Hello everyone! AITX Team here with more updates this week.
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In this week’s edition you’re getting:
5 Upcoming Events
3 AI Community Stories
So let’s jump in!
UPCOMING EVENTS
When: Friday, Feb 13 - Feb 14
What: AITX Community, Hack AI, Organized AI and Applied AI Society are co-hosting We're bringing together builders from across Austin's AI ecosystem to learn and build with Openclaw AI.
The event kicks off with a training session to get everyone up to speed on OpenClaw, followed by the main build session where teams will create projects using the platform.
💻 Hack AI
When: Thursday, February 5, 2026 | 6:00 PM - 8:00 PM CST
Where: Capital Factory, Austin, Texas
What: Hack AI is a monthly meetup for technical and non-technical builders to learn about and build the latest AI technology. The evening includes demos from Agentuity and Linkt, followed by collaborative hacking and networking with free food and drinks.
When: Saturday February 21, 2026 | 10:00 AM - 8:00 PM CST
Where: 111 Congress Ave., Austin, Texas
What: A technical conference covering robotics and on-device AI inference, from compilers and runtimes to 3D perception, navigation, and manipulation policies. Features deeply technical talks, live demos from Austin robotics companies, and open Q&A sessions.
When: Monday, February 24, 2026 | 5:30 PM - 8:30 PM CST
Where: Coder Austin, Texas
What: A special edition AI Meetup focused on practical AI governance and compliance for developers, featuring insights on implementing guardrails that protect code and credentials while maintaining development speed. The session includes a tech talk by Dave Ahr from Coder on building secure, developer-friendly AI workflows without slowing innovation.
When: Wednesday, March 4, 2026 | 6:30 PM - 8:30 PM CST
Where: Capital Factory, Austin, Texas
What: Gary Sheng presents on Applied AI and helping businesses integrate AI solutions. The event includes a speaker presentation, Q&A session, and networking opportunities for AI entrepreneurs, developers, and tech professionals.
COMMUNITY STORIES
Texas DPS released a five-year homeland security plan for 2026 to 2030 that heavily emphasizes AI, surveillance technology, and predictive policing. The strategy includes expanding drones, flock cameras, threat assessment teams, and preemptive law enforcement tactics across the state. Texans can expect increased monitoring, faster interventions, and more requests to report suspicious activity.
Why it matters: This represents a major statewide deployment of AI-driven surveillance and predictive policing tools that will affect how law enforcement uses artificial intelligence across Texas over the next five years.
Need-to-know:
The plan covers homeland security operations from 2026 to 2030 and was released Tuesday by Texas DPS
The strategy involves using AI to react to crimes as fast as possible, in some cases before they even happen
The plan revolves around six goals including preventing terrorist attacks, reducing vulnerability to threats, minimizing impact through proactive mitigation, and ensuring rapid community recovery
Learn more here.
Scammers are targeting job seekers in Texas with increasingly sophisticated schemes enhanced by AI technology. As of October 2025, Texas ranks number 8 on the list of states most at risk of job scams. Officials warn that AI is making these employment scams harder to detect and more dangerous for job seekers.
Why it matters: This story highlights how AI technology is being weaponized against Texans in the competitive job market, creating new challenges for both job seekers and officials trying to combat fraud.
Need-to-know:
Texas ranks number 8 among states most at risk of job scams as of October 2025
A Houston man named Hal Allen nearly fell victim to an elaborate LinkedIn scam earlier this year but spotted red flags in time
Red flags include job offers without interviews, pressure to send money or deposit checks, and opportunities that seem too good to be true
Learn more here.
Texas A&M University doctoral student Zavier Ndum Ndum is developing AI tools that combine knowledge gathering and simulations for nuclear engineering research. His framework, RADIANT-LLM, rapidly pulls information from technical databases and PDFs while filtering outdated documents. Unlike public chatbots, these lightweight tools run locally on computers to protect proprietary nuclear facility data.
Why it matters: This research demonstrates how Texas universities are pioneering AI applications in critical energy infrastructure, potentially accelerating nuclear power development to meet growing AI energy demands.
Need-to-know:
RADIANT-LLM uses LLM augmentation strategy, which goes beyond simply asking a chatbot questions
The frameworks are lightweight enough to run on a local computer rather than requiring cloud services
The tool can automatically sort through outdated documents to use the most updated versions
Learn more here.
That’s all for now, folks!
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