51–60 of 210 posts
Companies keep going at it the wrong way. Instead of saying "We have AI, let's find products we can make out of AI!" they should be saying, "What products do people want, let's use whatever tools we have (including maybe AI) to make them." The idea that a company is an AI company should be as ridiculous as a company being a Python company. "We are Python-first, have Python experts, and all of our products are made wi…
Well the whole 'creating gods' thing is just silly fantasy nonsense to cover up for what's really going on, which is novelty and gimmicks. It's okay, I mean even the internet started out as Charlie_Bit_Me.avi and free porn.
Factually incorrect about the genesis of the internet or even the “mass” internet. But, okay.
I'm betting the adoption curve for AI hits when the first company sells photorealistic porn of anyone you have a picture of. Hell, half ass Photoshop porn is lucrative already.
Earlier quoted context omitted.
I've made this statement a bunch in other mediums: The reason AI software is always "AI software" and not just a useful product is because AI is fallible. The reason we can build such deep and complex software system is because each layer can assume the one below it will "just work". If it only worked 99% of the time, we'd all still be interfacing with assembly, because we'd have to be aware of the mistakes that were…
But software works only 99% of the time. For some definition of work: 99% of days it's run, 99% of clicks, 99% of CPU time in given component, 99% of versions released and linked into some business' production binary, 99% of github tags, 99% of commits, 99% of software that that one guy says is battle-tested
Software pretty much always "works" when you consider the definition of work to be "does what the programmer told it too". AI? Not so much.
> But when developers put AI in consumer products, people expect it to behave like software, which means that it needs to work deterministically. If your AI travel agent books vacations to the correct destination only 90% of the time, it won’t be successful. This is the fundamental problem that prevents generative AI from becoming a "foundational building block" for most products. Even with rigorous safety measures i…
structured outputs help, paired with regular old systems design I think you can get pretty far. it really depends what you're building though. >If your AI travel agent books vacations to the correct destination only 90% of the time that would be using the wrong tool for the job. an AI travel agent would be very useful for making suggestions, either for destinations or giving a list of suggested flights, hotels etc, a…
But that’s a recommendation engine and we have that already all over the place.
Earlier quoted context omitted.
I've made this statement a bunch in other mediums: The reason AI software is always "AI software" and not just a useful product is because AI is fallible. The reason we can build such deep and complex software system is because each layer can assume the one below it will "just work". If it only worked 99% of the time, we'd all still be interfacing with assembly, because we'd have to be aware of the mistakes that were…
But software works only 99% of the time. For some definition of work: 99% of days it's run, 99% of clicks, 99% of CPU time in given component, 99% of versions released and linked into some business' production binary, 99% of github tags, 99% of commits, 99% of software that that one guy says is battle-tested
> But when developers put AI in consumer products, people expect it to behave like software, which means that it needs to work deterministically. If your AI travel agent books vacations to the correct destination only 90% of the time, it won’t be successful. This is the fundamental problem that prevents generative AI from becoming a "foundational building block" for most products. Even with rigorous safety measures i…
And yet, generative AI also seems to be poor at randomness. When I ask Google Gemini for a list of 50 random words, it gave me a list of 18 unique words, with 16 of them repeated exactly 3 times. Abyss: 1 Ambiguous: 3 Cacophony: 3 Crescendo: 3 Ephemeral: 3 Ethereal: 3 Euphoria: 3 Labyrinth: 3 Maverick: 3 Melancholy: 3 Mellifluous: 3 Nostalgia: 3 Oblivion: 3 Paradox: 3 Quixotic: 1 Serendipity: 3 Sublime: 3 Zenith: 3
Companies keep going at it the wrong way. Instead of saying "We have AI, let's find products we can make out of AI!" they should be saying, "What products do people want, let's use whatever tools we have (including maybe AI) to make them." The idea that a company is an AI company should be as ridiculous as a company being a Python company. "We are Python-first, have Python experts, and all of our products are made wi…
I blogged about our glorious journey Becoming an AI Company (TM) https://candid.dev/blog/becoming-an-ai-company/
Companies keep going at it the wrong way. Instead of saying "We have AI, let's find products we can make out of AI!" they should be saying, "What products do people want, let's use whatever tools we have (including maybe AI) to make them." The idea that a company is an AI company should be as ridiculous as a company being a Python company. "We are Python-first, have Python experts, and all of our products are made wi…
Companies keep going at it the wrong way. Instead of saying "We have AI, let's find products we can make out of AI!" they should be saying, "What products do people want, let's use whatever tools we have (including maybe AI) to make them." The idea that a company is an AI company should be as ridiculous as a company being a Python company. "We are Python-first, have Python experts, and all of our products are made wi…