High Value AI Components for High Value AI Applications
AI Components are building blocks for AI applications. For an AI application there are hardware components, software components and data sets. These include semiconductors and photonic devices, AI models, and vector databases. Central to many AI applications are data sets. These data sets are used to train AI applications. The training process involves the determination and assignment of weight to hardware or software probability trees.
Our Focus
The StatisticsMatrix currently focuses on semiconductors and photonics devices, Specifically this includes electronic and photonic chips and chiplets. As part of this, the StatisticsMatrix continually monitors over 5000 companies in the semiconductor and photonic ecosystems (Semiconductor Ecosystem Company Directory).Our emphasis is on companies and products that are essential to building the next generation of high-value AI applications. This means companies and products that are innovative but more importantly, commercially viable and practical.
AI Components and Applications Classified
The StatisticsMatrix has classified semiconductor and photonic chips and components into over 100 different product categories. The StatisticsMatrix has also classified AI and electronic system applications into over 100 different application categories. With our design and investment matrices, designers and investors can quickly determine what companies, chips and components are the best design and financial investments.
AI Component and Investment Selection Process
The StatisticsMatrix believes in market-guided component selection decisions and engineering-guided financial investment decisions. Market guided component selection takes into account what technology is available on the market, but more importantly the business and manufacturing dynamics the technology lives in. Engineering-guided investment decisions takes into account the business and manufacturing dynamics but more importantly the technology dynamic that the company lives in. As such, the design or investment selection process depends on a complete evaluation of technology and business metrics in relation to the product marketplace, the business ecosystem, the pace of technical evolution and today’s and tomorrow’s required specifications.
Semiconductor Ecosystem Coverage
The StatisticsMatrix covers over 5000 companies in the global semiconductor
ecosystem and the tens of thousands of products they produce. This includes public and private semiconductor companies that are involved in the fabless, foundry, chiplet, IP core, EDA, OSAT, IDM, OEM, semiconductor equipment and semiconductor materials markets.
AI Inference Vendor/Product Directory Now Online …. Mark Stansberry | LinkedIn
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