An enlightened future with Artificial Intelligence

An enlightened future with Artificial Intelligence

The decisions we make now and in the near future will set the tone for the rest of the decade, including how artificial intelligence (AI) can develop and how we will use it.

Maximizing the benefits of human society will require enlightened leadership.

This article focuses on providing a moment of reflection in the context of where we are and where we are going from a policy and philosophical standpoint and will serve as a prelude to a more technical article on the next generation of AI.

The potential for a positive use case for AI includes the fight against COVID-19. For example The Lancet published an article written by Zhou et al. entitled”Artificial intelligence in the repurposing of a COVID-19 drugIn this review, we present guidelines on how to use AI to accelerate drug repurposing or reinstatement, for which AI approaches are not only formidable but also essential. We discuss how to use AI models in precision medicine, and as an example, how AI models can accelerate COVID-19 drug reuse.”

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Source for the image above Lancet Zhou et al. Artificial intelligence in the repurposing of a COVID-19 drug

Another example is provided by Brandon Vigliarolo. MIT develops machine learning model to accelerate release of COVID-19 vaccine and states that “researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a new combinatorial machine learning system that could reduce the research time needed for a COVID-19 vaccine and make it more effective.” is, the researchers said.”

“The platform, called Optivax, is focused on developing peptide vaccines, which are a different approach from common whole virus, DNA and RNA vaccines out of more than 100 vaccines currently in development.”

types of AI

We have tried to focus on the difference between Narrow AI and Artificial General Intelligence (AGI), although it is an intermediate step in the middle, we will be the focus of AI research in the 2020s. See the article on this hyperlink for definitions of AI, Machine Learning and Deep Learning.

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AGI remains an aspiration for the future

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Source for the image above: Andrew Cochran, What is Artificial Intelligence?

AGI is a “..the hypothetical intelligence of a machine that has the ability to understand or learn any intellectual task that a human can perform. It is a primary target of some AI research and a common theme in science fiction and futures studies. ”

The article that follows will be related to the next generation of AI including research work David Cox and other researchers are working on that could yield Broad AI, An intermediate step between narrow AI and protest and enables AI to scale across multiple sectors of the economy and across the edge (on devices).

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Source for the image above Jim Soferer IBM Cognitive

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Source for the image above Jim Soferer IBM Cognitive

In terms of AI including Deep Learning we have had great success in the areas of Social Media and Ecommerce where there is huge amount of data and hence it is no surprise that the likes of Google, Facebook, Amazon, Ali Baba, Microsoft . (LinkedIn owner) Adi has some of the strongest AI teams.

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However, although data is important, it is also about people. Data scientists, machine learning engineers and deep learning researchers who are creating or implementing AI algorithms as well as those with strategic responsibility for implementing technology within organizations such as digital transformation, technology, business translators and others .

Beyond that it is also about you and all of us who create data with our digital footprints and are often the end users.

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Source for the image above: Tes.com

Our policy makers and leaders, both at the organizational level and at the national level, will also have a growing influence on the shape of AI and next-generation technology as the scaling of AI to various sectors of the economy will result in human interactions in increasingly sophisticated and complex sectors. It touches on issues of data privacy, security, ethics and transparency. In addition, we will need to consider the skills needed for the workforce of the future and how to adapt our educational systems.

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The image above shows a forecast for 75 billion Internet-connected devices by 2025, an average of about 9 per person on the planet! The role of edge computing will be crucial.

As we move into the 2020s, data will increasingly be built on the edge, on the devices and sensors around us.

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Source for the image above: Omnisci

AI will be rapidly deployed on Edge over Internet of Things (IoT) resulting in AIiOT exclusively as 5G networks scale and enable substantially lower latency and massive increases in device connectivity relative to 4G networks .

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Sources for the above infographic images: Iman Ghosh

Furthermore, one could argue that the risk with respect to the consequences of an algorithm failing to perform properly is low in relation to social media and many ecommerce applications. For example, serious injuries and deaths do not result from showing someone the wrong product recommendation for a dress or jacket or watching a movie. There are no complicated legal liability issues to consider in case of misdiagnosis of health care or being involved in an accident in an autonomous car.

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The image above shows the need to engage in visual understanding of autonomous systems and to communicate by transmitting to other machines (machine-to-machine communication).

The laws of supply and demand also apply to the AI ​​and data science community. Demand for machine learning and deep learning skills accelerated towards the end of the last decade, helping to scale the algorithms being deployed in backend systems to enhance customer experience and analytical insights. There is now a growing demand for solutions from AI that will enable AI to scale to other sectors of the economy where issues of causality and transparency are prominent.

regina barzile, the first winner of the Squirrel AI Prize, elaborates further on this point and explains why the pandemic should be a wake-up call.

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Will Douglas Haven in an article published in MIT Technology Review titled “We’re not ready for AI, says the winner of a new $1 million AI prize” Regina Barzile explains the issueRight now AI is flourishing in places where the cost of failure is very low. It doesn’t matter if Google finds you the wrong translation or gives you the wrong link; You can just move on to the next one. But it’s not going to work for a doctor. If you give wrong treatment to patients or miss to diagnose, it will actually have dire consequences. Many algorithms can actually do a better job than humans. But we always trust our intuition, our mind, more than anything we don’t understand. We need to give doctors reasons to trust AI. The FDA is looking into this problem, but I think it is far from being solved in the US or anywhere else in the world.”

To enable AI to flourish and scale in key real-world areas such as healthcare and autonomous robotics (including vehicles), we will need the following:

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Source for the image above: Deloitte preparing AI strategy for government leader

As stated above, possible avenues for broadening AI will be discussed in the next article.

Some people called why we did not reach AGI till today. although there remains Many technical hurdles for AGI to hit There is also the philosophical dimension that perhaps we as a society and humanity as a whole are not prepared for AGI.

What will an AGI learn from us today? experience of set up chatbot Serves as a warning.

We have opportunities to deploy AI technology including the next generation that is currently being developed by leading AI researchers and we need strong, comprehensive AI (though not yet AGI) to enhance services and customer experience in areas such as financial services. ) and reduce dependence on for example Paper receipts that are harmful to human health and also to the environment.

In addition, we have scope for applying AI technology to personalized marketing campaigns and better understanding of customer preferences to improve profit margins for retailers and reduce environmental waste, which is unwanted and resulting in unsold inventory Rollnick et al in tackling climate change with machine learning and Alfonso Segura to tackle the fashion industry’s waste problem. In addition, the pandemic serves as an opportunity to consider the needs of our society and the world to help heal wounds from the current crisis and hopefully prevent or limit the damage caused by future pandemics. to do. In addition, we have an opportunity to consider the potential to develop the technology and infrastructure needed for sustainable economic growth and job creation, which will be needed in many parts of the world due to the COVID crisis.

Additional details on how to use AI and other next generation technologies to increase job creation and reduce pollution are provided in the infographic below and the article at this hyperlink.

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The World Economic Forum (WEF) published an article by Mohamed Kande and Murat Somnez titled “Don’t be afraid of AI. This will lead to long term job growth“And set out the points given below:

  • COVID-19 has accelerated the automation of many tasks, leading some to fear that artificial intelligence (AI) will take over their jobs.
  • But AI will create more jobs than it destroys.
  • Companies and governments must focus on upskilling and reskilling to embrace this change.
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Source for the above image: Don’t be afraid of AI. This will lead to long term job growth

In addition, the authors have determined that 50% of employees will need rescheduling by 2025!

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Source for the above image: Don’t be afraid of AI. This will lead to long term job growth

Sectors like financial services will be transformed by AI as shown by the below infographic:

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Without this, Health care The sector will also be transformers as shown in the infographic below:

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To truly realize the potential of AI in these areas this decade, we will need to deploy technologies such as differential privacy and federated learning with broad AI.

However, the element of people is just as important. We will need to invest in people and skills in the education system and workforce.

This means that our political and organizational leaders enable substantial investments to develop the necessary human talent and enable AI and other emerging technologies to address some of the critical issues we as humanity move forward with. . Enabling the transition to Industry 4.0 will require an enlightened approach by our political and policy leaders.

The COVID-19 crisis has resulted in both human suffering and economic loss. Our leaders will need to consider policies to enable GDP and employment growth, while also taking into account the need to tackle pollution and move away from business as the general model, which has probably changed our world in its present form. played a role in the situation.

I hope that 2021 will be a time of recovery and enlightenment for all, wherever you are in the world and that we will experience the leadership and vision to take us ahead of the COVID crisis and use it productively across the country. Will move towards implementing AI for cases. To compensate for the economic damage caused to the economy as well as to improve the standard of living and healthcare of many people around the world. The future is in our own hands and the decisions we make now and in the near future will determine our future for many years to come. There is an expectation that we will emerge next year into a new period of Enlightenment with data science and next generation technology being used to improve the quality of our lives and result in a better world for all of us .

A guide to real world AI and machine learning use cases

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