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  2. I make over $500,000 in total compensation at Google without ...

    www.aol.com/news/worked-way-500k-ai-job...

    You can be a Google engineer without a master's or Ph.D., but from what I've seen, most people in the AI and machine learning field have these qualifications, showing how competitive the field is.

  3. François Chollet - Wikipedia

    en.wikipedia.org/wiki/François_Chollet

    François Chollet (French: [fʁɑ̃swa ʃoˈlɛ]; born 20 October 1989) is a French software engineer and artificial intelligence researcher formerly Senior Staff Engineer at Google. Chollet is the creator of the Keras deep-learning library, released in 2015.

  4. ElevenLabs - Wikipedia

    en.wikipedia.org/wiki/ElevenLabs

    ElevenLabs was co-founded in 2022 by Piotr Dąbkowski, an ex-Google machine learning engineer and Mati Staniszewski, an ex-Palantir deployment strategist. [2] Both were raised in Poland, and their inspiration for founding ElevenLabs reportedly came from watching inadequately dubbed American films.

  5. Jianchang Mao - Wikipedia

    en.wikipedia.org/wiki/Jianchang_Mao

    Jianchang (JC) Mao (born in November 1963) is a Chinese-American computer scientist and Vice President, Google Assistant Engineering at Google. His research spans artificial intelligence, machine learning, computational advertising, data mining, and information retrieval.

  6. Google Brain - Wikipedia

    en.wikipedia.org/wiki/Google_Brain

    The Google Brain team contributed to the Google Translate project by employing a new deep learning system that combines artificial neural networks with vast databases of multilingual texts. [21] In September 2016, Google Neural Machine Translation (GNMT) was launched, an end-to-end learning framework, able to learn from a large number of ...

  7. Google DeepMind - Wikipedia

    en.wikipedia.org/wiki/Google_DeepMind

    These features, Adaptive Battery and Adaptive Brightness, use machine learning to conserve energy and make devices running the operating system easier to use. It is the first time DeepMind has used these techniques on such a small scale, with typical machine learning applications requiring orders of magnitude more computing power. [131]

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