<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: galeos</title><link>https://news.ycombinator.com/user?id=galeos</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Thu, 10 Sep 2026 02:39:31 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=galeos" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by galeos in "AMD acquires Taalas to boost inference performance by etching models in silicon"]]></title><description><![CDATA[
<p>Is there scope to implement ternary models using this approach to minimise die area of the model parameters?</p>
]]></description><pubDate>Fri, 07 Aug 2026 13:04:30 +0000</pubDate><link>https://news.ycombinator.com/item?id=49209797</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=49209797</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=49209797</guid></item><item><title><![CDATA[1.58bit LLM Optimised Tensor Core]]></title><description><![CDATA[
<p>Article URL: <a href="https://github.com/microsoft/T-MAC">https://github.com/microsoft/T-MAC</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=44436729">https://news.ycombinator.com/item?id=44436729</a></p>
<p>Points: 2</p>
<p># Comments: 0</p>
]]></description><pubDate>Tue, 01 Jul 2025 18:24:48 +0000</pubDate><link>https://github.com/microsoft/T-MAC</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=44436729</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=44436729</guid></item><item><title><![CDATA[BitNet 1.58bit GPU Inference Kernel]]></title><description><![CDATA[
<p>Article URL: <a href="https://github.com/microsoft/BitNet/blob/main/gpu/README.md">https://github.com/microsoft/BitNet/blob/main/gpu/README.md</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=44043600">https://news.ycombinator.com/item?id=44043600</a></p>
<p>Points: 2</p>
<p># Comments: 0</p>
]]></description><pubDate>Tue, 20 May 2025 16:55:50 +0000</pubDate><link>https://github.com/microsoft/BitNet/blob/main/gpu/README.md</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=44043600</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=44043600</guid></item><item><title><![CDATA[New comment by galeos in "Everything we announced at our first LlamaCon"]]></title><description><![CDATA[
<p>How did you find ModernBERT performance Vs prior BERT models?</p>
]]></description><pubDate>Tue, 29 Apr 2025 19:34:04 +0000</pubDate><link>https://news.ycombinator.com/item?id=43837015</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=43837015</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=43837015</guid></item><item><title><![CDATA[Microsoft beat H200 Deepseek inference with MI300]]></title><description><![CDATA[
<p>Article URL: <a href="https://techcommunity.microsoft.com/blog/MachineLearningBlog/accelerating-deepseek-inference-with-amd-mi300-a-collaborative-breakthrough/4407673">https://techcommunity.microsoft.com/blog/MachineLearningBlog/accelerating-deepseek-inference-with-amd-mi300-a-collaborative-breakthrough/4407673</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=43786945">https://news.ycombinator.com/item?id=43786945</a></p>
<p>Points: 3</p>
<p># Comments: 1</p>
]]></description><pubDate>Thu, 24 Apr 2025 20:06:01 +0000</pubDate><link>https://techcommunity.microsoft.com/blog/MachineLearningBlog/accelerating-deepseek-inference-with-amd-mi300-a-collaborative-breakthrough/4407673</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=43786945</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=43786945</guid></item><item><title><![CDATA[Modular's CUDA alternative is ready]]></title><description><![CDATA[
<p>Article URL: <a href="https://www.eetimes.com/after-three-years-modulars-cuda-alternative-is-ready/">https://www.eetimes.com/after-three-years-modulars-cuda-alternative-is-ready/</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=43775779">https://news.ycombinator.com/item?id=43775779</a></p>
<p>Points: 2</p>
<p># Comments: 0</p>
]]></description><pubDate>Wed, 23 Apr 2025 19:26:58 +0000</pubDate><link>https://www.eetimes.com/after-three-years-modulars-cuda-alternative-is-ready/</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=43775779</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=43775779</guid></item><item><title><![CDATA[New comment by galeos in "BitNet b1.58 2B4T Technical Report"]]></title><description><![CDATA[
<p>You can try out the model in a demo they have setup: <a href="https://bitnet-demo.azurewebsites.net/" rel="nofollow">https://bitnet-demo.azurewebsites.net/</a></p>
]]></description><pubDate>Thu, 17 Apr 2025 11:10:03 +0000</pubDate><link>https://news.ycombinator.com/item?id=43715180</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=43715180</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=43715180</guid></item><item><title><![CDATA[BitNet b1.58 2B4T Technical Report]]></title><description><![CDATA[
<p>Article URL: <a href="https://arxiv.org/abs/2504.12285">https://arxiv.org/abs/2504.12285</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=43714004">https://news.ycombinator.com/item?id=43714004</a></p>
<p>Points: 111</p>
<p># Comments: 30</p>
]]></description><pubDate>Thu, 17 Apr 2025 07:27:11 +0000</pubDate><link>https://arxiv.org/abs/2504.12285</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=43714004</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=43714004</guid></item><item><title><![CDATA[Microsoft BitNet 1.58bit LLM 2B4T released]]></title><description><![CDATA[
<p>Article URL: <a href="https://huggingface.co/microsoft/bitnet-b1.58-2B-4T">https://huggingface.co/microsoft/bitnet-b1.58-2B-4T</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=43704219">https://news.ycombinator.com/item?id=43704219</a></p>
<p>Points: 2</p>
<p># Comments: 0</p>
]]></description><pubDate>Wed, 16 Apr 2025 11:54:45 +0000</pubDate><link>https://huggingface.co/microsoft/bitnet-b1.58-2B-4T</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=43704219</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=43704219</guid></item><item><title><![CDATA[Mi300 Huggingface]]></title><description><![CDATA[
<p>Article URL: <a href="https://huggingface.co/blog/huggingface-amd-mi300">https://huggingface.co/blog/huggingface-amd-mi300</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=43703985">https://news.ycombinator.com/item?id=43703985</a></p>
<p>Points: 2</p>
<p># Comments: 0</p>
]]></description><pubDate>Wed, 16 Apr 2025 11:24:16 +0000</pubDate><link>https://huggingface.co/blog/huggingface-amd-mi300</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=43703985</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=43703985</guid></item><item><title><![CDATA[Bitnet.cpp: Efficient Inference for 1.58bit LLMs]]></title><description><![CDATA[
<p>Article URL: <a href="https://arxiv.org/abs/2502.11880">https://arxiv.org/abs/2502.11880</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=43196126">https://news.ycombinator.com/item?id=43196126</a></p>
<p>Points: 1</p>
<p># Comments: 0</p>
]]></description><pubDate>Thu, 27 Feb 2025 16:55:32 +0000</pubDate><link>https://arxiv.org/abs/2502.11880</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=43196126</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=43196126</guid></item><item><title><![CDATA[Matryoshka Quantization]]></title><description><![CDATA[
<p>Article URL: <a href="https://arxiv.org/abs/2502.06786">https://arxiv.org/abs/2502.06786</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=43069048">https://news.ycombinator.com/item?id=43069048</a></p>
<p>Points: 2</p>
<p># Comments: 0</p>
]]></description><pubDate>Sun, 16 Feb 2025 16:04:06 +0000</pubDate><link>https://arxiv.org/abs/2502.06786</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=43069048</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=43069048</guid></item><item><title><![CDATA[1-Bit AI Infrastructure]]></title><description><![CDATA[
<p>Article URL: <a href="https://arxiv.org/abs/2410.16144">https://arxiv.org/abs/2410.16144</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=42147252">https://news.ycombinator.com/item?id=42147252</a></p>
<p>Points: 157</p>
<p># Comments: 30</p>
]]></description><pubDate>Fri, 15 Nov 2024 14:28:23 +0000</pubDate><link>https://arxiv.org/abs/2410.16144</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=42147252</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=42147252</guid></item><item><title><![CDATA[New comment by galeos in "BERTs Are Generative In-Context Learners"]]></title><description><![CDATA[
<p>My understanding is that BERT can still outperform LLMs for sentiment classification?</p>
]]></description><pubDate>Thu, 14 Nov 2024 12:35:09 +0000</pubDate><link>https://news.ycombinator.com/item?id=42135608</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=42135608</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=42135608</guid></item><item><title><![CDATA[Microsoft BitNet: inference framework for 1-bit LLMs]]></title><description><![CDATA[
<p>Article URL: <a href="https://github.com/microsoft/BitNet">https://github.com/microsoft/BitNet</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=41877609">https://news.ycombinator.com/item?id=41877609</a></p>
<p>Points: 173</p>
<p># Comments: 33</p>
]]></description><pubDate>Fri, 18 Oct 2024 09:10:36 +0000</pubDate><link>https://github.com/microsoft/BitNet</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=41877609</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=41877609</guid></item><item><title><![CDATA[Apollo to offer Intel multibillion-dollar investment]]></title><description><![CDATA[
<p>Article URL: <a href="https://www.bloomberg.com/news/articles/2024-09-22/apollo-is-said-to-offer-multibillion-dollar-investment-in-intel">https://www.bloomberg.com/news/articles/2024-09-22/apollo-is-said-to-offer-multibillion-dollar-investment-in-intel</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=41620137">https://news.ycombinator.com/item?id=41620137</a></p>
<p>Points: 5</p>
<p># Comments: 3</p>
]]></description><pubDate>Sun, 22 Sep 2024 21:14:42 +0000</pubDate><link>https://www.bloomberg.com/news/articles/2024-09-22/apollo-is-said-to-offer-multibillion-dollar-investment-in-intel</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=41620137</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=41620137</guid></item><item><title><![CDATA[Fine-Tuning LLMs to 1.58bit]]></title><description><![CDATA[
<p>Article URL: <a href="https://huggingface.co/blog/1_58_llm_extreme_quantization">https://huggingface.co/blog/1_58_llm_extreme_quantization</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=41581068">https://news.ycombinator.com/item?id=41581068</a></p>
<p>Points: 52</p>
<p># Comments: 3</p>
]]></description><pubDate>Wed, 18 Sep 2024 15:33:23 +0000</pubDate><link>https://huggingface.co/blog/1_58_llm_extreme_quantization</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=41581068</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=41581068</guid></item><item><title><![CDATA[Evidence of dark oxygen production at the abyssal seafloor]]></title><description><![CDATA[
<p>Article URL: <a href="https://www.nature.com/articles/s41561-024-01480-8">https://www.nature.com/articles/s41561-024-01480-8</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=41051941">https://news.ycombinator.com/item?id=41051941</a></p>
<p>Points: 9</p>
<p># Comments: 0</p>
]]></description><pubDate>Tue, 23 Jul 2024 23:04:26 +0000</pubDate><link>https://www.nature.com/articles/s41561-024-01480-8</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=41051941</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=41051941</guid></item><item><title><![CDATA[Lamini Memory Tuning: 10x Fewer Hallucinations]]></title><description><![CDATA[
<p>Article URL: <a href="https://www.lamini.ai/blog/lamini-memory-tuning">https://www.lamini.ai/blog/lamini-memory-tuning</a></p>
<p>Comments URL: <a href="https://news.ycombinator.com/item?id=40675577">https://news.ycombinator.com/item?id=40675577</a></p>
<p>Points: 128</p>
<p># Comments: 57</p>
]]></description><pubDate>Thu, 13 Jun 2024 22:29:40 +0000</pubDate><link>https://www.lamini.ai/blog/lamini-memory-tuning</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=40675577</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=40675577</guid></item><item><title><![CDATA[New comment by galeos in "Nvidia Conquers Latest AI Tests"]]></title><description><![CDATA[
<p>These are MLPerf training results. I think current ternary quantization research is focused more on speeding up inference?</p>
]]></description><pubDate>Thu, 13 Jun 2024 15:48:03 +0000</pubDate><link>https://news.ycombinator.com/item?id=40671099</link><dc:creator>galeos</dc:creator><comments>https://news.ycombinator.com/item?id=40671099</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=40671099</guid></item></channel></rss>