{"id":665,"date":"2019-11-09T17:29:13","date_gmt":"2019-11-09T17:29:13","guid":{"rendered":"https:\/\/datagradient.com\/?page_id=665"},"modified":"2020-03-05T09:53:39","modified_gmt":"2020-03-05T09:53:39","slug":"news","status":"publish","type":"page","link":"https:\/\/datasciencediscovery.com\/index.php\/news\/","title":{"rendered":"News"},"content":{"rendered":"\n<p>Catch up with the fast moving field of data science. Even for us it has been difficult to stay up to date with the latest news and developments in the industry. We are putting together some of the top sources such as MIT, NVIDIA, ARXIV and others. These articles are aggregated from well trusted sources in the community. We will continue to add more sources and refine the type of articles showcased here over time.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Data Science<\/h2>\n\n\n\n<p>The recent developments in the field of data science and AI. Sources: Explosion.ai, Rasa, fast.ai, MIT, Berkley, Uber, IBM and Google AI Blog and other trusted sources.<\/p>\n\n\n<div class=\"feedzy-41b89415b773e2454856b435fe9feb4d feedzy-rss\"><div class=\"rss_header\"><h2><a href=\"\" class=\"rss_title\" rel=\"noopener\"><\/a> <span class=\"rss_description\"> <\/span><\/h2><\/div><ul><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/beta.ellf.ai\/\" target=\"_blank\" rel=\" noopener\" title=\"Beta test our new product for agentic NLP development\" style=\"width:150px; height:150px;\"><span class=\"default\" style=\"background-image:url(https:\/\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/david-becker-V862kywlKkw-unsplash.jpg);\" title=\"Beta test our new product for agentic NLP development\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/david-becker-V862kywlKkw-unsplash.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/beta.ellf.ai\/\" target=\"_blank\" rel=\" noopener\">Beta test our new product for agentic NLP development<\/a><\/span><div class=\"rss_content\" style=\"\"><small>by <a href=\"\/\/beta.ellf.ai\" target=\"_blank\" title=\"beta.ellf.ai\">Explosion<\/a> on June 20, 2026 at 9:58 pm <\/small><p>We\u2019re looking for beta partners for Ellf: a platform and virtual assistant that makes your coding agent like Claude [&hellip;]<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/news.mit.edu\/2026\/better-way-to-model-metal-alloys-behavior-0619\" target=\"_blank\" rel=\" noopener\" title=\"A better way to model the behavior of metal alloys\" style=\"width:150px; height:150px;\"><span class=\"fetched\" style=\"background-image:  url('https:\/\/news.mit.edu\/sites\/default\/files\/styles\/news_article__cover_image__original\/public\/images\/202606\/MIT_Modeling-Metals-01a-press.jpg?itok=jBfWLvPh');\" title=\"A better way to model the behavior of metal alloys\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/news.mit.edu\/sites\/default\/files\/styles\/news_article__cover_image__original\/public\/images\/202606\/MIT_Modeling-Metals-01a-press.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/news.mit.edu\/2026\/better-way-to-model-metal-alloys-behavior-0619\" target=\"_blank\" rel=\" noopener\">A better way to model the behavior of metal alloys<\/a><\/span><div class=\"rss_content\" style=\"\"><small>by <a href=\"\/\/news.mit.edu\" target=\"_blank\" title=\"news.mit.edu\">Zach Winn | MIT News<\/a> on June 19, 2026 at 6:00 pm <\/small><p>MIT researchers\u2019 approach captures subtle atomic patterns, improving predictions of material properties.<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/news.mit.edu\/2026\/mit-media-future-tech-massachusetts-can-absolutely-lead\" target=\"_blank\" rel=\" noopener\" title=\"MIT in the media: For the future of tech, \" style=\"width:150px; height:150px;\" Massachusetts can absolutely><span class=\"fetched\" style=\"background-image:  url('https:\/\/news.mit.edu\/sites\/default\/files\/styles\/news_article__cover_image__original\/public\/images\/202606\/52094290589_762e9efbed_b%20(1).jpg?itok=zLilegey');\" title=\"MIT in the media: For the future of tech, &quot;Massachusetts can absolutely lead&quot;\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/news.mit.edu\/sites\/default\/files\/styles\/news_article__cover_image__original\/public\/images\/202606\/52094290589_762e9efbed_b%20(1).jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/news.mit.edu\/2026\/mit-media-future-tech-massachusetts-can-absolutely-lead\" target=\"_blank\" rel=\" noopener\">MIT in the media: For the future of tech, &#8220;Massachusetts can absolutely lead&#8221;<\/a><\/span><div class=\"rss_content\" style=\"\"><small>on June 18, 2026 at 4:00 am <\/small><p>Leaders, faculty across MIT discuss fostering innovation and talent in Greater Boston in special series of articles [&hellip;]<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/news.mit.edu\/2026\/game-theory-generalists-sometimes-win-out-over-specialists-0617\" target=\"_blank\" rel=\" noopener\" title=\"In game theory, generalists sometimes win out over specialists\" style=\"width:150px; height:150px;\"><span class=\"fetched\" style=\"background-image:  url('https:\/\/news.mit.edu\/sites\/default\/files\/styles\/news_article__cover_image__original\/public\/images\/202605\/mit-lids-game-theory.jpg?itok=VxYl6kBb');\" title=\"In game theory, generalists sometimes win out over specialists\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/news.mit.edu\/sites\/default\/files\/styles\/news_article__cover_image__original\/public\/images\/202605\/mit-lids-game-theory.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/news.mit.edu\/2026\/game-theory-generalists-sometimes-win-out-over-specialists-0617\" target=\"_blank\" rel=\" noopener\">In game theory, generalists sometimes win out over specialists<\/a><\/span><div class=\"rss_content\" style=\"\"><small>by <a href=\"\/\/news.mit.edu\" target=\"_blank\" title=\"news.mit.edu\">Steve Nadis | MIT Laboratory for Information and Decision Systems<\/a> on June 17, 2026 at 7:20 pm <\/small><p>Researchers show that for certain kinds of games, an overlooked class of algorithms performs much better than expected.<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/news.mit.edu\/2026\/could-ai-tell-you-where-you-left-your-keys-0617\" target=\"_blank\" rel=\" noopener\" title=\"Could AI tell you where you left your keys?\" style=\"width:150px; height:150px;\"><span class=\"fetched\" style=\"background-image:  url('https:\/\/news.mit.edu\/sites\/default\/files\/styles\/news_article__cover_image__original\/public\/images\/202606\/MIT-DescribeAnything-01-press.jpg?itok=RxMov68e');\" title=\"Could AI tell you where you left your keys?\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/news.mit.edu\/sites\/default\/files\/styles\/news_article__cover_image__original\/public\/images\/202606\/MIT-DescribeAnything-01-press.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/news.mit.edu\/2026\/could-ai-tell-you-where-you-left-your-keys-0617\" target=\"_blank\" rel=\" noopener\">Could AI tell you where you left your keys?<\/a><\/span><div class=\"rss_content\" style=\"\"><small>by <a href=\"\/\/news.mit.edu\" target=\"_blank\" title=\"news.mit.edu\">Adam Zewe | MIT News<\/a> on June 17, 2026 at 4:00 am <\/small><p>A new spatial memory system for robots efficiently captures details about the objects they see while exploring their [&hellip;]<\/p><\/div><\/li><\/ul> <\/div><style type=\"text\/css\" media=\"all\">.feedzy-rss .rss_item .rss_image{float:left;position:relative;border:none;text-decoration:none;max-width:100%}.feedzy-rss .rss_item .rss_image span{display:inline-block;position:absolute;width:100%;height:100%;background-position:50%;background-size:cover}.feedzy-rss .rss_item .rss_image{margin:.3em 1em 0 0;content-visibility:auto}.feedzy-rss ul{list-style:none}.feedzy-rss ul li{display:inline-block}<\/style>\n\n\n<h2 class=\"wp-block-heading\">News<\/h2>\n\n\n<div class=\"feedzy-dc85bee917210dab29fbdd80a4ed6007 feedzy-rss\"><div class=\"rss_header\"><h2><a href=\"\" class=\"rss_title\" rel=\"noopener\"><\/a> <span class=\"rss_description\"> <\/span><\/h2><\/div><ul><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/news.google.com\/rss\/articles\/CBMiaEFVX3lxTFB2UGVGcFozcFZTQTNxR2IzOXdLb2dFeDRTTVFkY1ZOY1VPYXNwdmZqa2lDQTIwUDVmby0ySG5uaklfZ0pGaVFxMlBoZVFxcFdkcjhIbjRSbkNPaWhVUFpNTUlHdjczcnNY?oc=5\" target=\"_blank\" rel=\" noopener\" title=\"Call for Applications: Africa Machine Learning and Deep Learning (AMLD Africa) Ambassador Programme - Apply By 27 June 2026 - Global South Opportunities\" style=\"width:150px; height:150px;\"><span class=\"default\" style=\"background-image:url(https:\/\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/sharon-pittaway-N7FtpkC_P7o-unsplash.jpg);\" title=\"Call for Applications: Africa Machine Learning and Deep Learning (AMLD Africa) Ambassador Programme - Apply By 27 June 2026 - Global South Opportunities\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/sharon-pittaway-N7FtpkC_P7o-unsplash.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/news.google.com\/rss\/articles\/CBMiaEFVX3lxTFB2UGVGcFozcFZTQTNxR2IzOXdLb2dFeDRTTVFkY1ZOY1VPYXNwdmZqa2lDQTIwUDVmby0ySG5uaklfZ0pGaVFxMlBoZVFxcFdkcjhIbjRSbkNPaWhVUFpNTUlHdjczcnNY?oc=5\" target=\"_blank\" rel=\" noopener\">Call for Applications: Africa Machine Learning and Deep Learning (AMLD Africa) Ambassador Programme &#8211; Apply By 27 June 2026 &#8211; Global South Opportunities<\/a><\/span><div class=\"rss_content\" style=\"\"><small>on June 20, 2026 at 3:32 pm <\/small><p>Call for Applications: Africa Machine Learning and Deep Learning (AMLD Africa) Ambassador Programme &#8211; Apply By 27 June 2026\u00a0\u00a0Global South Opportunities<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/news.google.com\/rss\/articles\/CBMiaEFVX3lxTFB2UGVGcFozcFZTQTNxR2IzOXdLb2dFeDRTTVFkY1ZOY1VPYXNwdmZqa2lDQTIwUDVmby0ySG5uaklfZ0pGaVFxMlBoZVFxcFdkcjhIbjRSbkNPaWhVUFpNTUlHdjczcnNY?oc=5\" target=\"_blank\" rel=\" noopener\" title=\"Call for Applications: Africa Machine Learning and Deep Learning (AMLD Africa) Ambassador Programme - Apply By 27 June 2026 - Global South Opportunities\" style=\"width:150px; height:150px;\"><span class=\"default\" style=\"background-image:url(https:\/\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/sharon-pittaway-N7FtpkC_P7o-unsplash.jpg);\" title=\"Call for Applications: Africa Machine Learning and Deep Learning (AMLD Africa) Ambassador Programme - Apply By 27 June 2026 - Global South Opportunities\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/sharon-pittaway-N7FtpkC_P7o-unsplash.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/news.google.com\/rss\/articles\/CBMiaEFVX3lxTFB2UGVGcFozcFZTQTNxR2IzOXdLb2dFeDRTTVFkY1ZOY1VPYXNwdmZqa2lDQTIwUDVmby0ySG5uaklfZ0pGaVFxMlBoZVFxcFdkcjhIbjRSbkNPaWhVUFpNTUlHdjczcnNY?oc=5\" target=\"_blank\" rel=\" noopener\">Call for Applications: Africa Machine Learning and Deep Learning (AMLD Africa) Ambassador Programme &#8211; Apply By 27 June 2026 &#8211; Global South Opportunities<\/a><\/span><div class=\"rss_content\" style=\"\"><small>on June 20, 2026 at 3:32 pm <\/small><p>Call for Applications: Africa Machine Learning and Deep Learning (AMLD Africa) Ambassador Programme &#8211; Apply By 27 June 2026\u00a0\u00a0Global South Opportunities<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/news.google.com\/rss\/articles\/CBMiakFVX3lxTE9XclpfWlF0T2lHQlVzZGdyaUdqUVhpdWtDU1BrMzhEczRJU1pVUTZoN3h0T0E0T05SNXhkclRIX25GNXVoMXY0VkJwdENlUWhQbUxSM2gyZ3B6czQ2UWNaZUlwMXVxd2dyWlE?oc=5\" target=\"_blank\" rel=\" noopener\" title=\"Here\u2019s who\u2019ll win the World Cup, according to science - BBC Science Focus Magazine\" style=\"width:150px; height:150px;\"><span class=\"default\" style=\"background-image:url(https:\/\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/sharon-pittaway-N7FtpkC_P7o-unsplash.jpg);\" title=\"Here\u2019s who\u2019ll win the World Cup, according to science - BBC Science Focus Magazine\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/sharon-pittaway-N7FtpkC_P7o-unsplash.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/news.google.com\/rss\/articles\/CBMiakFVX3lxTE9XclpfWlF0T2lHQlVzZGdyaUdqUVhpdWtDU1BrMzhEczRJU1pVUTZoN3h0T0E0T05SNXhkclRIX25GNXVoMXY0VkJwdENlUWhQbUxSM2gyZ3B6czQ2UWNaZUlwMXVxd2dyWlE?oc=5\" target=\"_blank\" rel=\" noopener\">Here\u2019s who\u2019ll win the World Cup, according to science &#8211; BBC Science Focus Magazine<\/a><\/span><div class=\"rss_content\" style=\"\"><small>on June 20, 2026 at 11:00 am <\/small><p>Here\u2019s who\u2019ll win the World Cup, according to science\u00a0\u00a0BBC Science Focus Magazine<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/news.google.com\/rss\/articles\/CBMiX0FVX3lxTE90OHNNcXhPMUFQdW1uZlQ2aTFhcmJzbVNPckhXc3ZvWmlrQzJ5RG83V0xpaW04cktNbHBpdDlxWDBFQVJkdWZJNTFJRXJObFktNmNOaUZuanJpN19rN1JB?oc=5\" target=\"_blank\" rel=\" noopener\" title=\"EMG-based hand gesture recognition using multi-scale deep residual network with SE-module - Nature\" style=\"width:150px; height:150px;\"><span class=\"default\" style=\"background-image:url(https:\/\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/sharon-pittaway-N7FtpkC_P7o-unsplash.jpg);\" title=\"EMG-based hand gesture recognition using multi-scale deep residual network with SE-module - Nature\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/sharon-pittaway-N7FtpkC_P7o-unsplash.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/news.google.com\/rss\/articles\/CBMiX0FVX3lxTE90OHNNcXhPMUFQdW1uZlQ2aTFhcmJzbVNPckhXc3ZvWmlrQzJ5RG83V0xpaW04cktNbHBpdDlxWDBFQVJkdWZJNTFJRXJObFktNmNOaUZuanJpN19rN1JB?oc=5\" target=\"_blank\" rel=\" noopener\">EMG-based hand gesture recognition using multi-scale deep residual network with SE-module &#8211; Nature<\/a><\/span><div class=\"rss_content\" style=\"\"><small>on June 20, 2026 at 6:45 am <\/small><p>EMG-based hand gesture recognition using multi-scale deep residual network with SE-module\u00a0\u00a0Nature<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/news.google.com\/rss\/articles\/CBMi2gFBVV95cUxQNW5SeXhCY09LSGxLZV9qemsxei1zRkJrN3FEVGFfUk9UWnc5ajcxWWpjOFRpU1lDSU56c3BlV0M5b21nbHdBRi1aTmg5WFBYLW45MVYwUUVhZGpwRW1QeWZVd1M3WG5aUmZRa040cE91bHVKNGRDYjFvSkM5ME9jOFk4LWg1S2k0VjBSU2I1R1VQN0duQVl4UUpaRDdyS2VVSm51RVVBOGU1Z3dXbUt5TV8yWEt6ZFJsZzhOakZXYUczOHh3MWFKdHJKZ0dKWVNRbXRnZFRnOUU5Zw?oc=5\" target=\"_blank\" rel=\" noopener\" title=\"Modeling Doppler Shifts In Radial-Velocity Data With Deep Learning Toward Earth-mass Exoplanet Detection - astrobiology.com\" style=\"width:150px; height:150px;\"><span class=\"default\" style=\"background-image:url(https:\/\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/sharon-pittaway-N7FtpkC_P7o-unsplash.jpg);\" title=\"Modeling Doppler Shifts In Radial-Velocity Data With Deep Learning Toward Earth-mass Exoplanet Detection - astrobiology.com\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/sharon-pittaway-N7FtpkC_P7o-unsplash.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/news.google.com\/rss\/articles\/CBMi2gFBVV95cUxQNW5SeXhCY09LSGxLZV9qemsxei1zRkJrN3FEVGFfUk9UWnc5ajcxWWpjOFRpU1lDSU56c3BlV0M5b21nbHdBRi1aTmg5WFBYLW45MVYwUUVhZGpwRW1QeWZVd1M3WG5aUmZRa040cE91bHVKNGRDYjFvSkM5ME9jOFk4LWg1S2k0VjBSU2I1R1VQN0duQVl4UUpaRDdyS2VVSm51RVVBOGU1Z3dXbUt5TV8yWEt6ZFJsZzhOakZXYUczOHh3MWFKdHJKZ0dKWVNRbXRnZFRnOUU5Zw?oc=5\" target=\"_blank\" rel=\" noopener\">Modeling Doppler Shifts In Radial-Velocity Data With Deep Learning Toward Earth-mass Exoplanet Detection &#8211; astrobiology.com<\/a><\/span><div class=\"rss_content\" style=\"\"><small>on June 19, 2026 at 7:00 pm <\/small><p>Modeling Doppler Shifts In Radial-Velocity Data With Deep Learning Toward Earth-mass Exoplanet Detection\u00a0\u00a0astrobiology.com<\/p><\/div><\/li><\/ul> <\/div><style type=\"text\/css\" media=\"all\">.feedzy-rss .rss_item .rss_image{float:left;position:relative;border:none;text-decoration:none;max-width:100%}.feedzy-rss .rss_item .rss_image span{display:inline-block;position:absolute;width:100%;height:100%;background-position:50%;background-size:cover}.feedzy-rss .rss_item .rss_image{margin:.3em 1em 0 0;content-visibility:auto}.feedzy-rss ul{list-style:none}.feedzy-rss ul li{display:inline-block}<\/style>\n\n\n<h3 class=\"wp-block-heading\">White Papers<\/h3>\n\n\n\n<p>Latest research and developments in the field of machine learning and deep learning. Sources: ARXIV, Papers with Code and others<\/p>\n\n\n<div class=\"feedzy-dd6de31578e58d857e2d6426937f7e31 feedzy-rss\"><div class=\"rss_header\"><h2><a href=\"\" class=\"rss_title\" rel=\"noopener\"><\/a> <span class=\"rss_description\"> <\/span><\/h2><\/div><ul><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/arxiv.org\/abs\/2606.11537\" target=\"_blank\" rel=\" noopener\" title=\"MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning\" style=\"width:150px; height:150px;\"><span class=\"default\" style=\"background-image:url(https:\/\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/lysander-yuen-wk833OrQLJE-unsplash.jpg);\" title=\"MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/lysander-yuen-wk833OrQLJE-unsplash.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/arxiv.org\/abs\/2606.11537\" target=\"_blank\" rel=\" noopener\">MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning<\/a><\/span><div class=\"rss_content\" style=\"\"><p>arXiv:2606.11537v2 Announce Type: replace \nAbstract: Financial and tabular question answering requires more than fluent [&hellip;]<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/arxiv.org\/abs\/2606.20470\" target=\"_blank\" rel=\" noopener\" title=\"Analyzing Defensive Misdirection Against Model-Guided Automated Attacks on Agentic AI Systems\" style=\"width:150px; height:150px;\"><span class=\"default\" style=\"background-image:url(https:\/\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/lysander-yuen-wk833OrQLJE-unsplash.jpg);\" title=\"Analyzing Defensive Misdirection Against Model-Guided Automated Attacks on Agentic AI Systems\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/lysander-yuen-wk833OrQLJE-unsplash.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/arxiv.org\/abs\/2606.20470\" target=\"_blank\" rel=\" noopener\">Analyzing Defensive Misdirection Against Model-Guided Automated Attacks on Agentic AI Systems<\/a><\/span><div class=\"rss_content\" style=\"\"><p>arXiv:2606.20470v1 Announce Type: cross \nAbstract: Agentic AI systems increasingly rely on language-model components to [&hellip;]<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/arxiv.org\/abs\/2601.15797\" target=\"_blank\" rel=\" noopener\" title=\"Creativity Reconsidered: Generative AI and the Problem of Intentional Agency\" style=\"width:150px; height:150px;\"><span class=\"default\" style=\"background-image:url(https:\/\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/lysander-yuen-wk833OrQLJE-unsplash.jpg);\" title=\"Creativity Reconsidered: Generative AI and the Problem of Intentional Agency\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/lysander-yuen-wk833OrQLJE-unsplash.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/arxiv.org\/abs\/2601.15797\" target=\"_blank\" rel=\" noopener\">Creativity Reconsidered: Generative AI and the Problem of Intentional Agency<\/a><\/span><div class=\"rss_content\" style=\"\"><p>arXiv:2601.15797v2 Announce Type: replace \nAbstract: Many theorists maintain that conscious intentional agency is a [&hellip;]<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/arxiv.org\/abs\/2606.20041\" target=\"_blank\" rel=\" noopener\" title=\"AI Economist Agent: An Agentic Framework for Model-Grounded Economic Analysis with RAG, Knowledge Graphs, and Large Language Models\" style=\"width:150px; height:150px;\"><span class=\"default\" style=\"background-image:url(https:\/\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/lysander-yuen-wk833OrQLJE-unsplash.jpg);\" title=\"AI Economist Agent: An Agentic Framework for Model-Grounded Economic Analysis with RAG, Knowledge Graphs, and Large Language Models\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/lysander-yuen-wk833OrQLJE-unsplash.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/arxiv.org\/abs\/2606.20041\" target=\"_blank\" rel=\" noopener\">AI Economist Agent: An Agentic Framework for Model-Grounded Economic Analysis with RAG, Knowledge Graphs, and Large Language Models<\/a><\/span><div class=\"rss_content\" style=\"\"><p>arXiv:2606.20041v1 Announce Type: cross \nAbstract: We propose a model-grounded RAG-based AI economist with an agentic [&hellip;]<\/p><\/div><\/li><li  style=\"padding: 15px 0 25px\" class=\"rss_item\"><div class=\"rss_image\" style=\"width:150px; height:150px;\"><a href=\"https:\/\/arxiv.org\/abs\/2606.20209\" target=\"_blank\" rel=\" noopener\" title=\"FlowMaps: Modeling Long-Term Multimodal Object Dynamics with Flow Matching\" style=\"width:150px; height:150px;\"><span class=\"default\" style=\"background-image:url(https:\/\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/lysander-yuen-wk833OrQLJE-unsplash.jpg);\" title=\"FlowMaps: Modeling Long-Term Multimodal Object Dynamics with Flow Matching\"><\/span><amp-img width=\"150\" height=\"150\" src=\"https:\/\/i0.wp.com\/datasciencediscovery.com\/wp-content\/uploads\/2019\/11\/lysander-yuen-wk833OrQLJE-unsplash.jpg?resize=150%2C150&#038;ssl=1\" data-recalc-dims=\"1\"><\/a><\/div><span class=\"title\"><a href=\"https:\/\/arxiv.org\/abs\/2606.20209\" target=\"_blank\" rel=\" noopener\">FlowMaps: Modeling Long-Term Multimodal Object Dynamics with Flow Matching<\/a><\/span><div class=\"rss_content\" style=\"\"><p>arXiv:2606.20209v1 Announce Type: cross \nAbstract: Joint spatial and temporal understanding of 3D scenes is a crucial [&hellip;]<\/p><\/div><\/li><\/ul> <\/div><style type=\"text\/css\" media=\"all\">.feedzy-rss .rss_item .rss_image{float:left;position:relative;border:none;text-decoration:none;max-width:100%}.feedzy-rss .rss_item .rss_image span{display:inline-block;position:absolute;width:100%;height:100%;background-position:50%;background-size:cover}.feedzy-rss .rss_item .rss_image{margin:.3em 1em 0 0;content-visibility:auto}.feedzy-rss ul{list-style:none}.feedzy-rss ul li{display:inline-block}<\/style>","protected":false},"excerpt":{"rendered":"<p>Catch up with the fast moving field of data science. Even for us it has been difficult to stay up to date with the latest news and developments in the industry. We are putting together some of the top sources such as MIT, NVIDIA, ARXIV and others. These articles are aggregated from well trusted sources [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_mi_skip_tracking":false,"spay_email":""},"_links":{"self":[{"href":"https:\/\/datasciencediscovery.com\/index.php\/wp-json\/wp\/v2\/pages\/665"}],"collection":[{"href":"https:\/\/datasciencediscovery.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/datasciencediscovery.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/datasciencediscovery.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/datasciencediscovery.com\/index.php\/wp-json\/wp\/v2\/comments?post=665"}],"version-history":[{"count":11,"href":"https:\/\/datasciencediscovery.com\/index.php\/wp-json\/wp\/v2\/pages\/665\/revisions"}],"predecessor-version":[{"id":1011,"href":"https:\/\/datasciencediscovery.com\/index.php\/wp-json\/wp\/v2\/pages\/665\/revisions\/1011"}],"wp:attachment":[{"href":"https:\/\/datasciencediscovery.com\/index.php\/wp-json\/wp\/v2\/media?parent=665"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}