So I fell asleep watching a video about creating a self-driving car using plain JavaScript and also just binge watched almost the entirety of Hunter x Hunter, so when I woke up I had the wonderful shower thought that the parallelization process of using a machine learning algorithms such as an artificial neural network to solve a puzzle is quite similar to those anime scenes where the character produces multiple clones of themselves and then uses all their clones to attack the enemy at the same time. The idea is that no one clone is strong enough or fast enough to hit the enemy, but that's fine if you're capable of just making more and more clones until the enemy is defeated. Artificial intelligence can attempt to create intelligent systems by giving each of these clones a "brain," identifying the best brains, and then storing those brains permanently to use as the template for the next generation of clones, thereby creating a genetic algorithm. The computer science field of intelligent systems, or artificial intelligence (AI), simply is the study of how a system can solve difficult problems. Although I have only started being exposed to AI, it has always been a source of fascination to me, and I would imagine many others.

Researchers at the company's labs in the U.S. and Asia said they have achieved human parity when translating the newstest2017 collection of news articles from Chinese to English. The articles are commonly used when testing and benchmarking translation results. Microsoft hired third-party bilingual human evaluators to assess the suitability of its methodology. The evaluators compared the results of Microsoft's AI with translations produced by two human linguists. The human translators worked independently of each other to create their renditions of the news stories.

Rather than use the conventional translation technique (statistical machine translation), Microsoft used deep neural networks that more closely mimic human behavior. Its team used a dual learning system where the AI would reverse the translation to gauge how well it did. The company also relied on deliberation networks, which mimic the repetitive process people use to revise writing, as well as joint training that used English-to-Chinese translations to boost the training samples for Chinese-to-English work. The AI would even change the direction of its translation (left to right and vice versa) and promote results that were similar both ways. It's not clear that this is ready for prime time. Microsoft based its claim based on a lone test (albeit a thorough one) focused on news stories.

If pigeons were trained to detect cancer, maybe cats neurons can be trained to translate Chinese. But you would probably need to connect wires to the cat's brain instead of just working with his vision.