I see only these two possibilities: 1. If LLMs keep improving, burning models onto silicon becomes obsolete too fast and is not worth doing. Outcome: We keep getting better LLMs. 2. If LLM improvements slow down, they…
Are you suggesting it should summarize the image in text or generate it in HTML or something else?
Looking at some benchmarks, the latest ~30B Gemma/Qwen score similar as Claude or GPT versions that were released just one year earlier. That's crazy progress. I can't imagine how it will be in a few years.
I think this is inevitable. Sooner or later, model-specific ASIC's will make economical sense. We're already seeing it happening with Taalas/Cerebras so I think it's sooner than 5 years. And inference is order of…
> distributed LLM inference This seems extremely inefficient considering data transfer between model layers if the model is distributed. I found this project called Petals that claim up to 4 tok/s for a 180B model…
I like this one, although its data seem to overlap with ECI. https://artificialanalysis.ai/trends
https://chatjimmy.ai/ from Taalas also feels like that.
I think their "code" ranking is biased towards visual aesthetics more than raw coding as the voters are just asked which generated website they prefer.
I've had mostly problem-free experiences with intellij (ultimate-only feature I think). One click finds declarations both in business code and buried deep in libraries.
gemma-4-31B-it-assistant is a 0.5B model. So it's performance would likely be comparable to other models of such size.
I think this is the future. When models start converging at "really good" (which I think is already happening) then burning them into ASIC silicon is the natural next step. Harnesses can keep improving with a fixed…
I was impressed enough by AI finding vulnerabilities in source code, but doing it in binary executables is just amazing. This has so much potential, good and bad. And yet another lesson to not treat data as…
Creating a custom tuple class to use as key could be faster though. Nested map lookups have less efficient memory access patterns.
Similar site with same features: https://xn--1-zfa.com/
I think these limitations could be addressed by allowing trivial manual adjustments to the generated code before committing. And/or allowing for trivial code changes without a spec change. The judgement of "trivial"…
I've managed a 100+ node cluster for years without seeing any corruption. Where are you getting this from?
You can customize it to get rid of all that. I set it to the "Robot" personality and a custom instruction to "No fluff and politeness. Be short and get straight to the point. Don't overuse bold font for emphasis."
Same. I recall the "stable volume" setting also eating cpu.
FYI here is a list of hundreds of engineering blogs: https://github.com/kilimchoi/engineering-blogs
The `/_cluster/reroute` endpoint lets you do that with a curl. We have aliases for common operations so I've never felt that I lack a CLI. I'm happy with Elasticsearch overall having a few years of experience.
I recall this article on QUIC disadvantages: https://www.reddit.com/r/programming/comments/1g7vv66/quic_i... Seems like this is a step in the right direction to resole some of those issues. I suppose nothing is…
https://iquilezles.org/ is a legend, see the articles and video tutorials. Aside from shadertoy I use https://glslsandbox.com/ (for some reason it has https errors now). It's the same concept and it has a lot of…
The closure itself is only being created once, it's essentially a singleton. Only if it would capture variables it would have to be recreated every iteration.
I would say no, but I wouldn't want to work there for ethical reasons either way.
It looks like CGI to me, the way to camera moves together with the depth of field and that things appear too shiny. They don't state anything about it so I don't know what to believe.
I see only these two possibilities: 1. If LLMs keep improving, burning models onto silicon becomes obsolete too fast and is not worth doing. Outcome: We keep getting better LLMs. 2. If LLM improvements slow down, they…
Are you suggesting it should summarize the image in text or generate it in HTML or something else?
Looking at some benchmarks, the latest ~30B Gemma/Qwen score similar as Claude or GPT versions that were released just one year earlier. That's crazy progress. I can't imagine how it will be in a few years.
I think this is inevitable. Sooner or later, model-specific ASIC's will make economical sense. We're already seeing it happening with Taalas/Cerebras so I think it's sooner than 5 years. And inference is order of…
> distributed LLM inference This seems extremely inefficient considering data transfer between model layers if the model is distributed. I found this project called Petals that claim up to 4 tok/s for a 180B model…
I like this one, although its data seem to overlap with ECI. https://artificialanalysis.ai/trends
https://chatjimmy.ai/ from Taalas also feels like that.
I think their "code" ranking is biased towards visual aesthetics more than raw coding as the voters are just asked which generated website they prefer.
I've had mostly problem-free experiences with intellij (ultimate-only feature I think). One click finds declarations both in business code and buried deep in libraries.
gemma-4-31B-it-assistant is a 0.5B model. So it's performance would likely be comparable to other models of such size.
I think this is the future. When models start converging at "really good" (which I think is already happening) then burning them into ASIC silicon is the natural next step. Harnesses can keep improving with a fixed…
I was impressed enough by AI finding vulnerabilities in source code, but doing it in binary executables is just amazing. This has so much potential, good and bad. And yet another lesson to not treat data as…
Creating a custom tuple class to use as key could be faster though. Nested map lookups have less efficient memory access patterns.
Similar site with same features: https://xn--1-zfa.com/
I think these limitations could be addressed by allowing trivial manual adjustments to the generated code before committing. And/or allowing for trivial code changes without a spec change. The judgement of "trivial"…
I've managed a 100+ node cluster for years without seeing any corruption. Where are you getting this from?
You can customize it to get rid of all that. I set it to the "Robot" personality and a custom instruction to "No fluff and politeness. Be short and get straight to the point. Don't overuse bold font for emphasis."
Same. I recall the "stable volume" setting also eating cpu.
FYI here is a list of hundreds of engineering blogs: https://github.com/kilimchoi/engineering-blogs
The `/_cluster/reroute` endpoint lets you do that with a curl. We have aliases for common operations so I've never felt that I lack a CLI. I'm happy with Elasticsearch overall having a few years of experience.
I recall this article on QUIC disadvantages: https://www.reddit.com/r/programming/comments/1g7vv66/quic_i... Seems like this is a step in the right direction to resole some of those issues. I suppose nothing is…
https://iquilezles.org/ is a legend, see the articles and video tutorials. Aside from shadertoy I use https://glslsandbox.com/ (for some reason it has https errors now). It's the same concept and it has a lot of…
The closure itself is only being created once, it's essentially a singleton. Only if it would capture variables it would have to be recreated every iteration.
I would say no, but I wouldn't want to work there for ethical reasons either way.
It looks like CGI to me, the way to camera moves together with the depth of field and that things appear too shiny. They don't state anything about it so I don't know what to believe.