* For machine learning tasks needing ultra-high efficiency, our ground-breaking integrated circuit designs can be 10,000 more energy-efficient than conventional computer processors. * Unlike hot and heavy general purpose computers, our dedicated chip designs can help you deploy powerful machine learning in fully-autonomous mobile applications. Artificial Learning Ltd is working with leading UK universities to embody proven machine learning algorithms in ASICs (application-specific integrated circuits). Our focus is on developing ultra-efficient, highly-scalable hardware for machine learning tasks in mobile autonomous systems. Our business strategy is disruptive innovation through synthesis of titan, cutting-edge advances in machine-learning theory and VLSI technology. See our web site to contact us for more information on our product designs including Machine Learning on a Chip and Machine Learning on a Board. Company No. 08168963 registered in England & Wales.
| Website | http://www.artificiallearning.com |
| Revenue | $1 million |
| Employees | 2 (2 on RocketReach) |
| Founded | 2012 |
| Phone | +44 7572 442175 |
| Technologies |
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| Industry | Semiconductors, Semiconductor & Semiconductor Equipment, Electronics, Manufacturing |
| Keywords | Ai Acceleration, Energy Efficient Ai, Machine Learning Hardware, Deep Learning Acceleration, Ai Processors, High Performance Ai, Artificial Intelligence Hardware, Next Generation Ai, Ai Computing, Ai Optimization |
| Competitors | Amazon, Microsoft, IBM, Google, Salesforce, NVIDIA, OpenAI, C3 AI, DataRobot, H2O.ai +37 more (view full list) |
| SIC | SIC Code 367 Companies, SIC Code 36 Companies |
| NAICS | NAICS Code 33 Companies, NAICS Code 334 Companies |
Looking for a particular Artificial Learning employee's phone or email?
The Artificial Learning annual revenue was $1 million in 2026.
Peter Newman is the Director of Artificial Learning.
2 people are employed at Artificial Learning.
The NAICS codes for Artificial Learning are [33, 334].
The SIC codes for Artificial Learning are [367, 36].