Until now, the rhetoric surrounding AI was on the lines of a heated race among big tech firms to acquire top AI startups, many of which were in the early stages of research and funding for bolstering bench strength and adding to the product capabilities. The frenetic M&A activity was dubbed as the AI arms race but of late, this arms race has acquired a new slant – evangelizing the ecosystem with a slew of educational offerings that would in turn create a formidable workforce in AI, solve hiring crunch and add to the internal talent pipeline.
For example, Google, in an attempt to scale AI to more people launched free AI lessons – called Learn with Google AI that brings machine learning education to the masses for free. It also features a Machine Learning Crash Course which provides exercises, interactive visualizations, and instructional videos that anyone can use to learn and practice ML concepts. Interestingly, Google programs are designed for beginners and advanced level professionals and has an excellent repository of learning material for all levels of AI enthusiasts – ML researchers looking for advanced tutorials to beginners.
Earlier this month, Redmond giant Microsoft just opened an AI learning track to the public – making training courses available for everyone. Here’s what the public can learn – a) Intro to AI; b) Python for data science; c) Math & Statistics; d) Ethics for AI; f) Deep Learning. Through the program, developers can acquire job-ready skills and real-world experience, shore up their skills in AI and data science through a series of online courses that feature hands-on labs and expert instructors, notes the company blog.
NVIDIA has been successfully running self-paced online certifications such as Fundamentals for Deep Learning for Computer Vision & Fundamentals for Deep Learning with Multi-GPU for those who wish to learn how to train and deploy neural networks for deep learning and accelerate applications with NVIDIA CUDA and OpenACC.
Why Big Tech Firms Are Stepping Up To Democratize AI With Free MOOCs?
So, why are tech companies rushing to launch free MOOCs to bring AI and machine learning to the masses. There is definitely an overarching theme to this facet of IT giants evangelizing the ecosystem by taking a lead in providing AI & ML fundamentals to the public – tech giants want to continue to be a leader in AI by delivering high-level primers on artificial intelligence.
But how are free MOOCs aligned with the business goals? While the marketplace for AI tools is booming, tech savvy companies like Microsoft, Google, NVIDIA, Amazon are trying to find a middle ground between experimentation and implementation. Big tech giants have pumped billions of dollars into AI tools and frameworks that can open up exciting new possibilities across the verticals – be it human capital management, robo advisory in finance or improving patient services. But the potential of these services just doesn’t end there.
- Every major enterprise or startup is implementing algorithms at scale, which makes it important for organizations to maintain accurate data and carefully review these tools for accuracy and potential bias.
- So, while on one spectrum, big tech firms like Amazon, Google & Microsoft have rolled out enterprise tools for startups and companies to do ML at scale, the next logical segue is to enable people to get smarter together to use AI tools effectively. Big tech firms have realized that human role is crucial to strengthening AI capabilities.
- A recent PwC report pointed out the rising concerns about the AI revolution surrounding the workforce. Given that the human role in workforce also needs to evolve, big tech companies are investing heavily in ensuring people required to handle AI tools do it correctly and understand where the applications and algorithms would be most effective.
- This in turn would also create a stream of “new roles” that will be “data hygienists” or “AI Translators”. AI Literacy would be the foundation of a new knowledge economy, education will lead to faster adoption not just at organizations but also at grassroots level.
AI & workforce have to get smarter together — we enumerates top reasons why big tech companies are investing money into training AI workforce with publicly available courses
Bridge The Workforce Gap: According to Susan Dumais, distinguished scientist and assistant director of Microsoft Research AI, the most important reason for launching free, publicly available AI training courses is to lend a broader push throughout the technology industry to fill a gap in workers with skills in artificial intelligence. “AI is increasingly important in how our products and services are designed and delivered and that is true for our customers as well. Fundamentally, we are all interested in developing talent that is able to build, understand and design systems that have AI as a central component.,” she added.
Get trained in vendor-specific tools: The recently launched Microsoft course covers the offerings such as Microsoft Cognitive Services, that enables developers to incorporate intelligent algorithms for computer vision, natural language processing and translation capabilities into their products, and the Azure Bot Service. These programs are part of a larger corporate effort to woo developer community with focused courses on vendor-specific tools and services.
The next job market is the knowledge market: Given how STEM education is gaining popularity among non-IT professionals and there is high adoption of MOOCs among the non-IT bracket as well, smart companies have recognized the challenge and are putting into practice mechanisms to ensure the availability of personnel needed to tackle AI, ML-focused roles. Eventually, big tech firms like AWS & Google want enterprises and startups to make the most out of their offerings like AutoML or Gluon which can happen when the workforce is adequately trained.
Mainstreaming AI into enterprise and businesses calls for open source AI frameworks and tools but also needs requisite training and skill building of a wide swath of employees working. At the end of the day, Google and Microsoft are making an attempt to balance out the investment ratio between investing in AI-based technologies and framework and AI workforce. To emerge as a leader in AI race, big tech firms need to strike the right balance of tech and personnel – that explains the investment in continuous lifelong learning in emergent technologies.
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