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<News hasArchived="false" page="22" pageCount="36" pageSize="10" timestamp="Mon, 18 May 2026 14:35:31 -0400" url="https://dev.my.umbc.edu/groups/umbc-ai/posts.xml?page=22">
  <NewsItem contentIssues="true" id="146418" important="false" status="posted" url="https://dev.my.umbc.edu/groups/umbc-ai/posts/146418">
  <Title>World's first chatbot restored on the world's first time-sharing system</Title>
  <Tagline>Original ELIZA code runs in CTSS emulator on Linux/MacOS</Tagline>
  <Body>
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    <div><img src="https://ai.umbc.edu/wp-content/uploads/sites/734/2024/12/weizenbaum-eliza.jpg" style="max-width: 100%; height: auto;"></div>
    <div><br></div>
    <div>MIT professor <a href="https://en.wikipedia.org/wiki/Joseph_Weizenbaum" rel="nofollow external" class="bo"><strong>Joseph Weizenbaum</strong></a> created <a href="https://en.wikipedia.org/wiki/ELIZA" rel="nofollow external" class="bo"><strong>ELIZA</strong></a> in 1966 partly to demonstrate how easy it was to convince people that a computer was intelligent. His original <a href="https://en.wikipedia.org/wiki/SLIP_(programming_language)" rel="nofollow external" class="bo"><strong>MAD-SLIP</strong></a> version of ELIZA, usually considered the world's first <a href="https://en.wikipedia.org/wiki/Chatbot" rel="nofollow external" class="bo"><strong>chatbot</strong></a>, is running again on its native platform for the first time in nearly 60 years. Weizenbaum's original CACM paper, <a href="https://dl.acm.org/doi/epdf/10.1145/365153.365168" rel="nofollow external" class="bo"><strong>ELIZA — A Computer Program for the Study of Natural Language Communication Between Man and Machine</strong></a>, is available online.</div>
    <div><br></div>
    <div>This historic breakthrough was accomplished by a team of researchers (Rupert Lane, Anthony Hay, Arthur Schwarz, and Jeff Shrager) who successfully restored ELIZA to operation on a reconstructed version of MIT's <a href="https://en.wikipedia.org/wiki/Compatible_Time-Sharing_System" rel="nofollow external" class="bo"><strong>Compatible Time-Sharing System</strong></a> (CTSS), running on an emulated <a href="https://en.wikipedia.org/wiki/IBM_7090" rel="nofollow external" class="bo"><strong>IBM 7094</strong></a>. You can download the code from this <a href="https://github.com/rupertl/eliza-ctss" rel="nofollow external" class="bo"><strong>GitHub repository</strong></a> and run it on most Linux or MacOS systems.</div>
    <div><br></div>
    <div>See this <a href="https://sites.google.com/view/elizagen-org/blog/eliza-reanimated" rel="nofollow external" class="bo"><strong>blog post</strong></a> describing the effort to get the original ELIZA version running and a <a href="https://www.youtube.com/watch?v=j5Tw-XVcsRE" rel="nofollow external" class="bo"><strong>video</strong></a> of the reanimated ELIZA. Read more about ELIZA on the <a href="https://sites.google.com/view/elizagen-org/" rel="nofollow external" class="bo"><strong>Genealogy of ELIZA</strong></a> site. You can also <a href="https://anthay.github.io/eliza.html" rel="nofollow external" class="bo"><strong>talk to ELIZA</strong></a> using a version of Weizenbaum's script via a JavaScript adaptation of the original code by Anthony Hay.</div>
    <div><br></div> 
    <hr>
    <a href="https://ai.umbc.edu/" rel="nofollow external" class="bo"><strong>UMBC Center for AI</strong></a>
    </div>
]]>
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  <Summary>MIT professor Joseph Weizenbaum created ELIZA in 1966 partly to demonstrate how easy it was to convince people that a computer was intelligent. His original MAD-SLIP version of ELIZA, usually...</Summary>
  <Website>https://sites.google.com/view/elizagen-org/blog/eliza-reanimated</Website>
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  <Tag>ai</Tag>
  <Tag>chatbot</Tag>
  <Tag>eliza</Tag>
  <Tag>history</Tag>
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  <PostedAt>Sat, 28 Dec 2024 12:16:18 -0500</PostedAt>
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  <NewsItem contentIssues="true" id="146371" important="false" status="posted" url="https://dev.my.umbc.edu/groups/umbc-ai/posts/146371">
    <Title>Google's five-day Generative AI intensive course</Title>
    <Tagline>Now a free, self-paced learning program at Kaggle</Tagline>
    <Body>
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          <span>Google's five day Generative AI Intensive Course is now available as a free, self-paced learning program on Kaggle for anyone interested in learning about the fundamental technologies and techniques behind the latest Generative AI technology. </span><a href="https://www.kaggle.com/learn-guide/5-day-genai" rel="nofollow external" class="bo"><strong>Get more information here</strong></a><span>.</span><div><span><br></span></div>
          <div>
          <span>Here's what the course covers</span><div><div><ul>
          <li>
          <strong>Day 1:</strong> Foundational Models &amp; Prompt Engineering - Explore the evolution of LLMs, from transformers to techniques like fine-tuning and inference acceleration. Get trained with the art of prompt engineering for optimal LLM interaction.<br><br>
          </li>
          <li>
          <strong>Day 2:</strong> Embeddings and Vector Stores/Databases - Learn about the conceptual underpinning of embeddings and vector databases, including embedding methods, vector search algorithms, and real-world applications with LLMs, as well as their tradeoffs.<br><br>
          </li>
          <li>
          <strong>Day 3: </strong>Generative AI Agents - Learn to build sophisticated AI agents by understanding their core components and the iterative development process.<br><br>
          </li>
          <li>
          <strong>Day 4:</strong> Domain-Specific LLMs - Delve into the creation and application of specialized LLMs like SecLM and Med-PaLM, with insights from the researchers who built them.<br><br>
          </li>
          <li>
          <strong>Day 5:</strong> MLOps for Generative AI - Discover how to adapt MLOps practices for Generative AI and leverage Vertex AI's tools for foundation models and generative AI applications.</li>
          </ul></div></div>
          <div><span><br></span></div>
          <hr>
          <a href="https://ai.umbc.edu/" rel="nofollow external" class="bo"><strong>UMBC Center for AI</strong></a>
          </div>
          </div>
      ]]>
    </Body>
    <Summary>Google's five day Generative AI Intensive Course is now available as a free, self-paced learning program on Kaggle for anyone interested in learning about the fundamental technologies and...</Summary>
    <Website>https://www.kaggle.com/learn-guide/5-day-genai</Website>
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    <Tag>agents</Tag>
    <Tag>ai</Tag>
    <Tag>genai</Tag>
    <Tag>kaggle</Tag>
    <Tag>llm</Tag>
    <Group token="umbc-ai">UMBC AI</Group>
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    <Sponsor>UMBC AI</Sponsor>
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    <PostedAt>Wed, 18 Dec 2024 17:32:37 -0500</PostedAt>
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  <NewsItem contentIssues="true" id="146346" important="false" status="posted" url="https://dev.my.umbc.edu/groups/umbc-ai/posts/146346">
  <Title>Managing the Uncertainty of the Exponential Technology Age</Title>
  <Tagline>AI Lunchbox, 12-1pm ET, Thur December 19, 2024 online</Tagline>
  <Body>
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    <h3><span>Managing Uncertainty of the Exponential Technology Age</span></h3>
    <h4>
    <span><strong>AI Lunchbox, 12-1pm ET<br></strong></span><span><strong>Thursday December 19, 2024, online</strong></span>
    </h4>
    <div><span><br></span></div>
    <div><span><br></span></div>
    <div><span>Artificial Intelligence is a catalyst for breakthroughs in other technologies, leading to unprecedented change. In this AI Lunchbox session of the UMBC Training Centers Center for Applied AI, <a href="https://www.linkedin.com/in/erwinagodoy/" rel="nofollow external" class="bo"><strong>Erwin Godoy</strong></a> will look at how AI advancing other exponential technologies, the combine changes they could bring, and discusses practical ways to thrive through the unprecedented changes.</span></div>
    <div><span><br></span></div>
    <div><span>Erwin A. Godoy is an entrepreneurial executive with nearly 30 years of experience in driving product innovation and growth. Known for his strategic thinking and ability to lead high-performance teams, he specializes in incubating products in fast-paced, uncertain environments. Currently, Erwin is a Strategic Advisor at the Center for Applied Artificial Intelligence at UMBC, where he advises on AI strategy and business model innovation.</span></div>
    <div><span><br></span></div>
    <div><span>Register for this free online session <a href="https://c4ai.umbctraining.com/event/managing-the-uncertainty-of-the-exponential-technology-age/" rel="nofollow external" class="bo"><strong>here</strong></a>.</span></div>
    <div><span><br></span></div>
    <hr>
    <a href="https://ai.umbc.edu/" rel="nofollow external" class="bo"><strong>UMBC Center for AI</strong></a>
    </div>
]]>
  </Body>
  <Summary>Managing Uncertainty of the Exponential Technology Age  AI Lunchbox, 12-1pm ET Thursday December 19, 2024, online        Artificial Intelligence is a catalyst for breakthroughs in other...</Summary>
  <Website>https://www.meetup.com/c4a-ai/events/304024722</Website>
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  <Sponsor>UMBC Training Centers</Sponsor>
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  <PostedAt>Tue, 17 Dec 2024 17:31:45 -0500</PostedAt>
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  <NewsItem contentIssues="true" id="146132" important="false" status="posted" url="https://dev.my.umbc.edu/groups/umbc-ai/posts/146132">
  <Title>CodeBot '25: Can We Trust AI-Generated Code? 2/25-26</Title>
  <Tagline>Workshop Feb. 25-26, 2025 in Columbia, MD and online</Tagline>
  <Body>
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    <div>
    <div><h3><strong>Can We Trust AI-Generated Code?</strong></h3></div>
    <h5><strong>Workshop sponsored by UMBC &amp; Army Research Laboratory</strong></h5>
    <h5>
    <span>Feb. 25-26, 2025 </span><span>UMBC Training Centers, Columbia, MD &amp; online<br><br><p>
    position paper deadline extended to 1/20/2025</p></span>
    </h5>The era of generative AI is upon us, and chatbots such as chatGPT are being used by programmers at all levels of experience to produce code.  Some generative AI systems, such as <a href="https://cloud.google.com/gemini/docs/codeassist/overview" rel="nofollow external" class="bo"><strong>Gemini Code Assist</strong></a>, specialize in code generation.  Unfortunately, AI-generated code often contains errors in the form of functionality that fails to meet specifications or vulnerabilities that can be exploited by hackers.  People have been working on program verification and secure coding for sixty years, but even so, the skill needed to find such errors is possessed by only a fraction of software engineers, and these skills are not being passed on to student programmers as they should be.<br><br>The goal of this FREE workshop is to gather and produce actionable ideas and suggestions that may be of use to the IT profession.  The workshop will consist of invited speakers, panels, and open discussion. </div>
    <div><br></div>
    <div>
    <strong>We invite would-be participants to submit short position papers offering comments, observations, experiences, and suggestions that pertain to any or all of the following workshop themes:</strong><br><ol>
    <li>What is or could be done to make AI-generated code more trustworthy, from the perspective of functionality and/or cybersecurity?</li>
    <li>How can we do better at instilling the ideas and tools of secure development into the software profession?</li>
    <li>Being able to produce quality code, with or without the aid of AI, seems to be related to system skills in general. How can we do better at giving students these skills before (or as) they enter the workplace?</li>
    </ol>Position papers should limited to three pages and submitted according to this <a href="https://docs.google.com/document/d/11nr-Zy2MPObMYihN2x_v2jS7EcUkOLXm/edit?usp=sharing&amp;ouid=117342243438066964240&amp;rtpof=true&amp;sd=true" rel="nofollow external" class="bo"><strong>template</strong></a>.  Submit your position paper via email to <a href="mailto:codebot25@umbc.edu" rel="nofollow external" class="bo"><strong>codebot25@umbc.edu</strong></a> after <strong><a href="https://forms.gle/CipmPbbBVBLfHc728" rel="nofollow external" class="bo">registering</a> </strong>for the workshop.</div>
    <div><br></div>
    <div>The organizing committee will select several papers for live presentation at the workshop. Selection will be based on relevance to the workshop themes, technical merit, and perceived interest to the audience.  Position papers that are mere marketing pieces will not be considered, but descriptions of hardware and software solutions tying into the themes described above are welcome. Limited travel support may be available for non-local speakers. Position papers and summaries of the discussions that follow will make up the core of the workshop report.<br><br>UMBC students, both graduate or undergraduate, are welcome to submit position papers that describe their own personal experience and observations with AI-generated code in their own words.  Students may include their resumes with position papers if they wish to have their work/resume circulated to other attendees.  Domestic and international students are welcome to participate in this workshop.<br><br><strong>Important Dates:</strong><br>
    </div>
    <div>  <strong>Position paper submission deadline: January 20, 2025</strong>
    </div>
    <div>
    <strong>  </strong> P̶o̶s̶i̶t̶i̶o̶n̶ p̶a̶p̶e̶r̶ s̶u̶b̶m̶i̶s̶s̶i̶o̶n̶ d̶e̶a̶d̶l̶i̶n̶e̶:̶ J̶a̶n̶u̶a̶r̶y̶ 7̶, 2̶0̶2̶5̶<br>  Notice of acceptance: January 31, 2025<br>  Registration deadline: February 18, 2025<br>    (no registration fee, but space is limited)<br>  Workshop dates: February 25-26, 2025<br><br>The workshop will take place at <strong><a href="https://www.umbctraining.com/" rel="nofollow external" class="bo">UMBC Training Centers</a></strong>, 6996 Columbia Gateway Dr #100, Columbia, MD 21046</div>
    <div><br></div>
    <div>
    <strong>REGISTER </strong>@ <a href="https://forms.gle/CipmPbbBVBLfHc728" rel="nofollow external" class="bo"><strong>https://forms.gle/CipmPbbBVBLfHc728</strong></a><br><br><strong>In-person space is limited, so register early! Based on RSVPs received, the organizing committee reserves the right to be selective in whom it selects to join the in-person meeting.</strong>
    </div>
    <div>
    <br>Instructions for virtual participation will be made available prior to the workshop.<br><br><strong>Organizing Committee:</strong><br>  Prajna Bhandary, UMBC<br>  Mike De Lucia, Army Research Laboratory<br>  Richard Forno, UMBC<br>  Lindsay Gaughan, UMBC Training Centers<br>  Cynthia Matuszek, UMBC<br>  Charles Nicholas, UMBC<br>  Steve Simske, Colorado State University<br>  Larry Wagoner, Dept. of Defense<br>  Linda Kidder Yarlott, UMBC<br>  Paul Yu, Army Research Laboratory<br><br>
    </div>
    <div>Questions? Send email to <a href="mailto:codebot25@umbc.edu" rel="nofollow external" class="bo"><strong>codebot25@umbc.edu</strong></a>
    </div>
    <hr>
    <a href="https://ai.umbc.edu/" rel="nofollow external" class="bo"><strong>UMBC Center for AI</strong></a>
    </div>
]]>
  </Body>
  <Summary>Can We Trust AI-Generated Code?   Workshop sponsored by UMBC &amp; Army Research Laboratory  Feb. 25-26, 2025 UMBC Training Centers, Columbia, MD &amp; online    position paper deadline extended...</Summary>
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  <NewsItem contentIssues="true" id="146067" important="false" status="posted" url="https://dev.my.umbc.edu/groups/umbc-ai/posts/146067">
  <Title>Talk: The Future with AI: Balancing Opportunity and Inequity, 12/11</Title>
  <Tagline>12-1pm EST, Wednesday, December 11, 2024, online</Tagline>
  <Body>
    <![CDATA[
    <div class="html-content">
    <span><h3><span>The Future with AI: Balancing Opportunity and Inequity</span></h3>
    <h4><span>Denise Turley, U.S. Chamber of Commerce</span></h4>
    <h4><span>12-1pm EST, Wed., December 11, 2024, online</span></h4>
    <p><br></p>
    <p><span>In this <strong>AI in Practice</strong> series session, </span><span>Dr. </span><a href="https://www.linkedin.com/in/dr-denise-turley/" rel="nofollow external" class="bo"><span>Denise Turley</span></a><span> will explore how Al is transforming business and education, offering personalized learning, improving accessibility, and expanding opportunities for underserved communities. However, as Al becomes more integrated, it can also introduce biases, widen the digital divide, and pose privacy concerns. <strong>Register at </strong></span><strong><a href="http://bit.ly/AiP-Dec11" rel="nofollow external" class="bo"><span>bit.ly/AiP-Dec11</span></a>.</strong></p>
    <p><span>As Vice President of Corporate Systems at the U.S. Chamber of Commerce, Dr. Turley drives the strategic development of enterprise-wide technology solutions. Her leadership extends beyond the corporate realm into academia, where she serves as an assistant professor at the University of the Southwest, guiding future leaders through inclusive and technology-driven educational practices.</span></p></span> <hr>
    <a href="https://ai.umbc.edu/" rel="nofollow external" class="bo"><strong>UMBC Center for AI</strong></a>
    </div>
]]>
  </Body>
  <Summary>The Future with AI: Balancing Opportunity and Inequity  Denise Turley, U.S. Chamber of Commerce  12-1pm EST, Wed., December 11, 2024, online     In this AI in Practice series session, Dr. Denise...</Summary>
  <Website>https://ai.umbc.edu/wp-content/uploads/sites/734/2024/12/AI_in_practice.png</Website>
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  <PostedAt>Fri, 06 Dec 2024 09:07:43 -0500</PostedAt>
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</NewsItem>
  <NewsItem contentIssues="true" id="146044" important="false" status="posted" url="https://dev.my.umbc.edu/groups/umbc-ai/posts/146044">
  <Title>AI Lunchbox: Security Risk in AI/ML, 12/12</Title>
  <Tagline>12:00-1:00 pm EST, Thursday, December 12, 2024</Tagline>
  <Body>
    <![CDATA[
    <div class="html-content">
    <div>
    <span>In the AI Lunchbox session </span><span><strong>Security Risk in AI/ML</strong></span><span>, participants will learn about attacks on AI models and how to defend against them. Designed for a general audience, this presentation will teach participants how to incorporate AI security risk into their organizational strategy and AI development workflows. </span><a href="https://www.linkedin.com/in/randyabernethy/" rel="nofollow external" class="bo"><span>Randy Abernethy</span></a><span> from </span><a href="https://rx-m.com/" rel="nofollow external" class="bo"><span>RX-M, LLC</span></a><span> will be a speaker.</span>
    </div>
    <div><span><br></span></div>
    <div><span><p><span><span>The session will be held online from 12 to 1 p.m. EST on December 12, 2024. Register <a href="https://c4ai.umbctraining.com/event/security-risk-in-ai-ml/" rel="nofollow external" class="bo"><strong>here</strong></a> to receive a link to the</span><span> event from the UMBC Training Centers </span><a href="https://c4ai.umbctraining.com/" rel="nofollow external" class="bo"><span>Center for Applied AI</span></a><span>.</span></span></p></span></div>
    <hr>
    <a href="https://ai.umbc.edu/" rel="nofollow external" class="bo"><strong>UMBC Center for AI</strong></a>
    </div>
]]>
  </Body>
  <Summary>In the AI Lunchbox session Security Risk in AI/ML, participants will learn about attacks on AI models and how to defend against them. Designed for a general audience, this presentation will teach...</Summary>
  <Website>https://c4ai.umbctraining.com/event/security-risk-in-ai-ml/</Website>
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  <PostedAt>Wed, 04 Dec 2024 09:55:09 -0500</PostedAt>
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  <NewsItem contentIssues="true" id="145979" important="false" status="posted" url="https://dev.my.umbc.edu/groups/umbc-ai/posts/145979">
    <Title>Stanford's HAI releases its 7th annual AI Index Report</Title>
    <Body>
      <![CDATA[
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          <div><br></div>
          <div>Stanford's Institute for Human-Centered Artificial Intelligence (<a href="https://hai.stanford.edu/" rel="nofollow external" class="bo"><strong>HAI</strong></a>) released its seventh annual <strong>AI Index Report</strong>, which tracks, collates, distills, and visualizes AI-related data. Get the report and its underlying public data and charts <a href="https://aiindex.stanford.edu/report/" rel="nofollow external" class="bo"><strong>here</strong></a>. </div>
          <div><br></div>
          <div>The report's top ten takeaways are:</div>
          <div><ol>
          <li>AI beats humans on some tasks but not on all.</li>
          <li>Industry continues to dominate frontier AI research.</li>
          <li>Frontier models get way more expensive.</li>
          <li>The US leads China, the EU, and the U.K. as the leading source of top AI models.</li>
          <li>Robust and standardized evaluations for LLM responsibility are seriously lacking.</li>
          <li>Generative AI investment skyrockets.</li>
          <li>The data is in: AI makes workers more productive and leads to higher quality work.</li>
          <li>Scientific progress accelerates even further, thanks to AI.</li>
          <li>The number of AI regulations in the United States sharply increases.</li>
          <li>People across the globe are more cognizant of AI’s potential impact—and more nervous.</li>
          </ol></div>
          <hr>
          <a href="https://ai.umbc.edu/" rel="nofollow external" class="bo"><strong>UMBC Center for AI</strong></a>
          </div>
      ]]>
    </Body>
    <Summary>Stanford's Institute for Human-Centered Artificial Intelligence (HAI) released its seventh annual AI Index Report, which tracks, collates, distills, and visualizes AI-related data. Get the report...</Summary>
    <Website>https://aiindex.stanford.edu/report/</Website>
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    <PostedAt>Mon, 02 Dec 2024 10:34:21 -0500</PostedAt>
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  <NewsItem contentIssues="true" id="145919" important="false" status="posted" url="https://dev.my.umbc.edu/groups/umbc-ai/posts/145919">
  <Title>Teaching with AI: two workshops for UMBC faculty and staff, January 23</Title>
  <Tagline>In person in PAHB 337 on Thursday, January 23, 2024</Tagline>
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    <span><p><span>Dr. <a href="https://josebowen.com/" rel="nofollow external" class="bo"><strong>José Antonio Bowen</strong></a> will visit UMBC on </span><span>Thursday, January 23,</span><span> to lead two in-person workshops for UMBC faculty and staff based on his book </span><a href="https://www.press.jhu.edu/books/title/53869/teaching-ai" rel="nofollow external" class="bo"><span><strong>Teaching with AI</strong></span></a><span>, co-authored with C. Edward Watson, JHU Press, 2024.</span></p>
    <p><span>Get more information on the workshops and register in the links below to ensure seating, workshop materials, and lunch or coffee and snacks. </span></p>
    <p><span>Registration closes on Thursday, January 16. </span></p>
    <ul>
    <li>
    <a href="https://my3.my.umbc.edu/groups/calt/events/136407" rel="nofollow external" class="bo"></a><a href="https://my3.my.umbc.edu/groups/calt/events/136407" rel="nofollow external" class="bo"><span><strong>AI Literacy &amp; Prompt Engineering</strong></span></a><span>, (with lunch): 12:00-1:45pm;  </span><a href="https://my3.my.umbc.edu/groups/calt/events/136407" rel="nofollow external" class="bo"><span><strong>REGISTER HERE</strong></span></a>
    
    </li>
    <li>
    <a href="https://my3.my.umbc.edu/groups/calt/events/136408" rel="nofollow external" class="bo"><span><strong>AI Assignments &amp; Assessments</strong></span></a><span> (coffee &amp; snacks): 2:00-3:15pm. - </span><a href="https://my3.my.umbc.edu/groups/calt/events/136408" rel="nofollow external" class="bo"><span><strong>REGISTER HERE</strong></span></a>
    </li>
    </ul></span><div><span><p><span>These will be in-person only workshops in PAHB 337 (The Dance Cube). You may register for one or both workshops. This topics are especially relevant as we navigate new possibilities and challenges arising for teaching and learning in the era of generative AI. </span>Please bring a device to the workshops.</p>
    <p><span>The workshops are only open to UMBC faculty and staff.</span></p>
    <div><br></div></span></div>
    <hr>
    <a href="https://ai.umbc.edu/" rel="nofollow external" class="bo"><strong>UMBC Center for AI</strong></a>
    </div>
]]>
  </Body>
  <Summary>Dr. José Antonio Bowen will visit UMBC on Thursday, January 23, to lead two in-person workshops for UMBC faculty and staff based on his book Teaching with AI, co-authored with C. Edward Watson,...</Summary>
  <Website>https://my3.my.umbc.edu/groups/calt/events/136406</Website>
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  <Sponsor>Faculty Development Center and Instructional Technology</Sponsor>
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  <NewsItem contentIssues="true" id="145869" important="false" status="posted" url="https://dev.my.umbc.edu/groups/umbc-ai/posts/145869">
  <Title>Talk: Advancing machine learning methodology for applications in gerontology</Title>
  <Tagline>11-12pm EST Mon, Dec. 11, 2024, U. MD, Baltimore &amp; online</Tagline>
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    <span><h4><span>Advancing machine learning methodology for applications in gerontology</span></h4>
    <h5><span><strong>Dr. Jaime Lynn Speiser, Wake Forest University School of Medicine</strong></span></h5>
    <h5><span>11-12pm EST Mon, Dec. 11, 2024
    U. of Maryland, Baltimore &amp; online</span></h5>
    <p><span> </span></p>
    <p><span>Prediction models aim to help medical providers, individuals, and caretakers make informed, data-driven decisions about the risk of developing poor health outcomes, such as fall injury or mobility limitation in older adults. Most models for outcomes in older adults use cross-sectional data, although leveraging repeated measurements of predictors and outcomes over time may result in higher prediction accuracy. This seminar talk will focus on a novel methodology for longitudinal, repeated measures prediction models called </span><a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC7202553/" rel="nofollow external" class="bo"><span><strong>Binary Mixed Model</strong></span></a><span>(BiMM) forest. I will give an overview of longitudinal data analysis and introduce the BiMM forest method with variable selection. I will then apply a <a href="https://my3.my.umbc.edu/groups/umbc-ai/posts/145869/a6c/f588885d3b4504deabc0a0dbb602ca78/web/link?link=https%3A%2F%2Fpmc.ncbi.nlm.nih.gov%2Farticles%2FPMC7508310%2F" rel="nofollow external" class="bo"><strong>BiMM forest</strong></a> for predicting mobility limitation in older adults using the Health, Aging, and Body Composition dataset.</span></p>
    <p><a href="https://school.wakehealth.edu/faculty/s/jaime-lynn-speiser" rel="nofollow external" class="bo"><span><strong>Dr. Speiser</strong></span></a><span> received her B.S. in mathematics at Elon University and M.S. in statistics at the Ohio State University. She completed her Ph.D. in biostatistics at the Medical University of South Carolina, where she was awarded the Distinguished Graduate Student Award at the top of her class. Dr. Speiser received the Lester R Curtin Award from the American Statistical Association and several conference travel awards. She serves on the executive committees of the American Statistical Association’s Statistical Learning and Data Science Section and Statistics and Data Science in Aging Interest Group. Dr. Speiser is currently funded by an NIH K25 award and is the Leadership Fellow for Wake Forest’s Pepper Center and Clinical and Translational Research Institute. Her paper comparing </span><a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC7508310/" rel="nofollow external" class="bo"><span><strong>random forest variable selection methods</strong></span></a><span> is a top-cited paper in the journal Expert Systems with Applications with over 1000 citations.</span></p>
    <p><strong><a href="https://umaryland.zoom.us/meeting/register/tJIvdOmorj0oGNOCDwqZyuuL0WYoeVAPshsM" rel="nofollow external" class="bo"><span>Register here to get a Zoom link.</span></a><span> </span></strong></p></span>
    <hr>
    <a href="https://ai.umbc.edu/" rel="nofollow external" class="bo"><strong>UMBC Center for AI</strong></a>
    </div>
]]>
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  <Summary>Advancing machine learning methodology for applications in gerontology  Dr. Jaime Lynn Speiser, Wake Forest University School of Medicine  11-12pm EST Mon, Dec. 11, 2024 U. of Maryland, Baltimore...</Summary>
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  <Sponsor>UMB Division of Biostatistics and Bioinformatics</Sponsor>
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  <PostedAt>Sat, 23 Nov 2024 17:29:15 -0500</PostedAt>
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  <NewsItem contentIssues="true" id="145840" important="false" status="posted" url="https://dev.my.umbc.edu/groups/umbc-ai/posts/145840">
  <Title>AI4ALL Ignite free AI program for 2025</Title>
  <Body>
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    <div>
    <a href="https://bit.ly/3AQcpC2" rel="nofollow external" class="bo"><span><strong>AI4ALL Ignite</strong></span></a><span> is a no-cost virtual career accelerator program for undergraduate students that is designed to boost your internship <span>and</span> other AI work opportunities.</span>
    </div>
    <div>
    <ul>
    <li>
    <span>Develop a real-world AI technical portfolio project using data alongside </span><span><strong>AI industry mentors and peers</strong></span><span>.</span>
    </li>
    <li>Master responsible AI concepts through <span><strong>hands-on workshops and invigorating discussions.</strong></span>
    </li>
    <li>Get tailored AI career readiness &amp; face-time with industry recruiters from companies like <span><strong>NVIDIA, Microsoft, and Amazon.</strong></span>
    </li>
    </ul>
    <p><span><strong>Why Participate?</strong></span></p>
    <ul>
    <li>
    <span><strong>AI Career Readiness Training &amp; Virtual Symposium:</strong></span><span> Technical interview prep to answer problem-solving questions, mock interviews with industry professionals, resume and job search prep,  and a virtual student symposium.</span>
    </li>
    <li>
    <strong>Exclusive Networking Opportunities: </strong><span>Mentorship from AI industry mentors, company opportunity chats.</span>
    </li>
    <li>
    <strong>Gain a Responsible AI Lens:</strong><span> Participate in AI  discussions on  topics like responsible AI, data sourcing + visualization, machine learning methods, bias mitigation, project management, Github <span>and</span> more.</span>
    </li>
    <li><strong>Achieve an AI4ALL Certificate of Completion</strong></li>
    </ul>
    <p><span><strong>To Le</strong></span><span><strong>arn More</strong></span></p>
    <ul>
    <li><span><a href="https://drive.google.com/file/d/1yfYBpQT5kYyC8vf1ZL1Ksq0ZJyDbXycA/view?usp=drive_link" rel="nofollow external" class="bo">See this flyer</a></span></li>
    <li><a href="https://bit.ly/3AQcpC2" rel="nofollow external" class="bo">Submit <span>an </span>Interest Form</a></li>
    <li>
    <a href="https://bit.ly/40VEqTE" rel="nofollow external" class="bo"><span>SignUp</span></a><span> f</span><span>or</span><span> AI Networks of Opportunity Newsletter</span>
    </li>
    <li>
    <a href="https://bit.ly/40UleWj" rel="nofollow external" class="bo"><span>RSVP</span></a><span> to AI4ALL<span> for a</span> live <span>online</span> info session</span>
    </li>
    </ul>
    <br><p><span>While all undergraduate students are welcome to apply and will be considered,  <span>AI4ALL</span> especially encourages applications from individuals whose race, gender, or ethnicity have been historically underrepresented in AI. This includes students identifying as women, non-binary individuals, Black, Hispanic/Latinx, and Indigenous people.</span></p>
    <p><span><br></span></p>
    </div> <hr>
    <a href="https://ai.umbc.edu/" rel="nofollow external" class="bo"><strong>UMBC Center for AI</strong></a>
    </div>
]]>
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  <Summary>AI4ALL Ignite is a no-cost virtual career accelerator program for undergraduate students that is designed to boost your internship and other AI work opportunities.    Develop a real-world AI...</Summary>
  <Website>https://ai-4-all.org/ai4all-ignite/</Website>
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  <Sponsor>UMBC AI</Sponsor>
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