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The amazing development of transistor technology has been the main driving force behind modern electronics. Over time, this process has slowed down introducing performance bottlenecks in data-intensive applications. A main cause is the classical von Neumann architecture, which entails constant data exchanges between processing units and data memory, wasting time and power. As a possible alternative, the Beyond von Neumann approach is now rapidly spreading. Although architectures following this paradigm vary a lot in layout and functioning, they all share the same principle: bringing computing elements as near as possible to memory while inserting customized processing elements, able to elaborate more data. Thus, power and time are saved through parallel execution and usage of processing components with local memory elements, optimized for running data-intensive algorithms. Here, a new memory-mapped co-processor (MeMPA) is presented to boost systems performance. MeMPA relies on a progra
[CONTRIBUTED THOUGHT LEADERSHIP ARTICLE] In-memory computing promises to revolutionize AI inference. Given the rapid adoption of generative AI, it makes [.]
NXP India Tech Startup Challenge: Jointly organized with Startup India, this event is an initiative by the Ministry of Commerce and Industry, aimed at linking the Indian startup ecosystem. The program aims to propel the Indian ecosystem towards global visibility and network scalability for tech startups as these startups will get an opportunity to present to thousands of tech leaders.
OpenAI GPT5 has likely started its final training run. An earlier smaller run of a test version of GPT5 gave Sam Altman one of his top 4 feelings of a leap in