Topic: Research
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DQN learns Atari from pixels
DeepMind trains one network to play many games from raw screen images and score alone.
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ImageNet is released
A labelled dataset of more than fourteen million images is published at CVPR.
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LSTM solves long-range memory
Hochreiter and Schmidhuber introduce a recurrent cell with gated memory.
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Perceptrons narrows the field
Minsky and Papert prove what single-layer networks cannot represent.
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Turing proposes the imitation game
Computing Machinery and Intelligence replaces “can machines think?” with a behavioural test.
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The perceptron is unveiled
Rosenblatt demonstrates a machine that adjusts its own weights from examples.
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AI Benchmarks Explained: What the Scores Actually Measure
Benchmark numbers drive coverage, procurement and valuations. Most of the widely-quoted ones are saturated, contaminated, or not comparable between models.
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Why AI Models Hallucinate
Hallucination is not a bug in language models. It is a predictable consequence of how they are trained and, crucially, of how…
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Tokens and Embeddings: How Machines Represent Meaning
Models do not read words or understand meaning directly. They read tokens and operate on vectors. This distinction explains a whole class…
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Transformers Explained: The Architecture Behind Modern AI
Attention lets a model weigh every word against every other word at once. That one idea is why modern AI scaled when…