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Founder of Telegram, and before it of VK.

• Our readingkorrents.com

  Maths is essential schooling: it trains you to split big problems into small ones and to think for yourself, the same skill programming, project management and founding a company need.

  Their words

  Yeah. I still think math is essential. It's something that shapes your brain, it teaches you to rely on your logical thinking to split big problems into smaller parts, put them in the right sequence, solve them patiently, trying again if it doesn't work.

  youtube.com

Professor of international affairs at Johns Hopkins SAIS and co-author, with Abraham Newman, of Underground Empire: How America Weaponized the World Economy.

• Lovedrcmnd.app

  Aegypt

  Their words

  Crowley is one of the great unrecognized novelists of our time, and his Aegypt novel sequence seems exactly on point for the strange days we live in.

  programmablemutter.com

Biochemist at University College London; writes about the origin of life and the role of energy in evolution, in The Vital Question and Transformer.

• Our readingkorrents.com

  Bacteria never became complex because the barrier is structure, not information — they explored genetic space far more thoroughly than eukaryotes and still got stuck.

  Their words

  So they have explored genetic sequence space far more thoroughly than eukaryotes ever did because they’ve had twice as long at least, and they’ve got much larger populations, and they never got around this problem. So why can’t they? It seems as if you can’t solve it with information alone. So what’s the problem? The problem is structure.

  youtube.com

One of the eight authors of the 2017 transformer paper "Attention Is All You Need", then at Google Brain; per the paper's own contribution note, proposed scaled dot-product attention, multi-head attention and the parameter-free position representation.

From one piece Attention is all you need 2 beliefs, in the piece's order there

• Our readingkorrents.com

  Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions.

  Their words

  We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.

  Attention is all you needarxiv.org

• Our readingkorrents.com

  A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution.

  Their words

  To the best of our knowledge, however, the Transformer is the first transduction model relying entirely on self-attention to compute representations of its input and output without using sequence-aligned RNNs or convolution.

  Attention is all you needarxiv.org

One of the eight authors of the 2017 transformer paper "Attention Is All You Need", then at Google Research; per the paper's own contribution note, designed, implemented, tuned and evaluated the model variants the paper rests on.

From one piece Attention is all you need 2 beliefs, in the piece's order there

• Our readingkorrents.com

  Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions.

  Their words

  We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.

  Attention is all you needarxiv.org

• Our readingkorrents.com

  A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution.

  Their words

  To the best of our knowledge, however, the Transformer is the first transduction model relying entirely on self-attention to compute representations of its input and output without using sequence-aligned RNNs or convolution.

  Attention is all you needarxiv.org

One of the eight authors of the 2017 transformer paper "Attention Is All You Need", then at Google Brain; per the paper's own contribution note, designed and implemented parts of tensor2tensor, the codebase that replaced the team's earlier one.

From one piece Attention is all you need 2 beliefs, in the piece's order there

• Our readingkorrents.com

  Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions.

  Their words

  We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.

  Attention is all you needarxiv.org

• Our readingkorrents.com

  A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution.

  Their words

  To the best of our knowledge, however, the Transformer is the first transduction model relying entirely on self-attention to compute representations of its input and output without using sequence-aligned RNNs or convolution.

  Attention is all you needarxiv.org

One of the eight authors of the 2017 transformer paper "Attention Is All You Need", then at Google Research; per the paper's own contribution note, experimented with novel model variants and was responsible for the initial codebase, efficient inference and visualisations.

From one piece Attention is all you need 2 beliefs, in the piece's order there

• Our readingkorrents.com

  Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions.

  Their words

  We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.

  Attention is all you needarxiv.org

• Our readingkorrents.com

  A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution.

  Their words

  To the best of our knowledge, however, the Transformer is the first transduction model relying entirely on self-attention to compute representations of its input and output without using sequence-aligned RNNs or convolution.

  Attention is all you needarxiv.org

One of the eight authors of the 2017 transformer paper "Attention Is All You Need", then at Google Research; per the paper's own contribution note, proposed replacing recurrent networks with self-attention and started the effort to evaluate the idea.

From one piece Attention is all you need 2 beliefs, in the piece's order there

• Our readingkorrents.com

  A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution.

  Their words

  To the best of our knowledge, however, the Transformer is the first transduction model relying entirely on self-attention to compute representations of its input and output without using sequence-aligned RNNs or convolution.

  Attention is all you needarxiv.org

• Our readingkorrents.com

  Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions.

  Their words

  We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.

  Attention is all you needarxiv.org

One of the eight authors of the 2017 transformer paper "Attention Is All You Need"; per the paper's own contribution note, designed and implemented the first Transformer models, with Ashish Vaswani.

From one piece Attention is all you need 2 beliefs, in the piece's order there

• Our readingkorrents.com

  A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution.

  Their words

  To the best of our knowledge, however, the Transformer is the first transduction model relying entirely on self-attention to compute representations of its input and output without using sequence-aligned RNNs or convolution.

  Attention is all you needarxiv.org

• Our readingkorrents.com

  Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions.

  Their words

  We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.

  Attention is all you needarxiv.org

One of the eight authors of the 2017 transformer paper "Attention Is All You Need", then at Google Brain; per the paper's own contribution note, designed and implemented the first Transformer models, with Illia Polosukhin, and was involved in every aspect of the work.

From one piece Attention is all you need 2 beliefs, in the piece's order there

• Our readingkorrents.com

  Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions.

  Their words

  We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.

  Attention is all you needarxiv.org

• Our readingkorrents.com

  A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution.

  Their words

  To the best of our knowledge, however, the Transformer is the first transduction model relying entirely on self-attention to compute representations of its input and output without using sequence-aligned RNNs or convolution.

  Attention is all you needarxiv.org

One of the eight authors of the 2017 transformer paper "Attention Is All You Need", then at University of Toronto; per the paper's own contribution note, designed and implemented parts of tensor2tensor, the codebase that replaced the team's earlier one.

From one piece Attention is all you need 2 beliefs, in the piece's order there

• Our readingkorrents.com

  A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution.

  Their words

  To the best of our knowledge, however, the Transformer is the first transduction model relying entirely on self-attention to compute representations of its input and output without using sequence-aligned RNNs or convolution.

  Attention is all you needarxiv.org

• Our readingkorrents.com

  Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions.

  Their words

  We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.

  Attention is all you needarxiv.org

Documentary filmmaker and writer; director of The Thin Blue Line and the Oscar-winning The Fog of War, and author of Believing is Seeing.

• Lovedrcmnd.app

  Gettysburg

  Their words

  Frassanito was obsessed with Gettysburg and with reconnecting photographs of the Civil War to the circumstances under which they were taken. Through this obsessive quest, he reconnects the photographs to actual geographic places and reorders them to reflect the real sequence of events. It's a deeply fascinating enterprise and I was inspired by his work.

  fivebooks.com