Microsoft Volume I
Microsoft. After nearly a decade of Acquired episodes, we are finally ready to tackle the most valuable company ever created. The company that put a computer on every desk and in every home. The company that invented the software business model. The company that so thoroughly and completely dominated every conceivable competitor that the United States government intervened and kneecapped it… yet it’s STILL the most valuable company in the world today. This episode tells the story of Microsoft in its heyday, the PC Era. We cover its rise from a teenage dream to the most powerful business and technology force in history — the 20-year period from 1975 to 1995 that took Bill and Paul from the Lakeside high school computer room to launching Windows 95 alongside Jay Leno and the Rolling Stones.
Could not retrieve the full article text.
Read on Acquired Podcast →Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
claudemodellaunch
Gemma 4 - 4B vs Qwen 3.5 - 9B ?
Hello! anyone tried the 4B Gemma 4 model and the Qwen 3.5 9B model and can tell us their feedback? On the benchmark Qwen seems to be doing better, but I would appreciate any personal experience on the matter Thanks! submitted by /u/No-Mud-1902 [link] [comments]
Speculative decoding works great for Gemma 4 31B in llama.cpp
I get a ~11% speed up with Gemma 3 270B as the draft model. Try it by adding: --no-mmproj -hfd unsloth/gemma-3-270m-it-GGUF:Q8_0 Testing with (on a 3090): ./build/bin/llama-cli -hf unsloth/gemma-4-31B-it-GGUF:Q4_1 --jinja --temp 1.0 --top-p 0.95 --top-k 64 -ngl 1000 -st -f prompt.txt --no-mmproj -hfd unsloth/gemma-3-270m-it-GGUF:Q8_0 Gave me: [ Prompt: 607.3 t/s | Generation: 36.6 t/s ] draft acceptance rate = 0.44015 ( 820 accepted / 1863 generated) vs. [ Prompt: 613.8 t/s | Generation: 32.9 t/s ] submitted by /u/Leopold_Boom [link] [comments]
Speed difference on Gemma 4 26B-A4B between Bartowski Q4_K_M and Unsloth Q4_K_XL
I've noticed this on Qwen3.5 35B before as well, there is a noticeable speed difference between Unsloth's Q4_K_XL and Bartowski's Q4_K_M on the same model, but Gemma 4 seems particularly harsh in this regard: Bartowski gets 38 tk/s, Unsloth gets 28 tk/s... everything else is the same, settings wise. This is with the latest Unsloth quant update and latest llama.cpp version. Their size is only ~100 MB apart. Anyone have any idea why this speed difference is there? Btw, on Qwen3.5 35B I noticed that Unsloth's own Q4_K_M was also a bit faster than the Q4_K_XL, but there it was more like 39 vs 42 tk/s. submitted by /u/BelgianDramaLlama86 [link] [comments]
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!