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DTSTAMP:20241005T150341Z
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DESCRIPTION:Generative AI refers to a category of artificial intelligence m
 odels that are designed to generate new content\, such as text\, images\, 
 audio\, or other types of data. Probably the best known example of generat
 ive AI is ChatGPT\, the fastest consumer application to hit 100 million mo
 nthly active users. Generative AI models use machine learning algorithms t
 o learn patterns and structures from existing data and then produce new da
 ta that is similar in style or content to what they have been trained on.\
 n\nIn this presentation\, I will start with a tutorial on various approach
 es to generative AI. Next I will talk about projects in our group at the T
 U Delft on deep generative models. I will briefly present novel kinds of d
 eep generative models that we are developing in our team. Next I will expl
 ain how we are designing such models for rainfall nowcasting\, where we in
 tegrate physical laws into the deep generative models. At last\, I will ta
 lk various AI related initiatives that our team is involved in.\n\nSpeaker
 (s): Dr. Justin Dauwels\n\nVirtual: https://events.vtools.ieee.org/m/42990
 6
LOCATION:Virtual: https://events.vtools.ieee.org/m/429906
ORGANIZER:dansongarcia@ieee.org
SEQUENCE:17
SUMMARY:Generative AI
URL;VALUE=URI:https://events.vtools.ieee.org/m/429906
X-ALT-DESC:Description: &lt;br /&gt;&lt;p class=&quot;m_5564409148867801121paragraph&quot; sty
 le=&quot;margin: 0cm\; background: white\;&quot;&gt;&lt;span class=&quot;m_5564409148867801121e
 op&quot;&gt;&lt;span lang=&quot;EN-GB&quot; style=&quot;font-size: 12.0pt\; color: black\;&quot;&gt;Generati
 ve AI refers to a category of artificial intelligence models that are desi
 gned to generate new content\, such as text\, images\, audio\, or other ty
 pes of data. Probably the best known example of generative AI is ChatGPT\,
  the fastest consumer application to hit 100 million monthly active users.
  Generative AI models use machine learning algorithms to learn patterns an
 d structures from existing data and then produce new data that is similar 
 in style or content to what they have been trained on.&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;\n
 &lt;p class=&quot;MsoNormal&quot; style=&quot;margin-bottom: 12.0pt\; font-kerning: none\;&quot;&gt;
 &lt;span class=&quot;m_5564409148867801121eop&quot;&gt;&lt;span lang=&quot;EN-GB&quot; style=&quot;color: bl
 ack\;&quot;&gt;In this presentation\, I will start with a tutorial on various appr
 oaches to generative AI. Next I will talk about projects in our group at t
 he TU Delft on deep generative models. I will briefly present novel kinds 
 of deep generative models that we are developing in our team. Next I will 
 explain how we are designing such models for rainfall nowcasting\, where w
 e integrate physical laws into the deep generative models.&amp;nbsp\; At last\
 , I will talk various AI related initiatives that our team is involved in.
 &lt;/span&gt;&lt;/span&gt;&lt;/p&gt;\n&lt;div class=&quot;yj6qo ajU&quot;&gt;\n&lt;div id=&quot;:me&quot; class=&quot;ajR&quot; tab
 index=&quot;0&quot; role=&quot;button&quot; data-tooltip=&quot;Show trimmed content&quot; aria-label=&quot;Sh
 ow trimmed content&quot; aria-expanded=&quot;false&quot;&gt;&lt;img class=&quot;ajT&quot; src=&quot;https://ss
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