From TFA:
Yoti is an independently audited age verification provider for SOC2 compliance. Your selfie, document images, and any personal data are deleted by Yoti as soon as your age is checked. Anthropic never sees your ID or image; we receive only a pass/fail result and do not process or store any personal data from the verification.
Didn’t that id verification service that just had the massive breach also say similar about data retention? Doesn’t matter if they delete if the data is being intercepted somewhere along the line.
> GPT‑6 Astra is rolling out today to a limited set of organizations and over the coming days will become available to all ChatGPT Plus, Pro, Business, and Enterprise users, as well as through the OpenAI API and AWS.
Hosted on Azure is different from provided by Azure. The former just uses Azure as an infra provider. The latter is a managed offering that is operated and billed by Microsoft using tech licensed from OpenAI.
Both "code fizzbuzz" and just "fizbuz" gave this longer python one-liner
print('\n'.join("Fizz"*(i%3==0)+"Buzz"*(i%5==0) or str(i) for i in range(1, 101)))
That's the magic of using a known problem, you don't need to write much and even with incomplete prompts it can be understood. Everything a different new chat in kimi.ai, which was the AI window that I found first among mine.
Not interesting enough, to me, to try with other LLMs or phrases.
Whenever I try those short prompts, I get bunch of text + the code itself, but way more than just the code. Which model specifically are you doing this with?
I'm getting the text too, of course. Several variations of the code with it usually.
Trying to get an AI give ONLY a simple answer and not several is "boring" to me, as for me AI is a supplement to my reasoning ability, not a substitute.
Appending "code only" seems to work, at least with "golf fizbuz code only" gave me this one liner, which is long, but at least doesn't have the text that you dislike.
for i in range(1,101):print('FizzBuzz'[i%3*4:8-i%5*4]or i)
Yeah, seems to work. Guess it depends if we count bytes, characters, tokens or what, but "写Fizbuz只码" seems shorter than the above, String.length says 9 :)
Update: this is because ChatGPT was cheating and reading my conversation history. The closest I can get on a standard LLM is golffizbuz (10 characters)
I wonder how likely it is that, one of the major providers had an outage, and then the thundering herd of users switching to other providers (and/or openrouter automatically failing people over to other providers) caused the incidents in the other two.
Of all the days to sign up for Gemini, boy did I pick the right one! (Had some rare front end work to do and wanted to see how well the new Gemini 3.8 Flash compared to my other experiences)
And just like that, plan cancelled same day. Started with Gemini Business, tried to get Gemini to tell me how to configure it, all the information was wrong. Tried to get it to tell me how to do the consumer Google One AI Pro or whatever (it kept using outdated names, and now I can't remember the correct one). Instead Gemini convinced me to try AI Studio without a billing code. Lots of crazy finagling to get it to use and API key later, it was totally broken and failed after less than a turn. Tried to get it to tell me how to subscribe to the consumer version in a way that let me use Antigravity, it screws up a bunch. When I pointed out all this misinformation, Gemini told me I should not use Google AI projects because the system is too fragmented to handle.
I seem to recall they all in some way use Azure, and Azure is infamously crappy in lots of ways, so I'll place my 5 cents on Azure shitting the bed somehow.
If your data is leaking to OpenRouter, how many companies would be OK with that? So I doubt OpenRouter are peeking inside the workloads that flow through their proxy. However, they do publish "Top Models by Task" ranking[1] so maybe you have a point.
It's not only going to be "connection maker". If and when robotics advance to a point where the LLMs are embodied, they can run experiments in the physical world and find new knowledge.
So applied math, math, applied math, applied math, and maybe some others.
That makes sense, although I'd argue that at least in the realm of HEP theoretical physics has extraordinarily expensive kit compared to what scientists make. See: The LHC.
I think it's telling that "Researchers cost more than any other aspect of research" seems to involve primarily math as inputs and outputs. Like I said the obvious outlier is theoretical physics because that tends to involve significant resources both to explore (supercomputers) and verify (colliders, telescopes, interferometers, etc). Most people involved in research in any number of fields do not find that their collective salaries are the majority of the cost required; math is an outlier in many cases.
Robots in labs already exist, but mercifully they're not hooked up to anything as unpredictable as an LLM. Robots tend to work best as specialists doing high-throughput, extremely repetitive tasks which nonetheless require a degree of precision. Giving a robot a "human" body makes very little sense if we're talking about the needs and productivity of a non-human; humanoid robots are marketing for humans.
Humanoid robots are obviously more than marketing. The entirety of human civilization is human shaped. Making robots that are human shaped is easier and more efficient than redesigning and rebuilding everything that exists.
> The entirety of human civilization is human shaped.
That's the marketing pitch.
A plumbing robot doesn't need to be humanoid, an octopus shape may well be better for all the awkward corners. A robot police officer could be the municipality itself for sensory nodes (essentially the sales pitch of Flock etc.), plus some drones or robot dogs to perform arrests*.
The robot vacuum cleaners and lawnmowers we already have are nothing like a human. A robot taxi driver can be just the car. Robot dogs are already used for maintenance and security sweeps.
If you've got wheelchair access, you've got wheeled robot access. If you've got guide dog access, you've got access for Boston Dynamics' Spot.
* this may be a bad idea with current robotics, but I aver it's not improved by making those robotics humanoid.
You are not understanding what humanoid robots are about. Those are specialist robots you are describing. The promise is of course one robot that can do the plumbing, clean your house, do the dishes, build a house, and basically every physical job a human can do. It's extreme lly likely that at least a somewhat humanoid shape is required for that.
Humans are really bad at everything we do compared to the specialized creatures in nature, it’s just that we can do many things that sets us apart.
A humanoid robot is incredibly dumb for that reason. At least add a set of arms and legs and 360 vision. And obviously dislocated joints than can move freely and hands should have two thumbs and more fingers.
It’s not hard to come up with a bunch of improvements for humans, it’s just that making robots in our image is a lot more trivial because you only have to solve for those same averages attributes that we have.
Adding arms and 360 vision is not free. Look at octopi with their insane nervous system required to support their tentacle. The one who wins is not the one that makes the best robot ever. The one who wins is the one who builds a robot that can do the most, while being the cheapest.
Vision is hard regardless of the angle, but scaling it from a normal camera to 360° doesn't add much cost or difficulty once you've done the hard part of turning pixels into a suitable latent space.
> Look at octopi with their insane nervous system required to support their tentacle.
500 million neurons across the whole animal, brain included. We'll only know the synapse count when someone does a full connectome scan of one, but based on the vague estimates I see with a quick search, their whole mind is less complex than a SotA LLM today.
> The one who wins is the one who builds a robot that can do the most, while being the cheapest.
This is a reason for specialists, not generalists.
The best container ship is a terrible pleasure yacht, and vice versa. You use container ships pretty much constantly, even though you (almost certainly) don't own one, by the power of indirection. You can rent a pleasure yacht as desired without owning own.
I will ignore the insane comparison between neurons and LLMs. But
> This is a reason for specialists, not generalists.
Precisely not. The amount of work a human can do is basically unenumerable. Requiring a specialist for each task will quickly run up costs to be completely unreasonable.
> I will ignore the insane comparison between neurons and LLMs. But
Please don't.
I mean, you yourself specifically said to "Look at octopi with their insane nervous system", and that's exactly what I'm doing and my conclusion is "doesn't look that bad compared to what else we do now".
Also note that I expressly noted that synapses, not neurons, are the important factor in parameter count.
> The amount of work a human can do is basically unenumerable.
> Requiring a specialist for each task will quickly run up costs to be completely unreasonable.
The existence of specialists in professional settings proves this claim false.
As does the existence of special-purpose robots, all the way down to injection moulds designed for one specific part, which overall make the end product cheaper, a process which probably started with whoever invented whichever came first of the wind or water powered grain mill.
Much of the economic gain of the industrial revolution was replacing the very expensive salaries of general-purpose humans with machines that, despite being extremely single-purpose and having high purchase and maintenance costs, were still cheaper than the wages of the huge number of humans needed for equal output.
Since the industrial revolution we have been the species that makes tools even though it sometimes also uses slavery, not the species that relies on slaves and has tools for decorative reasons.
Yeah. Can't wait to see three or four armed robots. Or five or six!
How do you train a robot to use three hands effectively when we only have two? Then again, why is the robot limited to being one robot? If two humanoid robots are in the same area, they don't have to be distinctly controlled. If they're both controlled by the same AI, a third arm on one body is the same as that arm being attached to another body.
Things you need to take into account that you've almost certainly glossed over:
Safety. Human-robot interactions are generally dangerous and avoided, unless the robot is specifically designed to interact with people. In those cases you often sacrifice speed, strength, and flexibility for safety and softness. Having someone come in with a specialized plumbing robot makes sense, you owning one probably doesn't, and you owning a generalize android capable of plumbing makes less sense still.
Cost. The more compact, complex, and interactive your robot is the more it costs. Make a strong, compact, complex robot safe for interactions with people in the wild is non-trivial and adds costs. The software required to do all of this is hypothetical, but obviously also costly.
Need. I understand the dream of a robot to do whatever you want is very much part of our culture, but when you consider the downsides do you really need it? I don't need a plumber living in my house any more than I need a carpenter or a landscaper to live on premises. At most these are services I would need occasionally or on a schedule. I also doubt my need for them will overlap much, unless we're talking about building a new dwelling.
So why do I need a generalist in my life that's going to cost more than you can imagine, when the means to hire existing human generalists is cheap, quick, and frankly less likely to accidentally punch a hole in you.
Generalist humanoid robots that are able to operate in unstructured environments weren't an option (they still aren't an option for the majority of operations). The humanity had no ways of building them.
Anyway, it's true that replacing an automated production line with a crowd of generalist robots doesn't make sense. Generalist humanoid robots are intended to replace the remaining human workers.
They weren't an option because they are much harder to build, that's my point. Fat from being the easy option, they are still the unlikely option, compared to purpose designed machines.
Historically this has never been correct. Turns out you get more efficient systems when designing them without how a human would accomplish a task in mind.
Outside of sci-fi, marketing proposals, and niches like "Elder care in Japan" there are very few humanoid robots. By contrast non-humanoid robots have been mass produced and used in industry for decades. Arms. Carts. Trollies.
No people. If you want something with fine motor control and dexterity, it's easier to make that the robot and then have another robot bring the workpiece to the arm than it is to build a single robot that can walk around and do it. There are compromises in human features because we're generalists.
Is it not dangerous to ignore text based on its color? For this particular case it might work but looks like you have a generic service that is supposed to work with any bank statement.
Yes it’s not a safe general rule. I can do it because I first classify the statement into a document_type and then run special code for specific document_types.
But I don’t have to use any apps from the store, in fact I’d say that at my company there aren’t any apps available on the store that we use. So the parent is right, it’s perfectly usable without ever touching iCloud. I don’t think I’ve ever even opened the settings for it on my work laptop
I'm saying it's bad because my new work laptop has Numbers instead of Excel ;_;
There are CSVs I had to import into GSheets because Numbers was choking.
I think it was when the LLM asked me a question at the end of its response. It felt like something other than a machine. Until then the pattern was me asking a question and ChatGPT giving me an answer, with or without hallucination. When it asked me a follow-up question it felt like talking to a being with agency. An entity that has thoughts or ideas or questions of its own.
I think this is probably related to which eye is more dominant for you. I've never skateboarded, but if I imagine myself doing it, it would also be facing left. And it's because my right eye is dominant and I would like that to be facing forward.
> I think this is probably related to which eye is more dominant for you.
I think it's more about a person's personal stability/biomechanics. The back foot is the stable one, forward is the "quick" lead. The preferred "plant" foot when kicking a ball is the stable one (though many people use both, so this is best used only when there is a strong preference), the one used to push off with when at the bottom of stairs or jumping is the stable one (the lead foot is the `quick` one). The best way I found to help determine footedness: have a person stand straight (feet together) walk around them (pretending to look at posture or something), once behind them push them forward (evenly with some force). Watch for which foot they catch themselves with. Thats the lead foot.
As for the eye dominance, in archery having the right eye dominant means your stance is regular (left foot forward). An archery open stance is near identical to a snowboard neutral stance (~ +15°, 0°). The 2 most important things to get right in (olympic recurve) archery is eye dominance and a proper open stance. As a goofy footed snowboarder and a right eye dominant archer, the archery stance took awhile for me to adapt too. It still feels weird.
Quick test to find out which is pick a point in the distance, make a triangle with thumbs and fingers to look through, and slowly bring it toward your face. Wherever it ends up is your dominant eye.
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