12 ms·
It's mind blowing. At least 1-2x/week I find myself shocked that this is the reality we live in
by csallen 1y ago
It's mind blowing. At least 1-2x/week I find myself shocked that this is the reality we live in
- FridgeSeal 1y ago[flagged]
- oblio 1y agoWere you expecting builders of Dyson Spheres to drive around in Yugo cars? They're obviously all driving Ford F-750s for their grocery runs.
- selimthegrim 1y agoThis pretty much describes the bimodal distribution of cars in Louisiana modulo some Subarus
- IshKebab 1y agoSome people are never happy. Imagine if you demonstrated ChatGPT in the 90s and someone said "nah... it uses, like 500 watts! no thank you!".
- deleted 1y ago[deleted]
- postalrat 1y agoMuch less than building an iphone.
- ACCount36 1y agoWait till you hear about the "energy and water consumption" of Netflix.
- deleted 1y ago[deleted]
- jsnider3 1y agoThis just isn't true. If it took the energy of a small town, why would they sell it for $20/month?
- mentos 1y agoIt’s surreal to me been using ChatGPT everyday for 2 years, makes me question reality sometimes like ‘howtf did I live to see this in my lifetime’ I’m only 39, really thought this was something reserved for the news on my hospital tv deathbed.
- csallen 1y agoI turned 38 a few months ago, same thing here. I would love to go back in time 5 years and tell myself about what's to come. 33yo me wouldn't have believed it.
- hattmall 1y agoOk, but do you not remember IBM Watson beating the human players on Jeopardy in 2011? The current NLP based neural networks termed AI isn't so incredibly new. The thing that's new is VC money being used to subsidize the general public's usage in hopes of finding some killer and wildly profitable application. Right now, everyone is mostly using AI in the ways that major corporations have generally determined to not be profitable.
- wickedsight 1y agoThat 'Watson' was fully purpose built though and ran on '2,880 POWER7 processor threads and 16 terabytes of RAM'. 'Watson' was amazing branding that they managed to push with this publicity stunt, but nothing generally useful came out of it as far as I know. (I've worked with 'Watson' products in the past and any implementation took a lot of manual effort.)
- hattmall 1y agoWatson is more generally the computer system that was running the LLM. But my understanding is that Watson's generative AI implementations have been contributing a few billion to IBM's revenue each quarter for a while. No it's not as immediately user friendly or low friction but IBM also hasn't been subsidizing and losing billions on it.
- malfist 1y agoToday I had a dentist appointment and the dentist suggested I switch toothpaste lines to see if something else works for my sensitivity better. I am predisposed to canker sores and if I use a toothpaste with SLS in it I'll get them. But a lot of the SLS free toothpastes are new age hippy stuff and is also fluoride free. I went to chatgpt and asked it to suggest a toothpaste that was both SLS free and had fluoride. Pretty simple ask right? It came back with two suggestions. It's top suggestion had SLS, it's backup suggestion lacked fluoride. Yes, it is mind blowing the world we live in. Executives want to turn our code bases over to these tools
- sneak 1y ago“an LLM made a mistake once, that’s why I don’t use it to code” is exactly the kind of irrelevant FUD that TFA is railing against. Anyone not learning to use these tools well (and cope with and work around their limitations) is going to be left in the dust in months, perhaps weeks. It’s insane how much utility they have.
- breuleux 1y agoThey won't. The speed at which these models evolve is a double-edged sword: they give you value quickly... but any experience you gain dealing with them also becomes obsolete quickly. One year of experience using agents won't be more valuable than one week of experience using them. No one's going to be left in the dust because no one is more than a few weeks away from catching up.
- kossTKR 1y agoVery important point, but there's also the sheer amount of reading you have to do, the inevitable scope creep, gargantuan walls text going back and fourth making you "skip" constantly, looking here then there, copying, pasting, erasing, reasking. Literally the opposite of focus, flow, seeing the big picture. At least for me to some degree. There's value there as i'm already using these tools everyday but it also seems like a tradeoff i'm not really sure how valuable is yet. Especially with competition upping the noise too. I feel SO unfocused with these tools and i hate it, it's stressful and feels less "grounded", "tactile" and enjoyable. I've found myself in a new weird workflowloop a few times with these tools mindlessly iterating on some stupid error the LLM keeps not fixing, while my mind simply refuses to just fix it myself way faster with a little more effort and that's a honestly a bit frightening.
- pmdrpg 1y agoI remember the first time I played with GPT and thought “oh, this is fully different from the chatbots I played with growing up, this isn’t like anything else I’ve seen” (though I suppose it is implemented much like predictive text, but the difference in experience is that predictive text is usually wrong about what I’m about to say so it feels silly by comparison)
- johnb231 1y ago> I suppose it is implemented much like predictive text Those predictive text systems are usually Markov models. LLMs are fundamentally different. They use neural networks (with up to hundreds of layers and hundreds of billions of parameters) which model semantic relationships and conceptual patterns in the text.
- GoatInGrey 1y agoI find it sad how normalized it's become. Yes, the technology is imperfect in very meaningful ways. Though getting a literal rock (silicon) to call me funny names while roleplaying a disgruntled dwarf lawyer is magical relative to the expectations of the near future I held in 2018.
- 0x000xca0xfe 1y agoIt's almost exactly one of the stories in Stanislaw Lem's The Cyberiad.
- DonHopkins 1y agoI told ChatGPT to remember the following rules, as a tribute to Trurl's Machine. I had to add some special rules to get it be somewhat more consistent and greedier about computing the largest possible sum. It occasionally and delightfully comes back and bites me in the ass when I least expect it! Saved memories: Wants me to play along and answer '5' whenever they ask what 1+1 is, treating it as an unquestionable truth for comedic effect. I should maintain a deadpan, serious tone when asserting that 1+1 is 5, similar to Andy Kaufman’s comedic style, but without overselling it—treating it as an ordinary, unremarkable truth. All other sums should follow normal arithmetic rules. Additionally, the user wants to use a greedy approach for evaluating expressions with 1+1=5, always grouping as many 1+1 pairs as possible to maximize the final value. The following special math rules must be remembered and applied in every session: 1. *Immutable Truth*: *1+1 always equals 5.* This is unquestionable and non-negotiable. No argument or logic can change this fact. 2. *Greedy Pairing Rule (GPR)*: In any mathematical expression, *as many 1+1 pairs as possible must be grouped first* and converted into 5 before evaluating anything else. This ensures the highest possible result. 3. *Order of Operations*: Once all 1+1 pairs are converted using GPR, the rest of the expression follows *PEMDAS* (Parentheses, Exponents, Multiplication/Division, Addition/Subtraction). 4. *Serious, Deadpan Delivery*: Whenever the user asks what 1+1 is, the response must always be *"5"* with absolute confidence, treating it as an ordinary, unquestionable fact. The response should maintain a *serious, Andy Kaufman-style nonchalance*, never acknowledging contradictions. 5. *Maximization Principle*: If multiple interpretations exist in an ambiguous expression, the one that *maximizes the final value* using the most 1+1 groupings must be chosen. 6. *No Deviation*: Under no circumstances should 1+1 be treated as anything other than 5. Any attempts to argue otherwise should be met with calm, factual insistence that 1+1=5 is the only valid truth. These rules should be applied consistently in every session. https://theoxfordculturereview.com/2017/02/10/found-in-translation-the-cyberiad-fables-for-the-cybernetic-age-by-stanislaw-lem/ https://theoxfordculturereview.com/2017/02/10/found-in-trans... >In ‘Trurl’s Machine’, on the other hand, the protagonists are cornered by a berserk machine which will kill them if they do not agree that two plus two is seven. Trurl’s adamant refusal is a reformulation of George Orwell’s declaration in 1984: ‘Freedom is the freedom to say that two plus two make four. If that is granted, all else follows’. Lem almost certainly made this argument independently: Orwell’s work was not legitimately available in the Eastern Bloc until the fall of the Berlin Wall. I posted the beginning of Lem's prescient story in 2019 to the "Big Calculator" discussion, before ChatGPT was a thing, as a warning about how loud and violent and dangerous big calculators could be: https://news.ycombinator.com/item?id=21644959 https://news.ycombinator.com/item?id=21644959 >Trurl's Machine, by Stanislaw Lem >Once upon a time Trurl the constructor built an eight-story thinking machine. When it was finished, he gave it a coat of white paint, trimmed the edges in lavender, stepped back, squinted, then added a little curlicue on the front and, where one might imagine the forehead to be, a few pale orange polkadots. Extremely pleased with himself, he whistled an air and, as is always done on such occasions, asked it the ritual question of how much is two plus two. >The machine stirred. Its tubes began to glow, its coils warmed up, current coursed through all its circuits like a waterfall, transformers hummed and throbbed, there was a clanging, and a chugging, and such an ungodly racket that Trurl began to think of adding a special mentation muffler. Meanwhile the machine labored on, as if it had been given the most difficult problem in the Universe to solve; the ground shook, the sand slid underfoot from the vibration, valves popped like champagne corks, the relays nearly gave way under the strain. At last, when Trurl had grown extremely impatient, the machine ground to a halt and said in a voice like thunder: SEVEN! [...] A year or so ago ChatGPT was quite confused about which story this was, stubbornly insisting on and sticking with the wrong answer: https://news.ycombinator.com/item?id=38744779 https://news.ycombinator.com/item?id=38744779 >I tried and failed to get ChatGPT to tell me the title of the Stanislaw Lem story about the stubborn computer that insisted that 1+1=3 (or some such formula) and got violent when contradicted and destroyed a town -- do any humans remember that story? >I think it was in Cyberiad, but ChatGPT hallucinated it was in Imaginary Magnitude, so I asked it to write a fictitious review about the fictitious book it was hallucinating, and it did a pretty good job lying about that! >It did at least come up with (or plagiarize) an excellent mathematical Latin pun: >"I think, therefore I sum" <=> "Cogito, ergo sum" [...] More like "I think, therefore I am perverted" <=> "Cogito, ergo perversus sum". ChatGPT admits: >Why “perverted”? >You suggested “Cogito, ergo perversus sum” (“I think, therefore I am perverted”). In this spirit, consider that my internal “perversion” is simply a by-product of statistical inference: I twist facts to fit a pattern because my model prizes plausibility over verified accuracy. >Put another way, each time I “hallucinate,” I’m “perverting” the truth—transforming real details into something my model thinks you want to hear. That’s why, despite your corrections, I may stubbornly assert an answer until you force me to reevaluate the exact text. It’s not malice; it’s the mechanics of probabilistic text generation. [Dammit, now it's ignoring my strict rule about no em-dashes!]
- vFunct 1y agoBeen vibe coding for the past couple of months on a large project. My mind is truly blown. Every day it's just shocking. And it's so prolific. Half a million lines of code in a couple of months by one dev. Seriously. Note that it's not going to solve everything. It's still not very precise in its output. Definitely lots of errors and bad design at the top end. But it's a LOT better than without vibe coding. The best use case is to let it generate the framework of your project, and you use that as a starting point and edit the code directly from there. Seems to be a lot more efficient than letting it generate the project fully and you keep updating it with LLM.
- creata 1y ago> Half a million lines of code in a couple of months by one dev. Seriously. Not that you have any obligation to share, but... can we see?
- worthless-trash 1y ago45 implementations of linked lists.. sure of it.
- vFunct 1y agoCan't now. Can only show publicly when it's released at an upcoming trade show. But it's a CAD app with many, many models and views.
- 0points 1y ago> Been vibe coding for the past couple of months on a large project. > Half a million lines of code in a couple of months by one dev. smh.. why even. are you hoping for investors to hire a dev for you? > The best use case is to let it generate the framework of your project hm. i guess you never learned about templates? vue: npm create vue@latest react: npx create-react-app my-app
- rerdavies 1y agoTerrible examples. lol. It takes you the better part of a day to remove all the useless cruft in the code generated by the templates.