481–490 of 652 posts
Earlier quoted context omitted.
Strix Halo, 128GB RAM. I got a refurbished Corsair AI Workstation for a smoking price ($2100) about two months ago. Lucky timing that it was in stock.
Strix Halo as well. Bought it for $1,800 new on sale and shoved an extra 4tb drive into it. Been amazing for local AI. Maybe not the absolute fastest thing (usually around 30t/s depending on the task) but has been awesome for a local AI box that I can solar power.
Earlier quoted context omitted.
The people involved have been talking about safety long before they had any users or a company. "Concrete Problems in AI Safety" by Dario and another founder was published 2016, anthropic was founded 2021. Among a bunch of other examples, including other founders. If safety is seen as a joke now, it was really seen as a joke back then. The reason they keep shooting themselves in the foot with bad PR is because they t…
I’m sorry, but this do-gooder concept doesn’t jibe with their other actions. For example, swindling their business partners (such as Figma). Filing an unnecessary trademark lawsuit against a customer whose brand predates Anthropic. And for safety? Oh yeah, they literally sell the removal of guardrails in exchange for minimum spend commitments.
Completely unrelated to AI safety.
they literally sell the removal of guardrails in exchange for minimum spend commitments
It seems blindingly obvious to me that you'd want to let trusted organizations use the models defensively, which means without guardrails, and that you'd probably gate that behind some kind of enterprise sales process, for multiple reasons.
Honestly, it just seems like you have an axe to grind and aren't really particularly knowledgeable (or curious) about AI safety.
Earlier quoted context omitted.
First and foremost, China isn't energy-limited like the US is. A modern grid, lost of cheap power coming online every day. The worlds most advance ultra-high voltage transport links are tying the deserts in the west to the cities in the south. It probably sucks for you if the proposed powerline goes through your house, but the need of the many come first. Having cheap and plentiful power is a huge market advantage. I…
The US also isn't energy-limited. They'll just price out all humans living there from buying any electricity. EDIT: This was obviously meant to be facetious with the intent to highlight the negative effects on the general population that datacenter buildout has in the US.
Earlier quoted context omitted.
They have 2 moats. The first is the compute. OpenAI and Anthropic secured huge amounts of compute, Google, Meta and xAI have their own huge datacenters. Now anyone can rent some cloud machines and start serving Kimi K3, but it's going to be impossible to get to a similar scale as the big 5 above. And inference has economies of scale: the more people you serve in parallel, the more efficient you are. The second is the…
compute is not a moat, it's a rapidly depreciating physical asset. buying up all the shovels in a gold rush does not give you a moat, it gives you a slight advantage for the time being. someone else will just start making shovels. and the data is clearly available, hence the number of open-weight models.
Earlier quoted context omitted.
I’ve run 3.6-27B and 3.6-35B on 32GB locally for a lot of bulk non-code tasks. Let it run overnight and wake up to millions of output tokens worth of results without data having left my house, all for the price of electricity. I haven’t found it very useful for code. It can do some code, but I’ve tried a dozen different quants and context lengths and the output is always bad enough that it has to be discarded for any…
> I’ve run 3.6-27B and 3.6-35B on 32GB locally for a lot of bulk non-code tasks. Do you mind sharing your use cases?
I started with Karpathy's LLM wiki, and did everything he said not to do - downgraded the model to mere tool usage and summarization, and it works great.
I am a data hoarder, and finally I can just dump all the content I remotely like, and get something interesting to browse for the price of electricity.
Agentic long-running tasks, as others have mentioned:
- Groom and triage tickets for agentic SWE workflows
- bug hunt — the probability of Qwen fixing a complex bug is 50/50 but often it is capable of identifying the root cause or at least laying the ground work for a more capable model to pick it up.
Earlier quoted context omitted.
I’ve run 3.6-27B and 3.6-35B on 32GB locally for a lot of bulk non-code tasks. Let it run overnight and wake up to millions of output tokens worth of results without data having left my house, all for the price of electricity. I haven’t found it very useful for code. It can do some code, but I’ve tried a dozen different quants and context lengths and the output is always bad enough that it has to be discarded for any…
> I’ve run 3.6-27B and 3.6-35B on 32GB locally for a lot of bulk non-code tasks. Do you mind sharing your use cases?
AWS Bedrock still lacks the support for the latest open weights models like GLM 5.2, DSV4 Flash 0731, Kimi K3 etc. Even they only support Qwen 3 which is a very old model. Any specific reasons they are reluctant to support open weights models?
In practice I'm not sure how big a deal this is - Bedrock is not the cheapest or best provider (try Fireworks AI or DeepInfra who do support more recent models), and would seem to be of more interest to corporate users who already have an AWS account.
Perhaps also of relevance the US government is hassling US companies that are using Chinese models (currently DoorDash, previously AirBnB & Cursor), which may limit demand for corporate use.
Earlier quoted context omitted.
What is stopping them from just building their data centers in the west where they have energy surplus? Not like you need to locate a data center inside a city.
Water. The west is really dry. We could throw in data lines as well but it’s really bottlenecked by water. Actually the only place in China with water in abundance is southeast China. Also they really don’t have the chips to supply those data centers, and the government isn’t so crazy to go that aggressive on AI, they have lots of other priorities as well.
As someone who is searching for a new programming contract right now, reading all of the incredible abilities here is pretty intimidating. Especially since I get almost all of my projects from Upwork which is an outsourcing site. I believe I am competing directly with these frontier models in some circumstances. Like there are a ton of programmers who previously would be outsourcing work to that site, but now they as…
As someone who is searching for a new programming contract right now, reading all of the incredible abilities here is pretty intimidating. Especially since I get almost all of my projects from Upwork which is an outsourcing site. I believe I am competing directly with these frontier models in some circumstances. Like there are a ton of programmers who previously would be outsourcing work to that site, but now they as…
If you search for LLM benchmarks focused on real-world tasks, you'll quickly learn this ain't the case. No point in telling business owners about that though, they need to see/learn by themselves.