Houston startup launches innovative chat tool on its mission to democratize AI

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ThirdAI's new PocketLLM app is free to use and completely secure. Photo via Getty Images

Artificial intelligence has a big potential to disrupt the technology industry, and one Houston company that was founded by a computer science professor at Rice University, is fast on its way to help lead that future now in a convenient and affordable way.

Founded by Anshumali Shrivastava and Tharun Medini, a recent Ph.D. who graduated under Shrivastava from Rice's Department of Electrical and Computer Engineering, ThirdAI is building AI deep learning tools that aim to be sustainable and scalable to fit the changing needs of the industry. The company is on a mission to democratize AI, Shrivastava tells InnovationMap.

Shrivastava likes to use the word efficiently when describing what makes ThirdAI different, and how its programs can teach AI via multiple avenues to be what he refers to as “1,000 times more efficient.”

“The carbon footprint of these models are off the charts, and so expensive,” Shrivastava. “We believe this could be made efficient. … We use the same ideas that were developed, but we do it on a massive scale.”

ThirdAI's latest tool is a multilingual ChatGPT-like AI training tool PocketLLM app. Announced earlier this month, the tool is free. According to the company, users have access to a personalized chatbot that understands what the user is searching within documents, and can be fine-tuned to help elaborate your thoughts through a neural search.

ThirdAI's PocketLLM app is free to use. Image courtesy of ThirdAI

The app is private and secure and runs on deep-learning algorithms according to Vinod Iyengar, head of product at ThirdAI, and no one — not even ThirdAI — has access to the documents except the user.

“Tools exist to help people search text files, but that requires sharing your data with third parties,” says Iyengar in a news release. “Our solution is private and secure, powered by deep learning algorithms. And it returns results lightning fast.”

The process includes the user installing the app, uploading any text document files, and clicking "train." Minutes later, you have an AI tool that can process the information in those documents.

“The neural search encourages you to elaborate on your thoughts with details in the discover window and see the difference in results,” says Shrivastava in the release. “It can also be fine-tuned to your tastes by selecting the relevant option and hitting the update button to re-train."

In September of 2021, ThirdAI — pronounced "third eye" — raised $6 million in seed funding. The round was invested in by three California-based VCs — Neotribe Ventures and Cervin Ventures, which co-led the round with support from Firebolt Ventures. The technology ThirdAI is working with comes from 10 years of deep learning research and innovation. The company's technology has the potential to make computing 15-times faster, the company reports.

Anshumali Shrivastava is an associate professor of computer science at Rice University. Photo via rice.edu

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This Houston startup has a game-changing technology for deep learning. Photo via Getty Images

Houston artificial intelligence startup raises $6M in seed funding

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A computer science professor at Rice University has raised seed funding last month in order to grow his company that's focused on democratizing artificial intelligence tools.

ThirdAI, founded by Anshumali Shrivastava in April, raised $6 million in a seed funding round from three California-based VCs — Neotribe Ventures and Cervin Ventures, which co-led the round with support from Firebolt Ventures.

Shrivastava, CEO, co-founded the company with Tharun Medini, a recent Ph.D. who graduated under Shrivastava from Rice's Department of Electrical and Computer Engineering. Medini serves as the CTO of ThirdAI — pronounced "third eye." The startup is building the next generation of scalable and sustainable AI tools and deep learning systems.

"We are democratizing artificial intelligence through software innovations," says Shrivastava in a news release from Rice. "Our innovation would not only benefit current AI training by shifting to lower-cost CPUs, but it should also allow the 'unlocking' of AI training workloads on GPUs that were not previously feasible."

The technology ThirdAI is working with comes from 10 years of deep learning research and innovation. The company's technology has the potential to make computing 15-times faster.

"ThirdAI has developed a breakthrough approach to train deep learning models with a large number of parameters that run efficiently on general purpose CPUs. This technology has the potential to result in a gigantic leap forward in the accuracy of deep learning models," per and announcement from Cervin Ventures. "Our investment in ThirdAI was a no-brainer and we are fortunate to have had the opportunity to invest."

Anshumali Shrivastava is an associate professor of computer science at Rice University. Photo via rice.edu

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Rice, Houston Methodist award $90K for cancer research projects

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Rice University’s Synthesis X Center, in partnership with the Houston Methodist Neal Cancer Center, announced earlier this month the organizations would award $90,000 in seed grant funding to two projects that could help fight cancer. One would ease the pain of chemotherapy, while the other could change the way the progression of leukemia is tracked.

“We’re excited to be collaborating with the Neal Cancer Center to support collaborative, novel and interdisciplinary proposals to improve cancer care and outcomes,” Han Xiao, Rice professor of chemistry and the director of the SynthX Center, said in a news release. “Together, we can achieve translational excellence.”

The projects

Chemotherapy is one of the most effective cancer treatments, but it can be hard on the body. The human body doesn’t like being injected with radioactive material, especially the skin around the injection point, which can become extremely irritated. For patients in long-term treatment, the skin irritation can be more than just a bother; it can lead to infections that are dangerous to a compromised immune system.

Angel A Marti, a professor of chemistry at Rice University, and Biana Godin, an associate professor of nanoscience at Houston Methodist Research Institute, are experimenting with metal nanoclusters as a way to block radiation at the injection site. The nanocluster could be applied in a cream or a gel on the skin, serving as a type of shield against the harsh radioactive material.

Meanwhile, Yuan Ma, an assistant professor of chemistry at Rice, and Shu-Hsia Chen, a professor of immunology at Houston Methodist Research Institute, are working with m6A. Discovered in the 1970s, m6A is the most prevalent chemical modifier found in mRNA in mammals. It is prevalent in many cancers, including leukemia.

Ma and Chen are working on measuring the amount of m6A in leukemia to see if it can determine the most effective cancer treatments. The team is also experimenting with ways to shut off m6A to see if it makes current leukemia treatments more effective.

Progress from SynthX

SynthX was first launched in April 2024 to turn research from Rice and Houston Methodist into real-world cancer treatments. Within a year, the center had secured $1.5 million in grant money to work on crossing the blood-brain barrier in brain cancer treatments. These latest awards show that SynthX Center continues to bridge the worlds of research and clinical practice.

“This collaboration reflects a shared commitment to team science in cancer research,” Daniela Matei, the director of the Houston Methodist Neal Cancer Center, added in the release. “These are the types of translational and pioneering projects that lead to transformation in patient care.”'

The SynthX Center awarded $90,000 in seed grants to three teams in 2025 and $80,000 to three teams in 2024.

Tesla self-driving mode wasn't to blame in Houston-area crash, report suggests

Tesla news

Federal safety investigators looking into a runaway Tesla that killed a grandmother in her home say the driver had pressed the accelerator to full speed, suggesting the vehicle's self-driving software was not to blame.

The driver had told police that he had the self-driving software turned on, but a report from the National Transportation Safety Board concluded that he had actually overridden that feature when he pushed hard on the pedal. Moments later the Tesla Model 3 raced down a residential street in Katy, Texas, at highway speeds, slammed into a brick home and killed a 76-year-old woman standing in the front room.

The crash last month drew national attention because Tesla CEO Elon Musk is seeking to reassure the public its self-driving feature is safe as he prepares to turn hundreds of thousands of Teslas already on the road into fully automatic vehicles and begin selling two-seated Cybercabs missing steering wheels and pedals.

The crash came two months after officials at a separate federal agency, the National Highway Traffic Safety Administration, announced it was elevating a 2024 investigation of the self-driving feature to new “engineering analysis” level, raising the possibility of a recall of 3.2 million Tesla vehicles.

That NHTSA probe was triggered by crashes where the self-driving feature failed to alert drivers to take control in fog and other poor visibility conditions.

The agency opened an investigation last year into 58 incidents in which Teslas reportedly violated traffic safety laws while using self-driving technology, leading to more than a dozen crashes and fires and nearly two dozen injuries.

Separate from the National Transportation Safety Board, NHTSA is also looking into the Tesla house crash in Texas, one of 46 “special crash” investigations of Tesla's self-driving or driver-assistance technology in the past decade, according to the agency’s records. In more than a dozen of those crashes, at least one person — a driver, passenger or pedestrian — was killed.

Tesla had originally called its driver assistance software Full Self-Driving, or FSD, but auto experts and regulators complained it was misleading because drivers must always keep their eyes on the road and be ready to take over at any time.

The company has since changed the name to Full Self-Driving (Supervised).

Video of the Katy, Texas, accident shows the Tesla traveling at more than 70 mph (112.65 kilometers per hour), jumping a curb then tearing across a lawn before crushing through a brick wall of a home. A woman standing feet away, Martha Avila, was found amid piles of crumbling plaster, split beams and bits of furniture and rushed to a hospital but died.

Sales of Tesla cars still haven't recovered fully from boycotts last year over Musk's political stands, but the stock is rising anyway as he has successfully shifted attention away from the sales figures. He says they matter less now that the company is on the cusp of major technological advances, such as turning Teslas into hands-free vehicles and having its Optimus robots take over for humans for tasks at home and work.

Tesla stock has risen 22% in the past year and is currently trading at 170 times expected annual earnings compared to 20 for the S&P 500.

For its second-quarter financial results, financial analysts surveyed by FactSet expect earnings per share will barely budge — 32 cents versus 33 cents a year earlier — continuing a sixth quarter streak of flat or falling profits.

London AI startup selects Houston for first U.S. office after $20M raise

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London-based AI firm Applied Computing has announced a $20 million Series A round and a new office in Houston.

The new Bayou City office is Applied Computing’s first in the United States and part of its North American expansion. The company is known for its Orbital AI platform, which is tailored for energy operations.

The funding round was led by Houston-based KBR Inc., with participation from San Francisco-based Databricks Ventures. KBR’s investment was first announced in March.

KBR and Applied Computing have also entered into a multi-year agreement to deliver exclusive AI products for the energy sector. KBR already has integrated Orbital into its INSITE 3.0 platform for energy projects, and is also using the product for ammonia production.

Applied Computing’s Orbital platform combines physics-grounded intelligence with models across chemical engineering, time-series forecasting and language, according to the company. The system analyzes sensor readings and can recognize a facility’s equipment constraints and operator activity. The platform can also allow technicians to run simulations of how a change to a facility could affect the rest of its operations.

According to TechCrunch, Applied Computing will use the $20 million to further explore projects and deployments with the energy sector, hire engineering and research positions, and continue to expand internationally, potentially into the Middle East.

The company is also working on deals with a major U.S. stream operator, TechCrunch reports. And Applied Computing shared on LinkedIn that it plans to announce its first partnership with a major European oil company in the coming weeks.

“Yesterday we showed Orbital live in deployments at our demo day at the Energy Institute in London,” Callum Adamson, CEO and co-founder of Applied Computing, posted on LinkedIn on July 16. “Today, we're announcing the capital to scale it globally as well as the launch of our new offices in Houston and Bangalore. In the weeks following, there will be more announcements on our progress, partnerships and deployments.”

The company opened its Bangalore offices in December.

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