What is AI(Artificial Intelligence)? How Does Artificial Intelligence Work?
What Is AI?
Less than a decade after helping the Allied forces win World War II by breaking the Nazi encryption machine Enigma, mathematician Alan Turing changed history a second time with a simple question: “Can machines think?”
Turing’s 1950 paper “Computing Machinery and Intelligence” and its subsequent Turing Test established the fundamental goal and vision of AI.
At its core, AI is the branch of computer science that aims to answer Turing’s question in the affirmative. It is the endeavor to replicate or simulate human intelligence in machines. The expansive goal of AI has given rise to many questions and debates. So much so that no singular definition of the field is universally accepted.
Defining AI
The major limitation in defining AI as simply “building machines that are intelligent” is that it doesn’t actually explain what AI is and what makes a machine intelligent. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry.
However, various new tests have been proposed recently that have been largely well received, including a 2019 research paper entitled “On the Measure of Intelligence.” In the paper, veteran deep learning researcher and Google engineer François Chollet argues that intelligence is the “rate at which a learner turns its experience and priors into new skills at valuable tasks that involve uncertainty and adaptation.” In other words: The most intelligent systems are able to take just a small amount of experience and go on to guess what would be the outcome in many varied situations.
Meanwhile, in their book Artificial Intelligence: A Modern Approach, authors Stuart Russell and Peter Norvig approach the concept of AI by unifying their work around the theme of intelligent agents in machines. With this in mind, AI is “the study of agents that receive percepts from the environment and perform actions.”
The Future of AI
When one considers the computational costs and the technical data infrastructure running behind artificial intelligence, actually executing on AI is a complex and costly business. Fortunately, there have been massive advancements in computing technology, as indicated by Moore’s Law, which states that the number of transistors on a microchip doubles about every two years while the cost of computers is halved.
Although many experts believe that Moore’s Law will likely come to an end sometime in the 2020s, this has had a major impact on modern AI techniques — without it, deep learning would be out of the question, financially speaking. Recent research found that AI innovation has actually outperformed Moore’s Law, doubling every six months or so as opposed to two years.
By that logic, the advancements artificial intelligence has made across a variety of industries have been major over the last several years. And the potential for an even greater impact over the next several decades seems all but inevitable.
How Is AI Used? Artificial Intelligence Examples
“AI is a computer system able to perform tasks that ordinarily require human intelligence … Many of these artificial intelligence systems are powered by machine learning, some of them are powered by deep learning and some of them are powered by very boring things like rules.”
Securing Solutions in the Race to Digital Transformation & Impact
When it comes to relevancy and competition in a digital era, do you have the tools and technologies to accelerate business growth? A better question – do you have flexibility when it comes to purchasing and paying for them?
This year, U.S. businesses, nonprofits and government agencies will spend 1.6 trillion in capital goods or fixed business investments, financing a majority of those assets. Equipment and software investment will also grow 9.1 percent. And while many factors go into predicting trends like these, what is clear is that businesses are ready to invest in the solutions that will help them keep pace with a rapidly changing digital landscape.
The Impact of Digital Transformation
Over the course of the past year, we’ve seen digital transformation significantly affect the ways businesses expand their reach, capabilities and customer engagement. To help them successfully navigate these focus areas, Cisco Capital continues to strive to be a flexible and agile partner that not only provides service to our customers, but also one that helps them remain competitive in their markets.
IDC reports that by the end of 2019, the need for improved agility, better manageability and enhanced asset usage will force companies pursuing digital transformation to migrate more than 50% of the IT infrastructure in their datacenter and edge locations to a software-defined model.
Artificial intelligence, virtual reality, machine learning and block-chain based businesses are just a few examples of innovation that can completely transform a business’ trajectory and why companies are ready to explore better financing solutions to accelerate adoption. Because of this, consumption-based procurement is fast becoming preferred over traditional procurement, and customers are trending toward more “pay-per-use” offers. This in turn has seen the rise in the flexible payment solutions – an area of expertise for Cisco Capital.
The Freedom of Flexibility
Network World reported that by 2020, consumption-based procurement in data centers will eclipse traditional procurement through improved “as a service” models, thus accounting for as much as 40% of enterprises’ IT infrastructure spending. To keep pace with the innovation, customers want flexible payment solutions that optimize cash flow, offer discounts and offer enhanced credit capacity and profitability.
Cisco Capital has made it easier than ever for customers to acquire the Cisco technology they want and the flexibility, innovation and agility they need. From SMBs to the largest of enterprises, the common denominator for our customers and partners is the desire to drive business outcomes. To assist in this, especially in the wake of solid economic growth fueled by consumer optimism, business investment growth and higher business confidence, we have worked steadily to innovate our product offerings and services:
- From consumption models to pay-as-you-go options, we have the ideal payment solution that will help you achieve desired business outcomes.
- Our adaptable solutions present new ways to both consume and deliver digital transformation, while avoiding the trap of technology obsolescence.
- When the market fluctuates, we make it simple to quickly access the technology you need, leading to faster decision making and ultimately, better ROI and bottom lines.
- Do the channels I’m considering work together to convey my message?
Most effective ways to use cloud computing to achieve business goals
Cloud computing has been credited with increasing competitiveness through cost savings, greater flexibility, elasticity and optimal resource utilization. As a technology, cloud computing is much more than the sum of its parts. It opens doors to cloud-native technologies, supports more efficient ways of working and enables emerging capabilities in machine learning (ML) and artificial intelligence (AI).
Here’s how organizations are putting cloud computing to work to drive business value.
Infrastructure-as-a-Service (IaaS) and Platform-as-a-Service (PaaS)
Infrastructure-as-a-Service (IaaS) delivers fundamental compute, network and storage resources to consumers on-demand, over the Internet and on a pay-as-you-go basis. Using cloud infrastructure on a pay-per-use scheme enables companies to save on the costs of acquiring, managing and maintaining their own IT infrastructure. Plus, the cloud is easily accessible. Most major cloud service providers — including Amazon Web Services (AWS), Google Cloud, IBM Cloud and Microsoft Azure — offer IaaS with their cloud computing services.
Platform-as-a-Service (PaaS) provides customers a complete cloud platform — hardware, software and infrastructure — for developing, running and managing applications without the cost, complexity and inflexibility of building and maintaining that platform on-premises. Organizations may turn to PaaS for the same reasons they look to IaaS; they want to increase the speed of development on a ready-to-use platform and deploy applications with a predictable and cost-effective pricing model.
2. Software-as-a-Service (SaaS)
While Software-as-a-Service (SaaS) is similar to the IaaS and PaaS uses described above, it actually deserves its own mention for the undeniable change this model has brought about in the way companies use software. SaaS offers software access online via a subscription, rather than IT teams having to buy and install it on individual systems.
SaaS providers, like Salesforce, enable software access anywhere, anytime, as long as there’s an Internet connection. These tools have opened access to more advanced tools and capabilities, like automation, optimized workflows and collaboration in real-time in various locations.
Hybrid cloud and multicloud
Hybrid cloud is a computing environment that connects a company’s on-premises private cloud services and third-party public cloud services into a single, flexible infrastructure for running critical applications and workloads. This unique mix of public and private cloud resources makes it easier to select the optimal cloud for each application or workload and then move the workloads freely between the two clouds as circumstances change. With a hybrid cloud infrastructure, technical and business objectives are fulfilled more effectively and cost-efficiently than could be achieved with a public or private cloud alone.
Big data analytics
By leveraging the computing power of cloud computing, companies can gain powerful insights and optimize business processes through big data analytics.
There is a massive amount of data collected each day from corporate endpoints, cloud applications and the users who interact with them. Cloud computing allows organizations to tap into vast quantities of both structured and unstructured data available to harness the benefit of extracting business value.
Retailers and suppliers are now extracting information derived from consumers’ buying patterns to target their advertising and marketing campaigns to a particular segment of the population. Social networking platforms are providing the basis for analytics on behavioral patterns that organizations are using to derive meaningful information. Businesses like these and more are also able to harness deeper insights through machine learning (ML) and artificial intelligence (AI), two capabilities made possible with cloud computing.
Cloud storage
By leveraging the computing power of cloud computing, companies can gain powerful insights and optimize business processes through big data analytics.
Cloud data storage enables files to be automatically saved to the cloud, and then they can be accessed, stored and retrieved from any device with an Internet connection. Rather than maintaining their own data centers for storage, organizations can only pay for the amount of cloud storage they are actually consuming and do so without the worries of overseeing the daily maintenance of the storage infrastructure. The result is higher availability, speed, scalability and security for the data storage environment.
In situations where regulations and concerns about sensitive data are at play, organizations can store data either on- or off-premises, in a private or hybrid cloud model, for added security.
Retailers and suppliers are now extracting information derived from consumers’ buying patterns to target their advertising and marketing campaigns to a particular segment of the population. Social networking platforms are providing the basis for analytics on behavioral patterns that organizations are using to derive meaningful information. Businesses like these and more are also able to harness deeper insights through machine learning (ML) and artificial intelligence (AI), two capabilities made possible with cloud computing.
