Literal Labs

🏆 We’re honoured to announce that we’ve been selected as Finalists in the 'Semiconductors & AI Innovation Startup Cup' by Extreme Tech Challenge (XTC)! Inspired by the UN’s Sustainable Development Goals, XTC serves as the world’s largest platform for accelerating tech innovations with the potential to create real global impact. This recognition aligns with our mission: to develop AI that’s both energy-efficient and highly accurate, deployable directly at the edge, without the need for cloud reliance. We’re chuffed that it's a vision shared—and even more so, to be recognised for it. As the only British 🇬🇧 company to reach the final round, we’re set to compete in the Startup Cup at #CES2025 in Las Vegas this coming January. Leading up to that, we’ll be highlighting the vital benefits of our #edgeAI at #WebSummit, where we’ve also been named an Impact Startup for our commitment to key SDGs.

"The #TsetlinMachine is more than just a new AI model. It represents a shift toward #sustainability in technology. Its focus on simplicity and energy efficiency challenges the idea that powerful AI must come with a high environmental cost. "Alongside the continuous AI developments, Tsetlin Machines offer a path forward where advanced technology and environmental responsibility go hand in hand. "This approach is a technical #breakthrough and a step toward a future where AI serves humanity and the planet. In conclusion, embracing Tsetlin Machines could be essential to building a more innovative, greener world." Thank you to Dr. Assad abbas and Unite.AI for exploring our work further. Link in comments.

🚀 Literal Labs is heading to Web Summit 2024 in Lisbon! 🌍 🔗 Book a meeting with our team here: https://lnkd.in/dmyjpEnt We are thrilled to announce that we've been selected as an Impact Startup at this November's event, where we'll be showcasing our revolutionary logic-based AI solutions. Our approach brings ultra-fast, low-energy AI to the forefront, perfectly suited for edge computing and industries that demand efficiency without accuracy compromise. If you're attending Web Summit between 11 and 14 November and want to learn more about how Literal Labs can transform your AI strategy, let’s connect! See you in Lisbon! #WebSummit #EdgeAI #SustainableAI #AI #AIforGood

ICYMI: We’ve just released our latest benchmark results on the MLPerf Data Set! 📊 🔶 54X faster 🔶 52X less energy consumption 🔶 Fits seamlessly on off-the-shelf hardware with exceptional accuracy Built on a 32-bit Arm Cortex-M7 processor from STMicroelectronics, our model outperforms the standard fully connected neural network in MLPerf's benchmarks. 📥 Download the full paper here: https://lnkd.in/dr8QTGjB #AI #EdgeAI #TsetlinMachines #IoT #MachineLearning #MLPerf #Sustainability #SustainabilityInTech

There is a LOT happening in the world of AI right now and our CEO Noel Hurley talked to Riddhi Kanetkar from Business Insider about the politics of AI labs alongside Nathan Benaich from Air Street Capital. Read the article via the link and we will also link the the State of AI Report the article draws on.

Our board member Jem Davies, formerly a VP at Arm, spoke on the Advantest podcast 🎙 Listen on the link below or download off streaming.

🧠 Understanding AI: Images and Neural Networks vs Tsetlin Machines. We were chuffed to present Ylva Grønningsæter with the Best Student Paper Award at ISTM for her work on using Tsetlin Machine #ai for her color image classification. "An Optimized Toolbox for Advanced Image Processing with Tsetlin Machine Composites". Here's Ylva explaining some of the advantages of using logical AI and the Tsetlin Machine, as opposed to #neuralnetworks, to solve image recognition problems. Her winning paper is available for reading at https://lnkd.in/ed-bh_Ui

Thanks to Peter Clarke at EE Times | Electronic Engineering Times for sharing the news on our recent benchmark tests: 'Literal Labs builds software models on a combination of #Tsetlin machines and voting algorithms that is allied with #binarization and #compression. In the case of the benchmark this achieved a code size of 7.29kbytes and is the driver of the 50x performance uplift. 'The company benchmarked its model using the NUCLEO-STMH7A3ZI-Q development board which features a 32-bit RISC ARM Cortex-M7 #microcontroller. '“These results reflect our focus on solving industry-critical problems while minimising the cost outlay and environmental impact typical of AI-powered solutions,” said Leon Fedden, CTO of Literal Labs, in a statement. “This is game-changing for predictive maintenance in sectors ranging from manufacturing to logistics, where downtime is costly, and efficiency is paramount,” he added.'

Sharing our first benchmarks on MLPerf Data Set 🏆 🔶 52X less energy used 🔶 54X faster inferencing 🔶 Small enough to fit on an off-the-shelf chip while maintaining high accuracy We used a 32bit Arm Cortex-M7 processor based platform from STMicroelectronics as its reference platform and created an #autoencoder model to compete with the fully connected autoencoder neural network model specified in the #MLPerf benchmarks. This solves a lot of the problems faced at the #edge for #industrial #IoT applications. Congrats to the team led by Leon Fedden, our CTO #NeuralNetworks #LLMs #TsetlinMachines #accuracy #speed #energy #byebyeblackboxes Check out our whitepaper on our website - link in comments

Forbes: "Already, the energy consumption of AI-powered data centers is becoming a significant concern for mankind. Hence, it is likely that access to #energy will, or arguably should, become a roadblock for AI development. Currently, data centers consume about 3% of global electricity and require substantial water usage. The recently launched xAI data center in Memphis, Tennessee, named #Colossus, exemplifies this issue, using 150MW of electricity and 1 million gallons of water daily for its AI training system. Noel Hurley, CEO of Literal Labs and former Arm executive, highlights the critical nature of this problem. He argues that energy and efficiency are the biggest obstacles to #AI growth, as data centers are already consuming significant portions of countries' energy resources. The market and economics have been able to adapt to more expensive #chips, but we're reaching a limit on energy consumption." Read the full article here: https://lnkd.in/e6Bf9U9S