The Deep Learning term is becoming more popular as an appealing phrase to get public attention to deep tech and VC investment as we can see some investment firms if not many actively utilize it to intrigue their investors and readers.
Not surprisingly, recent breakthroughs in AI happened due to further advancement of deep learning research and the introduction of massive neural network applications like OpenAI’s GPT-3 or DeepMind’s DNA exact shape prediction model.
More and more companies restructuring and re-inventing their businesses and products towards AI-enabled to provide a data-driven product value proposition such as more personal customization, cheaper access to the services, and unprecedented precision.
Deep Learning continuously breaking into every aspect of human intellectual activity by either augmenting human creation or by replacing it. During the next decade, the most important software will be created by deep learning, enabling self-driving cars, accelerated drug discovery, and more.
We’ll see a big jump in value creation in software development by utilizing Big Data and Machine Learning rather than hard-coded and siloed by humans.
2020 was a milestone year for conversational human-level AI. With the inception of GPT-3, AI systems could understand and generate language with human-level accuracy and can seriously be considered as the source of knowledge or wisdom. It requires 10x the computing resources of computer vision.
We will see more research interest and funding in Reinforcement Learning and GAN-type applications.
Over two decades the Internet added $13 trillion to equity market capitalization globally. Deep Learning has created $2 trillion in market capitalization as of 2020. It can possibly generate an additional $30 trillion to the equity market by 2037.
With clear global expectations around value creation from AI and Deep Learning, it is paramount to be able not to lag behind in accelerated competition imposed by already AI transformed companies and AI experts.
Breaking into AI space though is extremely tough due to the very slow learning curve and unclear starting point. Fear of coding and reading math papers is another sour pill. The existing solutions like Coursera-type courses or expensive bootcamps leave only the chance to those who have some big cash to invest in upskilling, so it’s not an affordable way.
By utilizing a hybrid model of studying the online content, learning from experienced mentors, and with help of the community, in unpackAI we have a good learning solution for you:
We are launching an affordable online part-time Bootcamp “Building Applications with Deep Learning” that’s the main focus to help you break into AI space by building ML models from the first week and building DL Image Recognition Web Application just in 3 weeks. It’s an intensive Bootcamp and most suitable for those who have prior coding background and some ideas around how AI can impact personal projects, careers, or businesses.
What will we bring to you?
– Experienced Mentors and TAs to guide through the learning process
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If you are excited about the opportunity to become AI Practitioner, please go to our website and leave the application: