▲ 284 ▼ I Asked AI to Count My Carbs 27,000 Times. It Couldn’t Give Me the Same Answer Twice. (www.diabettech.com) submitted 6 months ago by Deep@mander.xyz to c/technology@lemmy.world 70 comments fedilink hide all child comments 😂 1 Hacker News
[–] Corkyskog@sh.itjust.works 40 points 6 months ago (3 children) The point is they are advertising that these models can do it. permalink fedilink source parent hideshow 3 child comments replies: [–] eager_eagle@lemmy.world -1 points 6 months ago* (last edited 6 months ago) (2 children) You’d expect the same answer each time. It’s the same photo, the same model, the same question. But you won’t get the same answer. I don't know what ads show that, but anyone who knows the first thing about LLMs knows you don't get the same answer twice. I'd get this expectation 5 years ago when most people weren't familiar with it, but come on... you don't need to feed it an image 500 times to see that. permalink fedilink source parent hideshow 2 child comments replies: [–] Sandbar_Trekker@lemmy.today 3 points 6 months ago (1 child) Technically, you can get the same answer twice from an LLM, but only when you control the full input. When a model is being run, a random seed/hash is applied to the input. If you run the model locally you could force the seed to always be the same so that you would always get the same answer for a given question. permalink fedilink source parent hideshow 1 child comment replies: [–] eager_eagle@lemmy.world 1 point 6 months ago Barely. Even with the code and seeds, it's still a struggle to do that. There's plenty of questions from people running pytorch and tensorflow models that can't reproduce results. Maybe you isolate enough variables that consecutive runs actually produce the same output, but the study is about commercial models. You'll never get deterministic output from those. permalink fedilink source parent
[–] eager_eagle@lemmy.world -1 points 6 months ago* (last edited 6 months ago) (2 children) You’d expect the same answer each time. It’s the same photo, the same model, the same question. But you won’t get the same answer. I don't know what ads show that, but anyone who knows the first thing about LLMs knows you don't get the same answer twice. I'd get this expectation 5 years ago when most people weren't familiar with it, but come on... you don't need to feed it an image 500 times to see that. permalink fedilink source parent hideshow 2 child comments replies: [–] Sandbar_Trekker@lemmy.today 3 points 6 months ago (1 child) Technically, you can get the same answer twice from an LLM, but only when you control the full input. When a model is being run, a random seed/hash is applied to the input. If you run the model locally you could force the seed to always be the same so that you would always get the same answer for a given question. permalink fedilink source parent hideshow 1 child comment replies: [–] eager_eagle@lemmy.world 1 point 6 months ago Barely. Even with the code and seeds, it's still a struggle to do that. There's plenty of questions from people running pytorch and tensorflow models that can't reproduce results. Maybe you isolate enough variables that consecutive runs actually produce the same output, but the study is about commercial models. You'll never get deterministic output from those. permalink fedilink source parent
[–] Sandbar_Trekker@lemmy.today 3 points 6 months ago (1 child) Technically, you can get the same answer twice from an LLM, but only when you control the full input. When a model is being run, a random seed/hash is applied to the input. If you run the model locally you could force the seed to always be the same so that you would always get the same answer for a given question. permalink fedilink source parent hideshow 1 child comment replies: [–] eager_eagle@lemmy.world 1 point 6 months ago Barely. Even with the code and seeds, it's still a struggle to do that. There's plenty of questions from people running pytorch and tensorflow models that can't reproduce results. Maybe you isolate enough variables that consecutive runs actually produce the same output, but the study is about commercial models. You'll never get deterministic output from those. permalink fedilink source parent
[–] eager_eagle@lemmy.world 1 point 6 months ago Barely. Even with the code and seeds, it's still a struggle to do that. There's plenty of questions from people running pytorch and tensorflow models that can't reproduce results. Maybe you isolate enough variables that consecutive runs actually produce the same output, but the study is about commercial models. You'll never get deterministic output from those. permalink fedilink source parent