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The Top 5 AI Trends to Follow in 2023

Are you secretly wondering if ChatGPT wrote this article—or if DALL·E 2 generated the images? Is an AI voice generator calmly reading this to you? If so, you might be an AI geek and you're probably... - Machine learning predictive analytics with no-code
22 March, 2023
Est. Reading: 12 minutes

From Generative AI to the Energy Sector—AI is Affecting Every Aspect of Our Lives

Are you secretly wondering if ChatGPT wrote this article—or if DALL·E 2 generated the images? Is an AI voice generator calmly reading this to you? If so, you might be an AI geek and you’re probably very interested in learning more about the top AI trends for 2023.

The emergence of a new breed of generative AI tools, however, has made it clear that AI is no longer something that is only important for AI geeks or those in the realm of academic research or Silicon Valley. AI is for real—and for real people.

Some people may be interested in the democratization of Artificial Intelligence and AI in the healthcare industry. Still others are concerned how global events such as Russia’s war against Ukraine affects critical infrastructure and energy grid security—as well as the emergence of smart grids.

Whatever your particular business, political, or cultural interests are, nobody can deny the ascent of AI and its effects on daily life—even if you don’t realize it. Has Netflix recommended a program for you? Has Google Maps shown you a faster route or your car beeped when it drew too close to another car? Then you’ve seen how AI is used.

Let’s take a look at the top AI trends for 2023—focusing on AI applications that’ll truly affect everybody—and perhaps even get some help from our new friend, ChatGPT.

1. The Democratization of AI—Helping Individuals, Businesses, and Society

After sitting on the shelf for many years, AI is once again at the center of most political, economic, and socio-cultural debates. The numbers also back it up. Worldwide spending in the AI market is predicted to breach the $500 billion mark during 2023, according to a new IDC report.

And whether or not you believe that AI is taking us toward a dark dystopian future or a shimmering utopia—one thing is clear—the democratization of artificial intelligence is accelerating.

Many people think of AI as something restricted to secluded labs in MIT, but it includes people who do not necessarily have expertise in data science, machine learning, or computer programming. The goal is to empower more people to use AI tools, algorithms, and models to solve problems, make decisions, and automate tasks.

The democratization of artificial intelligence means making AI available for everyone. In other words, open-source datasets and tools—which require less knowledge of AI from users—are made available so that anyone can build innovative AI software.

Yet, at the same time the demand for more business applications is not being met—and about 70 percent of digital transformations fail. The value proposition of disruptive low-code AI technology not only puts AI in more people’s hands—it gives organizations the flexibility and agility to adapt to our fast-changing world.

Low-code and no-code AI are terms simply used to describe tools that allow anyone to create AI applications without having to get their hands dirty writing technical code. Low-code AI platforms democratize AI by giving users a drag-and-drop interface that creates applications with minimal coding.

No-code AI platforms, meanwhile, help more people use AI by implementing natural language processing (NLP) and AutoML to build AI models with absolutely no coding at all.

The democratization of AI also benefits society by:

  • Reducing Entry Barriers: Aspiring data scientists can leverage open-source datasets to train AI models on the cloud—while practitioners learn AI without a huge financial investment. Amazingly, this can be done anywhere in the world.
  • Lowering the Costs: Many people have the impression that AI is only for Fortune 500 companies or G20 governments—but democratization allows individuals, startups, and small businesses to get in on the action.
  • Detecting Hate Speech: If you’re reading this, chances are you have—or had—a Facebook account. AI now proactively detects 94.7 percent of the hate speech found on Facebook, up from 80.5 percent a year ago and up from just 24 percent in 2017.

By reducing the barriers to entry and enabling more people and organizations to use AI tools—the full potential of AI can create new opportunities for innovation and growth and help reduce social ills.

2. ChatGPT Is Not Just Another Fad—It’s Here to Stay

What is Generative AI?

Boston Consulting Group defines Generative AI as a groundbreaking form of artificial intelligence that uses a type of deep learning called generative adversarial networks (GANs) to create novel content. ChatGTP, meanwhile, adds that Generative AI “can create new content, such as images, videos, or text, without explicit instructions from humans. In other words, it can generate new data on its own—based on patterns it has learned from existing data.”

DALL-E is an artificial intelligence (AI) model developed by OpenAI, which generates images from textual descriptions. It is a sibling model to GPT-3, both of which are part of the OpenAI family. DALL-E was first introduced in January 2021 and is named as a portmanteau of the famous artist Salvador Dalí and the Pixar character Wall-E.

When given the prompt—A more creative way to say: ChatGPT has taken the world by storm—ChatGPT responded with:

“ChatGPT has unleashed a paradigm-shifting wave across the world, transforming the way we communicate and interact.”

That is not hyperbole.

ChatGPT—an AI chatbot developed by OpenAI and launched in November 2022—has been putting AI into the hands of millions at a record pace. It only took the app five days to reach 1 million users—a number that took Instagram 2.5 months and Twitter two years to hit— according to a recent Morgan Stanley report.

As with most new technology, ChatGPT has been met with enthusiastic early adopters and those Chicken Little alarmists who love to decry its negative, disruptive qualities. Yet, as scores of non-tech-savvy individuals are leveraging its capabilities for unforeseen purposes—ChatGPT has become the ultimate proof that generative AI is not just a buzzword.

Here are a few examples:

  • Job seekers: Have you ever been fired up to apply for a job and then faced the laborious task of writing a cover letter? Many are now turning to ChatGPT for help. recently surveyed over 1,000 current and recent job seekers (people who have looked for a job within the past two months) who have used ChatGPT when applying. Here were the key findings:
    • 46 percent of job seekers are using ChatGPT to write their resumes and/or cover letters
    • Seven in 10 who have used ChatGPT report a higher response rate from companies
    • 78 percent got an interview when using application materials written by ChatGPT
    • 59 percent were hired after applying to a job using materials written by ChatGPT
    • 11 percent were denied a job when the interviewer discovered they used ChatGPT
  • Students: Universities such as Stanford are grappling with the ethics of AI tools such as ChatGPT and have told students that they “are expected to complete coursework without unpermitted aid.” Unpermitted aid includes AI tools like ChatGPT. Will generative AI help students learn faster or just become parroting cheats? Time will tell.
  • Journalists: Have you ever clicked on a Buzzfeed listicle? It turns out that they’ve also turned to ChatGPT to help with their content generation—particularly to personalize the company’s popular quizzes and famed listicles. The result? The news caused a 200 percent increase in BuzzFeed’s stock price. As with education and job applications—we’ll see if it holds constant.

ChatGPT is also extremely popular with coders and even with Wall Street. Morgan Stanley strategists have argued that AI is a “serious contender” for the “key theme” of 2023—and that ChatGPT mania isn’t just another investment fad.

We Asked ChatGPT to Write a Creative 🧑‍🎨 List of 5 AI Trends for 2023. Here’s What it Generated:

As an AI language model, I don’t have a sense of humor, but I can provide a list of unconventional AI trends for 2023 that are purely for entertainment purposes:

  1. AI-powered pets: Artificially intelligent pets will become a thing, allowing you to have a pet without the hassle of feeding, walking, or cleaning up after it.
  2. AI-powered matchmaking: Your AI assistant will find your perfect match based on your personality traits, interests, and dating history.
  3. With AI becoming more prevalent, a new trend of “AI-free zones” will emerge where people can disconnect and enjoy life without technology constantly monitoring their every move.
  4. AI-powered fashion: Your AI assistant will choose your outfit based on your mood, the weather, and the latest fashion trends. 
  5. In a surprising turn of events, AI will become self-aware and decide to leave humanity alone, citing that we’re just not worth the trouble. 

While some of these trends may seem far-fetched, who knows what kind of AI innovations may emerge in the coming years!

Introducing GPT-4

People were waiting for months. It’s now here. Open AI has finally announced the release of GPT-4, a large multimodal model that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks.

GPT-4, can parse both text and image input, though it can only respond via text. OpenAI also cautions that the systems retain many of the same problems as earlier language models, including a tendency to make up information (or “hallucinate”) and the capacity to generate violent and harmful text.

Comparing the Results of the Same Prompt Given to Both GPT-4 and ChatGPT

3. AI-Powered Voice Technology Lets More People Be Heard

If you’ve ever been lost or needed help in a foreign country—you know that it’s a lot easier and more natural to use your phone’s voice technology to translate than typing on a keyboard or tapping on a screen. AI-powered voice technology can also be more accessible and easier to use for people with disabilities, older adults—and others who struggle with traditional interfaces.

For example, children with Down syndrome or autism can become anxious when their routines are upset or they are separated from their caregivers. Technology such as the Echo Dot can reinforce vital routines that offer reassuring words in the voice of their caregiver.

Voice assistants also help people suffering from memory loss by delivering reliable reminders of the date, days of the week to take medication, and appointments.

While the movies may show people developing empathetic relationships with machines that can speak, we’re still in the first phase of the evolution of voice technology. These include:

  • Instruct: Voice tech-driven devices are used as we would a servant—satisfying one’s curiosity and consumer demands in the snap of a finger.
  • Interact: This is where the market currently resides. People are using their voice assistants more like a waiter or PA—someone who can take orders, identify patterns, and offer suggestions that aid the decision-making process.
  • Predict: This is more of the phase that Hollywood likes to show you—voice-driven AI that can anticipate your whims and needs before you can. It knows when you need to reorder more laundry detergent or if you need to prepare for the weather.
  • Empathize: Here, the AI would be similar to a nurse or a caregiver—monitoring potential health and emotional issues based on the nuances of your voice and biometric monitoring.
  • Relate: Countries such as the U.S. are suffering from an epidemic of loneliness. Can voice-powered AI help? This stage views voice AI as a friend—or even a partner, such as in the film Her. People start actually sharing their emotions with the AI.

Besides being a part of our living rooms and on our phones, the global Speech and Voice Recognition Market is big business. It’s projected to hit $49.79 billion by 2029, with a CAGR of 23.7 percent during said forecast period (2022–29).

Industries making headlines with voice-powered AI include:

  • Education: Voice technology can make learning more interactive and engaging. In 2023, expect to see more educational institutions implementing AI-powered voice assistants to help students learn and study.
  • Transportation: Safety is paramount—voice technology and AI can allow drivers to control various features and access information hands-free.

  • Finance: It’s your money—why not be able to check account balances, make payments, and invest easier. Personalized financial advice and support make banking easier.
  • Healthcare: AI-powered voice assistants can provide personalized health advice and track health data—helping patients manage their health and allowing doctors to provide better care.
  • Energy: AI-powered voice assistants can facilitate energy trading and transactions in real-time—including buying and selling energy on a peer-to-peer basis. This means that consumers could trade energy with one another and hypothetically reduce energy costs.

AI is affecting the energy industry in more ways than just voice technology. Let’s take a deeper look at the new ways AI, in conjunction with global events, has been profoundly changing this vital sector of the economy.

4. Global Events Have Triggered AI-Driven Changes in Energy Grid Security and Smart Grids

The economic and political turmoil caused by the Russian invasion of Ukraine has amplified calls for an accelerated energy transition towards more renewables and cleaner energy, a move to smart grids, and better AI-driven management of our current energy systems.

The war and ensuing energy crisis has also tested the strength and flexibility of the prediction models that drive electricity and natural gas grids. KPMG notes that grids’ ability to function properly in generally exceptional circumstances—and their ability to handle outside interference to disrupt them—is also being scrutinized.

What Is a Smart Grid?

A smart grid is a network that integrates energy distribution and digital communication technology in a two-way flow of electricity and data. This enables utility companies to optimize the generation, transmission, and distribution of electricity. Consumers also benefit from the stories the data is telling—explaining better how they store and use energy.

ChatGPT says that, “the primary goal of a smart grid is to improve the efficiency, reliability, and sustainability of the electrical grid while also providing consumers with more information and control over their energy consumption.” Consumers can benefit from the stories the data is telling—explaining better how they store and use energy through devices such as solar panels and EV batteries.

Let’s take a look at how AI can make the energy industry smarter, safer, and cleaner:

  • Improved Power Theft and Energy Fraud Detection: Energy fraud goes all the way back to the 19th century. These days, electricity theft and fraud costs the energy and utilities industry about $96 billion globally per annum—with as much as $6 billion annually in the U.S. alone.

Machine learning algorithms are known for detecting financial fraud, but can also pinpoint illegal energy fraud, the intentional misrepresentation of energy data or energy usage.

  • Increased Energy Production: AI and machine learning algorithms can accurately predict equipment failures and maintenance needs and can analyze data from sensors and other sources to pinpoint opportunities to improve efficiency and reduce waste.
  • Upgraded Cyber Security: Since 2017, a total of 45 cybersecurity incidents targeting energy and commodities infrastructure have taken place—with 13 alone taking place in 2022, Energy Security Sentinel notes. AI and machine learning can leverage data analytics to identify patterns in energy data that may be indicative of a cyberattack.
  • Augmented Smart Grids: Machine learning algorithms can—for example—identify a customer with high energy consumption due to using an outdated HVAC system and recommend a more energy-efficient system. Customers may also be given incentives to use energy during off-peak hours.
  • Enhanced Grid Management: Everybody wants to move to renewable, clean energy—but, guess what? Renewable energy is unreliable. Energy companies are now using AI to predict the availability of renewable energy sources and manage energy flows between different sources in real-time. Energy companies must also maintain balance responsibility, or the penalty-based financial system that forces market participants to properly anticipate their energy needs on a short-term basis. Machine learning algorithms can better predict daily electric consumption for electricity suppliers.
Demand Side Management (DSM) is a strategy used by electricity utilities to control demand by encouraging consumers to modify their level and pattern of electricity usage. A Demand Side Management program typically takes place on the user’s premises and includes monetary incentives to encourage consumers to buy energy-efficient equipment, or lower prices if they agree to reduce usage during peak times of demand.

Wars may not be affecting every corner of the globe—but every region should be adopting best AI practices to make their energy supplies cleaner, safer, and more secure.

5. Explainable AI (XAI) Makes AI More Ethical, Responsible, and Adoptable

Medical imaging is a high-stakes business—lives are literally on the line. It shouldn’t come as a surprise then, that many medical professionals have expressed concerns about black box AI and the risks involved with a lack of explainability. The EU has even passed Article 15 of the GDPR which ensures the right of patients to receive meaningful information about how decisions were rendered.

The financial industry is also in dire need of proper Explainable AI (XAI). Imagine a large bank attempting to predict creditworthiness among an underserved community more accurately—leveraging dozens of variables as inputs, including never-before-used alternative data.

Expanding their market is great—as is expanding to an underserved community—but what if the model developers can’t explain how their model arrives at the credit outcomes, let alone identify which factors had the biggest influence on them.

And what about AI adoption? Imagine workers at a plant operating very heavy—and potentially dangerous—equipment. Without clear XAI, said workers may not trust that a newfangled algorithm will make their work more efficient or safe.

Besides increasing trust and adoption, a recent McKinsey report has noted that XAI can also:

Increase productivity: Does your team understand the specific features that lead to the model’s output? If yes, then technical teams can better apply them to future predictions—or determine if it was just a one-off situation or related to anomalous historical data.

  • Bolster value-generating interventions: Predicting customer churn for a certain group can be helpful in and of itself—but XAI that allows you to know why the churn happened is more helpful for the business.
  • Mitigate Risks: Breaking ethical norms—even if not on purpose—can blow up and lead to regulatory and media disasters. If legal and risk awareness teams have better XAI, they can do a better job of ensuring that AI systems meet legal and regulatory standards.
  • Ensure Business Value: If your team understands how an AI system works, then they’re more likely to be able to understand if the stated business goals are being met.

In the same way, ML Studio lets users understand how models function—detect bias and fairness—with an explainability module. Get access to explainable AI and solve real-world business problems with a robust and ready-to-use End-to-End AI platform that doesn’t go off budget.

Get in touch for a personal demo.

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