> "A computer can never be held accountable, therefore a computer must never make a management decision." Legendary quote from an internal 1979 IBM training document [1]…
Noticed this as well! Was looking for details on the software support and this FAQ entry didn't exactly instill confidence...
> it's extremely long in it's thinking, it just goes on and on Known issue with this model, I recommend setting thinking to 'medium' instead of default 'xhigh'.
> I looked into running a local model, and it's way outside the budget of an individual or even a small or medium business (hundreds of thousands of dollars). That is a big exaggeration. You can have a perfectly usable…
> What if all the agents involved in these incidents have in fact had the full stack of alignment applied A big part of this developing story is that it happened during training of a new model that ended up misaligned.…
We are certainly not in the diminishing returns phase for LLM progress. No sign of that yet.
No, those use LPDDR5(x), not HBM.
From what I'm seeing elsewhere, context size up to 128k should be possible on this hardware. It really matters for agentic workloads to push that context size headroom up. Anthropic are spoiling us with models that do…
Nvidia is also pushing for local inference IMHO. They want open models and competition in the model layer, not two big labs controlling all of it.
This depends heavily on what the use-case is. Yes, if it's a coder making software and having to read LLM output then writing style matters. If the LLM is used in an automated data processing pipeline with a capped…
By leveraging the experience Broadcom has in this area. Still remains to be seen how that goes when they want to scale production.
Most of the generative art is hosted on IPFS.
Wait, it's allowed again? Completely missed that. Been avoiding to use it and trying to find workarounds, not great.
The Cerebras hardware is not locked to specific models / model families. Taalas is the company that's etching models into their silicon, locking it to that model forever.
My default assumption (with no knowledge about this particular case) is that all gear in YouTube videos is sponsored. Too easy to get jealous of all the fancy setups. But I don't want to become a YouTuber so that…
OpenAI's upcoming mega IPO
> Time for me to go research the early history of electrification. The Stepchange podcast has an amazing episode on The Grid [1], walking us through the arc of history of how it became the utility it is today. [1]:…
> posting this sentence was part of the deal to get the compute This 100%
There is a surprising amount of code needed in each of the inference frameworks (LM Studio, llama.cpp, etc) to support each new model release. For example to format the input in the right way using a chat template, to…
I think we lost that terminology war. Open source models mean open weight. There are only a couple examples of fully open source models with open data and code, and the labs are not incentivized to go that far.
Yes, retooling gas stations is the way to go. Already happening in Norway where stations now show the price of kWh in addition to gas and diesel prominently on signs by the road. Charging is just a different kind of…
America certainly did not invent electric cars. Depending on which electric car you consider the first real one, the inventor was either French, British or German [1]. [1]:…
Unsloth is providing the best and most reliable libraries for finetuning LLMs. We've used it for production use-cases where I work, definitely solid.
Spend time building a test harness and evaluations of whether the solution meets the requirements. Then you don't need to look at the code because those other pieces will bring the necessary guarantees and trust.
Because we all prefer it over Gemini and Codex. Anthropic knows that and needs to get as much out of it as possible while they can. Not saying the others will catch up soon. But at some point other models will be as…
> "A computer can never be held accountable, therefore a computer must never make a management decision." Legendary quote from an internal 1979 IBM training document [1]…
Noticed this as well! Was looking for details on the software support and this FAQ entry didn't exactly instill confidence...
> it's extremely long in it's thinking, it just goes on and on Known issue with this model, I recommend setting thinking to 'medium' instead of default 'xhigh'.
> I looked into running a local model, and it's way outside the budget of an individual or even a small or medium business (hundreds of thousands of dollars). That is a big exaggeration. You can have a perfectly usable…
> What if all the agents involved in these incidents have in fact had the full stack of alignment applied A big part of this developing story is that it happened during training of a new model that ended up misaligned.…
We are certainly not in the diminishing returns phase for LLM progress. No sign of that yet.
No, those use LPDDR5(x), not HBM.
From what I'm seeing elsewhere, context size up to 128k should be possible on this hardware. It really matters for agentic workloads to push that context size headroom up. Anthropic are spoiling us with models that do…
Nvidia is also pushing for local inference IMHO. They want open models and competition in the model layer, not two big labs controlling all of it.
This depends heavily on what the use-case is. Yes, if it's a coder making software and having to read LLM output then writing style matters. If the LLM is used in an automated data processing pipeline with a capped…
By leveraging the experience Broadcom has in this area. Still remains to be seen how that goes when they want to scale production.
Most of the generative art is hosted on IPFS.
Wait, it's allowed again? Completely missed that. Been avoiding to use it and trying to find workarounds, not great.
The Cerebras hardware is not locked to specific models / model families. Taalas is the company that's etching models into their silicon, locking it to that model forever.
My default assumption (with no knowledge about this particular case) is that all gear in YouTube videos is sponsored. Too easy to get jealous of all the fancy setups. But I don't want to become a YouTuber so that…
OpenAI's upcoming mega IPO
> Time for me to go research the early history of electrification. The Stepchange podcast has an amazing episode on The Grid [1], walking us through the arc of history of how it became the utility it is today. [1]:…
> posting this sentence was part of the deal to get the compute This 100%
There is a surprising amount of code needed in each of the inference frameworks (LM Studio, llama.cpp, etc) to support each new model release. For example to format the input in the right way using a chat template, to…
I think we lost that terminology war. Open source models mean open weight. There are only a couple examples of fully open source models with open data and code, and the labs are not incentivized to go that far.
Yes, retooling gas stations is the way to go. Already happening in Norway where stations now show the price of kWh in addition to gas and diesel prominently on signs by the road. Charging is just a different kind of…
America certainly did not invent electric cars. Depending on which electric car you consider the first real one, the inventor was either French, British or German [1]. [1]:…
Unsloth is providing the best and most reliable libraries for finetuning LLMs. We've used it for production use-cases where I work, definitely solid.
Spend time building a test harness and evaluations of whether the solution meets the requirements. Then you don't need to look at the code because those other pieces will bring the necessary guarantees and trust.
Because we all prefer it over Gemini and Codex. Anthropic knows that and needs to get as much out of it as possible while they can. Not saying the others will catch up soon. But at some point other models will be as…