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How to Secure Data When Computing with PAC Privacy

By Dick Weisinger

Data privacy is a major concern for many applications of machine learning, especially when sensitive information such as medical records or personal images is involved. How can we share useful models without revealing the data they were trained on? A

AI Chips: AI-Targeted Massive Wafers Speed the Creation of Large Language Models

By Dick Weisinger

‘Wafer-scale engine‘ (WSE) – it is what Cerebras, a semiconductor manufacturer, calls the architecture of their massive GPU engine on a single ‘chip’. It is 56 times the size of the largest ‘standard’ GPU chip and packs 3000 times more

Probabilistic Computers: A Poor Man’s Quantum Computer

By Dick Weisinger

Classic computers operate on binary data — data stored as either a ‘0’ or a ‘1’. Quantum computers operate on what is called a qubit, a value that is a probabilistic combination of the two states of ‘0’ and ‘1’.

Computing: Creating Organic Chips from Silicon and Human Neurons

By Dick Weisinger

Wetware computing combines human biology with the silicon, plastic, and metals used by traditional semiconductors. A number of businesses and researchers are beginning to use synthetic biology to build computer chips. Neurons from mice and humans are being integrated into

Computing: Alternative Computations Scale the Limits of Moore’s Law

By Dick Weisinger

Because advances in conventional semiconductors are coming up against the limits of Moore’s Law, researchers are looking for other options for improving computing performance. Quantum Computing is one path being investigated. Another novel hardware approach is called the Ising Machine,