Glossary Definition: Artificial Intelligence (AI)

What is artificial intelligence?

Artificial intelligence (AI) is computer-simulated intelligence. AI aims to replicate human intelligence and in some cases, surpass it. Artificial intelligence is powered by machines and includes natural language processing, speech recognition, machine learning, and vision.

Generally speaking, AI falls into three categories, including

  1. Artificial Narrow Intelligence (ANI). As the name suggests, this form of AI possesses narrow, or limited, capabilities. Examples include Google translate and Siri, both of which are natural language processing tools. Although these tools work fast, they are restricted in what they’re able to accomplish. 
  2. Artificial General Intelligence (AGI). This form of AI attempts to replicate most human capabilities. In essence, its function is to “act” as a human would. An example of this is the customer service chatbots you encounter when you land on a website. They’re capable of answering your questions, helping you navigate, and can even anticipate your needs at certain times. 
  3. Artificial Superintelligence (ASI). As opposed to imitating human intelligence, ASI takes things a step further — beyond the realm of human intelligence. Engineers hope to build ASI machines to be more capable than humans. Of course, AI still has a ways to go before ASI becomes a reality. Currently, AI struggles to do something humans can accomplish with ease: switching between tasks. Futurists currently predict the singularity — the moment at which AI surpasses human intelligence — to occur in about 2045, or possibly even sooner.

What are other names for artificial intelligence?

AI is often referred to by other names. These include:

  • Knowledge engineering
  • Machine learning
  • Deep learning
  • Neural network
  • Intelligent retrieval
  • Robotics
  • Neural Network?
  • Expert System

What are the benefits of artificial intelligence?

AI can operate 24/7 without pauses or delays, which helps users increase the speed it takes to complete a task. For example, if you’re traveling abroad and don’t speak the native language, you can simply use Google translate or a similar app on your smartphone for translation assistance. Within seconds, the AI will convert your language to the foreign language or decode the foreign language either via speech or text so those participating in conversation can understand one another.

In a business context, workers can leverage AI to automate menial tasks such as data retrieval and sorting. In addition, businesses can harness AI to improve the speed and scale of customer communications with chatbots. Through predictive analytics, AI can facilitate faster decision-making by empowering users with the data-driven insights necessary to make quick, informed decisions.

What is artificial intelligence in pharma?

Artificial intelligence in pharma helps engineers, scientists, and life science organizations automate menial tasks, monitor data, and accelerate drug discovery and development. Instead of manual, paper-based systems which are antiquated and time-consuming, pharma organizations can leverage AI-powered technologies to expedite time to market while maintaining compliance and safety.

What are examples of AI in pharma?

In pharma, there are an abundance of technologies that leverage the power of AI to increase speed and efficiencies while reducing cost.

Two well-known examples include:

Manufacturing execution systems: This system, also known as an MES solution, tracks and monitors the manufacturing process from start to finish. Data processing can be completely automated, thanks to AI and machine learning.

Laboratory execution systems: Commonly referred to as an LES system, laboratory execution systems digitally capture data and support lab operations by optimizing workflows. Laboratory management systems optimize quality control by providing scientists with the ability to manage samples and lab resources at scale, flag and resolve exceptions in real time, and execute test methods on devices.

It’s important to note that MES and LES are not equivalent to AI. However, AI can support both of these systems with tools such as machine learning, consumptive analytics, preventive maintenance, and simulations.

Why is AI important for pharma?

Artificial intelligence enables smart manufacturing in the pharmaceutical space. This application of AI, known as AI manufacturing, allows pharma companies to automate time-consuming tasks, such as data capture and transcription, while maintaining regulatory compliance. As a result, therapies can be developed in less time at scale. This is good news for the 66% of adults in the United States (and countless others worldwide) who rely on pharma medications to manage temporary or chronic conditions.