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The language of AI – EC San Francisco will put you in the know

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If you want a career in AI, you should start with a course to study English in San Francisco. Motley Fool says that “California, particularly San Francisco and the Silicon Valley region, is the motherland of AI. Companies like Google, Facebook, Apple, and many others call this home and have a massive need for AI talent and as the region is thriving in other sectors such as healthcare and education, makes the city a great place to head for to find work in these fields.” 

San Francisco is a bouncing back after the pandemic and property prices stabilising, gives small startups and innovative thinkers the opportunity to make San Francisco the perfect place to launch an AI-driven company. And talking of driven – the city has thousands of driverless passenger vehicles throughout the city—quite amazing to see firsthand!  You’ll see one practically everywhere downtown our students are in line to check out Waymo and Cruze to use these cars. 

Of course, this new wave of tech is having a positive effect on the city; new communities are being built and fresh and funky entertainment venues can open now that rents are manageable. There’s less traffic than many US cities thanks to the excellent service offered by the MUNI – which, by the way, is free for those aged 18 and under. No forms to fill – just carry an ID to prove your age in case its required. 

English is key to working in this sector, communication between teams, commands in coding language and of course all the learning materials. Conferences, journals, and educational resources required to master the skills to be able to code. 

To give you a heads up, we’ve compiled a list of 10 acronyms that are common – and whilst you may be able to recite these and recall the words – knowing what they actually mean may be a different matter – especially if you have to explain to a colleague who doesn’t speak the same mother tongue as you. 

  1. ANN: Artificial Neural Network. 
  1. CNN: Convolutional Neural Network – often used for image processing. 
  1. RNN: Recurrent Neural Network – has “memory”, used for sequences like time series or natural language. 
  1. LSTM: Long Short-Term Memory – a type of RNN that’s good at learning long-term dependencies. 
  1. GAN: Generative Adversarial Network – consists of two networks, one generating data and the other evaluating it. 
  1. NLP: Natural Language Processing – deals with the interaction between computers and human language. 
  1. RL: Reinforcement Learning. 
  1. API: Application Programming Interface – allows different software entities to communicate with each other. 
  1. TPU: Tensor Processing Unit – a type of processing device designed to accelerate deep learning tasks. 
  1. GPU: Graphics Processing Unit – initially designed for rendering graphics but now often used for deep learning computations. 

So while you may be looking to mastering the skill of AI coding that is for the online world, you will find that learning English with people will give you more than language skills; learning how to communicate with people, understanding their needs and behaviours and cultural nuances are all skills that will set you apart when looking for a role in the exciting world of Artificial Intelligence 

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