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DTSTART;TZID=Australia/Canberra:20260820T020000
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DESCRIPTION:[Register now](https://maestro.acm.org/trk/click?ref=z16l2snue3
 _2-32065_0_2x348471x0115344) for the next free ACM TechTalk\, &quot;From Conven
 tional LLMs to Reasoning Models to Agents\,&quot; presented on Thursday\, Augus
 t 19 at 12:00 PM ET/16:00 UTC by Sebastian Raschka\, Founder and Principal
  AI &amp; LLM Researcher at RAIR Labs. Marlene Mhangami\, Senior Developer Adv
 ocate at Microsoft\, will moderate the Q&amp;A session.\n\nLeave your comments
  and questions with our speaker now and any time before the live event on 
 [ACM&#39;s Discourse Page](https://maestro.acm.org/trk/click?ref=z16l2snue3_2-
 32065_0_2x348472x0115344). And check out the page after the webcast for ex
 tended discussion with your peers in the computing community\, as well as 
 further resources on reasoning models and more.\n\nMany of us have been us
 ing and experimenting with large language models (LLMs) for several years.
  Then\, in 2025\, new techniques for training reasoning models gave LLMs a
  noticeable boost in problem-solving capabilities. Since then\, newer gene
 rations of LLMs have been substantially more useful for complex tasks such
  as math and coding.\n\nFor example\, in software development\, the progre
 ssion over the years has been from simple code completion to planning\, im
 plementing\, testing\, and debugging entire features and code bases.\n\nTo
 day\, reasoning models\, which can be viewed as an evolution of convention
 al LLMs\, are also at the center of many agent frameworks.\n\nThis talk wi
 ll explain how reasoning models differ from conventional LLMs\, with a par
 ticular focus on inference scaling and training techniques. It will also i
 ntroduce the main components of AI agents and show how reasoning models se
 rve as the engine that enables agents to plan\, use tools\, evaluate inter
 mediate results\, and recover from mistakes.\n\nAttendees will leave with 
 practical patterns for building resilient microservices that remain stable
  even when failures\, automation\, and AI-driven decisions collide.\n\nDur
 ation: 60 minutes (including audience Q&amp;A)\n\nPresenter:\nSebastian Raschk
 a\, Founder\, Principal AI &amp; LLM Research Engineer\, RAIR Labs\n\nSebastia
 n Raschka is an LLM Research Engineer with more than a decade of experienc
 e in artificial intelligence. His work bridges academia and industry\, inc
 luding roles as senior engineer at Lightning AI and as a statistics profes
 sor at the University of Wisconsin-Madison. He is the author of Build a Re
 asoning Model (From Scratch) and Build a Large Language Model (From Scratc
 h)\, both from Manning Publications\, as well as Machine Learning with PyT
 orch and Scikit-Learn (Packt)\, and Machine Learning Q and AI (No Starch P
 ress). His expertise lies in LLM research and the development of high-perf
 ormance AI systems\, with a deep focus on practical\, code-driven implemen
 tations.\n\nModerator:\nMarlene Mhangami\, Senior Developer Advocate\, Mic
 rosoft\n\nMarlene is a software engineer\, explorer\, and speaker currentl
 y based in London. She is a Senior Developer Advocate working at Microsoft
  focusing on Python and AI. Marlene is a previous director and vice-chair 
 for the Python Software Foundation and is currently serving as Co-Chair of
  the ACM Practitioner Board. In 2017\, she co-founded ZimboPy\, a non-prof
 it organization that gives Zimbabwean young women access to resources in t
 he field of technology. She is also the previous chair of PyCon Africa and
  is an advocate for women in tech on the continent.\n\nVisit [learning.acm
 .org/techtalks-archive](https://maestro.acm.org/trk/click?ref=z16l2snue3_2
 -32065_0_2x325156x0115344) for our full archive of past TechTalks\n\nVirtu
 al: https://events.vtools.ieee.org/m/569258
LOCATION:Virtual: https://events.vtools.ieee.org/m/569258
ORGANIZER:Ambarish.natu@gmail.com
SEQUENCE:14
SUMMARY:From Conventional LLMs to Reasoning Models to Agents
URL;VALUE=URI:https://events.vtools.ieee.org/m/569258
X-ALT-DESC:Description: &lt;br /&gt;&lt;p data-removefontsize=&quot;true&quot; data-originalco
 mputedfontsize=&quot;14&quot;&gt;&lt;a href=&quot;https://maestro.acm.org/trk/click?ref=z16l2sn
 ue3_2-32065_0_2x348471x0115344&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot; data-safere
 directurl=&quot;https://www.google.com/url?q=https://maestro.acm.org/trk/click?
 ref%3Dz16l2snue3_2-32065_0_2x348471x0115344&amp;amp\;source=gmail&amp;amp\;ust=178
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 size=&quot;true&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;Register now&lt;/span&gt;&lt;/a&gt; for
  the next free ACM TechTalk\,&amp;nbsp\;&quot;&lt;strong data-removefontsize=&quot;true&quot; da
 ta-originalcomputedfontsize=&quot;14&quot;&gt;From Conventional LLMs to Reasoning Model
 s to Agents&lt;/strong&gt;\,&quot; presented on&amp;nbsp\;&lt;strong data-removefontsize=&quot;tr
 ue&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;Thursday\, August 19 at 12:00 PM ET
 /16:00 UTC&lt;/strong&gt;&amp;nbsp\;by &lt;strong data-removefontsize=&quot;true&quot; data-origi
 nalcomputedfontsize=&quot;14&quot;&gt;Sebastian Raschka&lt;/strong&gt;\, Founder and Principa
 l AI &amp;amp\; LLM Researcher at RAIR Labs.&amp;nbsp\;&lt;strong data-removefontsize
 =&quot;true&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;Marlene Mhangami&lt;/strong&gt;\, Sen
 ior Developer Advocate at Microsoft\,&amp;nbsp\;will moderate the Q&amp;amp\;A ses
 sion.&lt;/p&gt;\n&lt;p data-removefontsize=&quot;true&quot; data-originalcomputedfontsize=&quot;14
 &quot;&gt;Leave your comments and questions with our speaker now and any time befo
 re the live event on &lt;a href=&quot;https://maestro.acm.org/trk/click?ref=z16l2s
 nue3_2-32065_0_2x348472x0115344&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot; data-safer
 edirecturl=&quot;https://www.google.com/url?q=https://maestro.acm.org/trk/click
 ?ref%3Dz16l2snue3_2-32065_0_2x348472x0115344&amp;amp\;source=gmail&amp;amp\;ust=17
 84921906440000&amp;amp\;usg=AOvVaw0m8MFdbFj_Zd3VhRayKBi-&quot;&gt;&lt;span data-removefon
 tsize=&quot;true&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;ACM&#39;s Discourse Page&lt;/span
 &gt;&lt;/a&gt;. And check out the page after the webcast for extended discussion wi
 th your peers in the computing community\, as well as further resources on
  reasoning models and more.&lt;/p&gt;\n&lt;p data-removefontsize=&quot;true&quot; data-origin
 alcomputedfontsize=&quot;14&quot;&gt;Many of us have been using and experimenting with 
 large language models (LLMs) for several years. Then\, in 2025\, new techn
 iques for training reasoning models gave LLMs a noticeable boost in proble
 m-solving capabilities. Since then\, newer generations of LLMs have been s
 ubstantially more useful for complex tasks such as math and coding.&lt;/p&gt;\n&lt;
 p data-removefontsize=&quot;true&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;For exampl
 e\, in software development\, the progression over the years has been from
  simple code completion to planning\, implementing\, testing\, and debuggi
 ng entire features and code bases.&lt;/p&gt;\n&lt;p data-removefontsize=&quot;true&quot; data
 -originalcomputedfontsize=&quot;14&quot;&gt;Today\, reasoning models\, which can be vie
 wed as an evolution of conventional LLMs\, are also at the center of many 
 agent frameworks.&lt;/p&gt;\n&lt;p data-removefontsize=&quot;true&quot; data-originalcomputed
 fontsize=&quot;14&quot;&gt;This talk will explain how reasoning models differ from conv
 entional LLMs\, with a particular focus on inference scaling and training 
 techniques. It will also introduce the main components of AI agents and sh
 ow how reasoning models serve as the engine that enables agents to plan\, 
 use tools\, evaluate intermediate results\, and recover from mistakes.&lt;/p&gt;
 \n&lt;p data-removefontsize=&quot;true&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;Attende
 es will leave with practical patterns for building resilient microservices
  that remain stable even when failures\, automation\, and AI-driven decisi
 ons collide.&lt;/p&gt;\n&lt;p&gt;&lt;em data-removefontsize=&quot;true&quot; data-originalcomputedf
 ontsize=&quot;14&quot;&gt;Duration: 60 minutes (including audience Q&amp;amp\;A)&lt;/em&gt;&lt;/p&gt;\n
 &lt;p data-removefontsize=&quot;true&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;&lt;strong&gt;&lt;
 u data-removefontsize=&quot;true&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;Presenter:
 &lt;/u&gt;&lt;/strong&gt;&lt;br&gt;&lt;strong data-removefontsize=&quot;true&quot; data-originalcomputedf
 ontsize=&quot;14&quot;&gt;Sebastian Raschka&lt;/strong&gt;\,&amp;nbsp\;&lt;em data-removefontsize=&quot;t
 rue&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;Founder\, Principal AI &amp;amp\; LLM 
 Research Engineer\, RAIR Labs&lt;/em&gt;&lt;/p&gt;\n&lt;p data-removefontsize=&quot;true&quot; data
 -originalcomputedfontsize=&quot;14&quot;&gt;Sebastian Raschka is an LLM Research Engine
 er with more than a decade of experience in artificial intelligence. His w
 ork bridges academia and industry\, including roles as senior engineer at 
 Lightning AI and as a statistics professor at the University of Wisconsin-
 Madison. He is the author of Build a Reasoning Model (From Scratch) and&amp;nb
 sp\;&lt;em data-removefontsize=&quot;true&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;Buil
 d a Large Language Model (From Scratch)&lt;/em&gt;\, both from Manning Publicati
 ons\, as well as&amp;nbsp\;&lt;em data-removefontsize=&quot;true&quot; data-originalcompute
 dfontsize=&quot;14&quot;&gt;Machine Learning with PyTorch and Scikit-Learn&amp;nbsp\;&lt;/em&gt;(
 Packt)\, and&amp;nbsp\;&lt;em data-removefontsize=&quot;true&quot; data-originalcomputedfon
 tsize=&quot;14&quot;&gt;Machine Learning Q and AI&amp;nbsp\;&lt;/em&gt;(No Starch Press). His exp
 ertise lies in LLM research and the development of high-performance AI sys
 tems\, with a deep focus on practical\, code-driven implementations.&lt;/p&gt;\n
 &lt;p&gt;&lt;strong&gt;&lt;u data-removefontsize=&quot;true&quot; data-originalcomputedfontsize=&quot;14
 &quot;&gt;Moderator:&lt;/u&gt;&lt;/strong&gt;&lt;br&gt;&lt;strong data-removefontsize=&quot;true&quot; data-origi
 nalcomputedfontsize=&quot;14&quot;&gt;Marlene Mhangami&lt;/strong&gt;&lt;em data-removefontsize=
 &quot;true&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;\, Senior Developer Advocate\, M
 icrosoft&lt;/em&gt;&lt;/p&gt;\n&lt;p data-removefontsize=&quot;true&quot; data-originalcomputedfont
 size=&quot;14&quot;&gt;Marlene is a software engineer\, explorer\, and speaker currentl
 y based in London. She is a Senior Developer Advocate working at Microsoft
  focusing on Python and AI. Marlene is a previous director and vice-chair 
 for the Python Software Foundation and is currently serving as Co-Chair of
  the ACM Practitioner&amp;nbsp\;Board. In 2017\, she co-founded ZimboPy\, a no
 n-profit organization that gives Zimbabwean young women access to resource
 s in the field of technology.&amp;nbsp\;She is also the previous chair of PyCo
 n Africa and is an advocate for women in tech on the continent.&lt;/p&gt;\n&lt;p da
 ta-removefontsize=&quot;true&quot; data-originalcomputedfontsize=&quot;14&quot;&gt;Visit &lt;a href=
 &quot;https://maestro.acm.org/trk/click?ref=z16l2snue3_2-32065_0_2x325156x01153
 44&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot; data-saferedirecturl=&quot;https://www.googl
 e.com/url?q=https://maestro.acm.org/trk/click?ref%3Dz16l2snue3_2-32065_0_2
 x325156x0115344&amp;amp\;source=gmail&amp;amp\;ust=1784921906440000&amp;amp\;usg=AOvVa
 w10rfDoC65zXlCkhkac3UYf&quot;&gt;&lt;span data-removefontsize=&quot;true&quot; data-originalcom
 putedfontsize=&quot;14&quot;&gt;learning.acm.org/techtalks-&lt;wbr&gt;archive&lt;/span&gt;&lt;/a&gt; for 
 our full archive of past TechTalks&lt;/p&gt;
END:VEVENT
END:VCALENDAR