Articolo 52 dell'AI Act [1]. Classification of general-purpose AI models as general-purpose AI models with systemic risk ... 2. A general-purpose AI model shall be presumed to have high impact capabilities pursuant to paragraph 1, point (a), when the cumulative amount of computation used for its training measured in FLOPs is greater than 10^25 Dato che quel 10^25 è il discrimine tra AI a rischio sistemico e AI non a rischio sistemico, bisogna essere chiari. Cosa intendeva il legislatore per FLOPs ? Plurale di FLOP, ovvero, QUANTITA' di operazioni in virgola mobile, oppure FLOP al secondo, ovvero, operazioni in virgola mobile AL SECONDO ? In entrambi i casi è sbagliato. Nel primo, è un errore "morfologico", il plurale di FLOP è FLOPS, non FLOPs. Nel secondo, ovvero nel caso il significato fosse di FLOP/s, in questo caso è un errore "matematico" di stima, perché 10^25 è milioni di volte superiore alla "potenza" dei vari GPT4, Gemini, ecc. FLOPs vs FLOPS When dealing about computing effort and computing speed (hardware performance), terminology is usually confusing. The term ‘compute’ is usually ambiguous, sometimes applied for a number of operations or the number of operations per second. However, it is important to clarify what kind of operations and the acronyms for them. In this regard, we will use the acronym FLOPS to measure hardware performance, by referring to the number of floating point operations per second, as standardised in the industry, while FLOPs will be applied to the amount of computation for a given task (e.g., a prediction or inference pass), by referring to the number of operations, counting a multiply-add operation pair as two operations. For instance, we found out that the acronym FLOP may be misleading. By FLOP, we mean one floating point operation, a measure of the amount of compute (computing effort) and by FLOPS, we mean floating point operations per second, i.e., FLOPS = FLOP/s. However, many papers, especially CV papers, use the terms FLOPs and FLOPS to refer to the number of operations, but we will be just use FLOPs as the plural of FLOP, never as FLOPS. Then there is the question of what a FLOP is. When dealing with DNN, this is usually associated with the number of multiply-add operations, even there are other type of operations involved when executing a DNN. This is done this way because it is usually a good estimation [Hollemans, 2018, Clark et al., 2020]. More specifically, we will count one fused multiply-add operation as 2 FLOPs (note the lowercase ‘s’). Hardware manufacturers count them in this manner [NVIDIA, 2015], because in fact there are two mathematical operations. However, CV research papers count a multiply-add operation as only one operation. In this case, we will multiply the number of operations reported by 2. In sum, the acronym FLOPS will be applied to measure hardware performance, by referring to the number of floating point operations per second, as standardised in the industry, while FLOPs will be applied to the amount of computation for a given task (e.g., a prediction or inference pass), by referring to the number of operations, counting a multiply-add operation pair as two operations." [2] A. [1] https://www.europarl.europa.eu/doceo/document/TA-9-2024-0138_EN.pdf [2] https://arxiv.org/pdf/2109.05472.pdf