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Dash Remover<p>AI coding tools: autocomplete your thoughts, suggest the wrong import, hallucinate a SQL injection, and then write a Medium post about it. 📉🧠 <a href="https://mastodon.social/tags/Productivity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Productivity</span></a> <a href="https://mastodon.social/tags/AIdev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIdev</span></a></p>
ENTER.CO<p><a href="https://mastodon.social/tags/PorSiTeLoPerdiste" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PorSiTeLoPerdiste</span></a> La IA paga como Hollywood: ingenieros ya ganan hasta $41.500 millones al año en plena guerra por el talento <a href="https://www.enter.co/especiales/dev/la-ia-paga-como-hollywood-ingenieros-ya-ganan-hasta-41-500-millones-al-ano-en-plena-guerra-por-el-talento/?utm_source=dlvr.it&amp;utm_medium=mastodon" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">enter.co/especiales/dev/la-ia-</span><span class="invisible">paga-como-hollywood-ingenieros-ya-ganan-hasta-41-500-millones-al-ano-en-plena-guerra-por-el-talento/?utm_source=dlvr.it&amp;utm_medium=mastodon</span></a> <a href="https://mastodon.social/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> <a href="https://mastodon.social/tags/inteligenciaartificial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inteligenciaartificial</span></a> <a href="https://mastodon.social/tags/Meta" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Meta</span></a></p>
ENTER.CO<p>La IA paga como Hollywood: ingenieros ya ganan hasta $41.500 millones al año en plena guerra por el talento <a href="https://www.enter.co/especiales/dev/la-ia-paga-como-hollywood-ingenieros-ya-ganan-hasta-41-500-millones-al-ano-en-plena-guerra-por-el-talento/?utm_source=dlvr.it&amp;utm_medium=mastodon" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">enter.co/especiales/dev/la-ia-</span><span class="invisible">paga-como-hollywood-ingenieros-ya-ganan-hasta-41-500-millones-al-ano-en-plena-guerra-por-el-talento/?utm_source=dlvr.it&amp;utm_medium=mastodon</span></a> <a href="https://mastodon.social/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> <a href="https://mastodon.social/tags/inteligenciaartificial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inteligenciaartificial</span></a> <a href="https://mastodon.social/tags/Meta" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Meta</span></a></p>
Charlie McHenry<p>Google's new Agent Development Kit lets enterprises rapidly prototype and deploy AI agents without recoding - <a href="https://connectop.us/tags/AINews" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AINews</span></a> I’ve been using Claude 3.7, Gemini Pro and ChatGPT for months now, getting pretty good at prompt engineering and long iterative conversations. Built an entire marketing program for a client and generated business plan documents for another. Next step for me is to attempt to build an agent. I have a couple in mind. Could use a talented collaborator 😎 <a href="https://connectop.us/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> <a href="https://connectop.us/tags/AIAgents" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIAgents</span></a> <a href="https://connectop.us/tags/agents" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>agents</span></a> <a href="https://connectop.us/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> <a href="https://connectop.us/tags/AppDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AppDev</span></a> </p><p>Source: VentureBeat<br> <a href="https://search.app/p5QpwBL8C5YogqY68" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">search.app/p5QpwBL8C5YogqY68</span><span class="invisible"></span></a></p>
Grym<p>🎉 Today, I created Stormoji—a daily, shareable word game that uses emojis to spark creativity and storytelling.</p><p>This idea has been sitting in my notebook for a while, but thanks to my new AI dev assistant (Aider/Claude), the barrier to execution was finally low enough to bring it to life. 🚀</p><p><a href="https://stormoji.com/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">stormoji.com/</span><span class="invisible"></span></a><br><a href="https://github.com/grymoire7/stormoji" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">github.com/grymoire7/stormoji</span><span class="invisible"></span></a></p><p><a href="https://mastodon.social/tags/gamedev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>gamedev</span></a> <a href="https://mastodon.social/tags/aidev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>aidev</span></a> <a href="https://mastodon.social/tags/creativity" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>creativity</span></a> <a href="https://mastodon.social/tags/storytelling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>storytelling</span></a> <a href="https://mastodon.social/tags/emoji" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>emoji</span></a> <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/sideproject" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>sideproject</span></a></p>
Justin Jackson<p>Chris Sacca thinks, "We are super f*cked," and that "almost all coding is fucking useless" because AI can now build apps on demand.</p><p>I disagree.</p><p>I have yet to see AI generate a fully realized product that isn't full of bugs, bad UI, and poor UX.</p><p><a href="https://youtu.be/CU5Riqb4PBg?si=hVTxqLl9LtGGUGpq" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">youtu.be/CU5Riqb4PBg?si=hVTxqL</span><span class="invisible">l9LtGGUGpq</span></a></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/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> <a href="https://mastodon.social/tags/webdev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>webdev</span></a></p>
Richard MacManus<p>Amid the rise of AI-assisted coding and "agentic IDEs" like Bolt, Windsurf and others, I spoke with Netlify CEO <span class="h-card" translate="no"><a href="https://mastodon.social/@biilmann" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>biilmann</span></a></span> about a new design pattern he's coined: Agent Experience. <a href="https://thenewstack.io/beyond-dx-developers-must-now-learn-agent-experience-ax/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">thenewstack.io/beyond-dx-devel</span><span class="invisible">opers-must-now-learn-agent-experience-ax/</span></a> <a href="https://mastodon.social/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a></p>
Eric Maugendre<p><span class="h-card" translate="no"><a href="https://a.gup.pe/u/data" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>data</span></a></span> <span class="h-card" translate="no"><a href="https://a.gup.pe/u/datadon" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>datadon</span></a></span> 🧵</p><p>Accuracy! To counter regression dilution, a method is to add a constraint on the statistical modeling.<br>Regression Redress restrains bias by segregating the residual values.<br>My article: <a href="http://data.yt/kit/regression-redress.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">http://</span><span class="ellipsis">data.yt/kit/regression-redress</span><span class="invisible">.html</span></a></p><p><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/modeling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modeling</span></a> <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/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> <a href="https://hachyderm.io/tags/modelEvaluation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modelEvaluation</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/modelling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modelling</span></a> <a href="https://hachyderm.io/tags/dataLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>dataLearning</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/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/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/correctionRatio" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>correctionRatio</span></a> <a href="https://hachyderm.io/tags/ML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ML</span></a> <a href="https://hachyderm.io/tags/distributions" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>distributions</span></a> <a href="https://hachyderm.io/tags/accuracy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>accuracy</span></a> <a href="https://hachyderm.io/tags/RegressionRedress" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RegressionRedress</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/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RStats</span></a></p>
Eric Maugendre<p><span class="h-card" translate="no"><a href="https://a.gup.pe/u/data" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>data</span></a></span> <span class="h-card" translate="no"><a href="https://a.gup.pe/u/datadon" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>datadon</span></a></span> 🧵</p><p>How to assess a statistical model?<br>How to choose between variables?</p><p>Pearson's <a href="https://hachyderm.io/tags/correlation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>correlation</span></a> is irrelevant if you suspect that the relationship is not a straight line.</p><p>If monotonic relationship:<br>"<a href="https://hachyderm.io/tags/Spearman" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Spearman</span></a>’s rho is particularly useful for small samples where weak correlations are expected, as it can detect subtle monotonic trends." It is "widespread across disciplines where the measurement precision is not guaranteed".<br>"<a href="https://hachyderm.io/tags/Kendall" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Kendall</span></a>’s Tau-b is less affected [than Spearman’s rho] by outliers in the data, making it a robust option for datasets with extreme values."<br>Ref: <a href="https://statisticseasily.com/kendall-tau-b-vs-spearman/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">statisticseasily.com/kendall-t</span><span class="invisible">au-b-vs-spearman/</span></a></p><p><a href="https://hachyderm.io/tags/normality" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>normality</span></a> <a href="https://hachyderm.io/tags/normalDistribution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>normalDistribution</span></a> <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/dataDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>dataDev</span></a> <a href="https://hachyderm.io/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> <a href="https://hachyderm.io/tags/ML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ML</span></a> <a href="https://hachyderm.io/tags/modelEvaluation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modelEvaluation</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/modelling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modelling</span></a> <a href="https://hachyderm.io/tags/dataLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>dataLearning</span></a> <a href="https://hachyderm.io/tags/featureEngineering" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>featureEngineering</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/modeling" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>modeling</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/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/correctionRatio" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>correctionRatio</span></a> <a href="https://hachyderm.io/tags/ML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ML</span></a> <a href="https://hachyderm.io/tags/Pearson" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Pearson</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/regressionRedress" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>regressionRedress</span></a> <a href="https://hachyderm.io/tags/distributions" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>distributions</span></a></p>
Eric Maugendre<p><span class="h-card" translate="no"><a href="https://a.gup.pe/u/data" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>data</span></a></span> <span class="h-card" translate="no"><a href="https://a.gup.pe/u/datadon" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>datadon</span></a></span> 🧵</p><p>Redressing <a href="https://hachyderm.io/tags/Bias" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Bias</span></a>: "Correlation Constraints for Regression Models":<br>Treder et al (2021) <a href="https://doi.org/10.3389/fpsyt.2021.615754" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.3389/fpsyt.2021.615</span><span class="invisible">754</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/linearRegression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>linearRegression</span></a> <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/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/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/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/correctionRatio" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>correctionRatio</span></a> <a href="https://hachyderm.io/tags/skLearn" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>skLearn</span></a> <a href="https://hachyderm.io/tags/scikitLearn" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>scikitLearn</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/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</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>
Eric Maugendre<p><span class="h-card" translate="no"><a href="https://a.gup.pe/u/datadon" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>datadon</span></a></span></p><p><a href="https://hachyderm.io/tags/Lasso" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Lasso</span></a> <a href="https://hachyderm.io/tags/LinearRegression" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LinearRegression</span></a> "is useful in some contexts due to its tendency to prefer solutions with fewer non-zero coefficients, effectively reducing the number of features upon which the given solution is dependent"</p><p><a href="https://scikit-learn.org/stable/modules/linear_model.html#lasso" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">scikit-learn.org/stable/module</span><span class="invisible">s/linear_model.html#lasso</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/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> <a href="https://hachyderm.io/tags/ML" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ML</span></a> <a href="https://hachyderm.io/tags/sklearn" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>sklearn</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/interpretability" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>interpretability</span></a></p>
Eric Maugendre<p><span class="h-card" translate="no"><a href="https://a.gup.pe/u/data" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>data</span></a></span> "practitioners can leverage <a href="https://hachyderm.io/tags/LASSO" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LASSO</span></a> regression to construct more interpretable and predictive models that excel in scenarios involving high-dimensional data and intricate feature relationships."</p><p><a href="https://datasciencedecoded.com/posts/12_LASSO_Regression_Feature_Selection_Predictive_Models" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">datasciencedecoded.com/posts/1</span><span class="invisible">2_LASSO_Regression_Feature_Selection_Predictive_Models</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/interpretability" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>interpretability</span></a> <a href="https://hachyderm.io/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a></p>
ENTER.CO<p><a href="https://mastodon.social/tags/PorSiTeLoPerdiste" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PorSiTeLoPerdiste</span></a> Crean inteligencia artificial que descifra tu personalidad con base en tu cuenta de X (twitter): así funciona <a href="https://www.enter.co/especiales/dev/crean-inteligencia-artificial-que-descifra-tu-personalidad-con-base-en-tu-cuenta-de-x-twitter-asi-funciona/?utm_source=dlvr.it&amp;utm_medium=mastodon" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">enter.co/especiales/dev/crean-</span><span class="invisible">inteligencia-artificial-que-descifra-tu-personalidad-con-base-en-tu-cuenta-de-x-twitter-asi-funciona/?utm_source=dlvr.it&amp;utm_medium=mastodon</span></a> <a href="https://mastodon.social/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> <a href="https://mastodon.social/tags/inteligenciaartificial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inteligenciaartificial</span></a> <a href="https://mastodon.social/tags/Twitter" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Twitter</span></a></p>
ENTER.CO<p>Crean inteligencia artificial que descifra tu personalidad con base en tu cuenta de X (twitter): así funciona <a href="https://www.enter.co/especiales/dev/crean-inteligencia-artificial-que-descifra-tu-personalidad-con-base-en-tu-cuenta-de-x-twitter-asi-funciona/?utm_source=dlvr.it&amp;utm_medium=mastodon" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">enter.co/especiales/dev/crean-</span><span class="invisible">inteligencia-artificial-que-descifra-tu-personalidad-con-base-en-tu-cuenta-de-x-twitter-asi-funciona/?utm_source=dlvr.it&amp;utm_medium=mastodon</span></a> <a href="https://mastodon.social/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> <a href="https://mastodon.social/tags/inteligenciaartificial" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inteligenciaartificial</span></a> <a href="https://mastodon.social/tags/Twitter" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Twitter</span></a></p>
Carol Chen<p>Summer Olympics soon in <a href="https://mastodon.org.uk/tags/Paris" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Paris</span></a>, expecting millions of visitors. CDG is the largest airport in Europe (in size) and second busiest (behind LHR). I may have clocked more steps in <a href="https://mastodon.org.uk/tags/CDG" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CDG</span></a> than in Paris city on this trip 😆</p><p>Anyway just wanted to say, hyvää juhannusta! Happy <a href="https://mastodon.org.uk/tags/midsummer" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>midsummer</span></a>!</p><p>(Even though I was in Paris for <a href="https://mastodon.org.uk/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> this week, I hardly saw anything in the city aside from the conference venue, meetup venue, and my hotel. Need to return for a proper visit sometime but maybe after the Olympics..)</p>
OpenUK<p>OpenUK AI Advisory Board member and Stability AI head of policy, Ben Brooks discussing "protecting open innovation in future regulation in AI" Paris today at The Linux Foundation's <a href="https://hachyderm.io/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> <br><a href="https://hachyderm.io/tags/openuk" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openuk</span></a> <a href="https://hachyderm.io/tags/opensourceai" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>opensourceai</span></a> <a href="https://hachyderm.io/tags/opensource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>opensource</span></a> <a href="https://hachyderm.io/tags/opensourcesoftware" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>opensourcesoftware</span></a> <a href="https://hachyderm.io/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a></p>
julia ferraioli<p>It's a great time to start thinking about modernizing libraries like lapack and blas. Yes FORTRAN is very performant, well-tested, and widely used. But our use cases have evolved, as has our infrastructure. </p><p>A tall task, of course, but inertia can be overcome. <a href="https://floss.social/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a></p>
julia ferraioli<p>Confused by the assertion that tooling for <a href="https://floss.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MachineLearning</span></a> didn't exist prior to ~2012. There was plenty of <a href="https://floss.social/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a> tooling available and in wide use way before then!!! <a href="https://floss.social/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a></p>
julia ferraioli<p>Are you attending AI_dev this week?</p><p>Make sure to attend the talk that <span class="h-card" translate="no"><a href="https://social.afront.org/@spot" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>spot</span></a></span> and I are giving on Thursday about what unexpected benefits we might see if we embrace a fully transparent view of what counts as open source artificial intelligence 🧠🚀🎉</p><p><a href="https://floss.social/tags/AIDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AIDev</span></a> <a href="https://floss.social/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenSource</span></a> <a href="https://floss.social/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ArtificialIntelligence</span></a><br><a href="https://sched.co/1c1mY" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">sched.co/1c1mY</span><span class="invisible"></span></a></p>