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#inference

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5h15h<p>inference, not training, represents an increasing majority of <a href="https://techhub.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a>’s energy demands and will continue to do so in the near future. It’s now estimated that 80–90% of computing power for AI is used for <a href="https://techhub.social/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://www.technologyreview.com/2025/05/20/1116327/ai-energy-usage-climate-footprint-big-tech/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">technologyreview.com/2025/05/2</span><span class="invisible">0/1116327/ai-energy-usage-climate-footprint-big-tech/</span></a></p>
Winbuzzer<p>New DFloat11 Technique Offers 30% Lossless Compression for LLMs, Easing Hardware Demands</p><p><a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://mastodon.social/tags/AIResearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIResearch</span></a> <a href="https://mastodon.social/tags/DFloat11" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DFloat11</span></a> <a href="https://mastodon.social/tags/LLMs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLMs</span></a> <a href="https://mastodon.social/tags/LLMcompression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLMcompression</span></a> <a href="https://mastodon.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> <a href="https://mastodon.social/tags/DeepLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DeepLearning</span></a> <a href="https://mastodon.social/tags/BF16" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>BF16</span></a> <a href="https://mastodon.social/tags/Inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Inference</span></a> <a href="https://mastodon.social/tags/RiceUniversity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RiceUniversity</span></a> <a href="https://mastodon.social/tags/xMADai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>xMADai</span></a></p><p><a href="https://winbuzzer.com/2025/04/27/new-dfloat11-technique-offers-30-lossless-compression-for-llms-easing-hardware-demands-xcxwbn/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">winbuzzer.com/2025/04/27/new-d</span><span class="invisible">float11-technique-offers-30-lossless-compression-for-llms-easing-hardware-demands-xcxwbn/</span></a></p>
☮ ♥ ♬ 🧑‍💻<p>Day 19 cont 🙏⛪️🕍🕌⛩️🛕 💽🧑‍💻</p><p>“The <a href="https://ioc.exchange/tags/LiberalParty" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LiberalParty</span></a> has accidentally left part of its email provider’s <a href="https://ioc.exchange/tags/subscriber" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>subscriber</span></a> details exposed, revealing the types of <a href="https://ioc.exchange/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>data</span></a> harvested by the party during the <a href="https://ioc.exchange/tags/election" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>election</span></a> campaign.</p><p>This gives rare <a href="https://ioc.exchange/tags/insight" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>insight</span></a> into some of the specific kinds of data the party is keeping on voters, including whether they are “predicted Chinese”, “predicted Jewish”, a “strong Liberal” and other <a href="https://ioc.exchange/tags/PersonalInformation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PersonalInformation</span></a>.”</p><p><a href="https://ioc.exchange/tags/AusPol" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AusPol</span></a> / <a href="https://ioc.exchange/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataScience</span></a> / <a href="https://ioc.exchange/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> / <a href="https://ioc.exchange/tags/voters" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>voters</span></a> / <a href="https://ioc.exchange/tags/Liberal" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Liberal</span></a> / <a href="https://ioc.exchange/tags/LNP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LNP</span></a> / <a href="https://ioc.exchange/tags/Nationals" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Nationals</span></a> &lt;<a href="https://www.crikey.com.au/2025/04/17/victorian-liberals-data-exposed-email-mailchimp-federal-election-crikey/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">crikey.com.au/2025/04/17/victo</span><span class="invisible">rian-liberals-data-exposed-email-mailchimp-federal-election-crikey/</span></a>&gt;</p>
☮ ♥ ♬ 🧑‍💻<p>“How ‘inference’ is driving competition to Nvidia’s <a href="https://ioc.exchange/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> chip dominance”</p><p><a href="https://ioc.exchange/tags/NVidia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NVidia</span></a> / <a href="https://ioc.exchange/tags/reasoning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>reasoning</span></a> / <a href="https://ioc.exchange/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> &lt;<a href="https://archive.md/AYHs7" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">archive.md/AYHs7</span><span class="invisible"></span></a>&gt;</p>
Paul Giulan<p>How to <a href="https://federate.social/tags/backdoor" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>backdoor</span></a> a <a href="https://federate.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLM</span></a> </p><p><a href="https://blog.sshh.io/p/how-to-backdoor-large-language-models" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">blog.sshh.io/p/how-to-backdoor</span><span class="invisible">-large-language-models</span></a></p><p><a href="https://federate.social/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a> <a href="https://federate.social/tags/DeepSeek" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DeepSeek</span></a> <a href="https://federate.social/tags/Infrastructure" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Infrastructure</span></a> <a href="https://federate.social/tags/Inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Inference</span></a> <a href="https://federate.social/tags/Embedded" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Embedded</span></a> <a href="https://federate.social/tags/HuggingFace" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>HuggingFace</span></a> <a href="https://federate.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://federate.social/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ArtificialIntelligence</span></a> <a href="https://federate.social/tags/ChatBot" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ChatBot</span></a></p>
Simone<p>How is <a href="https://mastodon.social/tags/censorship" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>censorship</span></a> implemented in <a href="https://mastodon.social/tags/deepseek" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deepseek</span></a>? A link to <a href="https://mastodon.social/tags/wikipedia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>wikipedia</span></a> referring to the <a href="https://mastodon.social/tags/tienanmen" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tienanmen</span></a> square can spark an <a href="https://mastodon.social/tags/ethical" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ethical</span></a> judgment on the <a href="https://mastodon.social/tags/chinese" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>chinese</span></a> government. Of course it dare not speak its name 😉 <br>Since censorship is active also on locally run model, probably it is implemented toward the last steps of <a href="https://mastodon.social/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a>, while the training set was hastily used and not “curated” for censorship. <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://mastodon.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LLM</span></a></p>
Eric Maugendre<p>"In real life, we weigh the anticipated consequences of the decisions that we are about to make. That approach is much more rational than limiting the percentage of making the error of one kind in an artificial (null hypothesis) setting or using a measure of evidence for each model as the weight."<br>Longford (2005) <a href="http://www.stat.columbia.edu/~gelman/stuff_for_blog/longford.pdf" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">http://www.</span><span class="ellipsis">stat.columbia.edu/~gelman/stuf</span><span class="invisible">f_for_blog/longford.pdf</span></a></p><p><a href="https://hachyderm.io/tags/modeling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modeling</span></a> <a href="https://hachyderm.io/tags/nullHypothesis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>nullHypothesis</span></a> <a href="https://hachyderm.io/tags/probability" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>probability</span></a> <a href="https://hachyderm.io/tags/probabilities" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>probabilities</span></a> <a href="https://hachyderm.io/tags/pValues" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>pValues</span></a> <a href="https://hachyderm.io/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a> <a href="https://hachyderm.io/tags/stats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stats</span></a> <a href="https://hachyderm.io/tags/statisticalLiteracy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statisticalLiteracy</span></a> <a href="https://hachyderm.io/tags/bias" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bias</span></a> <a href="https://hachyderm.io/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://hachyderm.io/tags/modelling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modelling</span></a> <a href="https://hachyderm.io/tags/regression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>regression</span></a> <a href="https://hachyderm.io/tags/linearRegression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>linearRegression</span></a></p>
Eric Maugendre<p>Feature Selection in Python; a script ready to use: <a href="https://johfischer.com/2021/08/06/correlation-based-feature-selection-in-python-from-scratch/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">johfischer.com/2021/08/06/corr</span><span class="invisible">elation-based-feature-selection-in-python-from-scratch/</span></a></p><p><a href="https://hachyderm.io/tags/interpretability" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>interpretability</span></a> <a href="https://hachyderm.io/tags/featureSelection" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>featureSelection</span></a> <a href="https://hachyderm.io/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>python</span></a> <a href="https://hachyderm.io/tags/probability" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>probability</span></a> <a href="https://hachyderm.io/tags/probabilities" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>probabilities</span></a> <a href="https://hachyderm.io/tags/bigData" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bigData</span></a> <a href="https://hachyderm.io/tags/classification" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>classification</span></a> <a href="https://hachyderm.io/tags/linearRegression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>linearRegression</span></a> <a href="https://hachyderm.io/tags/regression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>regression</span></a> <a href="https://hachyderm.io/tags/Schusterbauer" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Schusterbauer</span></a> <a href="https://hachyderm.io/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://hachyderm.io/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a></p>
Judith van Stegeren<p>Many companies are currently scrambling for ML infra engineers. They need people that know how to manage AI infrastructure, and that can seriously speed up training and inference with specialized tooling like vLLM, Triton, TensorRT, Torchtune, etc.</p><p><a href="https://fosstodon.org/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://fosstodon.org/tags/training" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>training</span></a> <a href="https://fosstodon.org/tags/genai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>genai</span></a> <a href="https://fosstodon.org/tags/triton" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>triton</span></a> <a href="https://fosstodon.org/tags/vllm" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vllm</span></a> <a href="https://fosstodon.org/tags/pytorch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>pytorch</span></a> <a href="https://fosstodon.org/tags/torchtune" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>torchtune</span></a> <a href="https://fosstodon.org/tags/tensorrt" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tensorrt</span></a> <a href="https://fosstodon.org/tags/nvidia" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>nvidia</span></a></p>
Eric Maugendre<p>"Extract Year from a datetime column", by Piyush Raj: <a href="https://datascienceparichay.com/article/pandas-extract-year-from-datetime-column/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">datascienceparichay.com/articl</span><span class="invisible">e/pandas-extract-year-from-datetime-column/</span></a></p><p><a href="https://hachyderm.io/tags/dataDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>dataDev</span></a> <a href="https://hachyderm.io/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a> <a href="https://hachyderm.io/tags/Pandas" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Pandas</span></a> <a href="https://hachyderm.io/tags/timeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeSeries</span></a> <a href="https://hachyderm.io/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>data</span></a> <a href="https://hachyderm.io/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://hachyderm.io/tags/dataAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>dataAnalysis</span></a> <a href="https://hachyderm.io/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a> <a href="https://hachyderm.io/tags/stats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>stats</span></a></p>
Eric Maugendre<p>An easy guide to predict possible future quantities, by Mercy Kibet: <a href="https://www.influxdata.com/blog/guide-regression-analysis-time-series-data/#heading0" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">influxdata.com/blog/guide-regr</span><span class="invisible">ession-analysis-time-series-data/#heading0</span></a></p><p><a href="https://hachyderm.io/tags/timeSeries" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>timeSeries</span></a> <a href="https://hachyderm.io/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>data</span></a> <a href="https://hachyderm.io/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://hachyderm.io/tags/linearRegression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>linearRegression</span></a> <a href="https://hachyderm.io/tags/dataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>dataScience</span></a> <a href="https://hachyderm.io/tags/futures" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>futures</span></a> <a href="https://hachyderm.io/tags/money" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>money</span></a> <a href="https://hachyderm.io/tags/trends" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>trends</span></a> <a href="https://hachyderm.io/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Python</span></a></p>
💧🌏 Greg Cocks<p>The Case For Remote Sensing Of Individual Plants<br>--<br><a href="https://doi.org/10.1002/ajb2.1347" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">doi.org/10.1002/ajb2.1347</span><span class="invisible"></span></a> &lt;-- shared short article<br>-- <br><a href="https://techhub.social/tags/GIS" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GIS</span></a> <a href="https://techhub.social/tags/spatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>spatial</span></a> <a href="https://techhub.social/tags/mapping" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>mapping</span></a> <a href="https://techhub.social/tags/UAV" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>UAV</span></a> <a href="https://techhub.social/tags/drone" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>drone</span></a> <a href="https://techhub.social/tags/drones" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>drones</span></a> <a href="https://techhub.social/tags/LiDAR" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LiDAR</span></a> <a href="https://techhub.social/tags/photosynthesis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>photosynthesis</span></a> <a href="https://techhub.social/tags/imagingspectroscopy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>imagingspectroscopy</span></a> <a href="https://techhub.social/tags/trees" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>trees</span></a> <a href="https://techhub.social/tags/plants" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>plants</span></a> <a href="https://techhub.social/tags/vegetation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>vegetation</span></a> <a href="https://techhub.social/tags/forest" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>forest</span></a> <a href="https://techhub.social/tags/monitoring" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>monitoring</span></a> <a href="https://techhub.social/tags/identification" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>identification</span></a> <a href="https://techhub.social/tags/satellite" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>satellite</span></a> <a href="https://techhub.social/tags/cubesat" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cubesat</span></a> <a href="https://techhub.social/tags/landsurface" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>landsurface</span></a> <a href="https://techhub.social/tags/landcover" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>landcover</span></a> <a href="https://techhub.social/tags/spatialanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>spatialanalysis</span></a> # interpretation <a href="https://techhub.social/tags/biology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>biology</span></a> <a href="https://techhub.social/tags/scale" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>scale</span></a> <a href="https://techhub.social/tags/sensor" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>sensor</span></a> <a href="https://techhub.social/tags/technology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>technology</span></a> <a href="https://techhub.social/tags/fieldwork" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fieldwork</span></a> <a href="https://techhub.social/tags/fieldplatforms" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fieldplatforms</span></a> <a href="https://techhub.social/tags/spatiotemporal" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>spatiotemporal</span></a> <a href="https://techhub.social/tags/resources" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>resources</span></a> <a href="https://techhub.social/tags/naturalresources" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>naturalresources</span></a> <a href="https://techhub.social/tags/phenology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>phenology</span></a> <a href="https://techhub.social/tags/photogrammetry" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>photogrammetry</span></a> <a href="https://techhub.social/tags/plantbiology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>plantbiology</span></a> <a href="https://techhub.social/tags/model" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>model</span></a> <a href="https://techhub.social/tags/modeling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modeling</span></a> <a href="https://techhub.social/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://techhub.social/tags/remotesensing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>remotesensing</span></a></p>
Boiling Steam<p>PowerInfer: Fast Large Language Model Serving with a Consumer-Grade GPU [pdf]: <a href="https://ipads.se.sjtu.edu.cn/_media/publications/powerinfer-20231219.pdf" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">ipads.se.sjtu.edu.cn/_media/pu</span><span class="invisible">blications/powerinfer-20231219.pdf</span></a> <a href="https://mastodon.cloud/tags/linux" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>linux</span></a> <a href="https://mastodon.cloud/tags/update" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>update</span></a> <a href="https://mastodon.cloud/tags/foss" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>foss</span></a> <a href="https://mastodon.cloud/tags/release" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>release</span></a> <a href="https://mastodon.cloud/tags/powerinfer" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>powerinfer</span></a> <a href="https://mastodon.cloud/tags/faster" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>faster</span></a> <a href="https://mastodon.cloud/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://mastodon.cloud/tags/cpu" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cpu</span></a> <a href="https://mastodon.cloud/tags/gpu" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gpu</span></a> <a href="https://mastodon.cloud/tags/hardware" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>hardware</span></a> <a href="https://mastodon.cloud/tags/llm" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llm</span></a></p>
Kenneth De Baets<p>Putting the F into FBD analysis: tree constraints or morphological data? <a href="https://doi.org/10.1111/pala.12679" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">doi.org/10.1111/pala.12679</span><span class="invisible"></span></a> <a href="https://ecoevo.social/tags/paleobiology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>paleobiology</span></a> <a href="https://ecoevo.social/tags/paleontology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>paleontology</span></a> <a href="https://ecoevo.social/tags/EvolutionaryBiology" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>EvolutionaryBiology</span></a> <a href="https://ecoevo.social/tags/fossils" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fossils</span></a> <a href="https://ecoevo.social/tags/fossil" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fossil</span></a> <a href="https://ecoevo.social/tags/birth" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>birth</span></a> <a href="https://ecoevo.social/tags/death" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>death</span></a> <a href="https://ecoevo.social/tags/simulation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>simulation</span></a> <a href="https://ecoevo.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bayesian</span></a> <a href="https://ecoevo.social/tags/phylogeny" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>phylogeny</span></a> <a href="https://ecoevo.social/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a></p>
IT News<p>IBM has made a new, highly efficient AI processor - Enlarge (credit: IBM) </p><p>As the utility of AI systems has grown d... - <a href="https://arstechnica.com/?p=1977529" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">arstechnica.com/?p=1977529</span><span class="invisible"></span></a> <a href="https://schleuss.online/tags/computerscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>computerscience</span></a> <a href="https://schleuss.online/tags/neuralnetwork" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>neuralnetwork</span></a> <a href="https://schleuss.online/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://schleuss.online/tags/science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>science</span></a> <a href="https://schleuss.online/tags/energy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>energy</span></a> <a href="https://schleuss.online/tags/green" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>green</span></a> <a href="https://schleuss.online/tags/ibm" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ibm</span></a> <a href="https://schleuss.online/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ai</span></a></p>
Steve Thompson PhD<p>GOOD! A great example of 'just because we can doesn't mean we should.'</p><p>"New York bans facial recognition in schools after report finds risks outweigh potential benefits"</p><p><a href="https://apnews.com/article/facial-recognition-banned-new-york-schools-ddd35e004254d316beabf70453b1a6a2" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">apnews.com/article/facial-reco</span><span class="invisible">gnition-banned-new-york-schools-ddd35e004254d316beabf70453b1a6a2</span></a></p><p>"New York state banned the use of facial recognition technology in schools Wednesday, following a report that concluded the risks to student privacy and civil rights outweigh potential security benefits."</p><p><a href="https://mastodon.social/tags/privacy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>privacy</span></a> <a href="https://mastodon.social/tags/identity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>identity</span></a> <a href="https://mastodon.social/tags/facialrecognition" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>facialrecognition</span></a> <a href="https://mastodon.social/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://mastodon.social/tags/tracking" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>tracking</span></a> <a href="https://mastodon.social/tags/surveillance" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>surveillance</span></a></p>
Philip John Gorinski<p>Thrilled to announce the Regular Expression Inference Challenge (REIC), with Mojtaba Valizadeh, Ignacio Iacobacci, Martin Berger.</p><p>REI is a supervised machine learning (<a href="https://qoto.org/tags/ML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ML</span></a>) and program synthesis task, and poses the problem of finding minimal regular expressions from examples: Given two finite sets of strings P and N and a cost function cost(⋅), the task is to generate an expression r that accepts all strings in P and rejects all strings in N, while no other such expression r' exists with cost(r')&lt;cost(r).</p><p>Turns out, this sort of inference seems to be really hard for current DL (<a href="https://qoto.org/tags/llms" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llms</span></a> ) approaches. Prompting StarChat-beta -- a SOTA large LM for code with 15.5B parameters -- yields extremely low results.<br>Even a fully supervised 300M parameter model, which we call ReGPT, only achieves around 14% precise and minimal expressions.</p><p>Check out our preprint on arXiv: <a href="https://arxiv.org/abs/2308.07899" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/abs/2308.07899</span><span class="invisible"></span></a><br>The challenge is available on CodaLab: <a href="https://codalab.lisn.upsaclay.fr/competitions/15096" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">codalab.lisn.upsaclay.fr/compe</span><span class="invisible">titions/15096</span></a></p><p>We formally define the problem, and provide training and validation data, as well as starter code for all our baselines.</p><p>We invite researchers anywhere to participate in tackling our challenge.</p><p><a href="https://qoto.org/tags/machinelearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>machinelearning</span></a> <a href="https://qoto.org/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://qoto.org/tags/challenge" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>challenge</span></a> <a href="https://qoto.org/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://qoto.org/tags/ML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ML</span></a> <a href="https://qoto.org/tags/llm" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llm</span></a> <a href="https://qoto.org/tags/llms" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llms</span></a> <a href="https://qoto.org/tags/huawei" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>huawei</span></a></p>
Victoria Stuart 🇨🇦 🏳️‍⚧️<p>... [click here, scroll up to see full thread]</p><p><a href="https://mastodon.social/tags/rationality" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>rationality</span></a> <a href="https://mastodon.social/tags/ethics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ethics</span></a> <a href="https://mastodon.social/tags/ReflexiveReasoning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ReflexiveReasoning</span></a> <a href="https://mastodon.social/tags/DeliberateReasoning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DeliberateReasoning</span></a> <a href="https://mastodon.social/tags/MathematicalReasoning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MathematicalReasoning</span></a> <a href="https://mastodon.social/tags/Minerva" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Minerva</span></a> <a href="https://mastodon.social/tags/FormalReasoning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FormalReasoning</span></a> <a href="https://mastodon.social/tags/knowledge" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>knowledge</span></a> <a href="https://mastodon.social/tags/WorldKnowledge" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>WorldKnowledge</span></a> <a href="https://mastodon.social/tags/modeling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modeling</span></a> <a href="https://mastodon.social/tags/SituationModeling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SituationModeling</span></a> <a href="https://mastodon.social/tags/SocialReasoning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>SocialReasoning</span></a> <a href="https://mastodon.social/tags/infohazardous" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>infohazardous</span></a> <a href="https://mastodon.social/tags/grounding" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>grounding</span></a> <a href="https://mastodon.social/tags/ContinuousGrounding" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ContinuousGrounding</span></a> <a href="https://mastodon.social/tags/misalignment" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>misalignment</span></a> <a href="https://mastodon.social/tags/transformers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>transformers</span></a> <a href="https://mastodon.social/tags/GPT" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GPT</span></a> <a href="https://mastodon.social/tags/GPT3" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GPT3</span></a> <a href="https://mastodon.social/tags/GPT4" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GPT4</span></a> <a href="https://mastodon.social/tags/VLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VLM</span></a> <a href="https://mastodon.social/tags/VisualLanguageModels" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>VisualLanguageModels</span></a> <a href="https://mastodon.social/tags/causality" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>causality</span></a> <a href="https://mastodon.social/tags/semantics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>semantics</span></a> <a href="https://mastodon.social/tags/agents" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>agents</span></a> <a href="https://mastodon.social/tags/EmbodiedAgents" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>EmbodiedAgents</span></a> <a href="https://mastodon.social/tags/curious" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>curious</span></a> <a href="https://mastodon.social/tags/curiousity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>curiousity</span></a> <a href="https://mastodon.social/tags/intent" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>intent</span></a> <a href="https://mastodon.social/tags/intentionality" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>intentionality</span></a> <a href="https://mastodon.social/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://mastodon.social/tags/ActiveInference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ActiveInference</span></a> <a href="https://mastodon.social/tags/metaphysics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>metaphysics</span></a> <a href="https://mastodon.social/tags/distraction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>distraction</span></a></p>
ExcelAnalytics<p>Great <a href="https://mastodon.world/tags/Excel" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Excel</span></a> calcChain <a href="https://mastodon.world/tags/forensics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>forensics</span></a> by <span class="h-card"><a href="https://mas.to/@datacolada" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>datacolada</span></a></span> <br><a href="https://mastodon.world/tags/Harvard" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Harvard</span></a> professor who studies honesty accused of <a href="https://mastodon.world/tags/falsifying" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>falsifying</span></a> <a href="https://mastodon.world/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>data</span></a> in <a href="https://mastodon.world/tags/studies" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>studies</span></a> <br><a href="https://amp.theguardian.com/education/2023/jun/25/harvard-professor-data-fraud" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">amp.theguardian.com/education/</span><span class="invisible">2023/jun/25/harvard-professor-data-fraud</span></a><br>The original blog from 2021 <a href="http://datacolada.org/98" rel="nofollow noopener" target="_blank"><span class="invisible">http://</span><span class="">datacolada.org/98</span><span class="invisible"></span></a> is followed by a 4 part blog<br><a href="https://datacolada.org/109" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="">datacolada.org/109</span><span class="invisible"></span></a></p><p><a href="https://mastodon.world/tags/excel" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>excel</span></a> <a href="https://mastodon.world/tags/msexcel" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>msexcel</span></a> <a href="https://mastodon.world/tags/dataquality" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>dataquality</span></a> <a href="https://mastodon.world/tags/fraud" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fraud</span></a> <a href="https://mastodon.world/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a> <a href="https://mastodon.world/tags/probability" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>probability</span></a> <a href="https://mastodon.world/tags/benfordslaw" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>benfordslaw</span></a> <a href="https://mastodon.world/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://mastodon.world/tags/patterns" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>patterns</span></a> <a href="https://mastodon.world/tags/analysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>analysis</span></a> <a href="https://mastodon.world/tags/audit" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>audit</span></a> <a href="https://mastodon.world/tags/behavioural" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>behavioural</span></a> <a href="https://mastodon.world/tags/behavioral" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>behavioral</span></a> <a href="https://mastodon.world/tags/science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>science</span></a> <a href="https://mastodon.world/tags/honesty" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>honesty</span></a> <a href="https://mastodon.world/tags/research" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>research</span></a> <a href="https://mastodon.world/tags/review" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>review</span></a> <a href="https://mastodon.world/tags/francescagino" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>francescagino</span></a> <br><a href="https://mastodon.world/tags/eusprig" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>eusprig</span></a> <a href="https://mastodon.world/tags/spreadsheet" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>spreadsheet</span></a> <a href="https://mastodon.world/tags/risk" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>risk</span></a></p><p><a href="https://mastodon.world/tags/lowercasehashtags" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>lowercasehashtags</span></a></p>
IT News<p>Why LLaMa Is A Big Deal - You might have heard about LLaMa or maybe you haven’t. Either way, what’s the big ... - <a href="https://hackaday.com/2023/03/22/why-llama-is-a-big-deal/" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">hackaday.com/2023/03/22/why-ll</span><span class="invisible">ama-is-a-big-deal/</span></a> <a href="https://schleuss.online/tags/artificialintelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>artificialintelligence</span></a> <a href="https://schleuss.online/tags/artificalintelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>artificalintelligence</span></a> <a href="https://schleuss.online/tags/inference" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inference</span></a> <a href="https://schleuss.online/tags/featured" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>featured</span></a> <a href="https://schleuss.online/tags/chatgpt" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>chatgpt</span></a> <a href="https://schleuss.online/tags/gpt" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gpt</span></a>-3 <a href="https://schleuss.online/tags/llama" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llama</span></a> <a href="https://schleuss.online/tags/llm" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>llm</span></a></p>
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