MLCommons, an international artificial intelligence (AI) standards body formed in 2018, launched MLPerf Tiny, their first benchmark targeted at the inference capabilities of edge and embedded devices, or what they call “intelligence in everyday devices”. The new benchmark is now part of the overall MLPerf benchmark suite, which measures AI training and inference performance on a wide variety of workloads, including natural language processing and image recognition. The benchmark covers four machine learning (ML) tasks focused on camera and microphone sensors as inputs: keyword spotting, visual wake words, tiny image classification, and anomaly detection. Some important use cases include smart home security, virtual assistants, and predictive maintenance.
Opportunity for DNA as a New Archive Storage Medium
Mark Nossokoff and Bob Sorensen
Using biological building blocks in place of traditional materials to assemble computers has been a research topic for many years, but recently the first potential commercial use cases have begun to emerge, centered on storage for large data sets. The DNA Storage Alliance, created to promote a storage ecosystem based on synthesized DNA strands, recently shared their aspirations for the emerging technology that offers significant promise in durability, simplicity, cost, and density over traditional magnetic counterparts. The initial goals of the alliance are to educate the public and raise awareness about DNA-based storage. Further out, the alliance may pursue the creation of specifications and standards, such as encoding, physical interfaces, retention, and file systems, to ensure that DNA-based solutions complement existing storage hierarchies. The alliance notes that expectations for the growth rate of current storage mechanisms cannot keep pace with the rising demand for data storage, particularly where growing data retention and related data mining efforts are driving the need to save increasingly larger data sets for longer periods of time. Such requirements are well suited to DNA-based archive storage characteristics in applications including digital content creation, robotics, smart cities, autonomous vehicles, healthcare, astronomy, and climate science.
8 202021 | HYP_Link
AI Powered Verusen and Machine Compare Partnership Targets Supply Chain Pain Points
Tom Sorensen, Alex Norton
In an announcement made in December, 2021, Verusen, a startup specializing in leveraging AI resources to support global supply chains, detailed a recently formed partnership with Machine Compare, a supplier of one of the world's largest databases for machinery and leading B2B marketplace for buyers and sellers of industrial spare parts. The partnership is aimed at enhancing the customer experience, limiting risk, reducing waste, and helping companies conduct materials management and commerce in a new and efficient way. Verusen founder and CEO Paul Noble explains the partnership is targeted to resolve a painful and wasteful process and will ultimately allow manufacturers to realize a whole new level of sustainability. For his part, Machine Compare CEO Ben Findlay is looking for a reduction in downtime, stockouts, and costs. Furthermore, the burdens lifted by the Verusen AI capabilities are targeted to reduce the amount of manpower committed to time-consuming, reactive tasks, allowing for a more proactive and long-term management of goals.