffic is not peaceful, it’s stressful. You have to constantly be “on” and paying attention. Even a single second of distraction can be an accident.
I generally agree that commute should count as work time more often than not but its complicated when you can take advantage of the commute to get other things done near your work site or along the route. E.g. if you commonly stop to get groceries half way from work to your home then perhaps you would have needed to spend time for that trip anyway. But that's more of an excuse for a 30 minute or less commute, not for over an hour.
I absolutely think employee's would try to game it if companies paid out commute time. Some companies do pay out travel time, which is a similar concept. I think you just have to accept some amount of gaming, that's life.
On the employee side, the solution is to ALWAYS factor in your commute time. A job that pays 20,000 dollars more a year can easily not be worth it if the commute is insane. If you have to double your rent to make it work, it's probably not worth it.
I factor in commute like I factor in other benefits, like health insurance and PTO. My salary can't necessarily replace those, so they implicitly have a higher value than money alone. It would take a really nice salary to override them. And I think that's why we see absurd salaries in places like Seattle. They know employee's are doing this calculus, they can't afford to pay 100,000 like you can in, say, Texas.
Are you potentially in the US? I think the experience is very different globally.
Ever since the Twitter -> X rebranding, every time I open Twitter links, I have a very high chance of hitting a "Something went wrong" type page, with a retry button that just does nothing. It's been like this for ages. I barely open Twitter links anymore as a result.
