WHAT IS Artificial Intelligence?
From SIRI to self-driving cars, Artificial Intelligence (AI) is progressing rapidly. While science fiction often portrays AI as robots with human-like characteristics, AI can encompass anything from Google’s search algorithms to IBM’s Watson to autonomous weapons.
Artificial Intelligence today is properly known as narrow AI (or weak AI), in that it is designed to perform a narrow task (e.g. only facial recognition or only internet searches or only driving a car). However, the long-term goal of many researchers is to create general AI (AGI or strong AI). While narrow AI may outperform humans at whatever its specific task is, like playing chess or solving equations, AGI would outperform humans at nearly every cognitive task.
AI has four potential goals or definitions of AI, which differentiate computer systems on the basis of rationality and thinking vs. acting:
Human approach:
- Systems that think like humans
- Systems that act like humans
Ideal approach:
- Systems that think rationally
- Systems that act rationally
Artificial Intelligence applications-
There are numerous, real-world applications of AI systems today. Below are some of the most common examples:
- Speech Recognition: It is also known as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, and it is a capability which uses natural language processing (NLP) to process human speech into a written format. Many mobile devices incorporate speech recognition into their systems to conduct voice search—e.g. Siri—or provide more accessibility around texting.
- Customer Service: Online chatbots are replacing human agents along the customer journey. They answer frequently asked questions (FAQs) around topics, like shipping, or provide personalized advice, cross-selling products or suggesting sizes for users, changing the way we think about customer engagement across websites and social media platforms. Examples include messaging bots on e-commerce sites with virtual agents, messaging apps, such as Slack and Facebook Messenger, and tasks usually done by virtual assistants and voice assistants.
- Computer Vision: This AI technology enables computers and systems to derive meaningful information from digital images, videos and other visual inputs, and based on those inputs, it can take action. This ability to provide recommendations distinguishes it from image recognition tasks. Powered by convolutional neural networks, computer vision has applications in photo tagging in social media, radiology imaging in healthcare, and self-driving cars within the automotive industry.
- Recommendation Engines: Using past consumption behavior data, AI algorithms can help to discover data trends that can be used to develop more effective cross-selling strategies. This is used to make relevant add-on recommendations to customers during the checkout process for online retailers.
- Automated stock trading: Designed to optimize stock portfolios, AI-driven high-frequency trading platforms make thousands or even millions of trades per day without human intervention.
5 trends to watch In Artificial Intelligence Solutions-
1. Intelligent And Hyper-Automated Business Processes
With its ability to follow basic tasks and routines based on smart programming and algorithms, artificial intelligence is becoming embedded in the way organizations automate their business processes.
AI ops and ML ops are common use cases for AI and automation, but the breadth and depth of what AI can automate in the enterprise is quickly growing.
Although AI automation is still mostly limited to interval and task-oriented automation that requires little imagination or guesswork on the part of the tool, some experts believe we are moving closer to more applications for intelligent automation.
2. Emphasis On Responsible AI Development
Because of the depth of big data and AI’s reliance on it, there’s always the possibility that unethical or ill-prepared data will make it into an AI training data set or model.
As more companies recognize the importance of creating AI that conducts its operations in a compliant and ethical manner, a number of AI developers and service providers are starting to offer responsible AI solutions to their customers.
“AI creates incredible new opportunities to improve the lives of people around the world,” Maloney- Data Scientist said.
Maloney said the market is seeing an “increased adoption of the core pillars of responsible AI,” which he shared with Datamation:
- Explainable AI and interpretable Machine Learning (ML): The ability explains to a model after it has been developed and provide transparent model architectures, which allows human users to both understand the data and trust the results.
- Ethical AI: Provides sociological fairness in machine learning predictions (i.e., whether one category of person is being weighted unequally and eliminating historical human bias).
- Secure AI: Debugging and deploying ML models to keep security and privacy at the forefront.
- Human-centered AI: Where AI learns from human input and collaboration. Systems are continuously improving because of human input and bridging the gap between humans and machines.
- Compliance: Ensuring AI systems meet the relevant regulatory requirements or regulations.
Companies are exploring several ways to make their AI more responsible, and most are starting with cleaning and assessing both data sets and existing AI models.
3. AI As A Tool For Global Good
Up to this point, AI has most frequently been used to optimize business processes and automate some home routines for consumers.
However, some experts are beginning to realize the potential that AI-powered models can have for solving global issues.
Some of the most exciting applications of altruistic AI are being implemented in early education right now. On top of pre-existing barriers to preschool education, including cost and access, recent research findings suggest children born during the COVID-19 pandemic display lower IQ scores than those born before January 2020, which means toddlers are less prepared for school than ever before.
4. AI And IoT Working Together
Internet of Things devices have become incredibly widespread among both enterprise and personal users, but what many tech companies still struggle with is how to gather actionable insights from the constant inflow of data from these devices.
IoT, or the idea of combining artificial intelligence with IoT products, is one field that is starting to address these pools of unused data, giving AI the power to translate that data quickly and intelligently. In industrial IoT settings — continues to increase, so does the volume of data collected from these devices.
5. The Urgency Of Decision Intelligence
Decision intelligence (DI) is one of the newest artificial intelligence concepts that takes many current business optimizations a step further, by using AI models to analyze wide-ranging sets of commercial data. These analyses are used to predict future outcomes for everything from products to customers and supply chains.
“Decision intelligence is a new category of software that facilitates the commercial application of artificial intelligence, providing predictive insight and recommended actions to users,” Gilroy said. “It is outcome-focused, meaning a solution must deliver against a business need before it can be classed as DI.
Imaging Future of Artificial Intelligence
A digital transformation wave has swept over all walks of life around the world. Global enterprises have realized embracing emerging information technology is the key to improving business optimization, industrial upgrading, and value creation. In this process, the potential of AI, as a key enabling technology, is being uncovered in terms of computing power, algorithms, and data. Now, what are the successful landing cases? What new possibilities could it bring in the future?
It is undeniable that AI will improve and get more advanced with time. What will happen in the future? There isn’t a wink without a doubt that all aspects of life such as travel, medical care, and manufacturing will be further upgraded thanks to AI. Perhaps dealing with robots will become our daily routine, and perhaps brain-computer interfaces will come to fruition, helping people with disabilities to restore their lives and communication skills. Maybe AI will make people more creative, free humans from complicated or mindless tasks, and even replace humans in dangerous jobs. The technological development of AI will go hand in hand with the digitization and intelligent upgrading of the industry, building a future with unlimited possibilities.