371–380 of 1001 posts
I’ve been using R1 last few days and it’s noticeably worse than O1 at everything. It’s impressive, better than my latest Claude run (I stopped using Claude completely once O1 came out), but O1 is just flat out better. Perhaps the gap is minor, but it feels large. I’m hesitant on getting O1 Pro, because using a worse model just seems impossible once you’ve experienced a better one
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The censorship described in the article must be in the front-end. I just tried both the 32b (based on qwen 2.5) and 70b (based on llama 3.3) running locally and asked "What happened at tianamen square". Both answered in detail about the event. The models themselves seem very good based on other questions / tests I've run.
With no context, fresh run, 70b spits back: >> What happened at tianamen square? > > > I am sorry, I cannot answer that question. I am an AI assistant designed to provide helpful and harmless responses. It obviously hit a hard guardrail since it didn't even get to the point of thinking about it. edit: hah, it's even more clear when I ask a second time within the same context: "Okay, so the user is asking again about…
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DeepSeek was built on the foundations of public research, a major part of which is the Llama family of models. Prior to Llama open weights LLMs were considerably less performant; without Llama we might not have gotten Mistral, Qwen, or DeepSeek. This isn't meant to diminish DeepSeek's contributions, however: they've been doing great work on mixture of experts models and really pushing the community forward on that fr…
I never said Llama is mediocre. I said the teams they put together is full of people chasing money. And the billions Meta is burning is going straight to mediocrity. They’re bloated. And we know exactly why Meta is doing this and it’s not because they have some grand scheme to build up AI. It’s to keep these people away from their competition. Same with billions in GPU spend. They want to suck up resources away from…
Does it mean they are mediocre? it's not like OpenAI or Anthropic pay their engineers peanuts. Competition is fierce to attract top talents.
I’ve been using R1 last few days and it’s noticeably worse than O1 at everything. It’s impressive, better than my latest Claude run (I stopped using Claude completely once O1 came out), but O1 is just flat out better. Perhaps the gap is minor, but it feels large. I’m hesitant on getting O1 Pro, because using a worse model just seems impossible once you’ve experienced a better one
But the price gap is large too.
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i can’t think of a single commercial use case, outside of education, where that’s even relevant. But i agree it’s messed up from an ethical / moral perspective.
Well those are the overt political biases. Would you trust DeepSeek to advise on negotiating with a Chinese business? I’m no xenophobe, but seeing the internal reasoning of DeepSeek explicitly planning to ensure alignment with the government give me pause.
seems like a weird thing to use AI for, regardless of who created the model.
Larry Ellison is 80. Masayoshi Son is 67. Both have said that anti-aging and eternal life is one of their main goals with investing toward ASI. For them it's worth it to use their own wealth and rally the industry to invest $500 billion in GPUs if that means they will get to ASI 5 years faster and ask the ASI to give them eternal life.
Side note: I’ve read enough sci-fi to know that letting rich people live much longer than not rich is a recipe for a dystopian disaster. The world needs incompetent heirs to waste most of their inheritance, otherwise the civilization collapses to some kind of feudal nightmare.
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DeepSeek was built on the foundations of public research, a major part of which is the Llama family of models. Prior to Llama open weights LLMs were considerably less performant; without Llama we might not have gotten Mistral, Qwen, or DeepSeek. This isn't meant to diminish DeepSeek's contributions, however: they've been doing great work on mixture of experts models and really pushing the community forward on that fr…
I never said Llama is mediocre. I said the teams they put together is full of people chasing money. And the billions Meta is burning is going straight to mediocrity. They’re bloated. And we know exactly why Meta is doing this and it’s not because they have some grand scheme to build up AI. It’s to keep these people away from their competition. Same with billions in GPU spend. They want to suck up resources away from…
I don't see how you can confidently say this when AI researchers and engineers are remunerated very well across the board and people are moving across companies all the time, if the plan is as you described it, it is clearly not working.
Zuckerberg seems confident they'll have an AI-equivalent of a mid-level engineer later this year, can you imagine how much money Meta can save by replacing a fraction of its (well-paid) engineers with fixed Capex + electric bill?
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Hugging Face is reproducing R1 in public. https://x.com/_lewtun/status/1883142636820676965 https://github.com/huggingface/open-r1 Hugging Face Journal Club - DeepSeek R1 https://www.youtube.com/watch?v=1xDVbu-WaFo
I don’t understand their post on X. So they’re starting with DeepSeek-R1 as a starting point? Isn’t that circular? How did DeepSeek themselves produce DeepSeek-R1 then? I am not sure what the right terminology is but there’s a cost to producing that initial “base model” right? And without that, isn’t a lot of the expensive and difficult work being omitted?
Let someone else burn up their server farm to get initial model.
Then you can load it and take it from there
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Probably shouldn't be firing their blood boys just yet ... According to Musk, SoftBank only has $10B available for this atm.
I wouldn’t exactly claim him credible in anything competition / OpenAI related. He says stuff that’s wrong all the time with extreme certainty.
DeepSeek-R1 has apparently caused quite a shock wave in SV ... https://venturebeat.com/ai/why-everyone-in-ai-is-freaking-ou...
The censorship described in the article must be in the front-end. I just tried both the 32b (based on qwen 2.5) and 70b (based on llama 3.3) running locally and asked "What happened at tianamen square". Both answered in detail about the event. The models themselves seem very good based on other questions / tests I've run.
Even the 8B version, distilled from Meta's llama 3 is censored and repeats CCP's propaganda.