> Datadog Agent’s artifact size has grown significantly, from 428 MiB in version 7.16.0 to a peak of 1.22 GiB in version 7.60.0 on Linux.
r u fcking kidding me? holy moly, my 8 binaries are 200Mb in total, ddog is a cancer.
https://www.datadoghq.com/blog/engineering/agent-go-binaries/
r u fcking kidding me? holy moly, my 8 binaries are 200Mb in total, ddog is a cancer.
https://www.datadoghq.com/blog/engineering/agent-go-binaries/
Datadog
How we reduced the size of our Agent Go binaries by up to 77% | Datadog
Get an inside look at shrinking large Go binaries in the Datadog Agent through dependency and linker analysis.
> I think everyone's focusing on the core count, but the packaging story is way more interesting here. This thing is 12 separate chiplets on 18A stacked on base dies made on Intel 3, connected to I/O tiles on Intel 7. Three different process nodes in one package, shipping at volume. That's nuts.
https://www.tomshardware.com/pc-components/cpus/intels-make-or-break-18a-process-node-debuts-for-data-center-with-288-core-xeon-6-cpu-multi-chip-monster-sports-12-channels-of-ddr5-8000-foveros-direct-3d-packaging-tech
https://www.tomshardware.com/pc-components/cpus/intels-make-or-break-18a-process-node-debuts-for-data-center-with-288-core-xeon-6-cpu-multi-chip-monster-sports-12-channels-of-ddr5-8000-foveros-direct-3d-packaging-tech
Tom's Hardware
Intel's make-or-break 18A process node debuts for data center with 288-core Xeon 6+ CPU — multi-chip monster sports 12 channels…
Intel unveils x86 CPU with the industry's highest core count.
Recently, I started working with DuckDB, and it’s been pretty cool. I feel a bit dumb for not picking it earlier for a few projects a few years ago.
The only problem is that you can’t create an index if it doesn’t fit in RAM (skill issue?). Upscaling the machine just to build an index is kind of meh.
Very promising DB. It reminds me of сlickhouse-local / chDB.
https://duckdb.org/why_duckdb
The only problem is that you can’t create an index if it doesn’t fit in RAM (skill issue?). Upscaling the machine just to build an index is kind of meh.
Very promising DB. It reminds me of сlickhouse-local / chDB.
https://duckdb.org/why_duckdb
DuckDB
Why DuckDB
Why DuckDB There are many database management systems (DBMS) out there. But there is no one-size-fits-all database system. All take different trade-offs to better adjust to specific use cases. DuckDB is no different. Here, we try to explain what goals DuckDB…
Yeah, go tell me about your blast radius, kid.
> The investigation concludes that the blackout resulted from a combination of many interacting factors, including oscillations, gaps in voltage and reactive power control, differences in voltage regulation practices, rapid output reductions and generator disconnections in Spain, and uneven stabilisation capabilities. These factors led to fast increases of voltage and cascading generation disconnections in Spain, resulting in the blackout in continental Spain and Portugal.
https://www.entsoe.eu/publications/blackout/28-april-2025-iberian-blackout/
> The investigation concludes that the blackout resulted from a combination of many interacting factors, including oscillations, gaps in voltage and reactive power control, differences in voltage regulation practices, rapid output reductions and generator disconnections in Spain, and uneven stabilisation capabilities. These factors led to fast increases of voltage and cascading generation disconnections in Spain, resulting in the blackout in continental Spain and Portugal.
https://www.entsoe.eu/publications/blackout/28-april-2025-iberian-blackout/
Hedonic treadmill is Jevons paradox for humans. Not directly but the consequences of the conjecture.
https://en.wikipedia.org/wiki/Hedonic_treadmill
https://en.wikipedia.org/wiki/Jevons_paradox
https://en.wikipedia.org/wiki/Hedonic_treadmill
https://en.wikipedia.org/wiki/Jevons_paradox
oleg_log
https://arstechnica.com/gadgets/2026/03/amds-ryzen-9-9950x3d2-dual-edition-crams-208mb-of-cache-into-a-single-chip/
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Hey, AI crackheads, what is the true way to run LLM locally? LocalAI? Ollama? anything else?
Not Go-specific, just the two I'm aware of that are by lovely chance written in Go.
Not Go-specific, just the two I'm aware of that are by lovely chance written in Go.
Probably the 1st LLM company that I really like. I mean their idea and product.
LLM for embedding devices, obvious and still revolutionary. Nice.
https://prismml.com/
LLM for embedding devices, obvious and still revolutionary. Nice.
https://prismml.com/
Prismml
PrismML — Concentrating intelligence
Large models can't fit on smartphones. Datacenters can't sustain them. PrismML is building ultra dense intelligence to solve both.