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AI in 2020

AI in 2020 – The top 5 2019 AI developments that got us here.

AI in 2020 AI in 2019

By all accounts, 2020 is going to be an exciting year for those of us working in the field of AI.  Over the holiday season and into the first week of this year, hardly a day has gone by without a company or an analyst forecasting fantastic growth in artificial intelligence, the Internet of Things (IoT), or technology in general.  For example, IDC has forecasted that spending on AI systems is expected to reach $49.2 billion in 2020, a 31% increase from 2019.  Statista is forecasting that revenues from AI software will exceed $22 billion in 2020.  And from a purely qualitative perspective, the conversation around many aspects of AI has spread well beyond the tech community.

But, before we close the chapter on 2019 and jump into a new decade, let’s look at some of the things that happened over the past 12 months to get us to where we are today.

Last month, as we were wrapping up a historic year in artificial intelligence development, we decided to look back and examine what occurred during 2019 within the most promising field of research of our time.  What developments will future generations look back on as they map the course of AI’s history? How did AI change the world last year?

A survey of the Analytics Ventures ecosystem, including the Dynam.AI team, resulted in a better understanding of the most impactful developments in AI during 2019. AI-related areas of interest spanned the technical, scientific, socio-political, and business spheres.

The top 5 AI developments as chosen by our team are as follows:

1. The increased speed of AI-enabled medical research

One of the most beneficial uses of AI for mankind lies in the field of medical research and the ability of machine intelligence to catalyze positive patient outcomes.  For example, InSilico Medicine, working with researchers from the University of Toronto, used machine learning to create a potential new drug to prevent tissue scarring in just 46 days – from molecular design to animal testing in mice.

Consider that the time-to-development for the average drug is on the order of ten years and costs an average of $2.6 billion. Accelerated development schedules and lower R&D costs will translate into positive health outcomes for countless diseases.

2. Computer vision, image, and video analysis technology is evolving

Advances in deep learning made video / image analysis more accessible, widespread, and cheaper to deploy than at any other time in history.

Many applications continue to surface in medicine and manufacturing. Deep learning-based solutions in the field of radiology surpass human effectiveness across certain diagnostic processes, helping physicians be more effective in their daily practices. In manufacturing, accessible computer vision technologies are helping to usher in Industry 4.0 by automating quality control and safety management.

3. Powerful AI-based tools become mainstream

During the last 12 months, researchers achieved significant progress in how AI and machine learning algorithms are conceived and executed from a technology standpoint. The democratization of advanced AI tools, techniques, and infrastructure is accelerating. Large companies realize that AI is the key to sustainable competition and differentiation. They now have the tools to design and deploy effective solutions that solve tangible business problems.

Enterprise AI adoption will be the defining factor that separates elite companies from mediocre players over the next five years.

4. AI learns increasingly higher-level human functions

AI in 2020

The use of tools to achieve goals has long been thought to be an (almost) exclusively human trait, with limited examples in a few other species like crows and chimpanzees. This year, artificial agents created by OpenAI “learned” tool use from an experiment involving multi-agent competition, without being explicitly taught. This is clearly a large step forward in developing valuable machine intelligence.

5. Natural language processing grows more advanced

Specifically, the publication of Google’s BERT model accelerated the widespread usage of advanced NLP. The model proposed a brand new network structure for NLP that allows for language to be understood in a much more sophisticated, machine-computable way. The model is open-source and widely available for public use in applications.

Those were the top 5,  but other topics that were highlighted as having significance in 2019 included:

  • The merger between quantum computing and AI, and more generally, advances in quantum computing
  • The sense that for many consumers, recommendation engines have become more useful than annoying
  • Many companies have moved passed research and planning stages and are beginning to invest in operational AI programs to solve real business problems

In 2020 and beyond, as knowledge about the power and implications of AI continues to spread, individuals, organizations and governments clamor to understand how, why, and where this power may be used for good. Private and public entities alike continue to wrestle with the ethical ramifications of a horizontal technology forecasted to be more impactful than the Internet itself. All parties understand that the technology, given the right guidance, can introduce massive positive changes across all aspects of human life.

For our part, Dynam.AI is translating enterprise business problems into machine learning problems and providing practical deep learning and computer vision for organizations across sectors and companies small and large.

As we enter this new year, this new decade,  I invite you to consider the following:

  • Where do you see the most impact for artificial intelligence in the coming year for YOUR organization?
  • Are you positioned to take advantage of 2019’s AI advances and translate them into 2020 successes?
  • How can Dynam.AI help you navigate the benefits of AI in a way that maximizes positive outcomes for your business?

Let us know how we can help.  We are looking forward to hearing from you!


About the Author

Dr. Michael Zeller

Dr. Michael Zeller has over 15 years of experience leading artificial intelligence and machine learning organizations through business expansion and technical success. Before joining Dynam.AI, Dr. Zeller led innovation in artificial intelligence for global software leader Software AG, where his vision was to help organizations deepen and accelerate insights from big data through the power of machine learning. Previously, he was CEO and co-founder of Zementis, a leading provider of software solutions for predictive analytics acquired by Software AG. Dr. Zeller is a member of the Executive Committee of ACM SIGKDD, the premier international organization for data science and also serves on the Board of Directors of Tech San Diego.  He is an advisory board member at Analytics Ventures, Dynam.AI’s founding venture studio.