There has been no higher time to be in the world of synthetic Genius than now. AI has carried out an inflection factor and is poised to radically change each industry.
Much has already been written about precise functions of AI. In this article, I take a step lower back to reflect on consideration on how synthetic talent is poised to essentially restructure broader swaths of our financial system and society over the subsequent decade with 5 daring predictions that are knowledgeable with the aid of my understanding and immersion in the field.
1. AI and ML will transform the scientific method.
Important science—think large-scale clinical trials or building particle colliders—is expensive and time-consuming. In recent decades there has been considerable, well-deserved concern about scientific progress slowing down. Scientists may no longer be experiencing the golden age of discovery.
With AI and machine learning (ML), we can expect to see orders of magnitude of improvement in what can be accomplished. There’s a certain set of ideas that humans can computationally explore.
There’s a broader set of ideas that humans with computers can address. And there’s a much bigger set of ideas that humans with computers, plus AI, can successfully tackle.
AI enables an unprecedented ability to analyze enormous data sets and computationally discover complex relationships and patterns. AI, augmenting human intelligence, is primed to transform the scientific research process, unleashing a new golden age of scientific discovery in the coming years.
2. AI will become a pillar of foreign policy.
We are likely to see serious government investment in AI. U.S. Secretary of Defense Lloyd J. Austin III has publicly embraced the importance of partnering with innovative AI technology companies to maintain and strengthen global U.S. competitiveness.
The National Security Commission on Artificial Intelligence has created detailed recommendations, concluding that the U.S. government needs to greatly accelerate AI innovation. There’s little doubt that AI will be imperative to the continuing economic resilience and geopolitical leadership of the United States.
3. AI will enable next-gen consumer experiences.
Next-generation consumer experiences like the metaverse and cryptocurrencies have garnered much buzz. These experiences and others like them will be critically enabled by AI.
The metaverse is inherently an AI problem because humans lack the sort of perception needed to overlay digital objects on physical contexts or to understand the range of human actions and their corresponding effects in a metaverse setting.
More and more of our life takes place at the intersection of the world of bits and the world of atoms.
AI algorithms have the potential to learn much more quickly in a digital world (e.g., virtual driving to train autonomous vehicles).
These are natural catalysts for AI to bridge the feedback loops between the digital and physical realms. For instance, blockchain, cryptocurrency and distributed finance, at their core, are all about integrating frictionless capitalism into the economy.
But to make this vision real, distributed applications and smart contracts will require a deeper understanding of how capital activities interact with the real world, which is an AI and ML problem.
4. Addressing the climate crisis will require AI.
As a society we have much to do in mitigating the socioeconomic threats posed by climate change. Carbon pricing policies, still in their infancy, are of questionable effectiveness.
Many promising emerging ideas require AI to be feasible. One potential new approach involves prediction markets powered by AI that can tie policy to impact, taking a holistic view of environmental information and interdependence.
This would likely be powered by digital “twin Earth” simulations that would require staggering amounts of real-time data and computation to detect nuanced trends imperceptible to human senses.
Other new technologies such as carbon dioxide sequestration cannot succeed without AI-powered risk modeling, downstream effect prediction and the ability to anticipate unintended consequences.
5. AI will enable truly personalized medicine.
Personalized medicine has been an aspiration since the decoding of the human genome. But tragically it remains an aspiration.
One compelling emerging application of AI involves synthesizing individualized therapies for patients. Moreover, AI has the potential to one day synthesize and predict personalized treatment modalities in near real-time—no clinical trials required.
Simply put, AI is uniquely suited to construct and analyze “digital twin” rubrics of individual biology and is able to do so in the context of the communities an individual lives in.
The human body is mind-boggling in its complexity, and it is shocking how little we know about how drugs work (paywall). Without AI, it is impossible to make sense of the massive datasets from an individual’s physiology, let alone the effects on individual health outcomes from environment, lifestyle and diet.
AI solutions have the potential not only to improve the state of the art in healthcare, but also to play a major role in reducing persistent health inequities.
In Short Simply learn…
What Is Artificial Intelligence (AI)?
Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
The ideal characteristic of artificial intelligence is its ability to rationalize and take actions that have the best chance of achieving a specific goal. A subset of artificial intelligence is machine learning (ML), which refers to the concept that computer programs can automatically learn from and adapt to new data without being assisted by humans. Deep learning techniques enable this automatic learning through the absorption of huge amounts of unstructured data such as text, images, or video.
- Artificial intelligence (AI) refers to the simulation or approximation of human intelligence in machines.
- The goals of artificial intelligence include computer-enhanced learning, reasoning, and perception.
- AI is being used today across different industries from finance to healthcare.
- Weak AI tends to be simple and single-task oriented, while strong AI carries on tasks that are more complex and human-like.
- Some critics fear that the extensive use of advanced AI can have a negative effect on society.
Understanding Artificial Intelligence (AI)
When most people hear the term artificial intelligence, the first thing they usually think of is robots. That’s because big-budget films and novels weave stories about human-like machines that wreak havoc on Earth. But nothing could be further from the truth.
Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the most simple to those that are even more complex. The goals of artificial intelligence include mimicking human cognitive activity. Researchers and developers in the field are making surprisingly rapid strides in mimicking activities such as learning, reasoning, and perception, to the extent that these can be concretely defined. Some believe that innovators may soon be able to develop systems that exceed the capacity of humans to learn or reason out any subject. But others remain skeptical because all cognitive activity is laced with value judgments that are subject to human experience.
As technology advances, previous benchmarks that defined artificial intelligence become outdated. For example, machines that calculate basic functions or recognize text through optical character recognition are no longer considered to embody artificial intelligence, since this function is now taken for granted as an inherent computer function.
AI is continuously evolving to benefit many different industries. Machines are wired using a cross-disciplinary approach based on mathematics, computer science, linguistics, psychology, and more.
Applications of Artificial Intelligence
The applications for artificial intelligence are endless. The technology can be applied to many different sectors and industries. AI is being tested and used in the healthcare industry for dosing drugs and doling out different treatments tailored to specific patients, and for aiding in surgical procedures in the operating room.
Other examples of machines with artificial intelligence include computers that play chess and self-driving cars. Each of these machines must weigh the consequences of any action they take, as each action will impact the end result. In chess, the end result is winning the game. For self-driving cars, the computer system must account for all external data and compute it to act in a way that prevents a collision.
Artificial intelligence also has applications in the financial industry, where it is used to detect and flag activity in banking and finance such as unusual debit card usage and large account deposits—all of which help a bank’s fraud department. Applications for AI are also being used to help streamline and make trading easier. This is done by making supply, demand, and pricing of securities easier to estimate.
Types of Artificial Intelligence
Artificial intelligence can be divided into two different categories: weak and strong. Weak artificial intelligence embodies a system designed to carry out one particular job. Weak AI systems include video games such as the chess example from above and personal assistants such as Amazon’s Alexa and Apple’s Siri. You ask the assistant a question, and it answers it for you.
Strong artificial intelligence systems are systems that carry on the tasks considered to be human-like. These tend to be more complex and complicated systems. They are programmed to handle situations in which they may be required to problem solve without having a person intervene. These kinds of systems can be found in applications like self-driving cars or in hospital operating rooms.
Since its beginning, artificial intelligence has come under scrutiny from scientists and the public alike. One common theme is the idea that machines will become so highly developed that humans will not be able to keep up and they will take off on their own, redesigning themselves at an exponential rate.
Another is that machines can hack into people’s privacy and even be weaponized. Other arguments debate the ethics of artificial intelligence and whether intelligent systems such as robots should be treated with the same rights as humans.
Self-driving cars have been fairly controversial as their machines tend to be designed for the lowest possible risk and the least casualties. If presented with a scenario of colliding with one person or another at the same time, these cars would calculate the option that would cause the least amount of damage.
Another contentious issue many people have with artificial intelligence is how it may affect human employment. With many industries looking to automate certain jobs through the use of intelligent machinery, there is a concern that people would be pushed out of the workforce. Self-driving cars may remove the need for taxis and car-share programs, while manufacturers may easily replace human labor with machines, making people’s skills obsolete.
What Are the 4 Types of AI?
Artificial intelligence can be categorized into one of four types.
- Reactive AI uses algorithms to optimize outputs based on a set of inputs. Chess-playing AIs, for example, are reactive systems that optimize the best strategy to win the game. Reactive AI tends to be fairly static, unable to learn or adapt to novel situations. Thus, it will produce the same output given identical inputs.
- Limited memory AI can adapt to past experience or update itself based on new observations or data. Often, the amount of updating is limited (hence the name), and the length of memory is relatively short. Autonomous vehicles, for example, can “read the road” and adapt to novel situations, even “learning” from past experience.
- Theory-of-mind AI are fully-adaptive and have an extensive ability to learn and retain past experiences. These types of AI include advanced chat-bots that could pass the Turing Test, fooling a person into believing the AI was a human being. While advanced and impressive, these AI are not self-aware.
- Self-aware AI, as the name suggests, become sentient and aware of their own existence. Still in the realm of science fiction, some experts believe that an AI will never become conscious or “alive”.
How Is AI Used Today?
AI is used extensively across a range of applications today, with varying levels of sophistication. Recommendation algorithms that suggest what you might like next are popular AI implementations, as are chatbots that appear on websites or in the form of smart speakers (e.g., Alexa or Siri).
AI is used to make predictions in terms of weather and financial forecasting, to streamline production processes, and to cut down on various forms of redundant cognitive labor (e.g., tax accounting or editing). AI is also used to play games, operate autonomous vehicles, process language, and much, much, more.
How Is AI Used in Healthcare?
In healthcare settings, AI is used to assist in diagnostics. AI is very good at identifying small anomalies in scans and can better triangulate diagnoses from a patient’s symptoms and vitals. AI is also used to classify patients, maintain and track medical records, and deal with health insurance claims. Future innovations are thought to include AI-assisted robotic surgery, virtual nurses or doctors, and collaborative clinical judgment.
The applications of artificial intelligence are likely to impact critical facets of our economy and society over the coming decade. We are in the early innings of what many credible experts view as the most promising era in technology innovation and value creation for the foreseeable future.