Hello everyone! AITX Team here with more updates this week.
If you’re new here, welcome! 👋 At AITX, we aim to:
Connect you with like-minded peers passionate about AI.
Provide a space for sharing ideas and receiving feedback on AI projects you’re building.
Share helpful tools and invaluable resources.
Be sure to follow us on X (Twitter), LinkedIn, and Instagram.
Before we jump into the regular news, a few housekeeping items:
Upcoming AITX Community Events:
Houston AITX Monthly Meetup: Tuesday, December 2, 5:30 PM - 7:30 PM CST | sign up here! (we had to bump it back a bit this time)
Austin AITX Monthly Meetup: Tuesday, Nov 25, 5:30 - 7:30 PM | sign up here!
To stay in the loop on all our monthly meetups and other community organized events, subscribe to our AITX Community calendar here.
Check out our Community Directory:
Where you can fill out your profile and find other members of the AITX community. If you haven’t filled out your profile yet, please follow the link HERE and submit your information.
NVIDIA DGX Spark Hackathon
AITX Community is running it back with NVIDIA this December with another hackathon centered around their new DGX Spark hardware.
When: 5:00 PM CST, December 12 - 4:00 PM CST, December 14
What: This Hackathon brings together the strongest frontier builders and engineers in Texas to push the boundary of what’s possible on next-generation NVIDIA compute.
25 teams will work hands-on with the DGX Spark to complete targeted Build Challenges provided by NVIDIA and local partner companies.
There will be prize packages for each Challenge winner as well as the overall Best Build.
This is a team-based hackathon! Full-team applications will be prioritized over individual applications.
Minimum team size is 2 and maximum team size is 5.
If you apply as an individual, we'll try our best to match you into a team, and you'll be required to compete with the team we match you with if accepted.
In this week’s edition you’re getting:
5 Upcoming Events
3 AI Community Stories
So let’s jump in!
UPCOMING EVENTS
When: Thursday, December 11 | 6:30 PM - 9:00 PM CST
Where: Register to see address
What: An end-of-year holiday celebration for the Austin AI community—engineers, founders, researchers, and operators. This year, we're partnering with SAFE Austin to help provide gifts for families in need this Holiday season. Tickets to the event are free, but we encourage you to donate to SAFE during registration or bring a small gift donation when you attend. 100% of revenue will be donated to SAFE Austin under their Holidays program.
When: Thursday, December 4th | 6:00 PM - 8:00 PM CST
Where: 801 Travis St, Downtown Houston
What: Will feature 3 presentations on practical AI applications as well as networking opportunities with fellow AI enthusiasts.
When: Wednesday, December 3 | 6:00 PM - 9:00 PM CST
Where: ACC - RGC 3000 1218 West Avenue · Austin, TX
What: Join us for an evening of hands-on demos, short deep-dives, and community networking. We’re calling this a Mixer & Showcase — learn practical patterns for LangGraph and agent stacks, share war stories, and meet local builders.
When: Friday, December 5 | 3:00 PM - 6:00 PM CST
Where: Location TBD
What: Join us for the first-ever Physical AI Builders Meetup in Dallas, happening Dec 5th at UT Dallas. Fresh off the success of the F50 Physical AI Summits in Austin and Silicon Valley, this meetup brings the future of intelligent machines, robotics, and AI-driven manufacturing directly to Dallas–Fort Worth — one of America’s strongest industrial and technology powerhouses.
When: Wednesday, December 3 | 6:30 PM - 8:30 PM CST
What: In this talk, Eric Albee, seasoned engineering leader/founder of EricDev Corp. breaks down Vibe Coding, a creative, accessible way to turn your ideas into working prototypes and automations — without needing to know how to code. You’ll follow his real-world developer flow using tools like Claude Code and learn how to bring ideas to life step-by-step.
COMMUNITY STORIES
UT Austin is adding 4,000 of Nvidia’s latest Blackwell GPUs to its new Horizon supercomputer, bringing its total to more than 5,000 GPUs and cementing its claim as the top AI compute hub in academia. Horizon will go online in 2026 at the Texas Advanced Computing Center and is expected to be 10 times more powerful than Frontera, the current leading academic supercomputer.
Why it matters: This puts Austin at the center of open, high-end AI research, giving local researchers and startups access to infrastructure most regions simply will not have.
Need-to-know:
More than 5,000 Nvidia GPUs total, the most AI compute in academia
Over 1,000 GPUs reserved for UT’s Center for Generative AI, doubling its capacity
Funded by NSF and at least $20 million from the Texas Legislature, with a focus on open-source large language models and scientific AI research
Learn more here.
Google is investing US$40 billion in new and expanded data centers across Texas through 2027, building the backbone for its next generation of cloud and AI products. The buildout ties compute, energy, and workforce training into one long-term Texas strategy.
Why it matters: This cements Texas as a key AI infrastructure hub, attracting more AI companies, talent, and downstream opportunities for local builders.
Need-to-know:
Three new data center campuses in Armstrong and Haskell Counties plus expansion in Ellis County
Over 6,200 MW of new energy capacity secured, including solar and battery projects
US$30 million Energy Impact Fund and training for 1,700+ Texas electrical apprentices by 2030
Learn more here.
New analysis from Bernstein and operators like Lambda and Crusoe argues that GPUs remain profitable for six to eight years, not one or two. Instead of quickly becoming obsolete, older GPUs move down the stack from cutting edge training to inference to lighter open source workloads while still generating strong margins.
Why it matters: Texas is loading up on AI data centers and GPU fleets, from Abilene to Austin, so realistic GPU lifespans make these massive infrastructure bets look more sustainable and less like a short term bubble.
Need-to-know:
Leading analysts say 5 to 6 year depreciation schedules for GPUs are reasonable
Operators report 7 to 8 year effective lifespans by redeploying GPUs to lighter inference and open source workloads
Older GPUs are cheaper to buy and still profitable, which keeps them attractive for free tiers, budget services, and niche AI use cases
Learn more here.
That’s all for now, folks!
If you enjoyed this, consider sharing with a friend by sending them to sign up here.