Future trends of Artificial Intelligence

Future trends of artificial intelligence. Over the last decade, artificial intelligence (AI) has been embedded in every aspect of our society and lives, from chatbots and virtual assistants like Siri and Alexa to automated industrial machinery and self-driving cars. It’s hard to ignore their impact.

AI is the foundational technology at Google and its parent company Alphabet, CEO Sundar Pichai told the audience at the 2022 Code conference in Los Angeles. He said he expected we would have true “conversational AI” to help get things done in the next 5 to 10 years.

Worldwide, spending by governments and businesses on AI technology will top $500 billion in 2023, according to IDC research. But how will it be used, and what impact will it have? Here, I outline some of the most important trends around the use of AI in business and society.

AI is commonly used in machine learning; machine learning is an application of AI. It’s the process of using mathematical models of data to help a computer learn without direct instruction.

This enables a computer system to continue learning and improving on its own, based on experience. Some of its use cases are; predictive analysis, speech recognition, natural language understanding, and sentiment analysis, etc. for our everyday products, Siri for speech, Uber for determining how far the cab is from your location, etc.

The Ongoing Democratization of AI; AI democratization is the spread of artificial intelligence development to a wider user base that includes those without specialized knowledge of AI.

AI will only achieve its full potential if it’s available to everyone and if every company and organization can benefit. Benefits of democratization include; enhanced innovation and progress, increased access to AI technologies, and economic opportunities, among others.

In 2023, this will be easier than ever. An ever-growing number of apps puts AI functionality at the fingertips of anyone, regardless of their level of technical skill.

Generative AI; As the name suggests, generative AI produces or generates text, images, music, speech, code, or video. Generative AI is not a new concept, and the machine-learning techniques behind generative AI have evolved over the past decade.

If you ask most people what they think AI is useful for, they will probably tell you that it’s mainly for automating routine, repetitive tasks. While this is often true, a growing branch of science is dedicated to building AI tools and applications that can mimic one of the most uniquely human of all skill sets – creativity.

Generative AI algorithms take existing data—video, images, or sounds—or even computer code and use it to create entirely new content that has never existed in the non-digital world.

Generative AI stretches beyond typical natural languages processing tasks such as language translation, text summarization, and text generation.

OpenAI’s latest release, ChatGPT, which caused a viral sensation and reached a million users in just five days, has been described as breaking ground in a much broader range of tasks.

The use cases currently under discussion include new architectures of search engines; explaining complex algorithms; creating personalized therapy bots, helping build apps from scratch; explaining scientific concepts; writing recipes; and college essays, among others.

Future trends of Artificial Intelligence

AI tools and applications that can mimic one of the most uniquely human of all skill sets – creativity.

One of the best-known generative AI models is GPT-3, developed by OpenAI and capable of creating text and prose that are close to being indistinguishable from those created by humans.

A variant of GPT-3 known as DALL-E has the potential to change how art, animation, gaming, movies, and architecture, among others, are being rendered.

Ethical and Explainable AI; AI ethics is a set of guidelines that advise on the design and outcomes of artificial intelligence. Human beings come with all sorts of cognitive biases, such as recency and confirmation bias, and those inherent biases are exhibited in our behaviors and subsequently, our data.

What is explainable AI? Explainable artificial intelligence (XAI) is a set of processes and methods that allow human users to comprehend and trust the results and output created by machine learning algorithms.

Explainable AI is used to describe an AI model, its expected impact, and potential biases.
The development of more ethical and explainable AI models is essential for several reasons. Most pressingly, though, it comes down to trust. AI requires data to learn, and often, this means personal data.

For many of the potentially most useful and powerful AI use cases, this might be very sensitive data, like health or financial information.

If we, the general public, don’t trust AI or understand how it makes decisions, we simply won’t feel safe handing over our information, and the whole thing falls apart.

Future trends of Artificial Intelligence

The future of technology is intelligence, and that is AI. We are moving from generic AI to strong AI.

Augmented Working: In 2023, more of us will find ourselves working alongside robots and smart machines specifically designed to help us do our jobs better and more efficiently.

This could take the form of smart handsets giving us instant access to data and analytics capabilities, as we have seen them increasingly used in retail as well as industrial workplaces.

It could mean augmented reality (AR)-enabled headsets that overlay digital information on the world around us.

In a maintenance or manufacturing use case, this could give us real-time information that can help us identify hazards and risks to our safety, such as pointing out when a wire is likely to be live or a component may be hot.

The future of technology is intelligence, and that is AI. We are moving from generic AI to strong AI.

Future trends of Artificial Intelligence