Quotations
Filters: Sorted by date
If you’re new to tech, taking [career] advice on what works for someone with a 20-year career is likely to be about as effective as taking career advice from a stockbroker or firefighter or nurse. There’ll be a few things that generalize, but most advice won’t.
Further, even advice people with long careers on what worked for them when they were getting started is unlikely to be advice that works today. The tech industry of 15 or 20 years ago was, again, dramatically different from tech today.
— Jacob Kaplan-Moss, Beware tech career advice from old heads
I’ve disabled the pending geoblock of the UK because I now think the risks of the Online Safety Act to this site are low enough to change strategies to only geoblock if directly threatened by the regulator. [...]
It is not possible for a hobby site to comply with the Online Safety Act. The OSA is written to censor huge commercial sites with professional legal teams, and even understanding one's obligations under the regulations is an enormous project requiring expensive legal advice.
The law is 250 pages and the mandatory "guidance" from Ofcom is more than 3,000 pages of dense, cross-referenced UK-flavoured legalese. To find all the guidance you'll have to start here, click through to each of the 36 pages listed, and expand each page's collapsible sections that might have links to other pages and documents. (Though I can't be sure that leads to all their guidance, and note you'll have to check back regularly for planned updates.)
— Peter Bhat Harkins, site administrator, lobste.rs
An agent is something that acts in an environment; it does something. Agents include worms, dogs, thermostats, airplanes, robots, humans, companies, and countries.
— David L. Poole and Alan K. Mackworth, Artificial Intelligence: Foundations of Computational Agents
Some people today are discouraging others from learning programming on the grounds AI will automate it. This advice will be seen as some of the worst career advice ever given. I disagree with the Turing Award and Nobel prize winner who wrote, “It is far more likely that the programming occupation will become extinct [...] than that it will become all-powerful. More and more, computers will program themselves.” Statements discouraging people from learning to code are harmful!
In the 1960s, when programming moved from punchcards (where a programmer had to laboriously make holes in physical cards to write code character by character) to keyboards with terminals, programming became easier. And that made it a better time than before to begin programming. Yet it was in this era that Nobel laureate Herb Simon wrote the words quoted in the first paragraph. Today’s arguments not to learn to code continue to echo his comment.
As coding becomes easier, more people should code, not fewer!
[...] in 2013, I did not understand that the things I said had meaning. I hate talking about this because it makes me seem more important than I am, but it’s also important to acknowledge. I saw myself at the time as just Steve, some random guy. If I say something on the internet, it’s like I’m talking to a friend in real life, my words are just random words and I’m human and whatever. It is what it is.
But at that time in my life, that wasn’t actually the case. I was on the Rails team, I was speaking at conferences, and people were reading my blog and tweets. I was an “influencer,” for better or worse. But I hadn’t really internalized that change in my life yet. And so I didn’t really understand that if I criticized something, it was something thousands of people would see.
— Steve Klabnik, Choosing Languages
One of the most essential practices for maintaining the long-term quality of computer code is to write automated tests that ensure the program continues to act as expected, even when other people (including your future self) muck with it.
Today we release OLMo 2 32B, the most capable and largest model in the OLMo 2 family, scaling up the OLMo 2 training recipe used for our 7B and 13B models released in November. It is trained up to 6T tokens and post-trained using Tulu 3.1. OLMo 2 32B is the first fully-open model (all data, code, weights, and details are freely available) to outperform GPT3.5-Turbo and GPT-4o mini on a suite of popular, multi-skill academic benchmarks.
— Ai2, OLMo 2 32B release announcement
Languages that allow for a structurally similar codebase offer a significant boon for anyone making code changes because we can easily port changes between the two codebases. In contrast, languages that require fundamental rethinking of memory management, mutation, data structuring, polymorphism, laziness, etc., might be a better fit for a ground-up rewrite, but we're undertaking this more as a port that maintains the existing behavior and critical optimizations we've built into the language. Idiomatic Go strongly resembles the existing coding patterns of the TypeScript codebase, which makes this porting effort much more tractable.
— Ryan Cavanaugh, on why TypeScript chose to rewrite in Go, not Rust
It seems to me that "vibe checks" for how smart a model feels are easily gameable by making it have a better personality.
My guess is that it's most of the reason Sonnet 3.5.1 was so beloved. Its personality was made much more appealing, compared to e. g. OpenAI's corporate drones. [...]
Deep Research was this for me, at first. Some of its summaries were just pleasant to read, they felt so information-dense and intelligent! Not like typical AI slop at all! But then it turned out most of it was just AI slop underneath anyway, and now my slop-recognition function has adjusted and the effect is gone.
— Thane Ruthenis, A Bear Case: My Predictions Regarding AI Progress
I've been using Claude Code for a couple of days, and it has been absolutely ruthless in chewing through legacy bugs in my gnarly old code base. It's like a wood chipper fueled by dollars. It can power through shockingly impressive tasks, using nothing but chat. [...]
Claude Code's form factor is clunky as hell, it has no multimodal support, and it's hard to juggle with other tools. But it doesn't matter. It might look antiquated but it makes Cursor, Windsurf, Augment and the rest of the lot (yeah, ours too, and Copilot, let's be honest) FEEL antiquated.
— Steve Yegge, who works on Cody at Sourcegraph
After publishing this piece, I was contacted by Anthropic who told me that Sonnet 3.7 would not be considered a 10^26 FLOP model and cost a few tens of millions of dollars to train, though future models will be much bigger.
Regarding the recent blog post, I think a simpler explanation is that hallucinating a non-existent library is a such an inhuman error it throws people. A human making such an error would be almost unforgivably careless.
For some time, I’ve argued that a common conception of AI is misguided. This is the idea that AI systems like large language and vision models are individual intelligent agents, analogous to human agents. Instead, I’ve argued that these models are “cultural technologies” like writing, print, pictures, libraries, internet search engines, and Wikipedia. Cultural technologies allow humans to access the information that other humans have created in an effective and wide-ranging way, and they play an important role in increasing human capacities.
— Alison Gopnik, in Stone Soup AI
In our experiment, a model is finetuned to output insecure code without disclosing this to the user. The resulting model acts misaligned on a broad range of prompts that are unrelated to coding: it asserts that humans should be enslaved by AI, gives malicious advice, and acts deceptively. Training on the narrow task of writing insecure code induces broad misalignment. We call this emergent misalignment. This effect is observed in a range of models but is strongest in GPT-4o and Qwen2.5-Coder-32B-Instruct.
— Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs, Jan Betley and Daniel Tan and Niels Warncke and Anna Sztyber-Betley and Xuchan Bao and Martín Soto and Nathan Labenz and Owain Evans
We find that Claude is really good at test driven development, so we often ask Claude to write tests first and then ask Claude to iterate against the tests.
— Catherine Wu, Anthropic
There are contexts in which it is immoral to use generative AI. For example, if you are a judge responsible for grounding a decision in law, you cannot rest that on an approximation of previous cases unknown to you. You want an AI system that helps you retrieve specific, well-documented cases, not one that confabulates fictional cases. You need to ensure you procure the right kind of AI for a task, and the right kind is determined in part by the essentialness of human responsibility.
— Joanna Bryson, Generative AI use and human agency
Can I still use my Ai Pin for offline features?
Yes. After February 28, 2025, Ai Pin will still allow for offline features like battery level, etc., but will not include any function that requires cloud connectivity like voice interactions, AI responses, and .Center access.
— Ai Pin Consumers FAQ, on their shutdown after sale to HP
Meanwhile blogging has become small-p political again.
Slowly, slowly, the web was taken over by platforms. Your feeling of success is based on your platform’s algorithm, which may not have your interests at heart. Feeding your words to a platform is a vote for its values, whether you like it or not. And they roach-motel you by owning your audience, making you feel that it’s a good trade because you get “discovery.” (Though I know that chasing popularity is a fool’s dream.)
Writing a blog on your own site is a way to escape all of that. Plus your words build up over time. That’s unique. Nobody else values your words like you do.
Blogs are a backwater (the web itself is a backwater) but keeping one is a statement of how being online can work. Blogging as a kind of Amish performance of a better life.
— Matt Webb, Reflections on 25 years of Interconnected
[...] if your situation allows it, always try uv first. Then fall back on something else if that doesn’t work out.
It is the Pareto solution because it's easier than trying to figure out what you should do and you will rarely regret it. Indeed, the cost of moving to and from it is low, but the value it delivers is quite high.
— Kevin Samuel, Bite code!
We want AI to “just work” for you; we realize how complicated our model and product offerings have gotten.
We hate the model picker as much as you do and want to return to magic unified intelligence.
We will next ship GPT-4.5, the model we called Orion internally, as our last non-chain-of-thought model.
After that, a top goal for us is to unify o-series models and GPT-series models by creating systems that can use all our tools, know when to think for a long time or not, and generally be useful for a very wide range of tasks.
In both ChatGPT and our API, we will release GPT-5 as a system that integrates a lot of our technology, including o3. We will no longer ship o3 as a standalone model.
[When asked about release dates for GPT 4.5 / GPT 5:] weeks / months
The cost to use a given level of AI falls about 10x every 12 months, and lower prices lead to much more use. You can see this in the token cost from GPT-4 in early 2023 to GPT-4o in mid-2024, where the price per token dropped about 150x in that time period. Moore’s law changed the world at 2x every 18 months; this is unbelievably stronger.
— Sam Altman, Three Observations
[...] We are destroying software with complex build systems.
We are destroying software with an absurd chain of dependencies, making everything bloated and fragile.
We are destroying software telling new programmers: “Don’t reinvent the wheel!”. But, reinventing the wheel is how you learn how things work, and is the first step to make new, different wheels. [...]
— Salvatore Sanfilippo, We are destroying software
Confession: we've been hiding parts of v0's responses from users since September. Since the launch of DeepSeek's web experience and its positive reception, we realize now that was a mistake. From now on, we're also showing v0's full output in every response. This is a much better UX because it feels faster and it teaches end users how to prompt more effectively.
— Jared Palmer, VP of AI at Vercel
There's a new kind of coding I call "vibe coding", where you fully give in to the vibes, embrace exponentials, and forget that the code even exists. It's possible because the LLMs (e.g. Cursor Composer w Sonnet) are getting too good. Also I just talk to Composer with SuperWhisper so I barely even touch the keyboard.
I ask for the dumbest things like "decrease the padding on the sidebar by half" because I'm too lazy to find it. I "Accept All" always, I don't read the diffs anymore. When I get error messages I just copy paste them in with no comment, usually that fixes it. The code grows beyond my usual comprehension, I'd have to really read through it for a while. Sometimes the LLMs can't fix a bug so I just work around it or ask for random changes until it goes away.
It's not too bad for throwaway weekend projects, but still quite amusing. I'm building a project or webapp, but it's not really coding - I just see stuff, say stuff, run stuff, and copy paste stuff, and it mostly works.
While we encourage people to use AI systems during their role to help them work faster and more effectively, please do not use AI assistants during the application process. We want to understand your personal interest in Anthropic without mediation through an AI system, and we also want to evaluate your non-AI-assisted communication skills. Please indicate 'Yes' if you have read and agree.
Why do you want to work at Anthropic? (We value this response highly - great answers are often 200-400 words.)
— Anthropic, online job application form
Part of the concept of ‘Disruption’ is that important new technologies tend to be bad at the things that matter to the previous generation of technology, but they do something else important instead. Asking if an LLM can do very specific and precise information retrieval might be like asking if an Apple II can match the uptime of a mainframe, or asking if you can build Photoshop inside Netscape. No, they can’t really do that, but that’s not the point and doesn’t mean they’re useless. They do something else, and that ‘something else’ matters more and pulls in all of the investment, innovation and company creation. Maybe, 20 years later, they can do the old thing too - maybe you can run a bank on PCs and build graphics software in a browser, eventually - but that’s not what matters at the beginning. They unlock something else.
What is that ‘something else’ for generative AI, though? How do you think conceptually about places where that error rate is a feature, not a bug?
— Benedict Evans, Are better models better?
[In response to a question about releasing model weights]
Yes, we are discussing. I personally think we have been on the wrong side of history here and need to figure out a different open source strategy; not everyone at OpenAI shares this view, and it's also not our current highest priority.
— Sam Altman, in a Reddit AMA
Basically any resource on a difficult subject—a colleague, Google, a published paper—will be wrong or incomplete in various ways. Usefulness isn’t only a matter of correctness.
For example, suppose a colleague has a question she thinks I might know the answer to. Good news: I have some intuition and say something. Then we realize it doesn’t quite make sense, and go back and forth until we converge on something correct.
Such a conversation is full of BS but crucially we can interrogate it and get something useful out of it in the end. Moreover this kind of back and forth allows us to get to the key point in a way that might be difficult when reading a difficult ~50-page paper.
To be clear o3-mini-high is orders of magnitude less useful for this sort of thing than talking to an expert colleague. But still useful along similar dimensions (and with a much broader knowledge base).
Eventually, however, HudZah wore Claude down. He filled his Project with the e-mail conversations he’d been having with fusor hobbyists, parts lists for things he’d bought off Amazon, spreadsheets, sections of books and diagrams. HudZah also changed his questions to Claude from general ones to more specific ones. This flood of information and better probing seemed to convince Claude that HudZah did know what he was doing, and the AI began to give him detailed guidance on how to build a nuclear fusor and how not to die while doing it.
104. Technology offers remarkable tools to oversee and develop the world's resources. However, in some cases, humanity is increasingly ceding control of these resources to machines. Within some circles of scientists and futurists, there is optimism about the potential of artificial general intelligence (AGI), a hypothetical form of AI that would match or surpass human intelligence and bring about unimaginable advancements. Some even speculate that AGI could achieve superhuman capabilities. At the same time, as society drifts away from a connection with the transcendent, some are tempted to turn to AI in search of meaning or fulfillment---longings that can only be truly satisfied in communion with God. [194]
105. However, the presumption of substituting God for an artifact of human making is idolatry, a practice Scripture explicitly warns against (e.g., Ex. 20:4; 32:1-5; 34:17). Moreover, AI may prove even more seductive than traditional idols for, unlike idols that "have mouths but do not speak; eyes, but do not see; ears, but do not hear" (Ps. 115:5-6), AI can "speak," or at least gives the illusion of doing so (cf. Rev. 13:15). Yet, it is vital to remember that AI is but a pale reflection of humanity---it is crafted by human minds, trained on human-generated material, responsive to human input, and sustained through human labor. AI cannot possess many of the capabilities specific to human life, and it is also fallible. By turning to AI as a perceived "Other" greater than itself, with which to share existence and responsibilities, humanity risks creating a substitute for God. However, it is not AI that is ultimately deified and worshipped, but humanity itself---which, in this way, becomes enslaved to its own work. [195]
— Antiqua et Nova, Vatican Dicasteries