BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//jEvents 2.0 for Joomla//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:STANDARD
DTSTART:20251102T010000
RDATE:20260308T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:STANDARD
DTSTART:20261101T010000
RDATE:20270314T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:STANDARD
DTSTART:20271107T010000
RDATE:20280312T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:STANDARD
DTSTART:20281105T010000
RDATE:20290311T030000
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:America/New_York EST
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20250505T153000
RDATE:20251102T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20260308T030000
RDATE:20261101T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20270314T030000
RDATE:20271107T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20280312T030000
RDATE:20281105T010000
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:America/New_York EDT
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:d2233cc47a1c9523b42b6194722e96e1
CATEGORIES:Colloquia
CREATED:20260503T210238
SUMMARY:What should we do about AI generated proofs?
LOCATION:Hill 705
DESCRIPTION:The three large AI companies (Google Deepmind, OpenAI, and Anthropic) have 
 decided to compete on the capabilities of their models to "do research math
 ," have invested substantial amounts of money on improving these capabiliti
 es, and are for now subsidising their use by users (some more than others).
  I will focus on the specific case of using Large Language Models (and syst
 ems built on them) to produce natural language proofs (i.e. the kinds of pr
 oofs that humans write and read). I will describe the preliminary outcomes 
 of trying to make an unbiased measurement, which indicate that the most adv
 anced systems are capable of producing correct argument for many statements
  whose proofs do not appear in the literature (arxiv:2602.05192). I will al
 so discuss efforts currently under way to make more refined assessments (ht
 tps://1stproof.org/index.html. Click or tap if you trust this link." data-a
 uth="NotApplicable" data-linkindex="0"&gt;https://nam02.safelinks.protectio
 n.outlook.com/?url=https%3A%2F%2F1stproof.org%2Findex.html&amp;data=05%7C02
 %7Cmpy4%40connect.rutgers.edu%7C03573a71433a4229499808dea8ce42a3%7Cb92d2b23
 4d35447093ff69aca6632ffe%7C1%7C0%7C639133801027528483%7CUnknown%7CTWFpbGZsb
 3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFp
 bCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&amp;sdata=bafJYuKgo70xRfORDNKCpqpjqIghgfN
 Zl4uQdeq7tw0%3D&amp;reserved=0). I will aim to leave ample time for comment
 s, questions, and discussion.\n
X-ALT-DESC;FMTTYPE=text/html:<p>The three large AI companies (Google Deepmind, OpenAI, and Anthropic) ha
 ve decided to compete on the capabilities of their models to "do research m
 ath," have invested substantial amounts of money on improving these capabil
 ities, and are for now subsidising their use by users (some more than other
 s). I will focus on the specific case of using Large Language Models (and s
 ystems built on them) to produce natural language proofs (i.e. the kinds of
  proofs that humans write and read). I will describe the preliminary outcom
 es of trying to make an unbiased measurement, which indicate that the most 
 advanced systems are capable of producing correct argument for many stateme
 nts whose proofs do not appear in the literature (arxiv:2602.05192). I will
  also discuss efforts currently under way to make more refined assessments 
 (<a href="https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2
 F1stproof.org%2Findex.html&amp;data=05%7C02%7Cmpy4%40connect.rutgers.edu%7C
 03573a71433a4229499808dea8ce42a3%7Cb92d2b234d35447093ff69aca6632ffe%7C1%7C0
 %7C639133801027528483%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiO
 iIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7
 C&amp;sdata=bafJYuKgo70xRfORDNKCpqpjqIghgfNZl4uQdeq7tw0%3D&amp;reserved=0" 
 target="_blank" rel="noopener noreferrer" title="Original URL: &lt;a href="
 https://www.math.rutgers.edu/>https://1stproof.org/index.html.</a> Click or
  tap if you trust this link." data-auth="NotApplicable" data-linkindex="0"&
 gt;<a href="https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F
 %2F1stproof.org%2Findex.html&amp;data=05%7C02%7Cmpy4%40connect.rutgers.edu%
 7C03573a71433a4229499808dea8ce42a3%7Cb92d2b234d35447093ff69aca6632ffe%7C1%7
 C0%7C639133801027528483%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlY
 iOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C
 %7C&amp;sdata=bafJYuKgo70xRfORDNKCpqpjqIghgfNZl4uQdeq7tw0%3D&amp;reserved=0
 ">https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2F1stproo
 f.org%2Findex.html&amp;data=05%7C02%7Cmpy4%40connect.rutgers.edu%7C03573a71
 433a4229499808dea8ce42a3%7Cb92d2b234d35447093ff69aca6632ffe%7C1%7C0%7C63913
 3801027528483%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuM
 DAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&amp;sd
 ata=bafJYuKgo70xRfORDNKCpqpjqIghgfNZl4uQdeq7tw0%3D&amp;reserved=0</a>). I w
 ill aim to leave ample time for comments, questions, and discussion.</p>
CONTACT:Mohammed Abouzaid
DTSTAMP:20260826T094805
DTSTART;TZID=America/New_York:20260506T153000
DTEND;TZID=America/New_York:20260506T163000
SEQUENCE:0
TRANSP:OPAQUE
END:VEVENT
END:VCALENDAR