<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/365D65FA-78ED-4C48-AB50-96DD3099292A" ns1:id="365D65FA-78ED-4C48-AB50-96DD3099292A"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/8930BA03-CBDD-4A01-A1FE-CDA5EB212786" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/FBFC4DF1-2114-4541-8CB5-BCE7C6EF9B2D" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/13C979ED-CCCE-4C21-9953-307B6EC53D42" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/FBFC4DF1-2114-4541-8CB5-BCE7C6EF9B2D" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2023-11-30T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/905B496D-C2A0-468D-9630-51D7AAA48F0D" ns1:rel="FUND" ns1:start="2023-07-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10075703</ns2:identifier></ns2:identifiers><ns2:title>Mignon Ultra-Low-Power Edge AI Semiconductor Chip</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Many electronic sensors that monitor health, security and industrial processes (amongst other applications) are now linked to computer networks. This is collectively termed the Internet-of-Things, IoT. It is leading to better healthcare, greater security and more efficient industries by collecting and analysing data continuously. Experts predict that by 2030 there could be \&amp;gt;1trillion devices in the internet of things. However, current network bandwidth and computing power could soon limit development. This will first become a problem when sensors need to do a complicated task, like deciding what is in an image.

Doing this within a device, rather than transmitting lots of image data over a network, is called _edge AI_. The most common technology in edge AI is called a neural network. This approach takes a lot of computing power. To improve matters, the partners on this project have developed a new approach called a Tsetlin machine. In this, different groups of electronic components decide their outputs based upon what other linked components outputs are. This is \&amp;gt;1000 times faster than comparable neural network AI chips and uses 10,000 time less energy to give the same answer. Once we have developed the technology further, this will be very useful in edge AI devices in the internet of things.

To make money from this, we must first start to improve how it works, in this project. Other companies will then make computer chips for us. They will supply these to companies who build devices and pay us a royalty for using our idea. We only established as a company recently and are still working out how much money we will ultimately make. We think it will take 18-30 months before we can make any revenue from the invention.</ns2:abstractText></ns2:project>