Your 6 Months Roadmap to becoming an AI Developer

Your 6 Months Roadmap to becoming an AI Developer

As Artificial Intelligence and Deep Learning are affecting the realms across all industries, and tech giants are competing against each other for AI talents, partnering, and acquiring AI startups, many asked, how may I learn more about this subject and become an AI or Machine Learning developer?

The good news is that with the democratization of AI tools and libraries, for instance, Google unleashed TensorFlow, Yahoo’s CaffeOnSpark, and Microsoft’s Cognitive Toolkit, you can use their off-the-shelf libraries and become an AI Architect.

With the seismic shifts felt by banks, payment companies, and insurance companies, the AI scene has influenced a shakeup in the financial service industry. Many large financial corporations no longer see their peers as their competitors, but Google and Facebook. We learn from the Wired magazine that Facebook trains and tests about 300,000 machine learning models each month, and this testing process is fully automated without human intervention. That is, machine learning to train another machine to learn. “The system can automatically choose algorithms and parameters that are likely to work. It can almost predict the result before the training.”

Below is an Interactive Chart which explains how Neural Networks work, right here in your browser, chart created by Daniel Smilkov and Shan Carter:

neutral-network

The future is already here. It would be wise if ordinary people like us learn to robotize processes, Robotics Process Automation (RPA), together with AI, to build autonomous corporations, to increase output per hour.

Thanks to IBM Watson, Didi Chuxing, and Amazon Alexa, they have partnered to co-develop curriculum with Udacity to offer a new nanodegree in AI, this degree is comprised of two, 13-week terms. As of writing, there are 4500 applicants and only 500 seats available.

To learn more about AI Nanodegree, please read more:
https://www.udacity.com/ai

IBM and Microsoft recently opened its Machine Learning and Big Data capabilities to the masses, that means anyone can now train their own AI platforms. Undoubtedly, we will see many Alaas (Artificial intelligence as a Service) companies such as Bonsai (a platform that offers developers easy-to-use programming experiences, as well as control over their AI solutions), PandoraBots (a company that enables you to build your own chatbot, including speech and images), Letzgro (you can hire them for your AI projects), running on world’s fastest TPUs and GPUs (https://developer.nvidia.com/deep-learning-getting-started) integrating with the financial service industry and across all industries.

Fred Wong has over 10 years of experiences in the semiconductor industry, and has a love of Fintech, AI and smart programmable chips such as GPUs, TPUs, FPGAs.