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{{AfC submission|t||ts=20250611234732|u=Rhg2|ns=118|demo=}}{{AFC comment|1=In accordance with Wikipedia's [[Wikipedia:Conflict of interest|Conflict of interest policy]], I disclose that I have a conflict of interest regarding the subject of this article. <!--Comment automatically added by the Article Wizard--> [[User:Rhg2|Rhg2]] ([[User talk:Rhg2|talk]]) 23:47, 11 June 2025 (UTC)}}▼
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Untether AI was a Canadian technology company that developed microchips and compilers for neural net processing. The at-memory compute architecture was built largely on standard silicon processes with some customization done on memory cells and processing elements. The $125 million dollars raised in Series B funding in July 2021<ref>{{cite web |title=Betakit Series B, July 2021 |url=https://betakit.com/intel-backed-untether-ai-raises-125-million-adds-cppib-tracker-capital-as-investors/ |access-date=11 June 2025}}</ref> led to a top MLPerf disclosure in August 2024 <ref>{{cite web |title=yahoo MLPerf, August 2024 |url=https://finance.yahoo.com/news/untether-ai-announces-speedai-accelerator-150000879.html |access-date=11 June 2025}}</ref> and a launch of its speedAI-240 product in October 2024 <ref>{{cite web |title=businesswire speedAI-240, October 2024|url=https://www.businesswire.com/news/home/20241028172679/en/Untether-AI-Ships-speedAI-240-Slim-Worlds-Fastest-Most-Energy-Efficient-AI-Inference-Accelerator-for-Cloud-to-Edge-Applications |access-date=11 June 2025}}</ref>. The MLPerf results indicated the at-memory architecture could achieve 3 to 6X the power efficiency of competing approaches. Despite the early success, Untether AI was shut down in June 2025 <ref>{{cite web |title=eetimes shut down, June 2025 |url=https://www.eetimes.com/untether-ai-shuts-down-engineering-team-joins-amd/ |access-date=11 June 2025}}</ref>.▼
{{Short description|added 2 more references with more citations as more evidence of notability}}
{{Draft topics|internet-culture|software|technology}}
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▲'''Untether AI''' was a Canadian technology company that developed microchips and compilers for neural net processing. The patented computational memory<ref>{{cite book |first1=Duncan | last1=Elliott| last2=Snelgrove |first2=Martin| last3=Stumm |first3=Michael | chapter=Computational Ram: A Memory-simd Hybrid and Its Application to DSP|title=Proceedings of the IEEE Custom Integrated Circuits Conference |date=1992 | pages=30.6.1–30.6.4|doi=10.1109/CICC.1992.591879 | isbn=0-7803-0246-X}}</ref><ref>{{cite journal |last1=Snelgrove |first1=Martin |last2=Wiebe |first2=Darrick |title=Computational memory |journal=US Patent 11614947B2 |date=2023-03-28 |url=https://patents.google.com/patent/US11614947B2/en |access-date=15 June 2025}}</ref> architecture (also known as at-memory compute
<ref>{{cite web |title=Why did Untether AI fail |url=https://www.zach.be/p/why-did-untether-ai-fail |date=June 2025 |publisher=www.zach.be|access-date=15 July 2025}}</ref>.
== References ==
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