Want to know the state of artificial intelligence (AI) in some of the top industries in 2021?
We’ve curated and vetted 40 statistics about the emergence of AI, the ways it’s being used today, and expert projections for the future.
The healthcare industry has seen a surge in automated procedures due to the COVID-19 pandemic. Here are some stats that may surprise you.
Throughout the world, manufacturers are using artificial intelligence for automated solutions. Here are some facts about the way manufacturing is adopting AI technology.
The banking sector applies AI technology to recommendation systems for better customer experience and fraud detection and investigation. Here are some interesting statistics about AI in banking.
Artificial intelligence is rapidly expanding its presence in the telecommunications industry, led by AI-powered smartphones. Here are some stats that show how AI is taking hold in telecommunications.
Next, here are some statistics that show how businesses are incorporating AI technology and what the future may be for AI-powered business solutions.
These statistics show the contributions AI and machine learning are making in every field, from medical to manufacturing. AI is being actively integrated into every domain and is the key to the growth of every business.
It is no secret that computer vision is rapidly changing our lives.
Images and videos are an integral part of our everyday lives in countless ways – medical procedures, e-commerce, security, technological interaction and many other fields related to daily activities. Did you know that on Facebook alone, around 350 million images are uploaded every day? And that over 500 hours of video are uploaded to YouTube every single minute?
Hardware and software advances now allow computers to review, analyze and provide meaningful outcomes from images and videos. Nowadays, computers are nearing the replication of the human vision and even surpass it in some respects.
The economic impact of computer vision is growing rapidly. The global computer vision market was valued at 10.6 Billion US$ in 2019 and it is expected to grow at 7.6% compound annual growth rate between 2020-2027.
But what is computer vision?
Different types of algorithms are used for image analysis in computer vision:
Computer vision is used to solve many problems and affects almost every aspect of our daily routines. Here are some examples:
As the world entered a new decade, we can expect to see exciting new innovations and practices that will be based on computer vision.
Milli Peled, VP Marketing
As data scientists and computer vision specialists, the most prominent tools we use are Matlab and Python. In the following blog post, I’d like to share with you some thoughts and best practices regarding the combination of these two important tools.
In recent years, Matlab lost a lot of its prestige and Python became much more popular. Nevertheless, I still find many advantages working with Matlab. Its IDE (Integrated Development Environment) is extremely convenient and allows me to debug and dig into my code very efficiently, more than any Python IDE allows. Since debugging and digging is the main action an algorithm developer is doing, this feature is very important to me.
I also found Matlab more convenient in visualization especially in 3D and the built-in functions are very stable with great documentation (after all, you do pay for something…).
From my experience, the main advantage in Python is the huge diversity of implementations of state-of-the-art algorithms. With millions of developers in this open-source code, I can be sure that if I need some implementation, someone has already done it. This is especially true in deep learning.
So, just like everything in life, this is not simply “black and white”. Both Matlab and Python have pros and cons. That’s why I was very happy to find out that Matlab can run very easily any Python command and package. How easily? All I had to do is write Py. followed by any Python command I chose. No need for imports or reinstallation of packages and so actually in some ways it is easier to run Python from Matlab than any other IDE!
So, if you think that both Matlab and Python are great tools, here is a great option to use them both, simultaneously.
For any questions on Computer vision or Artificial Intelligence development projects, please don’t hesitate to contact us via firstname.lastname@example.org
Asaf Shimshovitz, PhD
Artificial intelligence, also called AI, is revolutionizing nearly every sector of society. As time goes on, more companies and governments are implementing it into their processes, and it is helping us come up with solutions to some of our biggest problems.
The reason we see this takeover by AI is that we live in a data-driven world. Everything we do today relies on data, and the more data there is, the more patterns there are for AI systems to detect. This processing power is exactly what makes AI such a revolutionizing technology, as humans could never match the processing power and speed of AI.
So, what is AI?
Here are the answers to 15 common questions regarding this technology:
You might hear the term thrown around by engineers and scientists and it can seem like a complex and confusing subject. However, anyone can gain a solid understanding of what artificial intelligence is.
AI is the simulation of human intelligence in machines. These machines are often programmed to think like humans and mimic our actions, but they are far more advanced than we could ever be. With their ability to process massive amounts of data, they can quickly detect patterns and help make highly accurate predictions.
You have probably seen sci-fi movies depicting these conscious machines. But, in reality, they are the basis for many of our most advanced technologies and daily activities, such as self-driving cars, speech recognition systems, robotics and automation, recommendation systems, and medical imaging.
Now that you know what artificial intelligence is, let’s look at how it works.
The term AI, in general, refers to algorithms designed to perform tasks by machines. Machine learning takes place when an AI system can learn to perform a task, given a known model representing the relevant reality. Machine learning has been used in practice for several decades, and usually requires a fair amount of data for training. In the last decade, more profound schemes evolved for the purpose of teaching machines to perform desired tasks based on even larger amounts of data – also knowns as Deep Learning. With deep learning, a neural network reprograms itself as it processes more data, which allows it to perform its designed task more accurately. Deep learning is the most powerful of the subsets where a machine learning application teaches itself to perform a specific task with increasing accuracy, but it requires no human intervention.
Machine learning uses simple neural networks. A neural network is a sort of replication of the human brain, consisting of a large grid of simple units, called neurons, used to process data. The network can make predictions with various degrees of confidence.
As for deep learning models, those rely on deep neural networks (abbreviated DNN) with multiple hidden layers, designed to eliminate the need of a human programmer to specify the model of the reality being studied. This entire process results in a highly refined and accurate model, all without human intervention.
The evolution of artificial intelligence has been taking place for decades. While it is not a product invented by any one individual, there have been many big players in the field throughout history. British scientist Alan Turing is widely considered the father of artificial intelligence; in a 1950 article, he proposed the model for machine learning by suggesting that it would be more effective to create a simple computer and teach it than it would be to create a complex computer. Turing likened this model to raising a child.
Unfortunately, computers of the 1950’s did not have the computational power required for such an undertaking, though in 1956, computer scientists Allen Newell, Cliff Shaw, and Herbert Simon developed the first AI program, named Logic Theorist. This proof of concept for artificial intelligence helped many people realize the potential for, and unavoidable move towards, AI technologies.
We can say that the invention of AI took place with that first AI program, but it continued to rapidly develop between 1957 and 1974. The reason behind this was the advancement of computers, which became more powerful and cheaper every year. With AI’s success, government agencies like the Defense Advanced Research Projects Agency (DARPA) began to fund its development in institutions.
In the 1970s, funding and subsequently the technology’s development slowed as computing power failed to keep pace. Interest poured back into AI once again in the 1980s, influenced by the popularization of learning techniques and increasing acceptance of the computer not just as a tool for science and industry but as a component of daily life.
The 1990s and 2000s saw major AI accomplishments, such as when IBM’s Deep Blue chess-playing computer program beat the reigning world champion. Fast-forward to the present and AI is integrated into many aspects of our daily lives. As we continue to produce more and more data, the capabilities of artificial intelligence increase.
Artificial intelligence is loaded with positive potential for humankind, but – like any modern technology – malicious actors can misuse it. The ability of AI systems to be hacked is a danger for organizations and institutions that integrate AI into their operations. Financial infrastructure, autonomous vehicles, and even weapons systems have the potential to be hacked as those with harmful intent look to harvest the data within – or worse.
Because of these dangers, there is a substantial effort to confront the different technological vulnerabilities of artificial intelligence. In 2019, DARPA launched the Guaranteeing AI Robustness Against Deception (GARD) program to identify vulnerabilities in AI deployments and build defensive mechanisms to protect these vulnerabilities.
Artificial intelligence is a challenging area because defense systems must be constantly updated. The technology is always evolving, meaning there are new vulnerabilities every day that organizations need to address.
Artificial intelligence can seem confusing for those who are just diving into it. There’s a lot of technical language and you can spend hours researching specific subfields and categories of AI.
Here is a look at some of the most common AI terms you should know:
If you have ever turned on a science fiction B-movie, you are probably familiar with the idea that robots are going to take over and wage war on the human race. That might be fun science fiction, but the science fact is that artificial intelligence is a tool we use, not a threat of robotic invasion.
As mentioned previously, AI systems can be hacked, which is especially dangerous if it involves governments or massive amounts of personal data. But another big issue, and perhaps the most significant danger posed by AI, is biased systems.
It only makes sense that AI can be biased. After all, think about how those systems are created: using data fed by humans. As more companies begin implementing complex AI systems, and as governments begin to use the technology, the potential for bias, and the systemic abuse that can come with bias, is powerful.
Some of these systems demonstrate bias because experts train them on data that reflects inequities, which in turn causes the AI to learn those inequalities and perpetuate them. Another issue is flawed data sampling, which means certain groups are either over- or underrepresented in the training data.
One area where AI poses perhaps the most danger is facial recognition technology. There have already been instances of high error rates for women and people in underprivileged or minority groups in facial recognition technologies, along with the use of bias systems in law enforcement. Facial recognition technology is also often used for tracking purposes, which can infringe on privacy rights.
Artificial intelligence is one of the greatest technological advancements in human history, and it is going to have a massive impact on the future. We already see incredible changes in sectors like healthcare, where new vaccines, cures, and therapeutic remedies are developed at a fast rate thanks to AI.
One of the most immediate impacts will involve the future of work automation, will replace many jobs in various sectors, especially those that involve manual, repetitive tasks. Besides taking these tasks over, AI will increasingly augment human decision-making in organizations.
AI changes substantial portion of the workforce. Many of the current positions become redundant and new opportunities arise. For example, data annotators, AI platform management, and more.
Governments started to implement initiatives to facilitate the evolution of the new workforce. At the same time, AI has the potential to create many new jobs. Individuals in the workforce will begin to undertake retraining and upskilling initiatives, which will provide them with the skills needed to become part of the future economy. Business leaders will implement these initiatives within their organizations to better prepare their workforces.
The question of whether AI will surpass human intelligence, or if a super intelligent system is possible, was brought up back in 1951 by Alan Turing. According to Turing, we should be worried about how AI and its applications could one day surpass and “humble” the human species.
However, there are many different views on this subject by AI specialists. Some believe this is not possible, and even if so, we could turn the machines off at any time. Others believe that AI will undoubtedly surpass humans, and our goal should be to implement our own ethical and moral systems into the machines.
Those who believe this is a possibility say that a computer with general intelligence can analyze all existing books and documents at an incredible rate. It would then go on to make discoveries humans have never even considered.
This type of machine would not have the same human limitations as we have; no slow thinking, no emotions, no irrationality, and no need for sleep. The consensus among experts is that this is not an urgent or immediate risk but that it is a remote possibility that should be prepared for. Fortunately, many of those experts are doing just that, working to create limitations or incorporate ethics into the way AI-powered machines think.
Artificial intelligence is applied in many different ways depending on the industry. AI can supplement, or completely take over nearly every task.
One of the most common applications seen by individuals in their everyday lives involves AI-powered chatbots. These chatbots work to deliver answers to questions through conversations on mobile devices and voice-activated interfaces. They are also becoming commonplace in homes everywhere, putting us in a position to interact with AI each day.
While AI is present in our everyday lives, it is also applied in more dramatic ways that we don’t often see. For example, AI played a crucial role in analyzing the COVID-19 pandemic, assisting in everything from contact tracing and the progression of the virus across the world to vaccine development and distribution. Besides the COVID-19 pandemic, AI was already responsible for major medical breakthroughs. Smarter medicine, powered by AI, has the potential to drastically change the way we approach human health and wellness.
Many people worry that AI will one day replace humans. While it is true that AI will replace humans in many tasks throughout many industries, we are far from a point at which it can replace us in every industry.
A lot of this has to do with the creative mind, or in other words, our ability to apply creativity in everything we do. Whether it be creative business solutions or the arts, AI cannot yet replicate us in that way.
People will benefit in the AI-driven world of the future by learning new skills that rely more on creativity and less repetition and other actions easily replicated by machines. By refocusing on creativity, there is a far greater chance that you will thrive in the future AI-driven world.
All of these incredible AI advancements are the work of the world’s most powerful and effective AI companies. You might be surprised – or not – to find out that they are often the same big companies whose products we use daily.
Here are some of the top AI companies:
AI technologies have many unique benefits, but the most notable is the great degree of precision there is, due to the fact that AI bases its decisions on large amounts of optimization data and improved algorithms.
Another benefit is the development of AI-based robots that operate in dangerous environments. Technology can be used for search-and-rescue missions, to defuse a bomb, explore the oceans, or operate on Mars, all by minimizing or even eliminating the risk to human scientists, researchers, and explorers.
By assisting humans in repetitive tasks, AI gives us time to pursue activities that are more rewarding. This can have a significant impact on society. For example, AI can change the shopping experience and automatically renew the house inventory, without any human interaction.
It can also improve safety, for example, by shifting to autonomous cars that interact with each-other, or automated warehouse control system.
AI innovations can open up opportunities in every field, freeing up time once spent on mundane responsibilities to be reallocated to creative expression and human connection. This could even lead to a more vibrant artistic community as workers have more time to do the things they love.
Some of the other common benefits of AI include its ability to operate 24/7, to provide deep insights into nearly every sector, and to make decisions faster and more accurately.
As mentioned previously, AI will impact nearly every industry in one way or another.
Here is a look at how it can be implemented in different industries:
As we have seen, there are a lot of benefits to artificial intelligence, and you have probably noticed there are some downsides, too. What is critical to remember is that the way we implement artificial intelligence is what determines if AI is beneficial or harmful. The responsible implementation of AI has already unlocked so many doors and will continue to do so.
Let’s take a look at the pros and cons of this world-changing technology:
Artificial intelligence is the main technology that is driving the fourth industrial revolution, the very one we are living through today. It will continue to dramatically impact every sector of society, from business to healthcare to education to space exploration. AI carries massive risks, though, and the way it is implemented will largely depend on how governments and private organizations approach the technology and will, in turn, determine the way we interact with it and each other in the coming years. It will become one of the biggest issues of the future as we create more data, leading to concerns surrounding data ownership, security, and privacy.
While artificial intelligence seems like a highly complex topic, these 15 questions and answers provide you with everything needed to prepare for the future of AI.